Is this case really worth exploring? Or was the article written by a bored AI?
I find it striking that there are still so many people downplaying the latest developments of AI. We all feel that we are at the verge of a next revolution on par or even greater than the emergence of the www, while some people just can't to seem to let it sink in.
Just because people may have opinions different from yours doesn't mean they're denying reality. They just have a different opinion.
The hard, cold truth is that nobody knows the future. Everybody is just guessing.
Climate change is coming at us. That's still a prediction (it hasn't happened yet), but not believing in it right now is irrational and dangerous.
I don't think we can say that for AI. That AI will change the world is a belief. Doesn't mean that it won't.
Crypto's value fluctuation made more sense as a speculative asset class, and it clearly saw most of its traction there.
It's potential as a currency did lead to banks, financial institutions and governments taking a hard look at it. And CBDC's are an area of active investigation. So the hyper-optimists may have been off on some of their predictions, but something came out of it.
AGI-agencent tools are more grounded. They don't threaten to tear down existing entrenched institutions. They do one thing simple: commoditize and scale some level of intelligence. And they're pretty good at it, hence the hype.
Unless humanity develops a deep distaste for many things AI-made, the fascination will wear off and we'll be left with the cold hard truth of raw productivity increase and digital production on an unprecedented scale.
I disagree with this part. (I disagree with calling this tech "AGI-adjacent", too, but that's not the part I'm calling out here).
I'm not sure what you mean by "more grounded", but if you mean "more based in reality", I don't think this is clear. But, if what the evangelizers say is correct, it absolutely threatens to tear down entrenched institutions. It even threatens to tear down society itself by destroying what little trust remains.
IIRC, crypto was a little too idealistic in the promise of providing a digital currency without needing a central, trusted authority to back it. From my perspective, AI as we've seen it in the last few months simply provides a tool that can automate intelligent tasks easily.
I think the distinction is fuelled more by the companies and leading figures pushing the latter. OpenAI's stewardship, concerns for safety and generally downplaying how amazing these tools are while not ignoring the real effects they could have make AI sound more "grounded" than peak crypto was. Or it could just be the folks I pay more attention to.
> I disagree with calling this tech "AGI-adjacent", too, but that's not the part I'm calling out here
I think this rests mostly on the definition of "General" here. Here, I'm talking about LLMs as general task performers, as opposed to models created for more specific tasks. LLMs have proven to be more general purpose, which I'd argue makes them closer to the AGI ideal than, say, a sentiment analysis model.
Ah, I see. By that definition, it seems to me that cryptocurrency was actually more grounded than gpt.
Cryptocurrency (or even blockchain) has not (yet) changed the world. That was what everyone was predicting.
Then it hasn’t changed the world. That phrase doesn’t mean “a small number of things are different” it means that everything has pivoted.
That’s the definition of NOT changing the world.
but the examples of success so far seem cherrypicked leading to serious skepticism. there will be a revolution, and its already in progress dethroning entire business models but the future is still very uncertain.
what is humans role in this adventure into the singularity is even moreso clouded with more questions than answers
Bonus points for things that should cause us to make major adjustments (otherwise it doesn’t seem worth it to expend too much energy).
Have you ever looked at predictions from big consulting companies like McKinsey and the likes? "This new field with unlock a market of 30 billions in the next 5 years", that kind of crap?
In the fields where I worked, I used to take those predictions seriously (after all, they know better than I do, right?). What I realized is that they just don't have a damn clue. I can't blame them for failing: predicting the future is an unsolved problem. But making that kind of money by telling that kind of crap should honestly not be legal.
All that to say, some things are clearly coming right at us (ahem, climate change), some aren't (AI, for instance).
By all means keep your own estimates of what the world will look like in 10 years and act accordingly, but I'm trusting my own technologist's judgement on this one.
I’m excluding the desk jockey pundits from the argument, of course.
I am not estimating anything. I'm saying that there is no way to know where it will go. You are the one doing what the empty suits did: you are predicting something based on your beliefs only.
Not that you can't do it: everyone can believe what they want. But it would be wise to realize that it's a belief, even if you are a technologist.
I don't know, I don't see it this way. Bitcoin at the very beginning was an impressive piece of technology (still is), but it clearly did more harm than good.
Autonomous cars had some very impressive demos, and don't seem to have evolved much in a few years (it's impressive, but not good enough).
AI is making very impressive demos now, but it's not changing the world (what seems to work really well right now is to generate convincing disinformation at scale, which is not good).
To me it's all the same: impressive demo, but what matters is not the first 80%, it's the last 20. Everyone seems to be building infrastructure around what AI will become. Just like people built entire companies betting on the fact that cryptocurrencies would become global (they have not), or that blockchain would be useful outside from cryptocurrencies (it is not). Or like people built entire companies around "the new world with autonomous vehicles".
The problem is we got autonomous cars backwards. We needed multimodal GPT first. GPT-4 can look at a picture can tell you what's happening very clearly. Now, chain this together really fast and you have something that could be used for driving. I'm making no bets on when the hardware/models will be fast/cheap/power efficient enough to support this.
>but it's not changing the world
Eh, no, it is changed the world in a vast number of ways, but not spread very equally. On the scientific/AI side a whole bunch of "20 years away" and "We may never accomplish" have been changed to "now". On the language side things GPT has put any translation service on notice. Summerizers too.
I've never been a crypto fan. I believe there are purposes for it, but at the same time I have a bank that does all the same things.
What I do (did?) not have is an AI that actually solve real life problems that I run into now, and that's something that is both highly useful, and something that many people are willing to pay for.
Again, that's a belief :). Could totally be that they never become a thing, and nobody would be surprised.
It took longer than the likes of Tesla said, but it certainly hasn't been taking longer than a whole lot of people expected.
My prediction is that we're much more than a few years away from it becoming a reality in the way people imagine.
examples?
We haven't even seen a war coming right at us.
My old eyes can't see perfectly anymore, so I would probably miss it - whatever it is - anyway, but if you're so sure, would you bet everything you own on it?
> “[It] revealed an embryo of an electronic computer that it expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence. Later perceptrons will be able to recognize people and call out their names and instantly translate speech in one language to speech and writing in another language, it was predicted”
The section on "Past Winters" in TFA is a good part of the reason why you might want to not believe what you think you see coming right at us ....
Yes, I know. But there's no way to know if these people are right, right now. That will only be possible to know in the future, looking back, so it's still "predicting the future".
Probably, yes, especially after what happened to Cassandra.
Still a fun counterfactual to develop. Lessee, you do know the future, but do not run your mouth off. Matter of fact, you pooh-pooh any such notion ...
A good reason to consider "what if" is that it's still going to take a lot of effort to get from where we are to where expectations are. There's been many false starts recently: self-driving cars, 3D printing, VR/AR, crypto. 10 years on and they're all real technologies anyone can use and making progress every day, but the wild expectations hit reality. When we get there with AI (and we will, because expectations are a moving goalpost) it's good to have considered what we want to do about it. We don't want to waste years of resources on insurmountable roadblocks, we want ideas about why what worked before stopped and what easier paths forward might exist.
That is, I don't see many people downplaying AI but I do see people with lots of unanswerable questions about how long this current boom will last and where we'll wind up when it's over.
I think Moore’s Law could keep going for decades.[2] But even if it doesn’t...
If 1e35 FLOP is enough to train a transformative AI (henceforth, TAI) system,
which seems plausible, I think we could get TAI by 2040...
Second, power consumption is not improving except by going to 8&16 bit... there's not a lot of room there. Currently, we get <1000GFlOPs/W and even if we get 100x up to 100TFLOPs/W, you still need 10^17kWhr. OK algorithms get us another 10,000x... and it costs $1T to train 1 transformative AI. How many proof of concepts trials will be do at only $100B a pop?
It all just seems a bit flip and hopeful like Feb 2000. The 10^35 number seems like its just pulled out to be a number, when it could orders of magnitude up/dn.
https://www.researchgate.net/publication/354573934_Compute_a...
The 1e35 FLOP number is meant as a conservative upper bound and comes from here: https://www.lesswrong.com/s/5Eg2urmQjA4ZNcezy/p/rzqACeBGycZt...
The major fabs all have roadmaps for approaching 1 nm, and there are other advances that could allow you to keep going either if transistor size scaling stops (e.g., vertical scaling). (That said, I definitely don't think it's a given that HW price-performance keeps doubling at the same rate 10+ years.)
Mind you, there are always a variety of possibilities that people see, that is true, but this unique flavor of comment is unique because I haven't seen it expressed before. Not during crypto (as others are bringing it up).
It feels like there's a much more serious... insecurity? Maybe that's too aggressive of a word, but it's one that describes how this downplaying partially is rooted in this idea of a replacement, and lack of job security, and an uncertainty about what you should be spending your time on. All of this is so unique, nobody was feeling this way during crypto, not a single person. If you hated crypto, you were hating it because it sounds redundant, the "fans" were annoying, the environmental impact, etc - not a single one of these reasons came from this assumption that crypto will be the new norm.
So I think that's what a lot of the other comments are missing right now. The downplaying feels totally different now. As if even the people who are downplaying realize what's happening, but don't want it to be true.
I did like this blog post though, outside of what we're talking about.
A fair number of HN'ers are the "pull yourselves up by the bootstraps", "We don't need to stinking unions", "Social safety nets are for the weak" types. The potential for AGI causes a cognitive dissonance with them. They are intelligent enough to realize that AGI would nearly completely destroy their ability to make money, but at the same they don't want to release their ideals that "rugged individualism" is why they are better than everyone else, and they would need a more fair system to survive.
Maybe ChatGPT would have suggested that had I ran the comment through it prior instead of sounding like a bumbling fool lol
I'm a crypto and AI optimist, but a tempered optimist. I don't think either tech is imminently going to disrupt everything, but I think both technologies have their use cases. They are far more modest than their most ardent supporters would believe. However, over the course of decades, the tech can transform society, I still think that.
However, as with the internet itself, which never did live up to its loftiest, most optimistic ambitions, it's not to downplay the impact at all. Just thay eventually you do find a point where you grapple with the tradeoffs inherent in the technology and those are often sticky and intractable.
Yes! You’ve mentioned people downplaying, but this is someone who is 95% confident there won’t be an AI winter in the next seven years. That’s really quite confident. And the definition he gave makes it compatible with AI being the biggest thing since sliced bread. But if it gets funded at 3x bread and scales down to 1x bread, that will count.
What cost was this exploration? A blog post? An HN discussion. I think it’s so valuable for people to consider the scenarios they think are unlikely. I find this analysis much more interesting than all the dismissive “my job is safe, AI can’t [friction-point-of-existing-system]” posts. It’s certainly worth the investment of a few hours of work.
If that's the case, I think those, like most people, are taking the advancements seriously. I would say to those people: don't worry too much.
The impact will be big, but it doesn't have to mean people will not have a job anymore, the tools they use will be at another level.
You've made me realize the difference between the arguments I find weak vs strong. The weak argument is I can do something that ChatGPT can't. "I have people skills!". The strong argument is that as ChatGPT grows, I will grow with it.
The AI floodwaters are rising. People are climbing up the stairs when they should be building boats. If you seek shelter and are wrong about how far this goes, your attic will become a coffin.
5-7 years ago the progress with self driving cars seemed enormous, and the end of driving was just around the corner. And then all progress seemed to stall or recede, and it turned out that what seemed like huge progress was mostly hot air.
Maybe that’s not what happening now, but I don’t think a cautious approach is unwarranted.
Yep, but a lot of the current hype for GPT is that we're in the near-vertical segment of the sigmoid, and so people are like "woah, if that's where we are now, where will we be in 5-10 years?!". And the answer to that might be, pretty much where we are now. And maybe not, maybe it'll be better, but you can't assume linear improvements on a sigmoid curve.
In theory if we could make multi-modal GPT-4 go very fast, we could have it operate a car right now. It's too bad we don't have access to feed it images, because my guess is if you put a picture of an inside of the car and showed a kid chasing a ball into the road in front of it, it's first guess would be "hit the brakes".
- Redundant due to winner takes all dynamics. - Useless - Way to expensive for what it does. - Produced off of sky-high seed rounds at 150 MM.
This same dynamic happened with the www leading to an eventual crash - the mobile and social versions would have been more noticeable had it not happened in private markets and simultaneously with the valuation spike of the late teens. It would be almost more surprising if there wasn't a pull back eventually.
This also doesn't say anything about the people who work in AI. It's not a given that the legions of research scientists populating corporate labs will be the right people for new startups. Similarly it may turn out that prompt engineering is the dominant method for talking to LLMs rather than code.
Let people play with GPT 4 for a bit.
but the future is very unclear.
It's obvious at this point that we are figuring out how to create machines that think. While I agree that the future is unclear, in the sense that it's hard to make exact predictions, the trend is very clear. Significant efficiency improvements in many types of intellectual labor is almost certain.
I don't think it's priced in yet; the somewhat independent-minded among tech people are currently the only ones who have front-row seats to what's going on. But in a few years it will be obvious.
Honestly, I think the persistent exponential improvement in AI makes it obvious we're on track for superintelligent machines in a few decades as well (if that!), but the preceding paragraphs should at least be entering the realm of Overton.
Is this something you can see so clearly that you can describe it in specific terms?
At first we were perplexed by a computer beating Karpov at chess.
These days however we're not perplexed anymore that a lot of creative jobs have been replaced by AI. (I think those people will find another passion no doubt, that is another topic).
Next thing is less creative jobs. But i'm already thinking about climate change and hunger mitigation. You could call me an idealist, only time can tell, of course.
* generate digital images from natural language descriptions. ie. DALL-E
* suggest code and entire functions. ie. Copilot
* generate textual content: Generative Pre-trained Transformer. ie. ChatGPT
The future may be in other important endeavors:
* train on ... data and learn how to ... to automate ...
I think that the creativity is in your idea and not in what is being automatically generated.
Edit: That may the lesson of Stable Diffusion: ideas are very cheap, if you have a heuristic for what a good idea is. Generate a business, fix it by optimizing for measurable metrics, if it doesn't work, try again. Legal constraints can be interpreted by an LLM, fines are penalties for training.
I think in terms of human ingenuity, the digital space is finished in the long run. It will all be on the level of infrastructure funneling data to corporations.
The space to innovate with the low-hanging fruit still lies in engineering physical things, where implementation and testing is still a barrier to iterating quickly.