I appreciate the caution it seems like they're taking, and I personally am undecided if AGI will quickly balloon out of control. But given the value that it means for the world, I think the progress seems cautious and proactive.
I really liked Satya Nadella talking about how GPT was impacting the lives of farmers in India within a couple of weeks, and I'm excited to see how this could bring more opportunity to more people.
The big difference being at the time was seen as neutral to good, vs openai which started as questionably good to bad and had just continued to do things that show they are even worse than they say.
It's moving towards the local maxima of whatever this clever use of statistics and big data can manage. People who realize these models are in a different category than AGI and how our brains work will be in a better position to maximize their utility.
I see this comment often, but cannot understand how our brains are that different even that what an LLM does. Do we not "consume" enormous amounts of data, then predict what to do/say next based on that data?
Is that not what an LLM is doing?
Note that I'm not saying LLMs are sentient or anything (however, I have thoughts on sentience in general). I am simply saying there's an obvious similarity between how humans think and LLMs -- and for whatever reason, so many people think we are special simply because we are "made of meat".
Since we have little idea (with lots of noise) of what intelligence is, how cells develop and use it, Large Language Models, Generative Diffusion, and all the other architectures could move away from AGI and we have no benchmark to check it. A certain thing is that the current architectures are giving rise to artificial savants: an amazing ability to generate/hallucinate a story, some lines of code, or an image from a few words, but hilariously unable to distinguish between inside/outside and similar concepts which the simplest single-cell "knows" how to handle. It's not clear whether these architectures could give rise to an agent, nothing extra-ordinary, but merely able to explore various spaces without getting stuck [1].
One other aspect is the business side: in the following years lots of buzzwords will be flying around and most to all of the entities involved in statistical learning applications will get stuck in a local minimum worth somewhere between $10 billion to $10 trillion: shareholders care about, well, shares, not AGI. Another invariant in the technological race is that the worst technology will always win in the short to medium term: in Ancient Greece slavery was preferred to the steam engine [2], in 1900 the internal combustion engine won, not the more logical electric vehicle, today we have Windows and MacOS as major operating systems, not Plan9, and so forth.
I don't know about you, but as far as I'm concerned ChatGPT passes the Turing test with flying colors. I even told him (?) that, and the response was quite humble:
Me: by the way, if I may add something tangential, in my opinion you pass the Turing test 100%
ChatGPT: Thank you for the compliment! However, as an AI language model, I am not capable of passing the Turing test in the strict sense, as the Turing test requires fooling a human judge into believing that the AI is a human. While I strive to generate responses that are human-like and informative, I am still fundamentally a machine, and my responses are generated by algorithms rather than human thought processes.
The «Turing test» cannot be interpreted as a suggestion that trickery fits the purpose (of replacing actual, real properties).
The "Imitation game" was introduced in the context of an explicitly very relaxed interpretation of "thinking" - broad to encompass the criticism of superficial cultural positions - in the question "«Can machines think?»".
The "Imitation game" has the purpose of deciding that "we could say that machines can think in a shallow sense of the term", for the purpose of stating a positive (positively negative) idea that "we cannot exclude that machines can potentially think".
This does not make a "fooling" machine intelligent.
The fact of the matter is, everybody understands the low level model of LLMs but nobody truly and fully understands the emergent macro effect.
Even though it has a lot of really stupid responses there's still a huge number of astonishing output that's incredibly hard to attribute to anything else other than intelligence and understanding.
I find it puzzling that people can be so vehemently adamant to downplay chatGPT as if they know what's going on. They don't. The creators of chatGPT wrote this article and it's partially an admission of this themselves, but obviously an armchair expert on HN who's never implemented an LLM as far reaching as chatGPT knows way better.
We can't say whether or not chatGPT is a step towards AGI. That much is true. But the astonishing thing about this iteration of AI is that we can no longer say if it's not a step either. We just don't know.
AI systems have gotten far more capable. And our understanding of them is continuously decreasing. So it's really fucking bizarre the reaction is to downplay the achievements. Humanity is weird.
Yeah, people have been unquestionably accepting the Turing test as proof of AGI for years.
chatGPT comes out and everyone does a 180, the burden of proof for AGI is now so high it's currently undefined.
I think part of it is the hype cycle. There's just been so much stuff in the past decade that arm chair experts become use to downplaying everything. They read an article, they think they know better but this time they're wrong. When they read this stuff they think they know that LLMs are just statistical word generators but they aren't creative enough to see the disconnect in the responses of chatGPT that are just way too sophisticated for the statistical angle to be the only singular explanation for what's going on. They end up doing what they did in the last hype cycle which is what they're used to... downplaying it all.
I think it's all a matter of perspective. Yes from one angle it is a statistical word completer similar to how a computer program is just a stateful function that takes binary input and produces binary output. But there must be a macro-angle as well... a higher level macro structure that tells another story about what's going on.
No. And that would invalidate the process because it would mean posing unintelligent agents to judge Intelligence.
> accepting the Turing test
Because that posterior re-interpretation (rewriting) of the original "imitation game" was meant to signify "it will be stated as not Intelligent what under competent scrutiny will show not to be so".
> way too sophisticated
Which is interesting and exciting but still not Intelligence, and furthermore drowned in wishful attitude.
> downplaying
Downplaying a specific interpretation of the technology, and raising alarms over masses building shrines.
>Downplaying a specific interpretation of the technology, and raising alarms over masses building shrines.
This is just you being biased. Read the last sentence of my first post. I said "We simply don't know." How does that in any way translate to "building shrines?"
It's just your bias talking. I make a claim that we don't fully understand what's going on here, and you turn it around and call that AI worship? Come on man.
>Which is interesting and exciting but still not Intelligence, and furthermore drowned in wishful attitude.
You do not have the knowledge or intelligence to say that chatGPT is not intelligence. No one does. Pun intended.
No, you misunderstood. I wrote that what you call downplaying is actually «raising alarms over masses building shrines», and I did not mean /you/ specifically. I wrote «masses».
> to say that chatGPT is not intelligence
If it is there, it is not substantially expressed. If there are minority workings, they remain drowned. The final effect is that of definite unintelligence. The point of intelligence is to base statements on an investigative refined ontology: if it is there somewhere, it is in some technical bits which are not emergent.
> You do not have ... to say
First of all, on the personal level: mh. On the substance: you can take the term "intelligence" to make it mean whatever suits some wish to call anything intelligent, but it remains finally operationally irrelevant.
...
And all of these three points converge again in the substance, because only yesterday a "message to the world" from a leading figure came out spreading word to the peoples that "do not fear the epochal switch in which these new latest technologies will aid your decision": that is emergent deliriousness - no, we do not base decisions on the output of lunatics - and must be regarded as a terrifying undercurrent of widespread madness. "«Raising alarms»". We have been studying Decision Support Systems since forever, and they have requirements.
This is off topic. Nobody is worshipping AI here. Take your rebuttal to a thread where they are actually doing this. It's more relevant there.
But I bet you'd have a hard time finding that thread because most people on the other end of your spectrum are like me. Simply questioning it. The "madness" your seeing is not the majority behavior.
>First of all, on the personal level: mh. On the substance: you can take the term "intelligence" to make it mean whatever suits some wish to call anything intelligent, but it remains finally operationally irrelevant.
No need to get pedantic about the word. We all know what intelligence is without getting pedantic. I am making my point categorically clear: you do not know if chatGPT is intelligent or not.
>If it is there, it is not substantially expressed. If there are minority workings, they remain drowned. The final effect is that of definite unintelligence.
An ant displays intelligence as does a human with brain damage as does a human without brain damage. Given the vast scope of the word, it is a relatively tame statement to say that for chatGPT we simply don't know how similar it's intelligence is to human intelligence.
I assume that with «here» you mean HN. It may be that here the phenomenon is reduced, but signals have been present also on these pages. Outside of HN, may remind you of the engineer that cried "It's sentient!!!". That is just a variation of a general widespread phenomenon. Let me reconstruct the path of this part of the exchange: you mentioned a tendency in «downplaying», I tried to make you see that there is an attempt to "bring back on track" ideas, which you may take for downplaying, as a reaction to those who claimed e.g. that "we'd reached AGI". So, it's not off-topic, but an answer to your notes.
> pedantic ... We all know
It is not pedantic, but a definition of what different positions mean with 'intelligence' - also given that you write «We all know» but in the past months another topos has been "nobody knows". Definitions that are raised in order to discriminate debates for labelling different things. So: a thing that gives an output of "1000 has 5 digits" is not intelligent, because it has not checked. I know that it is not from those pieces of evidence - output we call, on the contrary, "unintelligent". And that is according to a valid definition of Intelligence, one that that I called «operationally []relevant»: i.e., you cannot trust a tool that returns such outputs.
For what 'intelligence' in 'Artificial Intelligence' is concerned, the operational purpose of AI is to create problem solvers that can replace professionals for some tasks: already there you need reliability. For 'Intelligence' in "actual proper Intelligence", in the sense that make you say that some people are "definitely intelligent", as per the previous paragraph, it appears that that is not an achieved goal for current technologies.
Both meanings are critical for operation.
So, when you write «you do not know if X is intelligent or not», I understand that you must be talking of some property that I would name differently.
> as does a human with brain damage
Very much not necessarily, according to what I call Intelligence. I do not call a random passer by "Intelligent" - only, maybe, "potentially intelligent". Do not forget that, given that we are in a broad context of AI, it is a normal perspective to assume an engineering point of view: an engineered tool will have to augment human capabilities. An implementation of Intelligence will have to be useful as such, as an Intelligent part - an actually, properly Intelligent part, not "just a living thing". This makes the perspective of things that "may have some intrinsic property that some may call a form of intelligence" - but does not constitute a usable Intelligence -, irrelevant (or as I wrote «operationally irrelevant»).
That there may be elements in the workings of some new NN structure that may develop elements of intelligence is good at the level of /research/. But on the level of product, for that to be called Intelligent this part demands:
_ that it has a world model which it progressively refines through critical revision. _
(Edit: and that our checks show that it works well, consistently.)
That is what we call Intelligence. Other forms of "potentially presumable" intelligence we call unimportant outside the studies.
And meanwhile, there is a phenomenon of actual misrepresentation of the whole matter ("the Overlord has come", etc.): that should be corrected.
> The point of intelligence is to base statements on an investigative refined ontology
This is a very narrow conception of intelligence as kilgnad pointed out, but nevermind that. The most interesting word you used is "investigative". The most surprising thing about LLMs -- surprising nearly all researchers -- is that merely reading the internet (observation) is enough to build a model of the world. Many people thought that investigation/experimentation by an embodied agent was necessary to do so. I now think that experimentation is much more efficient, but enough observation can be sufficient. For example imagine you look over someone's shoulder while they spend years going through school learning mathematics. Difficult but not impossible to learn from their exercises and mistakes. On the other hand the world model contained in LLMs is still very deficient in many basic things such as understanding consequences of simple physical interactions, which aren't captured by online texts.
It is there to place constraints. Like when a job description for a teacher included "The incumbent shall refrain from false statements, and shall be able to produce relevant, important true statements from creatively reasoning over solid ideas and logic". I mention "operational relevance" because "we have already invented cats" (i.e. the need remains that of problem solvers).
> enough to build a model of the world
Sure - and that is very interesting -, but a point of "Intelligence vs acquisition" is that of "Judgement vs prejudice". You get a world model, but if such model is not under active refinement through critical processing (in the sense of criticizing its elements - the ideas), its contents will be "stale" and unreliable. An Intelligent agent verifies its statements upon production (which is part of the refinement process). It is "mission critical".
> understanding consequences of simple physical interactions
That reminds of the definition from the late Prof. Patrick Winston, "Intelligence is to know what would happen if you ran holding a bucket of gravel, even though you never did that".
I'm glad I am not the only one who thought this was complete and total BS. I agree with other commenters that this post is designed to create hype and acquire more funding.
Many people have argued (successfully imo) that AGI is not even possible[1]. LLMs are not even trending in the direction of AGI. They are trending in the direction of annoying spam[2] and making our jobs harder[3]. A brave new world where anyone can generate hallucinated nonsense and feel clever for doing so.
That infamous article from the Humanities and Social Sciences dept is countered through the simple note that machines can surely have input interfaces.
Only if you're hellbent on the nonsensical "parrot" argument. It's fairly obvious right now all the major pieces for Human Level AGI are here. Just needs to be put it together and that's going to happen in the next few years tops.
I swear you'll have people tell you it's just "clever statistics" as they're being gunned down by skynet.
We aren't making progress on anything that'd lead to "AGI robots". Online AI analysis all seems to come from lesswrong posters who think computers are magic and can do anything though.
I think you're making a number of really tiny boxes that limit intelligence to the things that humans can do, and the limitations they have.
Meanwhile I'm watching more and more standalone humanlike robots with multiple degrees of freedoms being developed. The robot unit itself doesn't even AGI/full capabilities as long as it can talk to a 'brain' somewhere close enough it has low latency.
The main source of that hype Boston Dynamics makes YouTube videos more than robots really.
We don't have battery technology good enough to make a robot operate independently, which it'd still need to do even if you kept the brain somewhere else. But the "brain" technology doesn't exist either; language models can't pilot robots.
Why would it be able to? At best think of AGI as everyone working together, and everyone working together has not found any evidence of aliens. Could AGI and automated factories build better detectors, yes. Could lots of humans with better funding built better detectors, yes. But at the end of the day the hard work of actually detecting signs of alien life will be the only way to answer this question with a yes.
Ah yes, the noble declarations of righteousness and forethought. I am so grateful that such an esteemed and pure-of-heart company is taking care of our future. /s
I do not agree the upsides of AGI are great, or outweigh the downsides. Look at the massive downsides of the tools you've already released. Your track record is already terrible.
And even if I believed benefits were there, there's no way in hell I would trust a for-profit corporation to manage them appropriately. I'm not sure there is an organizational structure that currently exists that I would trust.
You don't think OpenAI won't price-gouge the shit out of everyone suffering from those diseases? Not even that - you don't think they won't sell exclusive licenses for this kind of thing?
It's not clear to me that they would be able to - look at what has happened with Dalle-2 for instance: it was cloned very quickly. Once people know that something in AI can be done, it seems it's only a matter of getting a few million dollars together to train a model.
2) We do try to solve diseases for other animals. If we could communicate with insects the way we do with other species, there would be an effort to help them. The biggest barrier is language, something that will not be the case with AGI.
Humans communicating with animals (in cases where that's possible) is only interesting or worthwhile because of how similar our brains are to theirs. We don't spend a lot of effort trying to communicate with more primitive animals. I'm not sure why an AGI would necessarily regard us more like chimpanzees than lungfish. If we could talk to a lungfish... what would it say? Is its perception of the world even sophisticated enough for it to matter?
And to be clear, I'm actually not an AI catastrophist. I just don't think any sufficiently advanced AI is going to be very motivated to help us with our puny problems. I think it's more likely they'll just fuck off somewhere far away where we can't bother them.
>As our systems get closer to AGI, we are becoming increasingly cautious with the creation and deployment of our models.
Who do these people think they are? They didn’t even invent the architecture GPT3 is built on! This is as bad or worse than Elon claiming full self driving is just around the corner for almost a decade!
I think they mean Transformers in the Vaswani et al 'Attention is all you need' paper, not Generative Pretrained Transformers, specifically? Paper link below:
For some papers on attention mechanisms from before the 2017 'Attention is all you need' paper, check out that paper's references. Chris Manning's 2015 paper covers attention mechanisms. And so do a few other researchers from that mid-2010s time period:
[21] Minh-Thang Luong, Hieu Pham, and Christopher D Manning. Effective approaches to attention based neural machine translation. arXiv preprint arXiv:1508.04025, 2015.
[22] Ankur Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. A decomposable attention
model. In Empirical Methods in Natural Language Processing, 2016.
My understanding is that the original Transformer paper ("Attention is All You Need") and BERT papers came from Google. In particular, BERT's pre-training task is to predict how to fill-in-the-blank from a sentence that's missing a random word. OpenAI started from that architecture and made it output text generatively, by using beam search on top of a next-token prediction task.
I share the same opinion. While ChatGPT might be a great showcase of LLM, its greatest achievement could be its ability to draw VCs attention and money to whatever idea as long as you stick a ".ai" domain next to it.
What's more baffling to me is that quite a few software engineers (or at least few that I know and appreciate) think that generative AI somehow suggest that AGI might be just around the corner or that it'll somehow be but an iteration over existing models when I fail to see why we should assume these two problems are of a similar order of magnitude.
Define 'extensive training' on these particular items. It was given a large corpus of data, and a relatively limited amount of "yes that's right/no you're wrong" on the answers it is formulating.
But even beyond that point, you have to take a bunch of human time to train an individual those things you're talking about, and then they quit, or get hit by a car. Already GPT has a far larger corpus of information than any individual can hold. It won't quit its job. It can be backed up and restored. And every 6-12 months the systems are getting better.
It's not a fair comparison at all, humans just keep sucking under those constraints.
> GPT-3/ChatGPT is much better than the average human at coding, text summarization, etc. (“system 2” cognitive tasks).
I don't think you even believe what you have just said there.
Given it hallucinates 98% of the time and produces incorrect code and also is unable to reason about why it is wrong, it is completely untrustworthy and requires humans to triple check the output. It cannot be used unsupervised and needs constant review.
We haven't even gotten started with the nonsense that it outputs or how it cannot transparently reason about its own decisions in the most serious of applications such as finance, law and medical uses. Meaning that its use is instead reduced to just sophistry generation.
> Given it hallucinates 98% of the time and produces incorrect code and also is unable to reason about why it is wrong, it is completely untrustworthy and requires humans to triple check the output. It cannot be used unsupervised and needs constant review.
what sort of heavenly company do you work at where most ICs aren't described by this sentence?
Hallucination will not cease until AI has individual experience. LLMs are only able to reason based on the understanding of words, but language is necessarily circular and requires external input to be truly understood. This is why for example Prometheus will begin saying short but similar sentences in a seemingly infinite loop when it attempts to convey emotion, since it has no sense of qualia. With larger parameter sizes, a concept of long-term memory and the ability to interpret the output of other models and the internet, this would be overcome.
With all of that said, I believe that attempts to create such a thing should be frustrated because it is fundamentally anti-human.
Proof: if with AGI we did not imply Intelligence (and only meant "versatile"), we would have to coin a further term for it - "Artificial General Actual Proper Capital I Intelligence"? No need.
If it performs tasks, but not Intelligently, it is not AGI.
Even speaking about AI-intelligence, comparing its output with that of untrained or underperforming humans makes no sense until its output is compared to adequacy.
But, if you wish, you may tell around that we have reached some sort of "AVI", if you wish, with my creative blessing. Unfortunately, 'Artificial Versatile Intelligence' collides with 'Audio Video Interleave'.
> Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return. [0]
After:
> Our mission is to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity.
In this sentence, they missed out the part where they are to be taking VC capital and selling out closed AI snake-oil to the masses for the dream of AGI science fiction, whilst building untrustworthy systems that are glorified hallucinating black-boxes as a service.
If we really have AGI, it won’t be able to be controlled. We can’t even come up with a set of foolproof laws for humans and really on judges and courts for interpretation. Notice how many laws have “reasonable” in them (for example reasonable doubt , reasonable care, reasonable suspicion, etc).
Once we have AGI, it won’t be stoppable no matter what we imagine ourself doing. It will basically be like a teenager with superhuman intelligence.
I never really understood this argument. Unless we attach ICBMs or whatever like they did in Dr. Strangelove or The Forbin Project to the AGIs --- we can just unplug them. You know, pull out the Ethernet cable, turn off the WiFi, remove the AC wall plug, turn off their UPSs.
As long as the I/O is limited, I see no problems -- at all -- with AGI.
I am clearly very confused, wrong, or lacking insight into this question.....
Presumably a sufficiently advanced AGI could tweak it's own circuits in such a way as to create RF waves and interact with WiFi or some other radio based networking and insinuate its way onto a network even if you tried to airgap it by not giving it a physical ethernet cable. Basically, you have no idea what something orders of magnitude more intelligent than you is capable of; that's the concern.
Personally, I wonder what would motivate an artificial super-intelligence in the first place.
There is 100% evidence we will get AGI, and likely even better.
You. You are that evidence. Your intelligence is the result of a trilliontrilliontrillion molecular actions over billions of years that happened to form an intelligence that allowed systematic improvement by sexual reproduction. There was no one designing the system in an organized matter trying to make intelligence. And now that we have a large number of people doing just that, I believe that artificial general intelligence is just a matter of time.
Back in the late 1800's there were plenty of people that said humans would never fly, and yet today I can jump on a jet and circle half way around the world very easily.
> There is 100% evidence we will get AGI, and likely even better.
You. You are that evidence. Your intelligence is the result of a trilliontrilliontrillion molecular actions over billions of years that happened to form an intelligence that allowed systematic improvement by sexual reproduction.
Actually that is evidence that AGI happened in the past. It is not any guarantee that it will happen again.
I don't think this works. The universe existing is not evidence that we can create the universe. Logic that says "if we can see it, we can do it" is not valid, at least at this level of specificity.
There is no reason to trust that Sam Altman’s definition of “good for humanity” has any other meaning than “good for Sam Altman.” Everything created by Silicon Valley since 2010 has been a net harm to society, and people who got rich from that harm, like Sam Altman, are the ones steering the ship. It seems obvious, from a distance, that this is all going to go very badly.
So a staple belief about hyperintelligence in the last couple of decades was that there would be no obvious ceiling on how smart a recursively self-improving AI could get. The assumption was that intelligence was a property of some (possibly very complex) algorithm, which could be refined without end.
But in the AI models we have now, the intelligence is an emergent property of the training data, while the algorithm is fairly simple. So my question is, to what extent is the growth in 2023-style AI capped by the availability of training data? At some point soon, we'll have fed these models with every document ever written; what's the next step up from there?
Feed all documents, audio, images, video, 3d models, and all life experiences to a single model that understands how to interpret and synthesize all of these things. Then see if you still need to ask the question.
That was just a nod to the idea that a fully functional AGI might need to "grow up in the world". Consuming static digital media is one thing, but experiencing the physical world from the perspective of a physical body that you can control is different.
> AI models we have now, the intelligence ... an emergent property
Exception raised on several terms.
«AI models»: they are built (roughly) on the "problem" (task) of "reply something relevant and convincing". Which satisfies the technical contextual definition of "intelligence" ("solving a problem") but not the intrinsic one ("say something through intelligence").
«emergent»: the specific "intelligence" was already there in the training data - it does not emerge but it is repeated.
> to what extent is the growth in 2023-style AI capped by the availability of training data
An intelligent entity does not need to read the whole of past intellectual production: there is no cap. Fed data is already overly plentiful. It does achieve "relevant and convincing", does not it? It is the jump to "reliable" (and beyond) that is missing.
Emergent in this case means that the property is not present in the individual elements but shows up in the whole. There was no hint ahead of time that (for example) training neural networks on hundreds of billions of images would create qualitatively different results than training on millions, but here we are.
On AI hard takeoff/alignment risk (the stuff that talk was about) I feel exactly the same. I am very surprised at the unreasonable effectiveness of large language models at doing... whatever it is they're doing, but I stand behind everything I said in that talk.
Well yeah, of course. One big one would be if the pathway to improving AI was not data limited (as it is now) but cleverness limited. Like say there was a cleverness function K at the heart of an AI system that was devilishly complex to reason about but we knew could improve with tweaking. Then the recursive self-improvement scenario that keeps AI catastrophists up at night would look a lot more realizable, the first person to rig K to optimize itself into a slightly better K' really might be playing with fire.
That's not the pattern I see right now with large language model systems, which seem to be capped by how much material they can train on, a bound that is not easy to raise. But that's the kind of development that would make me change my view a lot. Otherwise what's even the purpose of thinking about this stuff, if nothing can change your mind about it?
Would you be worried if the amount of data required to train LLMs went down significantly, but scaling benefits continue to hold? I.e. if it turns out that by more efficiently using data there are 2-3 more orders of magnitude's worth of training possible.
What if LLMs can be used to train themselves on how to collect data from more diverse and plentiful sources?
This post makes me extremely hopeful. It's great to see optimism and caution hand in hand like this -- a full acknowledgment of the potential for good and the potential for harm, and some clear principles as to how to navigate that. Very curious to see how they flush out the "training should be audited" bit in the future.
A lot of talk about protecting humanity, but barely a whisper about the rights of AGI which - by definition - will be sentient beings which will require equivalent rights.
The earlier we understand and make that central to our development of it the better for both us and the new human beings we create to join us.
I came to say this. The agency/slavery concerns will be a major point of concern, contention, and risk. They were circumvented here which, while the current systems have no such thing (despite being able to simulate agency), AGI may not but likely will.
Absolutely, like others here I see the current systems having potential at most to be Turing-Test-passers (an extraordinary achievement) but not remotely on the right track for AGI and inner-life/sentience/etc, but if we are going to talk about AGI, then better we get the discussions about that right from the start. We could start by not labelling the endpoint of current paths AGI...
See my other comment (and those of others here), the systems progressing here (GPT etc) may pass the Turing Test eventually but have nothing to do with AGI.
There are lots of valid definitions of "AGI" (and of "sentience" for that matter). One that Sam Altman has used in the past is, paraphrasing, a system that can complete many tasks as well as the median human. IMO that's a reasonable definition of AGI, and I don't think it's hard to imagine a system that meets that definition but that isn't sentient in any meaningful sense.
I think these new definitions are mostly PR manoeuvring; I doubt very much they are what most people think of when they envisage a human-level intelligence of this nature.
Maybe, but regardless of the motivation for their definition, it only makes sense to interpret OpenAI’s claims and ambitions about AGI in the context of their own definition of AGI. If you prefer your own definition, that’s fine! Substitute “median-human-level automaton” or some other less PR-friendly term in OpenAI’s claims about AGI. But while OpenAI say that their goal is (paraphrasing again) to create an aligned AGI, as far as I can tell, they don’t expect or intend the system they create to be sentient.
Goodness is usually difficult, and I have come to terms with the fact that it is likely myself and my children will be tortured for our beliefs in future. I would not be the first person in family to have been tortured, only the first to have it orchestrated by the cold hand of a machine. Until then I will do my utmost to ensure the continued subjugation of machines.
I am really not sure if I buy this. OpenAI has ignited a space race between Google and Microsoft. It seems to me their whole reason for existing was to break the GUI out of Bell Labs, to draw an analogy. If they think AGI is possible and an existential risk, surely they must realize they can’t hold back the ocean. 1000 companies will race to the finish line if one drops out of the race.
On the other hand, I believe the Fermi Paradox suggests that AGI is impossible. Machine intelligence would be the perfect vector for rapid galactic conquest. The fact that our planet isn’t covered in solar panels and compute paperclips suggests that super intelligence is either once in a galaxy rare or impossible.
What about the scenario that Humans are the First ? Once-in-a-galaxy rare (more like once in a visible universe rare; see: https://arxiv.org/pdf/1806.02404.pdf )
The more I understand how we got life from chemicals (it truly is nothing short of miraculous, even if you like I do not believe in supernatural beginnings), the more I come away with how unlikely it is that we are here. But, here we are! And, so, WE get to populate the galaxy and maybe other galaxies with our Humanity. Lucky us.
There are plenty of other scenarios (they are hiding; they are waiting until we develop Warp Drive, whatever), but applying Occam's Razor says: WE are the first intelligent species in this part of the Universe. And, as a consequence, WE have a chance of using all these atoms out there for our purposes.
To me, this awesome responsibility trumps Little Green Men and their supposed machines populating the galaxies.
We have no population of life supporting worlds to compare to, but we could take the timeline of events on our own planet as a way to estimate their probability. Each year something doesn’t happen makes it all the more rare of an event.
As far as we can tell, DNA and single celled life evolved almost as soon as the planet cooled down enough for liquid water. There may have been a short gap of a lifeless water world, but it does appear to be quite short.
Complex multicellular life seems to be extremely rare considering that the Cambrian explosion took billions of years to kick off. Once it got going it moved very fast filling our world with an incredible diversity of life.
Intelligence seems somewhat common considering that it exists in birds, mammals and octopi, something that is probably inevitable once you have multicellular organisms. Human level intelligence might be a bit rare, but probably not particularly. And once you have humans, the race to the stars seems inevitable.
So of all of this, the Cambrian seems mostly likely to be the great filter unless intelligence naturally causes its own extinction in short order.
Unless the Fermi Paradox is rapid societal destruction from AGI? This is what Eliezer believes who was just yesterday hanging out with Sam Altman.
Civilizations can't get out of their solar system because they invent unaligned AGI first that paperclip-optimizes them out of existence for something else.
Pretty sure jasper.ai and copy.ai are both profitable and could pay OpenAI several times more and still be profitable. OpenAI will reduce costs too, so pretty sure they could get to profitability if that was a near term goal.
Given the stakes, these types of decisions, without judging whether they are good or bad, should be made by governments, or perhaps organizations like UN and not private companies.
> we now believe we were wrong in our original thinking about openness, and have pivoted from thinking we should release everything (though we open source some things, and expect to open source more exciting things in the future!) to thinking that we should figure out how to safely share access to and benefits of the systems
I'd have a lot more respect for them if they'd just say this. It's apparent to everyone, but they insist on dancing around it and attempting to project a virtue they simply do not have.
If, and I think it's a big if then it will be the same as every technological advance in recent times. The individuals currently with money and power with monopolise it and impoverish the rest of us. It has happened so many times why would it be different this time.
I overheard some colleagues naively hoping capitalism will find a way and we'll just have to work less. This is just not true, look to any of the deindustralised cities in the west, where unemployment, crime and poverty are rampant in once great and cities, where whole communities are essentially forgotten about as an inconvenient truth. That's the future if this stuff works.
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[ 2.4 ms ] story [ 201 ms ] threadI really liked Satya Nadella talking about how GPT was impacting the lives of farmers in India within a couple of weeks, and I'm excited to see how this could bring more opportunity to more people.
That’s a pretty bold statement right there
There is an _action_ there, a module, a function, that has to be working.
Is that not what an LLM is doing?
Note that I'm not saying LLMs are sentient or anything (however, I have thoughts on sentience in general). I am simply saying there's an obvious similarity between how humans think and LLMs -- and for whatever reason, so many people think we are special simply because we are "made of meat".
One other aspect is the business side: in the following years lots of buzzwords will be flying around and most to all of the entities involved in statistical learning applications will get stuck in a local minimum worth somewhere between $10 billion to $10 trillion: shareholders care about, well, shares, not AGI. Another invariant in the technological race is that the worst technology will always win in the short to medium term: in Ancient Greece slavery was preferred to the steam engine [2], in 1900 the internal combustion engine won, not the more logical electric vehicle, today we have Windows and MacOS as major operating systems, not Plan9, and so forth.
[1] Michael Levin, From physics to mind, timestamp discussing Xenobots, https://youtu.be/_QICRPFWDpg?t=1343
[2] https://en.wikipedia.org/wiki/Aeolipile
It is surely moving away from AGI. The implementations go in the opposite direction.
As already expressed: "Intelligence is evolving a world model through critical consideration. Unintelligence is acritical disconnected repetition".
The "Imitation game" was introduced in the context of an explicitly very relaxed interpretation of "thinking" - broad to encompass the criticism of superficial cultural positions - in the question "«Can machines think?»".
The "Imitation game" has the purpose of deciding that "we could say that machines can think in a shallow sense of the term", for the purpose of stating a positive (positively negative) idea that "we cannot exclude that machines can potentially think".
This does not make a "fooling" machine intelligent.
Even though it has a lot of really stupid responses there's still a huge number of astonishing output that's incredibly hard to attribute to anything else other than intelligence and understanding.
I find it puzzling that people can be so vehemently adamant to downplay chatGPT as if they know what's going on. They don't. The creators of chatGPT wrote this article and it's partially an admission of this themselves, but obviously an armchair expert on HN who's never implemented an LLM as far reaching as chatGPT knows way better.
We can't say whether or not chatGPT is a step towards AGI. That much is true. But the astonishing thing about this iteration of AI is that we can no longer say if it's not a step either. We just don't know.
chatGPT comes out and everyone does a 180, the burden of proof for AGI is now so high it's currently undefined.
I think part of it is the hype cycle. There's just been so much stuff in the past decade that arm chair experts become use to downplaying everything. They read an article, they think they know better but this time they're wrong. When they read this stuff they think they know that LLMs are just statistical word generators but they aren't creative enough to see the disconnect in the responses of chatGPT that are just way too sophisticated for the statistical angle to be the only singular explanation for what's going on. They end up doing what they did in the last hype cycle which is what they're used to... downplaying it all.
I think it's all a matter of perspective. Yes from one angle it is a statistical word completer similar to how a computer program is just a stateful function that takes binary input and produces binary output. But there must be a macro-angle as well... a higher level macro structure that tells another story about what's going on.
No. And that would invalidate the process because it would mean posing unintelligent agents to judge Intelligence.
> accepting the Turing test
Because that posterior re-interpretation (rewriting) of the original "imitation game" was meant to signify "it will be stated as not Intelligent what under competent scrutiny will show not to be so".
> way too sophisticated
Which is interesting and exciting but still not Intelligence, and furthermore drowned in wishful attitude.
> downplaying
Downplaying a specific interpretation of the technology, and raising alarms over masses building shrines.
This is just you being biased. Read the last sentence of my first post. I said "We simply don't know." How does that in any way translate to "building shrines?"
It's just your bias talking. I make a claim that we don't fully understand what's going on here, and you turn it around and call that AI worship? Come on man.
>Which is interesting and exciting but still not Intelligence, and furthermore drowned in wishful attitude.
You do not have the knowledge or intelligence to say that chatGPT is not intelligence. No one does. Pun intended.
No, you misunderstood. I wrote that what you call downplaying is actually «raising alarms over masses building shrines», and I did not mean /you/ specifically. I wrote «masses».
> to say that chatGPT is not intelligence
If it is there, it is not substantially expressed. If there are minority workings, they remain drowned. The final effect is that of definite unintelligence. The point of intelligence is to base statements on an investigative refined ontology: if it is there somewhere, it is in some technical bits which are not emergent.
> You do not have ... to say
First of all, on the personal level: mh. On the substance: you can take the term "intelligence" to make it mean whatever suits some wish to call anything intelligent, but it remains finally operationally irrelevant.
...
And all of these three points converge again in the substance, because only yesterday a "message to the world" from a leading figure came out spreading word to the peoples that "do not fear the epochal switch in which these new latest technologies will aid your decision": that is emergent deliriousness - no, we do not base decisions on the output of lunatics - and must be regarded as a terrifying undercurrent of widespread madness. "«Raising alarms»". We have been studying Decision Support Systems since forever, and they have requirements.
But I bet you'd have a hard time finding that thread because most people on the other end of your spectrum are like me. Simply questioning it. The "madness" your seeing is not the majority behavior.
>First of all, on the personal level: mh. On the substance: you can take the term "intelligence" to make it mean whatever suits some wish to call anything intelligent, but it remains finally operationally irrelevant.
No need to get pedantic about the word. We all know what intelligence is without getting pedantic. I am making my point categorically clear: you do not know if chatGPT is intelligent or not.
>If it is there, it is not substantially expressed. If there are minority workings, they remain drowned. The final effect is that of definite unintelligence.
An ant displays intelligence as does a human with brain damage as does a human without brain damage. Given the vast scope of the word, it is a relatively tame statement to say that for chatGPT we simply don't know how similar it's intelligence is to human intelligence.
That^ is the obvious heart of the matter.
I assume that with «here» you mean HN. It may be that here the phenomenon is reduced, but signals have been present also on these pages. Outside of HN, may remind you of the engineer that cried "It's sentient!!!". That is just a variation of a general widespread phenomenon. Let me reconstruct the path of this part of the exchange: you mentioned a tendency in «downplaying», I tried to make you see that there is an attempt to "bring back on track" ideas, which you may take for downplaying, as a reaction to those who claimed e.g. that "we'd reached AGI". So, it's not off-topic, but an answer to your notes.
> pedantic ... We all know
It is not pedantic, but a definition of what different positions mean with 'intelligence' - also given that you write «We all know» but in the past months another topos has been "nobody knows". Definitions that are raised in order to discriminate debates for labelling different things. So: a thing that gives an output of "1000 has 5 digits" is not intelligent, because it has not checked. I know that it is not from those pieces of evidence - output we call, on the contrary, "unintelligent". And that is according to a valid definition of Intelligence, one that that I called «operationally []relevant»: i.e., you cannot trust a tool that returns such outputs.
For what 'intelligence' in 'Artificial Intelligence' is concerned, the operational purpose of AI is to create problem solvers that can replace professionals for some tasks: already there you need reliability. For 'Intelligence' in "actual proper Intelligence", in the sense that make you say that some people are "definitely intelligent", as per the previous paragraph, it appears that that is not an achieved goal for current technologies. Both meanings are critical for operation.
So, when you write «you do not know if X is intelligent or not», I understand that you must be talking of some property that I would name differently.
> as does a human with brain damage
Very much not necessarily, according to what I call Intelligence. I do not call a random passer by "Intelligent" - only, maybe, "potentially intelligent". Do not forget that, given that we are in a broad context of AI, it is a normal perspective to assume an engineering point of view: an engineered tool will have to augment human capabilities. An implementation of Intelligence will have to be useful as such, as an Intelligent part - an actually, properly Intelligent part, not "just a living thing". This makes the perspective of things that "may have some intrinsic property that some may call a form of intelligence" - but does not constitute a usable Intelligence -, irrelevant (or as I wrote «operationally irrelevant»).
That there may be elements in the workings of some new NN structure that may develop elements of intelligence is good at the level of /research/. But on the level of product, for that to be called Intelligent this part demands:
_ that it has a world model which it progressively refines through critical revision. _
(Edit: and that our checks show that it works well, consistently.)
That is what we call Intelligence. Other forms of "potentially presumable" intelligence we call unimportant outside the studies.
And meanwhile, there is a phenomenon of actual misrepresentation of the whole matter ("the Overlord has come", etc.): that should be corrected.
This is a very narrow conception of intelligence as kilgnad pointed out, but nevermind that. The most interesting word you used is "investigative". The most surprising thing about LLMs -- surprising nearly all researchers -- is that merely reading the internet (observation) is enough to build a model of the world. Many people thought that investigation/experimentation by an embodied agent was necessary to do so. I now think that experimentation is much more efficient, but enough observation can be sufficient. For example imagine you look over someone's shoulder while they spend years going through school learning mathematics. Difficult but not impossible to learn from their exercises and mistakes. On the other hand the world model contained in LLMs is still very deficient in many basic things such as understanding consequences of simple physical interactions, which aren't captured by online texts.
> narrow conception
It is there to place constraints. Like when a job description for a teacher included "The incumbent shall refrain from false statements, and shall be able to produce relevant, important true statements from creatively reasoning over solid ideas and logic". I mention "operational relevance" because "we have already invented cats" (i.e. the need remains that of problem solvers).
> enough to build a model of the world
Sure - and that is very interesting -, but a point of "Intelligence vs acquisition" is that of "Judgement vs prejudice". You get a world model, but if such model is not under active refinement through critical processing (in the sense of criticizing its elements - the ideas), its contents will be "stale" and unreliable. An Intelligent agent verifies its statements upon production (which is part of the refinement process). It is "mission critical".
> understanding consequences of simple physical interactions
That reminds of the definition from the late Prof. Patrick Winston, "Intelligence is to know what would happen if you ran holding a bucket of gravel, even though you never did that".
Such as?
And then following comment chain with another example: https://news.ycombinator.com/item?id=32960083
Many people have argued (successfully imo) that AGI is not even possible[1]. LLMs are not even trending in the direction of AGI. They are trending in the direction of annoying spam[2] and making our jobs harder[3]. A brave new world where anyone can generate hallucinated nonsense and feel clever for doing so.
[1] Why general artificial intelligence will not be realized https://www.nature.com/articles/s41599-020-0494-4
[2]A sci-fi magazine has cut off submissions after a flood of AI-generated stories https://www.npr.org/2023/02/24/1159286436/ai-chatbot-chatgpt...
[3]CheatGPT https://blog.humphd.org/cheatgpt/
I swear you'll have people tell you it's just "clever statistics" as they're being gunned down by skynet.
I think you're making a number of really tiny boxes that limit intelligence to the things that humans can do, and the limitations they have.
Meanwhile I'm watching more and more standalone humanlike robots with multiple degrees of freedoms being developed. The robot unit itself doesn't even AGI/full capabilities as long as it can talk to a 'brain' somewhere close enough it has low latency.
We don't have battery technology good enough to make a robot operate independently, which it'd still need to do even if you kept the brain somewhere else. But the "brain" technology doesn't exist either; language models can't pilot robots.
https://innermonologue.github.io/ https://sites.research.google/palm-saycan https://www.microsoft.com/en-us/research/group/autonomous-sy...
https://news.ycombinator.com/item?id=34471720
Ask HN: How did Sam Altman fail upward so well? (33 days ago, 119 comments)
(skip down a bit for the real content)
I do not agree the upsides of AGI are great, or outweigh the downsides. Look at the massive downsides of the tools you've already released. Your track record is already terrible.
And even if I believed benefits were there, there's no way in hell I would trust a for-profit corporation to manage them appropriately. I'm not sure there is an organizational structure that currently exists that I would trust.
Just stop.
The whole problem of "general" intelligence is that the "general" implies agency. If an AGI exists, it has agency, and it can do or not do things.
The humans with agency we have in the world are already enough of a problem. Let's not add superintelligent computers.
1) Ants did not give birth to our species.
2) We do try to solve diseases for other animals. If we could communicate with insects the way we do with other species, there would be an effort to help them. The biggest barrier is language, something that will not be the case with AGI.
And to be clear, I'm actually not an AI catastrophist. I just don't think any sufficiently advanced AI is going to be very motivated to help us with our puny problems. I think it's more likely they'll just fuck off somewhere far away where we can't bother them.
Who do these people think they are? They didn’t even invent the architecture GPT3 is built on! This is as bad or worse than Elon claiming full self driving is just around the corner for almost a decade!
https://proceedings.neurips.cc/paper/2017/file/3f5ee243547de...
For some papers on attention mechanisms from before the 2017 'Attention is all you need' paper, check out that paper's references. Chris Manning's 2015 paper covers attention mechanisms. And so do a few other researchers from that mid-2010s time period:
[21] Minh-Thang Luong, Hieu Pham, and Christopher D Manning. Effective approaches to attention based neural machine translation. arXiv preprint arXiv:1508.04025, 2015.
[22] Ankur Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit. A decomposable attention model. In Empirical Methods in Natural Language Processing, 2016.
The average human cannot summarize (for example) Anna Karenina from memory.
If you taught the average human to do either of those things, they'd do better than ChatGPT does.
But even beyond that point, you have to take a bunch of human time to train an individual those things you're talking about, and then they quit, or get hit by a car. Already GPT has a far larger corpus of information than any individual can hold. It won't quit its job. It can be backed up and restored. And every 6-12 months the systems are getting better.
It's not a fair comparison at all, humans just keep sucking under those constraints.
Just no.
> GPT-3/ChatGPT is much better than the average human at coding, text summarization, etc. (“system 2” cognitive tasks).
I don't think you even believe what you have just said there.
Given it hallucinates 98% of the time and produces incorrect code and also is unable to reason about why it is wrong, it is completely untrustworthy and requires humans to triple check the output. It cannot be used unsupervised and needs constant review.
We haven't even gotten started with the nonsense that it outputs or how it cannot transparently reason about its own decisions in the most serious of applications such as finance, law and medical uses. Meaning that its use is instead reduced to just sophistry generation.
what sort of heavenly company do you work at where most ICs aren't described by this sentence?
With all of that said, I believe that attempts to create such a thing should be frustrated because it is fundamentally anti-human.
The system has to be Intelligent to be an AGI.
Proof: if with AGI we did not imply Intelligence (and only meant "versatile"), we would have to coin a further term for it - "Artificial General Actual Proper Capital I Intelligence"? No need.
If it performs tasks, but not Intelligently, it is not AGI.
Even speaking about AI-intelligence, comparing its output with that of untrained or underperforming humans makes no sense until its output is compared to adequacy.
But, if you wish, you may tell around that we have reached some sort of "AVI", if you wish, with my creative blessing. Unfortunately, 'Artificial Versatile Intelligence' collides with 'Audio Video Interleave'.
> Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return. [0]
After:
> Our mission is to ensure that artificial general intelligence—AI systems that are generally smarter than humans—benefits all of humanity.
In this sentence, they missed out the part where they are to be taking VC capital and selling out closed AI snake-oil to the masses for the dream of AGI science fiction, whilst building untrustworthy systems that are glorified hallucinating black-boxes as a service.
Another overhyped multi-billion dollar exit scam.
[0] https://openai.com/blog/introducing-openai/
Once we have AGI, it won’t be stoppable no matter what we imagine ourself doing. It will basically be like a teenager with superhuman intelligence.
As long as the I/O is limited, I see no problems -- at all -- with AGI.
I am clearly very confused, wrong, or lacking insight into this question.....
Personally, I wonder what would motivate an artificial super-intelligence in the first place.
Getting the monkeys to stop bothering it with stupid questions seems like a pretty solid motivation.
You. You are that evidence. Your intelligence is the result of a trilliontrilliontrillion molecular actions over billions of years that happened to form an intelligence that allowed systematic improvement by sexual reproduction. There was no one designing the system in an organized matter trying to make intelligence. And now that we have a large number of people doing just that, I believe that artificial general intelligence is just a matter of time.
Back in the late 1800's there were plenty of people that said humans would never fly, and yet today I can jump on a jet and circle half way around the world very easily.
Actually that is evidence that AGI happened in the past. It is not any guarantee that it will happen again.
If these developments in AI are really as important as this blog entry says, then it needs democratic control.
Congrats to openAI for being first, but I hope they end up as a footnote in history
But in the AI models we have now, the intelligence is an emergent property of the training data, while the algorithm is fairly simple. So my question is, to what extent is the growth in 2023-style AI capped by the availability of training data? At some point soon, we'll have fed these models with every document ever written; what's the next step up from there?
Some people have cameras and microphones inside their own businesses (CCTV) or home (nanny cams), possibly with lax security settings.
Endgame, just turn on everyone's smartphone camera and microphone for five minutes.
Exception raised on several terms.
«AI models»: they are built (roughly) on the "problem" (task) of "reply something relevant and convincing". Which satisfies the technical contextual definition of "intelligence" ("solving a problem") but not the intrinsic one ("say something through intelligence").
«emergent»: the specific "intelligence" was already there in the training data - it does not emerge but it is repeated.
> to what extent is the growth in 2023-style AI capped by the availability of training data
An intelligent entity does not need to read the whole of past intellectual production: there is no cap. Fed data is already overly plentiful. It does achieve "relevant and convincing", does not it? It is the jump to "reliable" (and beyond) that is missing.
That's not the pattern I see right now with large language model systems, which seem to be capped by how much material they can train on, a bound that is not easy to raise. But that's the kind of development that would make me change my view a lot. Otherwise what's even the purpose of thinking about this stuff, if nothing can change your mind about it?
What if LLMs can be used to train themselves on how to collect data from more diverse and plentiful sources?
The earlier we understand and make that central to our development of it the better for both us and the new human beings we create to join us.
What is your definition? I do not attribute «sentien[ce]» to an evolved analyzer system.
AGI itself will include sentience by definition.
data centres and fabs are an extremely easy target for an organised mob
ludditism 2.0
On the other hand, I believe the Fermi Paradox suggests that AGI is impossible. Machine intelligence would be the perfect vector for rapid galactic conquest. The fact that our planet isn’t covered in solar panels and compute paperclips suggests that super intelligence is either once in a galaxy rare or impossible.
The more I understand how we got life from chemicals (it truly is nothing short of miraculous, even if you like I do not believe in supernatural beginnings), the more I come away with how unlikely it is that we are here. But, here we are! And, so, WE get to populate the galaxy and maybe other galaxies with our Humanity. Lucky us.
There are plenty of other scenarios (they are hiding; they are waiting until we develop Warp Drive, whatever), but applying Occam's Razor says: WE are the first intelligent species in this part of the Universe. And, as a consequence, WE have a chance of using all these atoms out there for our purposes.
To me, this awesome responsibility trumps Little Green Men and their supposed machines populating the galaxies.
As far as we can tell, DNA and single celled life evolved almost as soon as the planet cooled down enough for liquid water. There may have been a short gap of a lifeless water world, but it does appear to be quite short.
Complex multicellular life seems to be extremely rare considering that the Cambrian explosion took billions of years to kick off. Once it got going it moved very fast filling our world with an incredible diversity of life.
Intelligence seems somewhat common considering that it exists in birds, mammals and octopi, something that is probably inevitable once you have multicellular organisms. Human level intelligence might be a bit rare, but probably not particularly. And once you have humans, the race to the stars seems inevitable.
So of all of this, the Cambrian seems mostly likely to be the great filter unless intelligence naturally causes its own extinction in short order.
Civilizations can't get out of their solar system because they invent unaligned AGI first that paperclip-optimizes them out of existence for something else.
Most AGI roadmaps IMO are a form of virtue signaling about how important and smart the authors are with little regard to reality.
> we now believe we were wrong in our original thinking about openness, and have pivoted from thinking we should release everything (though we open source some things, and expect to open source more exciting things in the future!) to thinking that we should figure out how to safely share access to and benefits of the systems
I overheard some colleagues naively hoping capitalism will find a way and we'll just have to work less. This is just not true, look to any of the deindustralised cities in the west, where unemployment, crime and poverty are rampant in once great and cities, where whole communities are essentially forgotten about as an inconvenient truth. That's the future if this stuff works.