As the conversation was about the societal trend. For the vast majority of people the answer is <= 1 month and it drops off precipitously adding months on.
Having something dumb that just cycles through the state of the art for exploits is already absolutely incredible security tooling (if people bother to make it into a process which I'm less optimistic about)
That’s 22 million of capacity foregone for a marketing stunt. Or they had more capacity than demand which seems odd for a product that’s allegedly in constant demand etc. There just isn’t a sane way to look at this as…
Exorbitant Cloud costs and spending 22 million to solve a 1 million dollar maths problem isn’t investment though.
I think there’s some crossed wires here with the wider data centre build outs. OpenAI have their own flavours of sketchy behaviour but I’m not aware of them solely being on the hook for those amounts short of some weird…
That’s mostly not the Frontier Labs. They’re definitely creating a lot of the demand but the people taking out those loans are Neoclouds and Big Tech (hence why Facebook + Google et al suddenly all have terrible cash…
It’s like they were all trained on the same internet as the others and they all all have some sort of midpoint opinion that could be a reddit comment or one of the other websites dominated by western desk workers.
I’ve heard plenty of “tech enthusiasts” breezily talk about how close we are to natural language getting compiled down to machine code but has anyone credible got any idea if that’s even a path? Closest think I can…
Oils probably a poor metaphor but between the ubiquity of companies deriving significant value from data + analytics on larger than memory datasets and the recent mad rush for training data I don't think that is the…
Even if that scenario did happen (I agree I don't think most of the major providers would survive on a commodity utility model). Most of the advances in AI are driven by huge amounts of funding for research. If everyone…
This is a stream of disingenuity again. > It's not actually clear that subscription users are unprofitable as a group (and the group level is the only important one). [Open AI losing money on subscription…
Haskell community will be overjoyed.
They do different things and sit in different parts of the stack (training vs inference). TorchTPU seems more like a play to get more people familiar with Googles TPU chips as they want to sell them to people outside of…
If the frontier labs are struggling under the training costs and the leading open source models are making their progress by distilling from the frontier labs it sounds a bit like there’s something wrong with the…
Seems a bit of a disingenuous framing. Most of the arguments I see are some mix of 1. Their figures have been pretty dodgy or excluded training costs so why is it trustworthy this time? 2. API inference charged at a…
Sure they are that's what weights artifacts are surely?
> Your argument is that advanced mathematics, that did not solve navier stones Do you think playing dumb is making you look credible or something? The argument isn't "was maths in the dataset" the controversy was if…
The problem where the centrepiece of the controversy was OpenAI admitting the potential of using private work happening by mathematician users as inputs?
That’s interesting. My spare time tinkering is around offline first embedded querying/storage with more of a focus on operational data (in particular spatial/spatiotemporal). Most of the big offline users I’ve seen are…
What industries is It common to have data small enough that running an embedded databases makes sense but also the data is so large that the indices that database provides aren't sufficient and you need to roll your own…
Google's infra genuinely pushed the industry forward though, things like kubernetes and SRE methodology are generally useful even if you aren't Google. Reading this I'm not even sure this sounds like the best way to run…
> the new era of swe will demand more and more long term business + product direction and relationship building skills This is what agile software development was always meant to be in fairness. It was the business…
That's letting the terrorists win.
The coding loop and the review loop are orthogonal and probably should remain so. Not least because it's probably worth the money for more intelligent models for code reviews where it's a more focused task while coding…
This is the happy path for LLM assisted coding. Obviously consumes less tokens being more constrained and focused so it's not what gets the most marketing but having the second loop of code reviews seems worth…
As the conversation was about the societal trend. For the vast majority of people the answer is <= 1 month and it drops off precipitously adding months on.
Having something dumb that just cycles through the state of the art for exploits is already absolutely incredible security tooling (if people bother to make it into a process which I'm less optimistic about)
That’s 22 million of capacity foregone for a marketing stunt. Or they had more capacity than demand which seems odd for a product that’s allegedly in constant demand etc. There just isn’t a sane way to look at this as…
Exorbitant Cloud costs and spending 22 million to solve a 1 million dollar maths problem isn’t investment though.
I think there’s some crossed wires here with the wider data centre build outs. OpenAI have their own flavours of sketchy behaviour but I’m not aware of them solely being on the hook for those amounts short of some weird…
That’s mostly not the Frontier Labs. They’re definitely creating a lot of the demand but the people taking out those loans are Neoclouds and Big Tech (hence why Facebook + Google et al suddenly all have terrible cash…
It’s like they were all trained on the same internet as the others and they all all have some sort of midpoint opinion that could be a reddit comment or one of the other websites dominated by western desk workers.
I’ve heard plenty of “tech enthusiasts” breezily talk about how close we are to natural language getting compiled down to machine code but has anyone credible got any idea if that’s even a path? Closest think I can…
Oils probably a poor metaphor but between the ubiquity of companies deriving significant value from data + analytics on larger than memory datasets and the recent mad rush for training data I don't think that is the…
Even if that scenario did happen (I agree I don't think most of the major providers would survive on a commodity utility model). Most of the advances in AI are driven by huge amounts of funding for research. If everyone…
This is a stream of disingenuity again. > It's not actually clear that subscription users are unprofitable as a group (and the group level is the only important one). [Open AI losing money on subscription…
Haskell community will be overjoyed.
They do different things and sit in different parts of the stack (training vs inference). TorchTPU seems more like a play to get more people familiar with Googles TPU chips as they want to sell them to people outside of…
If the frontier labs are struggling under the training costs and the leading open source models are making their progress by distilling from the frontier labs it sounds a bit like there’s something wrong with the…
Seems a bit of a disingenuous framing. Most of the arguments I see are some mix of 1. Their figures have been pretty dodgy or excluded training costs so why is it trustworthy this time? 2. API inference charged at a…
Sure they are that's what weights artifacts are surely?
> Your argument is that advanced mathematics, that did not solve navier stones Do you think playing dumb is making you look credible or something? The argument isn't "was maths in the dataset" the controversy was if…
The problem where the centrepiece of the controversy was OpenAI admitting the potential of using private work happening by mathematician users as inputs?
That’s interesting. My spare time tinkering is around offline first embedded querying/storage with more of a focus on operational data (in particular spatial/spatiotemporal). Most of the big offline users I’ve seen are…
What industries is It common to have data small enough that running an embedded databases makes sense but also the data is so large that the indices that database provides aren't sufficient and you need to roll your own…
Google's infra genuinely pushed the industry forward though, things like kubernetes and SRE methodology are generally useful even if you aren't Google. Reading this I'm not even sure this sounds like the best way to run…
> the new era of swe will demand more and more long term business + product direction and relationship building skills This is what agile software development was always meant to be in fairness. It was the business…
That's letting the terrorists win.
The coding loop and the review loop are orthogonal and probably should remain so. Not least because it's probably worth the money for more intelligent models for code reviews where it's a more focused task while coding…
This is the happy path for LLM assisted coding. Obviously consumes less tokens being more constrained and focused so it's not what gets the most marketing but having the second loop of code reviews seems worth…