Game over. AGI is not imminent, and LLMs are not the royal road to getting there

That sign would be more valuable than the one Sam Altman’s been holding saying “AGI in 2025”

Symbolic AI didn’t die tho, it was just merged with deep learning either as complementary from the get go e.g. AlphaGo which uses Symbolic AI to feed a deep neural network or now as a post processing / interventionary technique for guiding and optimizing outputs of LLM, human in the loop and MoR are very much Symbolic AI techniques.

I'm not sure it's true that symbolic AI is dead, but I think Gary Marcus style symbolic AI is. His "next decade in AI" paper doesn't even mention symbolic regression. For those who don't know, linear regression tries to find a linear fit against a dataset. Quadratic regression a quadratic fit. And so on. Symbolic regression tries to find a symbolic expression that gives you an accurate data fit.

Symbolic regression has an extremely obvious advantage over neural networks, which is that it learns parameters and architecture simultaneously. Having the correct architecture means that the generalization power is greater and that the cost of evaluation due to redundant parameters is lower. The crippling downside is that the search space is so vast that it is only applicable to toy problems.

But Gary Marcus is in favour of hybrid architectures, so what would that look like? In the SymbolNet paper, they have essentially decided to keep the overall neural network architecture, but replaced the activation functions with functions that take multiple inputs aka symbols. The network can then be pruned down into a symbolic expression.

That in itself is actually a pretty damning blow to Gary Marcus, because now you have most of the benefits of symbolic AI with only a tiny vestige of investment into it.

What this tells us is that fixed activation functions with a single input appear to be a no go, but nobody ever said that biological neurons implement sigmoid, relu, etc in the first place. It's possible that the spike encoding already acts as a mini symbolic regressor and gives each neuron its own activation function equivalent.

The "Neuronal arithmetic" paper has shown that biological neurons can not only calculate sums (ANNs can do this), but also multiply their inputs, which is something the activation functions in artificial neural networks cannot do. LLMs use gating in their MLPs and attention to explicitly model multiplication.

There is also the fact that biological neurons form loops. The memory cells in LSTMs perform a similar function, but in the brain there can be memory cells everywhere whereas in a fixed architecture like LSTMs they are only where the designer put them.

It seems as if the problem with neural networks is that they're too static and inflexible and contain too much influence from human designers.

I don’t think either of your first two statements are accurate, what is your support for those claims?

GPT5 compared to the original GPT4 is a huge improvement. It exceeded all my expectations from 2 years ago. I really doubted most GPT4 limitations will be resolved so quickly.

If they manage a similar quality jump with GPT6, it will probably meet most reasonable definitions of AGI.

I’m not sure an ad hominem assault is any different. You make proclamations without any evidence as if what you say has any more credibility than the next person. In fact, this response makes a reasonable person discount you.

Sure, it reads like some biased and coping, possibly even interested or paid hit-piece as if what happens can be changed by just being really negative about LLMs, but maybe consider taking your own advice there, kid; you know, an extended break.

If our markets weren’t corrupt, everyone in the AI space would be bankrupt by now, and we could all wander down to the OpenAI fire sale and buy nice servers for pennies on the dollar.

I’m not convinced the current capabilities have impacted all that many people. I think the economy is much more responsible for the lack of jobs than “replacement with AI”, and most businesses have not seen returns on AI.

There is a tiny, tiny, tiny fraction of people who I would believe have been seriously impacted by AI.

Most regular people couldn’t care less about it, and the only regular people I know who do care are the ones actively boycotting it.

> > Serious question: Who in HN is actually looking forward to AGI existing?

I am.

It's he only serious answer to the question of space exploration. Rockets filled with squishy meat were never going to accomplish anything serious, unless we find a way of beating the speed of light.

Further, humanities greatest weakness is that we can't plan anything long-term. Our flesh decays too rapidly and our species is one of perpetual noobs. Fields are becoming too complex to master in a single lifetime. A decent super-intelligence can not only survive indefinitely, it can plan accordingly, and it can master fields that are too complex to fit inside a single human skull.

Sometimes I wonder if humanity wasn't just evolutions way of building AI's.

I was content even without AI. I’m good with whatever we have today as long we use them to change the life in a positive way.

I'm looking forward to artificial people existing. I don't see how they'd be a money-spinner, unless mind uploading is also developed and so they can be used for life extension. The LLM vendors have no relevance to AGI.

I am not against AGI, just the method and the players we have getting there. Instead of a curiosity to find intelligence, we just have rabid managers and derailed billionaires funding a race to … what? I don’t think even they know beyond a few hype words in their vocab and a buzz to bullshit powerpoint presentation.

> Serious question: Who in HN is actually looking forward to AGI existing?

90% of the last 12 batches of YC founders would love to believe they are pursuing AGI with their crappy ChatGPT wrapper, agent framework, observability platform, etc.

> For regular people the current AI capabilities have already led to either life changing skill improvement for those who make things for themselves or life changing likely permanent employment reduction for those who do things for others

This statement sums up the tech centric bubble HN lives in. Your average former, shop assistant, fisherman or wood worker isn't likely to see significant life improevments from the transformer tech deployed until now.

As a rule: inference is very profitable, frontier R&D is the money pit.

They need the money to keep pushing the envelope and building better AIs. And the better their AIs get, the more infra they'll need to keep up with the inference demand.

GPT-4.5's issue was that it wasn't deployable at scale - unlike the more experimental reasoning models, which delivered better task-specific performance without demanding that much more compute.

Scale is inevitable though - we'll see production AIs reach the scale of GPT-4.5 pretty soon. Newer hardware like GB200 enables that kind of thing.

They are raising the money because they can. While these businesses may go bankrupt, many people who ran these businesses will make hundreds of millions of dollars.

Either that or AGI is not the goal, rather it’s they want to function for, and profit off of , a surveillance state that might be much more valuable in the short term.

If by AGI you mean "can do any economic task humans currently do", that is within the range of a "few months," though the rollout will be incremental since each economic task has to be independently taught, there are supply chain issues, and AI-first companients will need to be developed to take best advantage of it, etc.

But all of this is much closer than people seem to realize.