Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI 2027

ai-2027.com

Post reply on HN
Print view View original

481–490 of 641 posts

Re: AI 2027

#481

Post by polynomial »

wg0 wrote: post #479

Very detailed effort. Predicting future is very very hard. My gut feeling however says that none of this is happening. You cannot put LLMs into law and insurance and I don't see that happening with current foundations (token probabilities) of AI let alone AGI. By law and insurance - I mean hire an insurance agent or a lawyer. Give them your situation. There's almost no chance that such a professional would come wrong…

> You cannot put LLMs into law and insurance

Cass Sunstein would very strongly disagree.

Re: AI 2027

#482

Post by lordswork »

bko wrote: post #404
stego-tech wrote: post #279

It’s good science fiction, I’ll give it that. I think getting lost in the weeds over technicalities ignores the crux of the narrative: even if this doesn’t lead to AGI, at the very least it’s likely the final “warning shot” we’ll get before it’s suddenly and irreversibly here. The problems it raises - alignment, geopolitics, lack of societal safeguards - are all real, and happening now (just replace “AGI” with “corpo…

> The problems it raises - alignment, geopolitics, lack of societal safeguards - are all real, and happening now (just replace “AGI” with “corporations”, and voila, you have a story about the climate crisis and regulatory capture). Can you point to the data that suggests these evil corporations are ruining the planet? Carbon emissions are down in every western country since 1990s. Not down per-capita, but down in abs…

Emissions are trending downward because of shift from coal to natural gas, growth in renewable energy, energy efficiencies, among other things. Major oil and gas companies in the US like Chevron and ExxonMobil have spent millions on lobbying efforts to resist stricter climate regulations and fight against the changes that led to this trend, so I'd say they are the closest to these evil corporations OP described. Additionally, the current administration refers to doing anything about climate change a "climate religion", so this downward trend will likely slow.

The climate regulations are still quite weak. Without a proper carbon tax, a US company can externalize the costs of carbon emissions and get rich by maximizing their own emissions.

Re: AI 2027

#483

Post by benlivengood »

Vegenoid wrote: post #474

I think we've actually had capable AIs for long enough now to see that this kind of exponential advance to AGI in 2 years is extremely unlikely. The AI we have today isn't radically different from the AI we had in 2023. They are much better at the thing they are good at, and there are some new capabilities that are big, but they are still fundamentally next-token predictors. They still fail at larger scope longer ter…

METR [0] explicitly measures the progress on long term tasks; it's as steep a sigmoid as the other progress at the moment with no inflection yet.

As others have pointed out in other threads RLHF has progressed beyond next-token prediction and modern models are modeling concepts [1].

[0] https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com...

[1] https://www.anthropic.com/news/tracing-thoughts-language-mod...

Re: AI 2027

#484

Post by Fraterkes »

benlivengood wrote: post #483
Vegenoid wrote: post #474

I think we've actually had capable AIs for long enough now to see that this kind of exponential advance to AGI in 2 years is extremely unlikely. The AI we have today isn't radically different from the AI we had in 2023. They are much better at the thing they are good at, and there are some new capabilities that are big, but they are still fundamentally next-token predictors. They still fail at larger scope longer ter…

METR [0] explicitly measures the progress on long term tasks; it's as steep a sigmoid as the other progress at the moment with no inflection yet. As others have pointed out in other threads RLHF has progressed beyond next-token prediction and modern models are modeling concepts [1]. [0] https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com... [1] https://www.anthropic.com/news/tracing-thoughts-language-mod...

The METR graph proposes a 6 year trend, based largely on 4 datapoints before 2024. I get that it is hard to do analyses since were in uncharted territory, and I personally find a lot of the AI stuff impressive, but this just doesn't strike me as great statistics.

Re: AI 2027

#485

Post by barotalomey »

somebodythere wrote: post #467
barotalomey wrote: post #440

It's always "soon" for these guys. Every year, the "soon" keeps sliding into the future.

AGI timelines have been steadily decreasing over time: https://www.metaculus.com/questions/5121/date-of-artificial-... (switch to all-time chart)

You meant to say that people's expectations have shifted. That's expected seeing the amount of hype this tech gets.

Hype affects market value tho, not reality.

Re: AI 2027

#486

Post by wruza »

nikisil80 wrote: post #451
visarga wrote: post #431

The story is entertaining, but it has a big fallacy - progress is not a function of compute or model size alone. This kind of mistake is almost magical thinking. What matters most is the training set. During the GPT-3 era there was plenty of organic text to scale into, and compute seemed to be the bottleneck. But we quickly exhausted it, and now we try other ideas - synthetic reasoning chains, or just plain synthetic…

Best reply in this entire thread, and I align with your thinking entirely. I also absolutely hate this idea amongst tech-oriented communities that because an AI can do some algebra and program an 8-bit video game quickly and without any mistakes, it's already overtaking humanity. Extrapolating from that idea to some future version of these models, they may be capable of solving grad school level physics problems and…

programming entire AAA video games

Even this is questionable, cause we're seeing it making forms and solving leetcodes, but no llm yet created a new approach, reduced existing unnecessary complexity (which we created mountains of), made something truly new in general. All they seem to do is rehash of millions of "mainstream" works, and AAA isn't mainstream. Cranking up the parameter count or the time of beating around the bush (aka cot) doesn't magically substitute for lack of a knowledge graph with thick enough edges, so creating a next-gen AAA video game is far out of scope of llm's abilities. They are stuck in 2020 office jobs and weekend open source tech, programming-wise.

Re: AI 2027

#488

Post by dcanelhas »

> Once the new datacenters are up and running, they’ll be able to train a model with 10^28 FLOP—a thousand times more than GPT-4.

Is there some theoretical substance or empirical evidence to suggest that the story doesn't just end here? Perhaps OpenBrain sees no significant gains over the previous iteration and implodes under the financial pressure of exorbitant compute costs. I'm not rooting for an AI winter 2.0 but I fail to understand how people seem sure of the outcome of experiments that have not even been performed yet. Help, am I missing something here?

Re: AI 2027

#489

Post by the8472 »

dcanelhas wrote: post #488

> Once the new datacenters are up and running, they’ll be able to train a model with 10^28 FLOP—a thousand times more than GPT-4. Is there some theoretical substance or empirical evidence to suggest that the story doesn't just end here? Perhaps OpenBrain sees no significant gains over the previous iteration and implodes under the financial pressure of exorbitant compute costs. I'm not rooting for an AI winter 2.0 but…

https://gwern.net/scaling-hypothesis exponential scaling has been holding up for more than a decade now, since alexnet.

And when there were the first murmurings that maybe we're finally hitting a wall the labs published ways to harness inference-time compute to get better results which can be fed back into more training.

Re: AI 2027

#490

Post by somebodythere »

barotalomey wrote: post #485
somebodythere wrote: post #467

Earlier quoted context omitted.

AGI timelines have been steadily decreasing over time: https://www.metaculus.com/questions/5121/date-of-artificial-... (switch to all-time chart)

You meant to say that people's expectations have shifted. That's expected seeing the amount of hype this tech gets. Hype affects market value tho, not reality.

I took your original post to mean that AI researchers' and AI safety researchers' expectation of AGI arrival has been slipping towards the future as AI advances fail to materialize! It's just, AI advances have been materializing, consistently and rapidly, and expert timelines have been shortening commensurately.

You may argue that the trendline of these expectations is moving in the wrong direction and should get longer with time, but that's not immediately falsifiable and you have not provided arguments to that effect.

Post reply on HN