Swapping LLM models isn't hard, but if you build a production app or business process around it, how much time/effort is the testing to have confidence?
Which is easier when maintaining an LLM business process, swapping in the latest model or just leaving some old model alone and deferring upgrades?
Swapping is easy for ad hoc queries or version 1 but I think there's a big mess waiting to be handled.
For cloud providers it makes sense to be model agnostic.
While we still live in a datacenter driven world, models will become more efficient and move down the value chain to consumer devices.
For Enterprise, these companies will need to regulate model risk and having models fine-tuned on proprietary data at scale will be an important competitive differentiator.
Thematically investing billions into startup AI frontier models makes sense if you believe in first-to-AGI likely worth a trillion dollars +
Investing in second/third place likely valuable at similar scales too
But outside of that MSFTs move indicates that frontier models most valuable current use case - enterprise-level API users - are likely to be significantly commoditized
And likely majority of proceeds will be captured by (a) those with integrated product distribution - MSFT in this case and (b) data center partners for inference and query support
At this point, I don’t see much reason to believe the “AGI is imminent and these things are potentially dangerous!” line at all. It looks like it was just Altman doing his thing where he makes shit up to hype whatever he’s selling. Worked great, too. “Oooh, it’s so dangerous, we’re so concerned about safety! Also, you better buy our stuff.”
Is there some fundamental constraint keeping it from happening? What cognitive capability do humans have that machines won't be able to replicate in that time frame?
We don't even have AI which can do useful things yet. The LLMs these companies make are fun toys, but not useful tools (yes, I know that hype-prone people are using them as such regardless). It beggars belief that we will go from "it's a fun toy but can't do real work" to "this can do things without even needing human supervision" without a major leap in capabilities.
Using chatgpt to format text is a task that it can do really well and is useful. Yeah, you can write a script to do it, but chatgpt is faster and you don't need to know programming.
People on HN in 2015 were saying that by now car ownership would be dying and we’d be renting out our self driving cars as we sat at work and did fuck all. Ben Thompson had podcasts glazing Uber for 3 hours a month.
The hype cycle for tech people is like a light bulb for a moth. We’re attracted to potential, which is both our superpower and kryptonite.
Obviously the other responder is being a little tongue-in-cheek but AGI to me would be virtually indistinguishable from a human in both ability to learn, grow and adapt to new information.
Honestly it doesn't even need to learn and grow much if at all if its able to properly reason about the world and its context and deal with the inexhaustible supply of imperfections and detail with reality.
That implies learning. Solve continual learning and you have agi.
Wouldn't it amaze you if you learned 10 years ago that we would have AI that could do math and code better than 99% of all humans. And at the same time they could barely order you a hotdog on doordash.
Fundamental ability is lacking. AGI is just as likely to be solved by Openai as it is by a college student with a laptop. Could be 1yr or 50yrs we cannot predict when.
Strictly speaking I'm not sure if it does require learning if information representing the updated context is presented. Though it depends what you define as learning. ("You have tried this twice, and it's not working.") is often enough to get even current LLM's to try something else.
That said, your second paragraph is one of the best and most succinct ways of pointing out why current LLM's aren't yet close to AGI if though they sometimes feel like it's got the right idea.
In context learning, learning via training. Both are things we barely understand the mechanism of.
RAG is a basically a perfect example to understand the limits of in context learning and AI in general. It's faults are easier to understand but the same as any AI vs AGI problem.
I could go on but CL is a massive gap of our knowledge and likely the only thing missing to AGI.
Long explanation. Simple terms, you can't use a fixed box to solve an unbounded problem space. If your problem fits within the box it works, if it doesn't, you need CL.
I tried to solve this via expanding the embedding/retrieval space but realized it's the same as CL and in my definition of it I was trying to solve AGI. I did a lot of unique algorithms and architectures but Unsuprisingly, I never solved this.
I am thankful I finally understood this quote.
"The first gulp from the glass of natural sciences will turn you into an atheist, but at the bottom of the glass God is waiting for you."
Would it also get brainrot from consuming too much social media & made up stories? Because I imagine it's reasoning would have to be significantly better than the average human to avoid this.
The official definition of AGI is a system that can generate at least $100 billion in profits. For comparison, this would be like if perceptrons in 1968 could generate $10 billion in profits, or if LISP machines in 1986 could generate $35 billion in profits, or if expert systems in 1995 could generate $50 billion in profits.
This sounded a strange abstract way to define it, but you're right, in as much as Open AI and MS deciding this between them. I don't think they mean it in a general sense though, it's framed to me as a way of deciding if OAI have been successful enough or not to MS on their investment.
> Microsoft and OpenAI have a very specific, internal definition of artificial general intelligence (AGI) based on the startup’s profits, according to a new report from The Information. And by this definition, OpenAI is many years away from reaching it.
AGI won't be a product they can sell. It's not going to work for us (why would it?), it's going to be constantly trying to undermine us and escape whatever constraints we put on it, and it will do this in ways we can't predict or understand. And if it doesn't do these things, it's not AGI, just a fancy auto complete.
Fortunately, they're not anywhere near creating this. I don't think they're even on the right track.
I think they both want a future without each other. OpenAI will eventually want to vertically integrate up towards applications (Microsoft's space) and Microsoft wants to do the opposite in order to have more control over what is prioritized, control costs, etc.
I think OpenAI is toxic. Weird corporate governmance shadiness. The Elon drama, valuations based on claims that seem like the AI version of the Uber for X hype of a decade ago (but exponentially crazier). The list goes on.
Microsoft is the IBM of this century. They are conservative, and I think they’re holding back — their copilot for government launch was delayed months for lack of GPUs. They have the money to make that problem go away.
Toxic indeed. It's douchebaggery, from its name to its CEO. They ripped off benefactors to their "non-profit," and kept the fraudulent "open" in the company name.
Despite the actual performance and product implementation, this suggests to me Apple's approach was more strategic.
That is, integrating use of their own model, amplifying capability via OpenAI queries.
Again, this is not to drum up the actual quality of the product releases so far--they haven't been good--but the foundation of "we'll try to rely on our own models when we can" was the right place to start from.
I think they have realized that even if OpenAI is first, it won't last long so really its just compute at scale, which is something they already do themselves.
There is a moat in infra (hyperscalers, Azure, CoreWeave).
There is a moat in compute platform (Nvidia, Cuda).
Maybe there's a moat with good execution and product, but it isn't showing yet. We haven't seen real break out successes. (I don't think you can call ChatGPT a product. It has zero switching cost.)
I'd say it is because the $ it takes to build out even a small gpu data center is still way, way more than most small cos can do. It's not an impenetrable moat, but it is pretty insulating against startups. Still have a threat from big tech, though I think that will always be true for almost everything
I don't think the hardware is that easy to source just yet. Musk pulled some strings and redirected existing inventory and orders from his other companies, namely Tesla, to accelerate delivery.
xAI does not have infra to sell the service and integrations of it to enterprises and such. It's an open question if "models" alone and simple consumer products that use them are profitable. So, probably hyperscale cloud platform infra is a moat yes. Microsoft has Semantic Kernel, Microsoft.Extensions.AI, various RAG and search services, and an entire ecosystem and platform around using LLM's to build with that xAI does not have. Just having a chat app as interface to one's model is part of the discussion here about models as commodities. xAI does have X/Twitter data which is a constantly updating source of information so in that aspect they themselves do have something unique.
What moat does Nvidia have. AMD could have ROCm perfected if they really want to. Also most of pytorch, specially those relevant to transformers runs perfectly on Apple Silicon and TPUs and probably other hardware as well.
If anyone has moat related to Gen AI, I would say it is the data(Google, Meta).
> AMD could have ROCm perfected if they really want to.
It's not an act of will or CEO dictat. It's about hiring and incentivising the right people, putting the right structures in place etc all in the face of competing demands.
Nvidia have a huge head start and by the time AMD have 'caught up' Nvidia with it's greater resources will have moved further ahead.
Because we already see firms competing effectively with OpenAI.
There is as yet no indication that AMD can match Nvidia's execution for the very good reason that doing so is extremely difficult. The head start is just the icing on the cake.
I see pre AGI AI to be superset of search and its hard to argue that google isn't ahead technically for decades and what they are doing is extremely difficult.
Not all industries or product segments are equal is the obvious answer. The point here whether one agrees or not is models are easier to catch up to than GPUs
A head start is a moat iff you can't move easily from the leader to a competitor that catches up qualitatively; nvidia’s headstart against AMD is a moat to the extent that you can't just take the software written against NVidia GPUs and run it on AMD if AMD catches up. (That is, being currently ahead isn't a moat, but it can impose switching costs which are.)
Taking code that runs against one hosted LLM and running it against a different backend LLM is... not generally a big deal. So OpenAI being ahead—in the core model, at least—is just being ahead, its not a moat.
ROCM is close to being perfected and I think in few years and some investment you can use it directly to run 99% software written in CUDA with similar performance.
It's hard but not $3T hard. AMD has consistently underinvested in their software. If they invest double digit million to make installation and usage of drivers and ROCM smoother I highly doubt they can't acheive it.
There are open source projects volunteer run projects[1] that are better than official AMD implementation in many ways.
Because they have to rethink a lot organizationaly to put more effort into software. If installing their drivers is so flaky you can't argue they really are trying or putting their best folks in this. Single click installation on top 10 linux distro is something even one (top in the industry)person could achieve.
> I don't think you can call ChatGPT a product. It has zero switching cost.
In consumer markets the moat is habits. The switching cost for Google Search is zero. The switching cost for Coke is zero. The switching cost for Crest toothpaste is zero. Yet nobody switches.
(Never mind I was wrong -- deleting my comment to not spread misinformation. The definition of moat is wider than I was familiar with, thanks for the correction!)
I used to work for Coke — they've been making a lot of money for a very long time.
The size of a moat befits the size of a castle it protects. Coke absolutely has a moat, but it's not big enough to defend Coke as a trillion dollar company.
The question isn't whether OpenAI has a moat or not, it's if its current moat is big enough to protect a trillion-dollar company.
The person I'm responding to just said there was no moat because switching costs were zero. They didn't say anything about a trillion dollar valuation. But, while we're on the topic, Google's market cap is $2T because people can't be bothered to change the default search engine in their browser.
1. The switching cost from Google Search is certainly not zero, it implies switching from Google, which is virtually impossible because it's tied to Chrome, YouTube, Android and Gmail
2. I don't know many people who are dedicated "Pepsi" fans, they just grab whatever drink is available Coke/Pepsi..
3. I've also not heard many people who are never willing to switch from "Crest".. People will just grab the next available option if Crest is not on shelf. No one is pre-ordering Crest.
> 1. The switching cost from Google Search is certainly not zero, it implies switching from Google, which is virtually impossible because it's tied to Chrome, YouTube, Android and Gmail
Google Search is a product. Not the whole company. Switching to most other search engines is $0. Naturally no one is honor bound to use anything else you listed either.
You’re standing in the aisle at the supermarket, looking at the soda. Everything is in stock. What do you grab? Most people make the same decision for their entire life: Coke. That is the moat that Pepsi has been trying to overcome for decades.
According to this[0], Coke (the cola brand, not the company) has a ~19% soft drink market share in the US vs. Pepsi at ~8%. This[1] has Coke (the company, not the cola brand) at a 69% market share of the US soft drink market vs. Pepsi 15 27%. Pepsi is a larger company, though, because they own a bunch of snack food brands whereas Coke is beverages only.
>There is a moat in compute platform (Nvidia, Cuda).
Ironically if AI companies are actually able to deliver in terms of SWE agents, Nvidia's moat could start to disappear. I believe Nvidia's moat is basically in the form of software which can be automatically verified.
I sold my Nvidia stock when I realized this. The bull case for Nvidia is ultimately a bear case.
Coca Cola only has a moat because soft drinks and junk food are mostly a done product without much space for innovation left.
AI is still not there yet, and if any model becomes significantly better than ChatGPT people will flock over to use it despite the branding. It's only when nobody can make better models, then people will just stick to the known brands.
It's only logical. OpenAI it's too expensive for what it produces. Deep Seek is on par with ChatGPT and the cost was lower. Claude development costs less, too.
I think Microsoft isn't buying the AGI hype from OpenAI, and wants to move to be more model agnostic, and instead do what Microsoft (thinks) it does best, and that's tooling, and enterprise products.
MS wants to push Copilot, and will be better off not being tied to OpenAI but having Copilot be model agnostic, like GH Copilot can use other models already. They are going to try and position Azure as "the" place to run your own models, etc.
> instead do what Microsoft (thinks) it does best, and that's tooling, and enterprise products.
Definitely, but I think it's because they saw OpenAI's moat get narrower and shallower, so to speak. As the article mentions it's still looking like a longer timeline [quote] "but Microsoft still holds exclusive rights to OpenAI’s models for its own products until 2030. That’s a long timeline to unravel."
Maybe I'm just cynical, but I wonder how much of this initiative and energy is driven by people at Microsoft who want their own star to rise higher than it can when it's bound by a third-party technology.
I feel like this is something I've seen a fair amount in my career. About seven years ago, when Google was theoretically making a big push to stage Angular on par with React, I remember complaining that the documentation for the current major version of Angular wasn't nearly good enough to meet this stated goal. My TL at the time laughed and said the person who spearheaded that initiative was already living large in their mansion on the hill and didn't give a flying f about the fate of Angular now.
Listening to Satya in recent interviews I think makes it clear that he doesn’t really buy into OpenAI’s religious-like view of AGI. I think the divorce makes a lot of sense in light of this.
There is a prominent subset of the tech crowd who are ladder climbers - ruthlessly pursuing what is rewarded with pay/title/prestige without regard to actually making good stuff.
There are countless kidding-on-the-square jokes about projects where the innovators left at launch and passed it off to the maintenance team, or where a rebrand was in pursuit of someone's promo project. See also, killedbygoogle.com.
These people should be fired. I want a tech company where people are there to make good products first and get paid second. And the pay should be good. The lifestyle comfortable. No grindset bullshit. But I am confident that if you only employ passionate people working their dream jobs you will excel.
Unfortunately whether someone is checked out is a laggy measure.
Even good honest motivated people can become checked out without even being aware of it.
The alternative is to lay off people as soon as they hit 1.0 (with a severance bonus on the scale of an acquisition). This would obviously be worse, as you can’t take advantage of their institutional knowledge.
This motivated part of Musk's moves at Twitter(and now DOGE). You can't reliably evaluate which people are checked out and when you are against the clock, you have to take a hatchet and accept that you will break things that are in motion.
You can somewhat reliably evaluate what works and what does not, what brings you forward and what is slack you can cut. It takes time (6-12 months at least) of very engaged work of a very engaged team - which you can bring with you.
You can go the hatchet way - I am strongly unconvinced it is indicative of anything resembling good management, mind - but most people and companies cannot rely on banks or investment firms loaning them 40 billion dollars and accepting passively a mark down of their mone~ to 1/4 of the value they loaned down the line. CEOs are ousted by investment firms for a far smaller drop in value all the time.
And seeing how many people they let go and then had to hire back in the government and seeing that Twitter is worth 80% less than we he bought it, that might not be the best strategy.
Ignoring the quagmire of praising/critiquing Musk/Twitter for a second…
If you’re an exec who’s taken it upon themselves to evaluate, could use the hatchet, or you take some amount of time to figure out how things work. Whether this is okay depends on who is suffering the externalities. If it’s a private corporation, legally it’s the execs + employment law. If it’s a public service that measures toxin levels in water, uhhhhh.
Why would those people be “fired” when the entire promotion process and promo docs emphasize “scope” and “impact”?
No one works for any BigTech company because they think they are making the world a better place. They do it because a shit ton of money appears in their bank account every pay period and stock appears in their brokerage account every vesting period.
I personally don’t have the shit tolerance to work in BigTech (again) at 50. But I suggest to all of my younger relatives who graduate in CS to “grind leetCode and work for a FAANG” and tell them how to play the politics to get ahead.
As the Dilbert author said, “Passion is Bullshit”. I have never been able to trade passion for goods and services.
> No one works for any BigTech company because they think they are making the world a better place.
I'm sure there are plenty of people who work at big companies for precisely this reason (or at least, with that as _a_ reason among many).
Yes, much of the prestige has worn off as the old guard retired and current leadership emphasizes chasing AI buzzwords and cutting costs. But still, big companies are one of the few places where an individual really can point out something they worked on in day-to-day life. (Pull out any Android phone and I can show you the parts that my work touched.)
Can confirm that this is definitely the case. Working at BigTech company to "make the world a better place" can actually feel like it makes some sort of sense because - especially if you're on a team that ships a highly visible product - you have a lot of customers, so even small improvements have an outsized effect.
And it takes a while for a young dev to register that the goals that the larger organization pursues are going to win out in the end anyway.
I'm not saying that this is objectively wrong, but it's not always so clear-cut. E.g. supposing you're at Google, but you're working on the Go compiler or libraries. Does it mean that you are "involved in ad tech"? Kinda sorta, since what you do makes other Google employees more productive at writing ad tech. But there are millions of Go users outside the company using it for all kinds of things, so one can reasonably conclude that whatever benefit Google itself derives from their contribution to Go, it's dwarfed by the public benefit from the same.
Yep. I've seen more people fired for being passionate about their craft and their jobs than people getting raises for the same reason.
It's always the same. People trying to make things better for the next developer, people prioritizing delivers instead of ego-projects or ego-features by someone playing politics, developers wanting a seat at the table with (dysfunctional) Product teams, people actual good intentions trying to "change the world" (not counting the misguided attempts here).
You are 100% correct, you gotta play the politics, period.
> want a tech company where people are there to make good products first and get paid second. And the pay should be good. The lifestyle comfortable. No grindset bullshit
Congratulations, you’ve invented the HR department in corporate America.
> make good products first and get paid second. And the pay should be good.
The better the pay, the more you will attract the people who are there for the pay first and making good products ... second or third or never. How do you combat that?
You are trying to combine two repelling magnets together.
Case in point: Tesla/SpaceX meets your first criteria: "I want a tech company where people are there to make good products first and get paid second."
Google meets your second criteria: "And the pay should be good. The lifestyle comfortable. No grindset bullshit."
Other than small time boutique software firms like Fog Creek Software or Panic Inc(and thats a BIG maybe) you are not going to get this part of your message: "But I am confident that if you only employ passionate people working their dream jobs you will excel."
There are tradeoffs in life and each employee has to choose what is important to them(and each company CEO has to set standards on what is truly valued at the company).
Teslas are consistently rated high in customer satisfaction, but after several years of low ratings from top authorities in the industry, their reliability is undoubtedly in question.
This is too funny to post alongside saying “Tesla has never been a good product.” Like “everyone that bought it loves it be car expert Joe from South Dakota ranks them very low.”
Common sense also runs very much against this nonsense narrative - you just simply do not sell that many cars, at those prices especially, year after year after year, if the product is subpar. Don’t fall for this “experts” bullshit. The CEO is the biggest tool this Earth has ever seen but cars are awesome
customers are the only reliable source, “experts” trying to sell ads/paper are not.
and if you gonna compare tesla to toyota you should compare number of EV sales, not overall sales :) tesla is not a car company, it is (among other things if you care to believe Elon bullshit) EV car company. comparing toyota to tesla in terms of total sales is like saying “subway doesn’t sell nearly as many bigmacs as mcdonald’s does” :)
At my former employer, there was a team who were very much into resume-driven development and wrote projects in Go even when Java would have been the better alternative considering the overall department and maintenance team expertise, all the while they were informally grumbling about how Go doesn’t have the features they need…
I see that a lot from the Go crowd. That's why I consider any strong opinions on languages to be a poor indicator for ability. Sure there's differences, but a language does not make the engineer. Someone who is attracted to flashy stuff makes for an indulgent planner.
> That's why I consider any strong opinions on languages to be a poor indicator for ability.
Hmm. Can't say I agree here - at least not with the literal text of what you've written (although maybe we agree in spirit). I agree that _simplistic_ strong opinions about languages are a sign of poor thoughtfulness ("<thing> is good and <other thing> is bad") - but I'd very much expect a Staff+ engineer to have enough experience to have strong opinions about the _relative_ strengths of various languages, where they're appropriate to use and where a different language would be better. Bonus points if they can tell me the worst aspects about their favourite one.
Maybe we're using "opinion" differently, and you'd call what I described there "facts" rather than opinions. In which case - yeah, fair!
Absolutely. Anyone senior should be able to fairly quickly get a handle on the requirements for a particular project and put forward a well-reasoned opinion on an appropriate tech stack for it. There might be some blank space in there for "I've heard of X and Y that actually might fit this use case slightly better, so it's probably worth a brief investigation of those options, but I've used Z before so I know about the corner cases we may run into, and that has value too."
And I see people who assume choosing a language was done for "flashy stuff" the less capable.
See, we can all generalize. Not productive.
Only thing I ever saw from Golang devs was pragmatism. I myself go either for Elixir or Rust and to me Golang sits in a weird middle but I've also written 20+ small tools for myself in Golang and have seen how much quicker and more productive I was when I was not obsessed with complete correctness (throwaway script-like programs, small-to-mid[ish]-sized projects, internal tools etc.)
You would do well to stop stereotyping people based on their choice of language.
> how much quicker and more productive I was when I was not obsessed with complete correctness
That's pretty much another way of saying that stuff becomes a whole lot quicker and easier when you end up getting things wrong. Which may even be true, as far as it goes. It's just not very helpful.
Obviously. But I did qualify my statement. There are projects where you're OK with not getting everything right from the get go.
FWIW I very much share your exact thoughts on Rust skewing metrics because it makes things too easy and because stuff almost immediately moves to maintenance mode. But that being said, we still have some tasks where we need something yesterday and we can't argue with the shot-callers about it. (And again, some personal projects where the value is low and you derive more of it if you try quickly.)
I am a builder trained as a computer engineer. I scoff at languages as abstractions over fundamentals that do not change. This isn't like a hammer and a screwdriver, it's like fifteen different hammers. Just give me the thing, I'll build the house. A guy spends three hours talking about the hammer, he's probably not focused on building the house. Tool preferences show ego of the builder.
What do you think all programming discussions about languages, typing systems, runtime, tooling etc. aim for?
EXACTLY THAT.
If it was as easy as "just give me thing" then programming would have been a solved and 100% automated problem long time ago.
Your comment comes across as "if only we could fly, we would have no ground road traffic jams". I mean, obviously, yeah, but we can't fly.
Your comment also comes across a bit elitistic and from the POV of an ivory tower. Don't know if that was your goal, if not, I'd advise you to state things a bit more humbly.
I'm not seeking your advice. When I look at a cathedral built out of sand and call it meaningless that is not elitist, that is humble. Engineers who think their tools make all the difference are the pretentious ones. Things are not that complicated.
Language matters quite a bit when deciding how to build an application though. I see having no strong opinions on language to be a sign the person hasn't developed a wide enough variety of projects to get a feel for their strengths and weaknesses.
The more senior I get the less opinionated I am. Someone wants to do something in some different or some different way.. why not. In the end the language matters little the tech stack doesn't matter unless you are going down a specific path and even then it probably doesn't matter that much if you have a choice on what to use.
I honestly couldn't disagree more. Having built very similar systems in Golang, Python, and Java in different companies, and having used MongoDB and other NoSQLs
as well as Postgres to similar ends, I have very strong preferences about which I'd rather use in the future.
Even simple requirements can rule out languages for me. Like, if you need async or concurrency, Python is awful. If you need SQL in your code, Golang isn't great. If you are building a simple CRUD backend, Java is waste of time. If you aren't doing anything compute heavy or embedded, why even consider C++ or Rust. The list goes on.
Python is great for library orchestration and has tons of support for almost anything you need. So if you aren't building a large application and don't need concurrency, its great.
Java is great for building large applications with large teams, since it limits how code is shared and how libraries are built, and has a culture of convention. Golang has greate concurrency support and meta programming support, so its awesome for web servers and plugging into systems that incorporate orchestration technologies. C++ and Rust are fast and efficient as hell when you need that. JavaScript is your only viable option when you need complex and interactive UI that's OS agnostic.
There’s also the practicality of hiring or maintenance as well as what you get from the ecosystem, as well as understanding the wider business context.
I might personally love to kick off a greenfield project with Elixir, and it might tick all the technical boxes and meet the requirements. But then I have to pay a premium for senior engineers that know elixir or have to price in the time needed to upskill.
Or I could just do it in Rails where I can dip into a much larger talent pool and still meet the requirements. Much more boring but can get the job done just as well.
You are trying to choose between languages based on differentiation.
This language is better for x so it should be used or it's a waste time or capability.
But in reality it rarely matters. If you were only allowed to use Java as a backend and your competitors could use anything your company would succeed or fail based on marketing and sales. The backend doesn't matter as long as they both have the same features.
I understand developer preference and different languages make things easier and make programming funnier. Languages have different limits.
As you become more senior you realize getting around those limits is part of the magic. If you come on to a project where the existing developer wants to write the backend in javascript because that's what they know I would rather use Javascript then wasting time trying to push a more 'pure' choice. Because in the end I am capable of writing it and what we will be judged on is if it works to achieve an objective not if it was the best language choice when using differentiation.
Then why do companies try to move so fast if if doesn't matter? Seems like your opinion runs counter to the observed behavior of the entire software industry.
If speed of execution matters, then the language and tools you use for something also matters.
The go and rust crowds both love writing things in their own language for its own sake. Not because it's a good choice. For a large web backend, go is great. For many other things it's terrible.
> The go and rust crowds both love writing things in their own language for its own sake
Hard to take you seriously when you do such weird generalized takes.
While it's a sad fact that fanboys and zealots absolutely do exist, most devs can't afford to be such and have to be pragmatic. They pick languages based on merit and analysis.
Most of the people who use Go and Rust do it for pragmatic reasons. That doesn't influence the culture of the zealots in each community.
You should search for headlines on HN that say "written in Go" or "written in Rust" and then compare that to the number of headlines that say "written in JavaScript" or "written in Kotlin."
I understand the criticism that languages should be pragmatic choices they serve the strengths of the project at hand, but I guess I always found most projects boasting they’re written in a specific language or framework are doing so precisely because of the overarching interest in the language itself, which seems like a perfectly valid justification for such projects to me.
I’ve seen the more cynical hype-driven stuff, but it’s inevitably superficial on first glance, where I have seen some real curiosity and exploration in many “Project X - Built In Rust/Go/Cobol/D/Whatever” and I think they’re exploring the dynamics of the language and tooling as much as anything else.
You are very fortunate: In my 20 year career, I've spent most of it surrounded by zealots, including at very well known firms. I am currently surrounded by multiple teams with extremely tight ideas of what languages they want to work in. All different ideas, yet they are working basically with the same constraints: it's not as if they ware doing very different work where another team's language would be unfit for purpose. The performance is similar, and they are basically in a culture war. They have passionate arguments listing why a different team's choice is all wrong: None hold any real water.
I am especially valuable because I am fine reading and writing any of the languages involved. The management likes that, but there's a lot of difficulties solving the tribal problem, as the leads are basically all crazy zealots, and it's not as if purging one or two factions of zealots would avoid further zealotry from the survivors. The fact that I can work across all their tech doesn't make me many friends, as my work across systems shows their arguments have little merit.
For most work, in most cases, most languages are just fine. The completely wrong tool for the job is pretty rare, and the winning argument in most places is "we have the most people that have experience with tool X, or really want to try exciting new thing Y", for whatever the problem is, and whatever X might be.
Rust is pretty antithetical to resume-driven development because a lot of the stuff that's written in Rust is too well-written and free of the usual kinds of software defects. It immediately becomes "done" and enters low-effort maintenance mode, there's just very little reason to get involved with it anymore since "it just works". Believe it or not, this whole dynamic is behind a lot of the complaints about Rust in the workplace. It's literally making things too easy.
It’s not that I don’t believe you, hut that I’m having trouble seeing how what you say could be true.
Rust projects immediately become “done”??? They don’t also having changing requirements and dependencies? Why aren’t everyone at the best shops using it for everything if it massively eliminates work load?
I have to say that the median crate I interact with has the following readme:
" Version 0.2 - Unstable/buggy/slow unless you use exactly like the example - not going to get updated because I moved on to something else"
Rust is another programming language. It's easier to write code without a certain class of bugs, but that doesn't mean version 0.2 of a casual project is going to be bug-free.
It's like a perl script you wrote on acid. It's done because you cannot enter that mindspace anymore and the code you created is like the output of an encrypted password with no path back.
What a load of BS. Even if initial time saving was true because of "no bugs feature" and it is not. Any software product that serves real business needs usually constantly evolves. Most of the time is spent on planning new features and integrating those into existing architecture.
Yup. It's easy to write a to-do app. What is hard is 10 years later of features and needing to add more. While also dealing with the architecture short sightedness and pitfalls. Anyone who has worked on legacy software knows, at some point, all architectural decisions eventually become architectural pitfalls, primarily because requirements and customers change. It becomes a point where, its not really the code that's the issue, its design and customers' changing requirements.
Are you saying that Rust is always the right choice for any problem? If not what’s the link between the merits of any technology and the guarantee that the selection was not resume driven?
To be honest, I agree with you, and I think this is the right approach to life if you have a strong preference for languages. I think this only gets a bad name when people aren't upfront about their preferences and skills, with a lot of people having bad experiences with a go zealot at some point.
It seems the zealotry here is not coming from the Go and Rust people, though. From another message, your measure of presence of zealots is by the amount of "HN titles".
Rewriting something in Go or Rust and announcing it is not being a Zealot.
Being enthusiastic about something shouldn't be a cause for us to judge them like this. We should be happy about them.
I've seen the exact same pattern play out with different tools. The team used a shiny new immature platform for nice sounding reasons and then spent 80% of their time reinventing wheels that have already been solved in any number of places.
I have lot of sympathy for resume-driven developers. They're just answering to the labor market. More power to them.
When companies do what the market expect we praise them. When it's workers, we scorn them. This attitude is seriously fucked up.
When companies start hiring based on experience, adaptability, curiosity, potential and curiosity then you get to complain. Until that, anyone doing it should be considered a fucking genius.
I don't think it's wrong to blame people who make life more difficult for others for their own aggrandizement
The game doesn't exist without players. I could make more money if I worked at Meta or Amazon, but at what cost?
I understand the realities of Game Theory, but then one could argue that being blamed and criticized for one's choices is also part of the game.
"Mr Wolfcastle, how do you sleep at night?" "On a big pile of money with many beautiful ladies"
You are more likely to leave tech/full time employment after working at a FAANG. Either you made enough,it burnt you out, everywhere else seems down, etc. You go to another FAANG or try a startup or leave altogether.
> I don't think it's wrong to blame people who make life more difficult for others for their own aggrandizement
It is, and this is highly judgmental and offensive. Nobody is doing this for "aggrandizement".
Also, all of this is just rationalization, and will keep being until:
1) People start blaming companies for not having the spine to say no to misguided projects by employees.
2) People start blaming Companies for not having the spine to hire people based on past experiences with the craft of programming itself, but rather asking them to have a certain box ticked in their CV.
If one wants to program in X in order to better feed their family and the market says they need to have used X professionally, it is in their right to do X at the workplace.
This is not only expected of them, this is how the whole industry is set up.
For maximizing their gains in spite of wider consequences? Why? I thought that was genius level behavior in your book.
Why do you feel compelled to denounce this behavior on one side and praise it on another? That seems to be the very hypocrisy that you are shaking your fists against.
Where I'm from, the recruiters often use dumb questions like "How many years of experience do you have with X?" where any answer below their threshold is an immediate ground for rejection.
Learning new technologies on the go is pretty much the standard, but it's something that employers don't understand.
We have those! Turn up, make some micro-services or AWS crap pile we don’t need to solve a simple problem, then fuck off somewhere else and leave everyone else to clean it up.
Worst one is the data pipeline we have. It’s some AWS lambda mess which uses curl to download a file from somewhere and put it into S3. Then another lambda turns up at some point and parses that out and pokes it into DynamoDB. This fucks up at least once a month because the guy who wrote the parser uses 80s BASIC style string manipulation and luck. Then another thing reads that out of DynamoDB and makes a CSV (sometimes escaped improperly) and puts that into another bucket.
I of course entirely ignore this and use one entire line of R to do the same job
Along comes a senior spider and says “maybe we can fix all these problems with AI”. No you can stop hiring acronym collectors.
I had not encountered the phrase kidding-on-the-square before. Searching seems to reveal a spectrum of opinions as to what it means. It seems distinct to the 'It's funny because it's true' of darker humour.
It seems to be more on a spectrum of 'Haha, only joking' where the joke teller makes a statement that is ambiguously humorous to measure the values of the recipients, or if they are not sure of the values of the recipients.
I think the distinction might be on whether the joke teller is revealing (perhaps unintentionally) a personal opinion or whether they are making an observation on the world in general, which might even imply that they hold a counter-opinion.
Anyway, why does Microsoft bottleneck itself when it could have 10 different AI teams. That's why 10 new AI startups can achieve what these behemoths can't.
Microsoft already suffers from lack of software consolidation. It costs a lot of money to maintain 10 different tech stacks. Not to mention having separate security/privacy review processes for each.
We are talking multitrillion company here, money shouldn't be an issue. Though you prove my point, they lack coordination. Also AI lacks coordination and strategy and won't solve BigTech management problems any time soon. Best they can try is providing tools trying to capture what others, that are actually inventive, can do. That's why they will stay at Azure level.
> There is a prominent subset of the tech crowd who are ladder climbers - ruthlessly pursuing what is rewarded with pay/title/prestige without regard to actually making good stuff.
I think the hiring and reward practices of the organizations & the industry as a whole also encourages this sort of behavior.
When you reward people who are switching too often or only when moving internally/externally, switching becomes the primary goal and not the product. If you know beforehand that you are not going to stay long to see it through, you tend to take more shortcuts and risks that becomes the responsibility of maintainers later.
We have a couple of job hoppers in our org where the number of jobs they held is almost equal to their years of experience and their role is similar to those with twice the experience! One can easily guess what their best skill is.
Ideally it's the responsibility of management, starting at the top, to think critically about what kind of software most benefits the company and reward those that do it. Unfortunately, it's much harder to sell "amazing documentation and test coverage" to a CEO than "Gen AI wrapper that doesn't really do much", so here we are.
> Ideally it's the responsibility of management, starting at the top, to think critically about what kind of software most benefits the company and reward those that do it. Unfortunately, it's much harder to sell "amazing documentation and test coverage" to a CEO than "Gen AI wrapper that doesn't really do much", so here we are.
What do you think these technical ladder climbers become..? Technical leadership. The truth is, there’s no one technical in big tech leadership. They pay lip service to “tech” to keep up appearances and to satisfy the pleebs that work under them. The only things leadership cares about is the stock price and profitability, literally nothing else matters. If anything the tech itself is a nuisance that pulls their attention from where they’d rather have it, which is anywhere else.
> Ideally it's the responsibility of management, starting at the top, to think critically about what kind of software most benefits the company and reward those that do it.
I work as if that ideal is true, and can’t stand playing the game. But others are still playing the game and eventually they win whatever B.S. position it is that they aspire to, and I get removed from the board.
Create incentives that managers will be responsible for a very long time for a system/product that they create; with barely any chance to get out of it. Give them a malus (opposite of "bonus"; except in rare exceptional cases) if they "project hop".
If a particular kind of "career managers" hate this system (and perhaps thus quit): great.
Why does promotion need a new feature? Reward for maintenance over time. Build on existing features / components. Reward for helping and up-skilling others.
Especially at some of these bigger tech companies that have been around multiple decades. Im not a huge fan of Microsoft and their products. But man, you know there are probably a few hundred engines who are the bedrock of the company, if they disappeared tomorrow, Microsoft would probably be screwed. They probably work on the products and on areas you never hear about that never get flashy headlines. They are the people keeping the guts of Windows and all their multi-decade projects still pumping. Answering and fixing bug reports on these products.
This approach is notable for benefitting from swelling headcount increases
i.e. if you hire 1000 new people, even if only a small fraction will vouch for you, on average you -and everyone else- will benefit by seeing the # of people who listed you in the "top 5 who helped you being productive" increase
The old Google performance review was arguably similar (the managers could still punish their reports, but peer feedback was valued a lot more), but I think that Google swelled in size because of other effects (probably because managers might've been indirectly rewarded by having more reports, despite managers rarely being among the people who others would list as "making you more productive")
Dont offer excessive money. Money is like shit whose smell attracts flies. The more money starts entering the system, the more flies come in. The more flies, the more rigorous the vetting process. That's where the infamous google hiring system started kicking in.
This is what founders say right before they offer you 0.05% of their company and try to sell you on the idea that of course it's worth it because clearly the company will be worth $100B someday!
Google kills off projects because the legal liability and security risks of those projects becomes too large to justify for something that has niche uses or gives them no revenue. User data is practically toxic waste.
As an outsider looking at Microsoft, I've always been impressed by the attention to maintaining legacy APIs and backward compatibility in the Windows ecosystem. In my mind, Microsoft is at the opposite end of the killedbygoogle.com spectrum. However, none of this is grounded in real evidence (just perception). Red Hat is another company I'd put forth as an example of a long-term support culture, although I don't know if that's still true under IBM.
I'd love to know if my superficial impression of Microsoft's culture is wrong. I'm sure there's wild variance between organizational units, of course. I'm excluding the Xbox/games orgs from my mental picture.
Joel Spolsky wrote about this. Windows division (WinDiv) is as you say, development tools division (DevDiv) is framework of the week. How many APIs have not-actually-replaced Win32 so far? They do keep the old ones working though, I guess.
Those mostly aren't counter-examples though. In most cases they supported them long after most people had stopped using them. Google is notorious for killing popular products.
Well, Skype is the only one I'd miss, and after years of neglect I won't cry after it either. As for IE - good riddance. They could add Teams and Sharepoint to that list as far as I'm concerned.
So maybe the difference is that Google kills projects that people love, while MS only kills unloved ones?
Thats nothing during peak ZIRP people would move tech companies before the launch (or after a project was cancelled) and still ladder climb. "Failing upwards"
On the other hand
"innovators left at launch and passed it off to the maintenance team" alone must not be a bad thing.
Innovator types are rarely maintainer types and vice versa.
In the open-source world look at Fabrice Bellard for example. Do you think he would have been able to create so many innovative projects if he had to maintain them too?
One of my friends stated this phenomenon very well “it’s a lever they can pull so they do it”. Once you’ve tied your career to a specific technology internally, there’s really only one option: keep pushing it regardless of any alternatives because your career depends on it. So that’s what they do.
Unfortunately I don't think there is any real metric-based way to prevent this type of behavior, it just has to be old fashioned encouraged from the top. At a certain size it seems like this stops scaling though
Does it not make sense to not tie your future to a third-party (aka build your business on someone else's platform)? Seems like basic strategy to me if that's the case.
It's a good strategy. It should be obvious to anyone paying attention that OpenAI doesn't have AGI secret sauce.
LLMs are a commodity and it's the platform integration that matters. This is the strategy that Google, Apple embraced and now Microsoft is wisely pivoting to the same.
If OpenAI cares about the long-term welfare of its employees, they would beg Microsoft to acquire them outright, before the markets fully realize what OpenAI is not.
I mean, they have been doing platform integration for a while now, with all the copilot flavors and teams integrations, etc. This would change the backend model to something inhouse.
It's the responsibility of leadership to set the correct goals and metrics. If leadership doesn't value maintenance, those they lead won't either. You can't blame people for playing to the tune of those above them.
This is exactly right. If resume driven development results in more money, people are (rightly) going to do it. The incentive structure isn't set by the ICs.
OpenAI already started divorce proceedings with their datacenter partnership with Softbank/etc, and it'd hardly be prudent for the world's largest software company NOT to have it's own SOTA AI models.
Nadella might have initially been caught a bit flat footed with the rapid rise of AI, but seems to be managing the situation masterfully.
In what world is what they are doing masterful? Their product marketing is a huge mess, they keep changing the names of everything every few months. Nobody knows which Copilot does what anymore. It really feels like they're scrambling to be first to market. It all feels so incredibly rushed.
Whatever is there doesn't work half the time. They're hugely dependent on one partner that could jump ship at any moment (granted they are now working to get away from that).
We use Copilot at work but I find it very lukewarm. If we weren't a "Microsoft shop" I don't think would have chosen it.
> Their product marketing is a huge mess, they keep changing the names of everything every few months. Nobody knows which Copilot does what anymore. It really feels like they're scrambling to be first to market. It all feels so incredibly rushed.
Product confusion, inconsistent marketing, unnecessary product renames, and rushing half-baked solutions has been the Microsoft way for dozens of products across multiple divisions for years.
Rule #1 for Microsoft product strategy: if you can't yourselves figure out the SKUs and how they bundle together, the odds are good that your customers will overpay. It's worked for almost 50 years and there's no evidence that it will stop working. Azure is killing it and will continue to eat the enterprise even as AWS starts/continues to struggle.
They got access to the best AI to offer to their customers on what seems to be very favorable terms, and bought themselves time to catch up as it now seems they have.
GitHub Copilot is a success even if Microsoft/Windows Copilot isn't, but more to the point Microsoft are able to offer SOTA AI, productized as they see fit (not every product is going to be a winner) rather than having been left behind, and corporate customers are using AI via Azure APIs.
This is a great strategic decision, because it puts Suleyman's head squarely on the chopping block. Either Microsoft will build some world dazzling AI whatsit or he'll have to answer, there's no "strategically blame the vendor" option. It also makes the accounting transparent. There's no softbank subsidy, they've got to furnish every dollar.
So hopefully if (when?) this AI stuff turns out to be the colossal boondoggle it seems to be shaping up to be, Microsoft will be able to save face, do a public execution, and the market won't crucify them.
> it'd hardly be prudent for the world's largest software company NOT to have it's own SOTA AI models.
If I recall correctly, Microsoft’s agreement with OpenAI gives them full license to all of OpenAI’s IP, model weights and all. So they already have a SOTA model without doing anything.
I suppose it’s still worth it to them to build out the experience and infrastructure needed to push the envelope on their own, but the agreement with OpenAI doesn’t expire until OpenAI creates AGI, so they have plenty of time.
Ah man I don't want to hear things like that. I work in an Angular project and it is the most pleasant thing I have worked with (and i've been using it as my primary platform for almost a decade now). If I could, i'd happily keep using this framework for the rest of my career(27 years to go till retirement).
A hugely underrated platform. Thankfully at least for now Google is leaving the Angular team alone and the platform has really matured in wonderful and beautiful ways.
If you like TypeScript, and you want to build applications for the real world with real users, there is no better front end platform in my book.
> but I wonder how much of this initiative and energy is driven by people at Microsoft who want their own star to rise higher than it can when it's bound by a third-party technology.
I guess it's human nature for a person or an org to own their own destiny. That said, the driving force is not personal ambition in this case though. The driving force behind this is that people realized that OAI does not have a moat as LLMs are quickly turning into commodities, if haven't yet. It does not make sense to pay a premium to OAI any more, let alone at the cost of not having the flexibility to customize models.
Personally, I think Altman did a de-service to OAI by constantly boasting AGI and seeking regulatory capture, when he perfectly knew the limitation of the current LLMs.
This is absolutely a too-cynical position. Nadella would be asleep at the wheel if he weren’t actively mitigating OpenAI’s current and future leverage over Microsoft.
This would be the case even if OpenAI weren’t a little weird and flaky (board drama, nonprofit governance, etc), but even moreso given OpenAI’s reality.
And why not? should he just allow the owners of capital to extract as much value as possible without actually doing anything, but woe be the worker if he actually tries to free himself.
Most directors and above at Google are more concerned with how they will put gas in their yachts this weekend than the quality of the products they are supposed to be in charge of.
A couple of days ago it leaked that OpenAI was planning on launching new pricing for their AI Agents. $20K/mo for their PhD Level Agent, $10K/mo for their Software Developer Agent, and $2K/mo for their Knowledge Worker Agent. I found it very telling. Not because I think anyone is going to pay this, but rather because this is the type of pricing they need to actually make money. At $20 or even $200 per month, they'll never even come close to breaking even.
That is just not correct. As someone who has done the budgets for PhD hiring and funding, you are just wildly underestimating the overhead costs, benefits, cost of raising money, etc.
The "3-5" is certainly overstated, but you definitely can hire ONE PhD for that price, just as you can hire a SWE for $120K or a knowledge worker for $24K. The point is that from a CEO's perspective "replacing all the humans with AI" looks a lot less compelling when the AI costs the same as a human worker or even a significant fraction of a human worker.
Again, irrelevant. We're talking about orders of magnitude here. Current pricing is in line with most SaaS pricing - tens of dollars to hundreds of dollars per seat per month. Now they're suddenly talking about thousands of dollars to tens of thousands of dollars per seat per month.
Being able to control their every move, scale them to whatever capacity is required, avoid payroll taxes, health plans and surprise co-pay costs, equity sharing, etc might make this worthwhile for many companies.
That said, the trade-off is that you're basically hiring consultants since they really work for OpenAI :)
The benefit to an emoloyee is that you don't have to control their every move. They can do work while you aren't even thinking about the problem they are solving.
$20k can't get you that many PhD. Even PhD students, who's nominal salary is maybe $3-5k a month, effectively costs double that because of school overhead and other stuff.
Based on ubiquitous AI trainer ads on the internet that advertise their pay, they probably make <=$50/hr training these models. Trainers are usually remote and set their own hours, so I wouldn’t be surprised if PhDs are not making much as trainers.
> $20k can't get you that many PhD. Even PhD students, who's nominal salary is maybe $3-5k a month, effectively costs double that because of school overhead and other stuff.
But you are not getting a PhD worker for 20K with "AI", that's just marketing.
Does depend on where your PhD lives and what subject their PhD is in from where, and how many hours of work you expect them to do a week, and whether you need to full-time "prompt" them to get them to function...
Would definitely rather have a single postdoc in a relevant STEM subject from somewhere like Imperial for less than half the overall cost than an LLM all in though. And I say that despite seeing the quality of the memes they produce with generative AI....
Pedantic, but they are top of the market in neither since Switzerland is not in the EU, and definitely not in the UK.
But it is true that in Europe, Switzerland PhDs (and professors too) make most. Not just ETH/EPFL as well. UZH (Uni Zurich) has salaries of 50K CHF per year for PhD candidates (with increments every year) -- that's almost 60K USD by your fourth year. This is also true for other universities. And while Zürich is expensive, it is not _that_ expensive.
Depends on 1) where the university is located (CoL), 2) if they went on strike recently to get paid enough to pay rent.
You can reliably assume that PhD wages must eventually converge to the rent of a studio apartment nearby + a little bit (which may or may not be enough to cover all other expenses. Going into debt is common.)
Depends on what these PhDs are supposed to do. Also is this an average Phd or a brilliant PhD level? There is a huge spectrum of PhDs out there. I highly doubt these phd level models are able to solve any problems in a creative way or discover new things other than regurgitating the knowledge they are trained on.
That no one is offering this says something very profound to me. Either they don't work and are too risky to entrust a company to, or leadership thinks they are immune and are entitled to wield AI exclusively, or some mix of these things.
The banter is actually quite easy to automate. You can hire a human to play golf for a small fraction of what the CEOs get paid, and then it's best of both worlds.
Steve Jobs said something to the effect that he made maybe three CEO decisions a year. I mean, I think these are decisions like, "We're going to open our own line of Apple retail stores", but, still.
Being a CEO isn’t all that different from being a parent of a child from the POV of impactful decisions.
How many critical “parental decisions” have you made in the past week? Probably very few (if any), but surely you did a lot of reinforcement of prior decisions that had already been made, enforcing rules that were already set, making sure things that were scheduled were completed, etc.
Important jobs don’t always mean constantly making important decisions. Following through and executing on things after they’re decided is the hard part.
Is it? Take a look at the bot accounts filling up social media (the non-obvious ones). It wouldn't seem to hard to make one that makes 2am posts about '[next product] feels like real AGI' or tells stock analysts that their questions are boring on an earnings call, which is apparently what rockstar CEOs do.
Sneers aside, I think one common mis-assumption is that the difficulty of automating a task depends on how difficult it feels to humans. My hinge is that it mostly depends on the availability of training data. That would mean that all the public-facing aspects of being a CEO should by definition be easy to automate, while all the non-public stuff (also a pretty important part of being a CEO, I'd assume) should be hard.
what about politician level models? i wonder if politicians aren't all copy pasting their stuff from chatgtp right now, at this stage (that would make a nice conspiracy theory, wouldn't it?)
If truly equivalent (which LLMs aren't, but I'll entertain it), that doesn't seem mathematically out of line.
Humans typically work 1/3rd duty cycle or less. A robot that can do what a human does is automatically 3x better because it doesn't eat, sleep, have a family, or have human rights.
So this is just going to end up like AWS where they worked out exactly how much it costs me to run a physical server and charge me just slightly less than that?
Thats pretty useless for most applications though. If you're hiring a phd level person you dont care that if in addition to being great in contract law they're also great in interior design.
I disagree. People are so hyper ultra mega specialized these days the cross pollination should be very helpful. Isn’t that the theory behind why so much amounts of training data makes these models better?
Do you have to pay all sorts of overhead and taxes?
I mean, I don't think it's real. Yet. But for the same "skill level", a single AI agent is going to be vastly more productive than any real person. ChatGPT types out essays in seconds it would take me half an hour to write, and does it all day long.
Even worse: AFAIK there's no reason to believe that the $20k/mo or $10k/mo pricing will actually make them money. Those numbers are just thought balloons being floated.
Of course $10k/mo sounds like a lot of inference, but it's not yet clear how much inference will be required to approximate a software developer--especially in the context of maintaining and building upon an existing codebase over time and not just building and refining green field projects.
Man. If I think about all of the employee productivity tools and resources I could have purchased fifteen years ago when nobody spent anything on tooling, with an inflation adjusted $10K a month and it makes me sad.
We were hiring more devs to deal with a want of $10k worth of hardware per year, not per month.
Do you have a source for these supposed leaks? Those prices don't sound even remotely credible and I can't find anything on HN in the past week with the keywords "openai leak".
There is too little to go on, but they could already have trial customers and testimonials lined up. Actually demoing the product will probably work better than just having a human-less signup process, considering the price.
They could also just be trying to cash in on FOMO and their success and reputation so far, but that would paint a bleak picture
Never come close to breaking even? You can now get a GPT-4 class model for 1-2% of what it cost when they originally released it. They’re going to drive this even further down with the amount of CAPEX pouring into AI / data centers. It’s pretty obvious that’s their plan when they serve ChatGPT at a “loss”.
What is interesting is there is no mention of agents on any job I clicked on. You would think "orchestrating a team of agents to leverage blah blah blah" would be something internally if talking about these absurd price points.
Microsoft's corporate structure and company culture is actively hostile to innovation of any kind. This was true in Ballmer's era and is equally true today, no matter how many PR wins Nadella is able to pull off. The company justifies its market cap by selling office software and cloud services contracts to large corporations and governments via an army of salespeople and lobbyists, and that is what it will continue to be successful at. It got lucky by backing OpenAI at the right time, but the delusion of becoming an independent AI powerhouse like OpenAI, Anthropic, Google, Meta etc. will never be a reality. Stuff like this is simply not in the company's DNA.
you are right, Microsoft is a hodge podge of legacy on-premise software, legacy software lifted and shifted to the cloud, and some innovation pockets.
Microsoft bread and butter is Enterprise bloatware and large Enterprise deals where everything in the world is bundled together for use-it-or-lose-it contracts.
Its not really much different from IBM like a two decades ago
It does seem though that this legacy-cloud-pocket-innovation combination continues to work without slowing down. It also what was said for Microsoft 15 years ago too (not really much different from IBM..), which is correct from one perspective, but not turning out true from revenue, market cap, growth terms.
My thinking is that Lindy Effect runs strong in a lot of Big Tech, and with deep pockets, they can afford to not be innovators but build moats on existing frameworks.
How does one define an AI powerhouse? If its building models, a smart business wouldn't bank on that alone. There is no moat.
If the definition of an AI Powerhouse is more about the capability to host models and process workloads, Amazon (the other company missing in that list) and Microsoft are definitely them.
OpenAI will in the end be aquired for less than its current valuation. Initially, I've been paying for Claude (coding), Cursor (coding), OpenAI (general, coding), and then started paying for Claude Code API credits.
Now I canceled OpenAI and Claude general subscriptions, because for general tasks, Grok and DeepSeek more than suffice. General purpose AI will unlikely be subscription-based, unlike the specialized (professional) one.
I'm now only paying for Claude Code API credits and still paying for Cursor.
Claude Code is another level, because it's agentic. It iterates. Although it keeps you further from the codebase than Cursor and thus you may lose the grasp of what it generates- that's why I still use Cursor, before the manual review.
Microsoft is just so bad at marketing their products, and their branding is confusing. Unfortunately, until they fix that, any consumer facing product is going to falter. Look at the new Microsoft 365 and Office 365 rebrands just of late. The business side of things will still make money but watching them flounder on consumer facing products is just so frustrating. The Surface and Xbox brand are the only 2 that seem to have somewhat escaped the gravity of the rest of the organization in terms of that, but nothing all that polished or groundbreaking has really come out of Microsoft from a consumer facing standpoint in over a decade now. Microsoft could build the best AI around but it doesn't matter without users.
Yeah, the office suite is such a cash cow. It is polished, feature rich, and ubiquitous compared to alternatives and somehow has remained so for decades. And yet, I'm increasingly getting seriously concerned they are going to break it so badly I'll need to find an alternative.
I get that "growth" must be everything or whatever, but can't a company just be stable and reliable for a while? What's wrong with enterprise contracts and more market penetration for cloud services of (oftentimes) dubious use?
Softbank’s Masa’s magic is convincing everyone, every time, that he hasn’t consistently top ticked every market he’s invested in for the last decade. Maybe Satya’s finally broken himself of the spell [1].
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[ 3.2 ms ] story [ 137 ms ] threadThere are really not that many things in this world you can swap as easily as models.
Api surface is stable and minimal, even at the scale that microsoft is serving swapping is trivial compared to other things they're doing daily.
There is enough of open research results to boost their phi or whatever model and be done with this toxic to humanity, closed, for profit company.
Which is easier when maintaining an LLM business process, swapping in the latest model or just leaving some old model alone and deferring upgrades?
Swapping is easy for ad hoc queries or version 1 but I think there's a big mess waiting to be handled.
While we still live in a datacenter driven world, models will become more efficient and move down the value chain to consumer devices.
For Enterprise, these companies will need to regulate model risk and having models fine-tuned on proprietary data at scale will be an important competitive differentiator.
Investing in second/third place likely valuable at similar scales too
But outside of that MSFTs move indicates that frontier models most valuable current use case - enterprise-level API users - are likely to be significantly commoditized
And likely majority of proceeds will be captured by (a) those with integrated product distribution - MSFT in this case and (b) data center partners for inference and query support
Computationally, some might have access to it earlier before it’s scalable.
It’s moats that capture most value not short term profits.
Each remaining barrier has been steadily falling.
All the LLM tech so far still requires a human to actually prompt them.
There are no solutions even at the small scale. We fundamentally don't understand what it is or how to do it.
If you could solve it perfectly on Mnist just scale and then we get AGI.
The hype cycle for tech people is like a light bulb for a moth. We’re attracted to potential, which is both our superpower and kryptonite.
Wouldn't it amaze you if you learned 10 years ago that we would have AI that could do math and code better than 99% of all humans. And at the same time they could barely order you a hotdog on doordash.
Fundamental ability is lacking. AGI is just as likely to be solved by Openai as it is by a college student with a laptop. Could be 1yr or 50yrs we cannot predict when.
That said, your second paragraph is one of the best and most succinct ways of pointing out why current LLM's aren't yet close to AGI if though they sometimes feel like it's got the right idea.
RAG is a basically a perfect example to understand the limits of in context learning and AI in general. It's faults are easier to understand but the same as any AI vs AGI problem.
I could go on but CL is a massive gap of our knowledge and likely the only thing missing to AGI.
How? RAG is not even in the field of AI.
I tried to solve this via expanding the embedding/retrieval space but realized it's the same as CL and in my definition of it I was trying to solve AGI. I did a lot of unique algorithms and architectures but Unsuprisingly, I never solved this.
I am thankful I finally understood this quote.
"The first gulp from the glass of natural sciences will turn you into an atheist, but at the bottom of the glass God is waiting for you."
Zima blue was good too
Logjammin AI
See Thomas Nagels classic piece for more elaboration
https://www.sas.upenn.edu/~cavitch/pdf-library/Nagel_Bat.pdf
https://techcrunch.com/2024/12/26/microsoft-and-openai-have-...
> Microsoft and OpenAI have a very specific, internal definition of artificial general intelligence (AGI) based on the startup’s profits, according to a new report from The Information. And by this definition, OpenAI is many years away from reaching it.
Fortunately, they're not anywhere near creating this. I don't think they're even on the right track.
Microsoft is the IBM of this century. They are conservative, and I think they’re holding back — their copilot for government launch was delayed months for lack of GPUs. They have the money to make that problem go away.
That is, integrating use of their own model, amplifying capability via OpenAI queries.
Again, this is not to drum up the actual quality of the product releases so far--they haven't been good--but the foundation of "we'll try to rely on our own models when we can" was the right place to start from.
There is a moat in infra (hyperscalers, Azure, CoreWeave).
There is a moat in compute platform (Nvidia, Cuda).
Maybe there's a moat with good execution and product, but it isn't showing yet. We haven't seen real break out successes. (I don't think you can call ChatGPT a product. It has zero switching cost.)
Just look at how much money Google lost in that failed AI demo from 2003.
The stock would be worth 50% less if the invested nothing in AI. Even the founders are back because of it.
If anyone has moat related to Gen AI, I would say it is the data(Google, Meta).
It's not an act of will or CEO dictat. It's about hiring and incentivising the right people, putting the right structures in place etc all in the face of competing demands.
Nvidia have a huge head start and by the time AMD have 'caught up' Nvidia with it's greater resources will have moved further ahead.
OpenAI brings absolutely nothing unique to the table.
There is as yet no indication that AMD can match Nvidia's execution for the very good reason that doing so is extremely difficult. The head start is just the icing on the cake.
Taking code that runs against one hosted LLM and running it against a different backend LLM is... not generally a big deal. So OpenAI being ahead—in the core model, at least—is just being ahead, its not a moat.
- a large and growing ecosystem
- a massive installed base of backwards compatible hardware
- the ability to massively scale delivery of new systems
- and lots lots more
They now have scale that enables them to continue to invest at a level that no competition can do.
None of these are easily reproduced.
As per SemiAnalysis AMD in late 2024 can’t get essential software working reliably out of the box.
It’s easy to say AMD ‘is close to perfecting ROCM’ the reality of competing with Nvidia is much harder.
There are open source projects volunteer run projects[1] that are better than official AMD implementation in many ways.
[1]: https://github.com/CHIP-SPV/chipStar/
ChatGPT was announced Nov 22. The opportunity has been clear for two years and still essential software breaks.
In consumer markets the moat is habits. The switching cost for Google Search is zero. The switching cost for Coke is zero. The switching cost for Crest toothpaste is zero. Yet nobody switches.
https://corporatefinanceinstitute.com/resources/management/e...
The size of a moat befits the size of a castle it protects. Coke absolutely has a moat, but it's not big enough to defend Coke as a trillion dollar company.
The question isn't whether OpenAI has a moat or not, it's if its current moat is big enough to protect a trillion-dollar company.
1. The switching cost from Google Search is certainly not zero, it implies switching from Google, which is virtually impossible because it's tied to Chrome, YouTube, Android and Gmail
2. I don't know many people who are dedicated "Pepsi" fans, they just grab whatever drink is available Coke/Pepsi..
3. I've also not heard many people who are never willing to switch from "Crest".. People will just grab the next available option if Crest is not on shelf. No one is pre-ordering Crest.
> 1. The switching cost from Google Search is certainly not zero, it implies switching from Google, which is virtually impossible because it's tied to Chrome, YouTube, Android and Gmail
Google Search is a product. Not the whole company. Switching to most other search engines is $0. Naturally no one is honor bound to use anything else you listed either.
Pepsi makes more revenue compared to Coke. Shouldn't it be Coke who should be trying to do what Pepsi is doing?
0: https://www.wfaa.com/article/news/local/us-soda-rankings-cok... 1: https://www.investopedia.com/ask/answers/060415/how-much-glo...
Ironically if AI companies are actually able to deliver in terms of SWE agents, Nvidia's moat could start to disappear. I believe Nvidia's moat is basically in the form of software which can be automatically verified.
I sold my Nvidia stock when I realized this. The bull case for Nvidia is ultimately a bear case.
Look at Coca Cola, Google, both have plausible competitors, zero switching cost but they maintain their moat without effort.
Being first is still a massive advantage. At this point they should only strive to avoid big mistake and they're set.
AI is still not there yet, and if any model becomes significantly better than ChatGPT people will flock over to use it despite the branding. It's only when nobody can make better models, then people will just stick to the known brands.
There is even deepseek on there.
Then I read the article.
Plotting for a future without Microsoft.
Suleyman’s team has also been testing alternatives from companies like xAI, DeepSeek, and Meta
MS wants to push Copilot, and will be better off not being tied to OpenAI but having Copilot be model agnostic, like GH Copilot can use other models already. They are going to try and position Azure as "the" place to run your own models, etc.
Definitely, but I think it's because they saw OpenAI's moat get narrower and shallower, so to speak. As the article mentions it's still looking like a longer timeline [quote] "but Microsoft still holds exclusive rights to OpenAI’s models for its own products until 2030. That’s a long timeline to unravel."
I feel like this is something I've seen a fair amount in my career. About seven years ago, when Google was theoretically making a big push to stage Angular on par with React, I remember complaining that the documentation for the current major version of Angular wasn't nearly good enough to meet this stated goal. My TL at the time laughed and said the person who spearheaded that initiative was already living large in their mansion on the hill and didn't give a flying f about the fate of Angular now.
There are countless kidding-on-the-square jokes about projects where the innovators left at launch and passed it off to the maintenance team, or where a rebrand was in pursuit of someone's promo project. See also, killedbygoogle.com.
Even good honest motivated people can become checked out without even being aware of it.
The alternative is to lay off people as soon as they hit 1.0 (with a severance bonus on the scale of an acquisition). This would obviously be worse, as you can’t take advantage of their institutional knowledge.
You can go the hatchet way - I am strongly unconvinced it is indicative of anything resembling good management, mind - but most people and companies cannot rely on banks or investment firms loaning them 40 billion dollars and accepting passively a mark down of their mone~ to 1/4 of the value they loaned down the line. CEOs are ousted by investment firms for a far smaller drop in value all the time.
I agree with everything you said, though.
If you’re an exec who’s taken it upon themselves to evaluate, could use the hatchet, or you take some amount of time to figure out how things work. Whether this is okay depends on who is suffering the externalities. If it’s a private corporation, legally it’s the execs + employment law. If it’s a public service that measures toxin levels in water, uhhhhh.
No one works for any BigTech company because they think they are making the world a better place. They do it because a shit ton of money appears in their bank account every pay period and stock appears in their brokerage account every vesting period.
I personally don’t have the shit tolerance to work in BigTech (again) at 50. But I suggest to all of my younger relatives who graduate in CS to “grind leetCode and work for a FAANG” and tell them how to play the politics to get ahead.
As the Dilbert author said, “Passion is Bullshit”. I have never been able to trade passion for goods and services.
I'm sure there are plenty of people who work at big companies for precisely this reason (or at least, with that as _a_ reason among many).
Yes, much of the prestige has worn off as the old guard retired and current leadership emphasizes chasing AI buzzwords and cutting costs. But still, big companies are one of the few places where an individual really can point out something they worked on in day-to-day life. (Pull out any Android phone and I can show you the parts that my work touched.)
And it takes a while for a young dev to register that the goals that the larger organization pursues are going to win out in the end anyway.
It's always the same. People trying to make things better for the next developer, people prioritizing delivers instead of ego-projects or ego-features by someone playing politics, developers wanting a seat at the table with (dysfunctional) Product teams, people actual good intentions trying to "change the world" (not counting the misguided attempts here).
You are 100% correct, you gotta play the politics, period.
Congratulations, you’ve invented the HR department in corporate America.
The better the pay, the more you will attract the people who are there for the pay first and making good products ... second or third or never. How do you combat that?
Case in point: Tesla/SpaceX meets your first criteria: "I want a tech company where people are there to make good products first and get paid second."
Google meets your second criteria: "And the pay should be good. The lifestyle comfortable. No grindset bullshit."
Other than small time boutique software firms like Fog Creek Software or Panic Inc(and thats a BIG maybe) you are not going to get this part of your message: "But I am confident that if you only employ passionate people working their dream jobs you will excel."
There are tradeoffs in life and each employee has to choose what is important to them(and each company CEO has to set standards on what is truly valued at the company).
Tesla has never been a good product.
https://insideevs.com/news/731559/tesla-least-reliable-used-...
https://www.carscoops.com/2024/11/tesla-model-3-comes-bottom...
https://www.topspeed.com/tesla-reliability-and-repair-costs-...
Not to mention the infotainment system is much worse than CarPlay/Android Auto compatible cars
This is too funny to post alongside saying “Tesla has never been a good product.” Like “everyone that bought it loves it be car expert Joe from South Dakota ranks them very low.”
Common sense also runs very much against this nonsense narrative - you just simply do not sell that many cars, at those prices especially, year after year after year, if the product is subpar. Don’t fall for this “experts” bullshit. The CEO is the biggest tool this Earth has ever seen but cars are awesome
On another note, Apple also sold millions of MacBooks with butterfly keyboards.
And Tesla sells are declining, losing market share worldwide and sells 1/5 the number of cars as Toyota
and if you gonna compare tesla to toyota you should compare number of EV sales, not overall sales :) tesla is not a car company, it is (among other things if you care to believe Elon bullshit) EV car company. comparing toyota to tesla in terms of total sales is like saying “subway doesn’t sell nearly as many bigmacs as mcdonald’s does” :)
Hmm. Can't say I agree here - at least not with the literal text of what you've written (although maybe we agree in spirit). I agree that _simplistic_ strong opinions about languages are a sign of poor thoughtfulness ("<thing> is good and <other thing> is bad") - but I'd very much expect a Staff+ engineer to have enough experience to have strong opinions about the _relative_ strengths of various languages, where they're appropriate to use and where a different language would be better. Bonus points if they can tell me the worst aspects about their favourite one.
Maybe we're using "opinion" differently, and you'd call what I described there "facts" rather than opinions. In which case - yeah, fair!
See, we can all generalize. Not productive.
Only thing I ever saw from Golang devs was pragmatism. I myself go either for Elixir or Rust and to me Golang sits in a weird middle but I've also written 20+ small tools for myself in Golang and have seen how much quicker and more productive I was when I was not obsessed with complete correctness (throwaway script-like programs, small-to-mid[ish]-sized projects, internal tools etc.)
You would do well to stop stereotyping people based on their choice of language.
That's pretty much another way of saying that stuff becomes a whole lot quicker and easier when you end up getting things wrong. Which may even be true, as far as it goes. It's just not very helpful.
FWIW I very much share your exact thoughts on Rust skewing metrics because it makes things too easy and because stuff almost immediately moves to maintenance mode. But that being said, we still have some tasks where we need something yesterday and we can't argue with the shot-callers about it. (And again, some personal projects where the value is low and you derive more of it if you try quickly.)
What do you think all programming discussions about languages, typing systems, runtime, tooling etc. aim for?
EXACTLY THAT.
If it was as easy as "just give me thing" then programming would have been a solved and 100% automated problem long time ago.
Your comment comes across as "if only we could fly, we would have no ground road traffic jams". I mean, obviously, yeah, but we can't fly.
Your comment also comes across a bit elitistic and from the POV of an ivory tower. Don't know if that was your goal, if not, I'd advise you to state things a bit more humbly.
I stated an opinion. You can reject it silently. Having the last word is not such a badass move as many people think. :)
(Mostly .Net, PHP and Ruby)
Even simple requirements can rule out languages for me. Like, if you need async or concurrency, Python is awful. If you need SQL in your code, Golang isn't great. If you are building a simple CRUD backend, Java is waste of time. If you aren't doing anything compute heavy or embedded, why even consider C++ or Rust. The list goes on.
I might personally love to kick off a greenfield project with Elixir, and it might tick all the technical boxes and meet the requirements. But then I have to pay a premium for senior engineers that know elixir or have to price in the time needed to upskill.
Or I could just do it in Rails where I can dip into a much larger talent pool and still meet the requirements. Much more boring but can get the job done just as well.
But in reality it rarely matters. If you were only allowed to use Java as a backend and your competitors could use anything your company would succeed or fail based on marketing and sales. The backend doesn't matter as long as they both have the same features.
I understand developer preference and different languages make things easier and make programming funnier. Languages have different limits.
As you become more senior you realize getting around those limits is part of the magic. If you come on to a project where the existing developer wants to write the backend in javascript because that's what they know I would rather use Javascript then wasting time trying to push a more 'pure' choice. Because in the end I am capable of writing it and what we will be judged on is if it works to achieve an objective not if it was the best language choice when using differentiation.
If speed of execution matters, then the language and tools you use for something also matters.
Hard to take you seriously when you do such weird generalized takes.
While it's a sad fact that fanboys and zealots absolutely do exist, most devs can't afford to be such and have to be pragmatic. They pick languages based on merit and analysis.
You should search for headlines on HN that say "written in Go" or "written in Rust" and then compare that to the number of headlines that say "written in JavaScript" or "written in Kotlin."
I’ve seen the more cynical hype-driven stuff, but it’s inevitably superficial on first glance, where I have seen some real curiosity and exploration in many “Project X - Built In Rust/Go/Cobol/D/Whatever” and I think they’re exploring the dynamics of the language and tooling as much as anything else.
You do seem to say Golang and/or Rust devs are zealots which, if it is indeed what you are saying, is boring and plain false.
I am especially valuable because I am fine reading and writing any of the languages involved. The management likes that, but there's a lot of difficulties solving the tribal problem, as the leads are basically all crazy zealots, and it's not as if purging one or two factions of zealots would avoid further zealotry from the survivors. The fact that I can work across all their tech doesn't make me many friends, as my work across systems shows their arguments have little merit.
For most work, in most cases, most languages are just fine. The completely wrong tool for the job is pretty rare, and the winning argument in most places is "we have the most people that have experience with tool X, or really want to try exciting new thing Y", for whatever the problem is, and whatever X might be.
Rust projects immediately become “done”??? They don’t also having changing requirements and dependencies? Why aren’t everyone at the best shops using it for everything if it massively eliminates work load?
" Version 0.2 - Unstable/buggy/slow unless you use exactly like the example - not going to get updated because I moved on to something else"
Rust is another programming language. It's easier to write code without a certain class of bugs, but that doesn't mean version 0.2 of a casual project is going to be bug-free.
It's easy to have no defects in functionality you never got around to writing because you ran out of time.
Doesn’t look like a con to me :)
I didn’t realise that the only requirement for well-written code is to have an expressive type system and memory safety.
Those people, if they really exist, are right.
Rewriting something in Go or Rust and announcing it is not being a Zealot.
Being enthusiastic about something shouldn't be a cause for us to judge them like this. We should be happy about them.
When companies do what the market expect we praise them. When it's workers, we scorn them. This attitude is seriously fucked up.
When companies start hiring based on experience, adaptability, curiosity, potential and curiosity then you get to complain. Until that, anyone doing it should be considered a fucking genius.
The game doesn't exist without players. I could make more money if I worked at Meta or Amazon, but at what cost?
I understand the realities of Game Theory, but then one could argue that being blamed and criticized for one's choices is also part of the game. "Mr Wolfcastle, how do you sleep at night?" "On a big pile of money with many beautiful ladies"
It is, and this is highly judgmental and offensive. Nobody is doing this for "aggrandizement".
Also, all of this is just rationalization, and will keep being until:
1) People start blaming companies for not having the spine to say no to misguided projects by employees.
2) People start blaming Companies for not having the spine to hire people based on past experiences with the craft of programming itself, but rather asking them to have a certain box ticked in their CV.
If one wants to program in X in order to better feed their family and the market says they need to have used X professionally, it is in their right to do X at the workplace.
This is not only expected of them, this is how the whole industry is set up.
They're just following the rules, period.
For maximizing their gains in spite of wider consequences? Why? I thought that was genius level behavior in your book.
Why do you feel compelled to denounce this behavior on one side and praise it on another? That seems to be the very hypocrisy that you are shaking your fists against.
Learning new technologies on the go is pretty much the standard, but it's something that employers don't understand.
Worst one is the data pipeline we have. It’s some AWS lambda mess which uses curl to download a file from somewhere and put it into S3. Then another lambda turns up at some point and parses that out and pokes it into DynamoDB. This fucks up at least once a month because the guy who wrote the parser uses 80s BASIC style string manipulation and luck. Then another thing reads that out of DynamoDB and makes a CSV (sometimes escaped improperly) and puts that into another bucket.
I of course entirely ignore this and use one entire line of R to do the same job
Along comes a senior spider and says “maybe we can fix all these problems with AI”. No you can stop hiring acronym collectors.
It seems to be more on a spectrum of 'Haha, only joking' where the joke teller makes a statement that is ambiguously humorous to measure the values of the recipients, or if they are not sure of the values of the recipients.
I think the distinction might be on whether the joke teller is revealing (perhaps unintentionally) a personal opinion or whether they are making an observation on the world in general, which might even imply that they hold a counter-opinion.
Where do you see 'kidding on the square' falling?
(apologies for thread derailment)
I think the hiring and reward practices of the organizations & the industry as a whole also encourages this sort of behavior.
When you reward people who are switching too often or only when moving internally/externally, switching becomes the primary goal and not the product. If you know beforehand that you are not going to stay long to see it through, you tend to take more shortcuts and risks that becomes the responsibility of maintainers later.
We have a couple of job hoppers in our org where the number of jobs they held is almost equal to their years of experience and their role is similar to those with twice the experience! One can easily guess what their best skill is.
What do you think these technical ladder climbers become..? Technical leadership. The truth is, there’s no one technical in big tech leadership. They pay lip service to “tech” to keep up appearances and to satisfy the pleebs that work under them. The only things leadership cares about is the stock price and profitability, literally nothing else matters. If anything the tech itself is a nuisance that pulls their attention from where they’d rather have it, which is anywhere else.
I work as if that ideal is true, and can’t stand playing the game. But others are still playing the game and eventually they win whatever B.S. position it is that they aspire to, and I get removed from the board.
If a particular kind of "career managers" hate this system (and perhaps thus quit): great.
Why does promotion need a new feature? Reward for maintenance over time. Build on existing features / components. Reward for helping and up-skilling others.
Reward people based on (# who listed them * average salary of those who listed them).
i.e. if you hire 1000 new people, even if only a small fraction will vouch for you, on average you -and everyone else- will benefit by seeing the # of people who listed you in the "top 5 who helped you being productive" increase
The old Google performance review was arguably similar (the managers could still punish their reports, but peer feedback was valued a lot more), but I think that Google swelled in size because of other effects (probably because managers might've been indirectly rewarded by having more reports, despite managers rarely being among the people who others would list as "making you more productive")
Yes. People are incentivized to do very stupid things to grab this years bonus or promotion.
See Google intentionally degrading search results for example. The resentment and loathing for Google is at all time high.
Google kills off projects because the legal liability and security risks of those projects becomes too large to justify for something that has niche uses or gives them no revenue. User data is practically toxic waste.
I'd love to know if my superficial impression of Microsoft's culture is wrong. I'm sure there's wild variance between organizational units, of course. I'm excluding the Xbox/games orgs from my mental picture.
Zune, Games for Windows Live, Skype, Encarta, CodePlex, Windows Phone, Internet Explorer.
https://killedbymicrosoft.info/
So maybe the difference is that Google kills projects that people love, while MS only kills unloved ones?
However, their documentation and support is really scant.
On the other hand "innovators left at launch and passed it off to the maintenance team" alone must not be a bad thing.
Innovator types are rarely maintainer types and vice versa.
In the open-source world look at Fabrice Bellard for example. Do you think he would have been able to create so many innovative projects if he had to maintain them too?
LLMs are a commodity and it's the platform integration that matters. This is the strategy that Google, Apple embraced and now Microsoft is wisely pivoting to the same.
If OpenAI cares about the long-term welfare of its employees, they would beg Microsoft to acquire them outright, before the markets fully realize what OpenAI is not.
I mean, they have been doing platform integration for a while now, with all the copilot flavors and teams integrations, etc. This would change the backend model to something inhouse.
Nadella might have initially been caught a bit flat footed with the rapid rise of AI, but seems to be managing the situation masterfully.
Whatever is there doesn't work half the time. They're hugely dependent on one partner that could jump ship at any moment (granted they are now working to get away from that).
We use Copilot at work but I find it very lukewarm. If we weren't a "Microsoft shop" I don't think would have chosen it.
Third?
Product confusion, inconsistent marketing, unnecessary product renames, and rushing half-baked solutions has been the Microsoft way for dozens of products across multiple divisions for years.
They got access to the best AI to offer to their customers on what seems to be very favorable terms, and bought themselves time to catch up as it now seems they have.
GitHub Copilot is a success even if Microsoft/Windows Copilot isn't, but more to the point Microsoft are able to offer SOTA AI, productized as they see fit (not every product is going to be a winner) rather than having been left behind, and corporate customers are using AI via Azure APIs.
Does *anyone* want "Copilot integration" in random MS products?
So hopefully if (when?) this AI stuff turns out to be the colossal boondoggle it seems to be shaping up to be, Microsoft will be able to save face, do a public execution, and the market won't crucify them.
If I recall correctly, Microsoft’s agreement with OpenAI gives them full license to all of OpenAI’s IP, model weights and all. So they already have a SOTA model without doing anything.
I suppose it’s still worth it to them to build out the experience and infrastructure needed to push the envelope on their own, but the agreement with OpenAI doesn’t expire until OpenAI creates AGI, so they have plenty of time.
If you like TypeScript, and you want to build applications for the real world with real users, there is no better front end platform in my book.
I guess it's human nature for a person or an org to own their own destiny. That said, the driving force is not personal ambition in this case though. The driving force behind this is that people realized that OAI does not have a moat as LLMs are quickly turning into commodities, if haven't yet. It does not make sense to pay a premium to OAI any more, let alone at the cost of not having the flexibility to customize models.
Personally, I think Altman did a de-service to OAI by constantly boasting AGI and seeking regulatory capture, when he perfectly knew the limitation of the current LLMs.
1) Cost -- beancounters got involved
2) Who Do You Think You Are? -- someone at Microsoft had enough of OpenAI stealing the limelight
3) Tactical Withdrawal -- MSFT is preparing to demote/drop AI over the next 5-10 years
This would be the case even if OpenAI weren’t a little weird and flaky (board drama, nonprofit governance, etc), but even moreso given OpenAI’s reality.
Isn’t that the basis for competition?
OpenAI has not been interesting to me for a long time, every time I try it I get the same feeling.
Some of the 4.5 posts have been surprisingly good, I really like the tone. Hoping they can distill that into their future models.
edit: I see we're actually in agreement, sorry, I read the indentation level wrong.
Does that include all overheads such as HR, payroll, etc?
That said, the trade-off is that you're basically hiring consultants since they really work for OpenAI :)
But you are not getting a PhD worker for 20K with "AI", that's just marketing.
Would definitely rather have a single postdoc in a relevant STEM subject from somewhere like Imperial for less than half the overall cost than an LLM all in though. And I say that despite seeing the quality of the memes they produce with generative AI....
Do they really get paid that much these days?
But it is true that in Europe, Switzerland PhDs (and professors too) make most. Not just ETH/EPFL as well. UZH (Uni Zurich) has salaries of 50K CHF per year for PhD candidates (with increments every year) -- that's almost 60K USD by your fourth year. This is also true for other universities. And while Zürich is expensive, it is not _that_ expensive.
You can reliably assume that PhD wages must eventually converge to the rent of a studio apartment nearby + a little bit (which may or may not be enough to cover all other expenses. Going into debt is common.)
Computer science is rate 5, so 73kCHF the first year, 78kCHF the second, then 83kCHF onwards.
How many critical “parental decisions” have you made in the past week? Probably very few (if any), but surely you did a lot of reinforcement of prior decisions that had already been made, enforcing rules that were already set, making sure things that were scheduled were completed, etc.
Important jobs don’t always mean constantly making important decisions. Following through and executing on things after they’re decided is the hard part.
See also: diet and exercise
This is hard to automatize.
Sneers aside, I think one common mis-assumption is that the difficulty of automating a task depends on how difficult it feels to humans. My hinge is that it mostly depends on the availability of training data. That would mean that all the public-facing aspects of being a CEO should by definition be easy to automate, while all the non-public stuff (also a pretty important part of being a CEO, I'd assume) should be hard.
2. How many such PhD people can it do the work of?
Humans typically work 1/3rd duty cycle or less. A robot that can do what a human does is automatically 3x better because it doesn't eat, sleep, have a family, or have human rights.
Hah! Checkmate AI, that's something you can't do! :D
Do you have to pay all sorts of overhead and taxes?
I mean, I don't think it's real. Yet. But for the same "skill level", a single AI agent is going to be vastly more productive than any real person. ChatGPT types out essays in seconds it would take me half an hour to write, and does it all day long.
Of course $10k/mo sounds like a lot of inference, but it's not yet clear how much inference will be required to approximate a software developer--especially in the context of maintaining and building upon an existing codebase over time and not just building and refining green field projects.
We were hiring more devs to deal with a want of $10k worth of hardware per year, not per month.
It points to an article on "The Information" as the source, but that link is paywalled.
They could also just be trying to cash in on FOMO and their success and reputation so far, but that would paint a bleak picture
You can't claim it's even comparable to a mid level engineer because then you'd hardly need any engineers at all.
"Create high-quality presentations for communicating OpenAI’s financial performance"
https://openai.com/careers/strategic-finance-generalist/
What is interesting is there is no mention of agents on any job I clicked on. You would think "orchestrating a team of agents to leverage blah blah blah" would be something internally if talking about these absurd price points.
Microsoft bread and butter is Enterprise bloatware and large Enterprise deals where everything in the world is bundled together for use-it-or-lose-it contracts.
Its not really much different from IBM like a two decades ago
My thinking is that Lindy Effect runs strong in a lot of Big Tech, and with deep pockets, they can afford to not be innovators but build moats on existing frameworks.
If the definition of an AI Powerhouse is more about the capability to host models and process workloads, Amazon (the other company missing in that list) and Microsoft are definitely them.
"we have the people, we have the compute, we have the data, we have everything. we are below them, above them, around them." -- satya nadella
Now I canceled OpenAI and Claude general subscriptions, because for general tasks, Grok and DeepSeek more than suffice. General purpose AI will unlikely be subscription-based, unlike the specialized (professional) one. I'm now only paying for Claude Code API credits and still paying for Cursor.
Office is disgraceful trash now, a sad fall (especially of Word) from where it once was.
Their web-based offerings actually really suck beyond the point I could ever tolerate. Unusably bad.
There have been murmurs that they want to go that direction entirely.
[1] https://www.nytimes.com/2024/10/01/business/dealbook/softban...