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Ask HN: So.. what's next after LLMs?
34 points by moomoo11 6 months ago | hide | past | favorite | 34 comments
I'm curious as to what comes after this "shove LLM into everything and call it a day" phase is over.

I'm also not exactly convinced when some CEO fires 100 employees in these market conditions, and then says how AI is helping them. Sorry, but these aren't exactly companies that are pushing the needle forward (mostly BPO and low margin non-tech businesses, or companies that have been around a while and still don't seem to get anywhere). It isn't that sexy to say we fired 100 people to save $5 million opex, I'm sure they want to raise more money slapping "AI" onto their brand.

So what's next?

Are you working on something interesting that pushes the boundaries? Or what are you following that some of us don't know much about?




First we had deep learning - i.e fully connected layers with some data conditioning in between. This kicked off the current ML ecosystem, when people figured out stuff like auto encoders.

Then we had RNN, which have the output fed back into the input. This gave the networks some form of memory.

Then we had Transformers, which are basically parallel processors. I.e generate 3 outputs in parallel, multiply them together. This was basically just a better form of compression applicable to everything.

The general trend here is that someone discovers some architecture that works out nicely and then everyone builds something around it. This is probably going to be the future. Google has some neat things with automated robotics, OpenAi has their A* stuff thats supposed to be "accurate" instead of probabilistic.

Then there is the hardware piece, which I know much less about, but hoping companies like Tinycorp or Tenstorrent give us a way to reliably run something like GPT3 full parameter model at home.


Accurate Vs probabilistic is exactly the phrase I've been looking for. Thanks


> Tinycorp or Tenstorrent

Not only framework optimization and hardware optimization are progressing: also algorithmic optimization.

For example, https://infini-ai-lab.github.io/Sequoia-Page/


My guess is the next big AI product will be local/edge and always-running (can initiate conversation passively). I also think deeply integrated AI into non-conversational software (again, local AI) capable of understanding and working within the embedded domain will become more widespread.


My wishful thinking is that instead of the corporate lead "ai evolution" some breakthrough and leak turns it into an "ai revolution" where a free linux OS comes with absolute privacy enforcement, ad busting in all forms of media and sites, automatic dark pattern removing web browser, untracable piracy, mass scale detection and highlighting of country trends in censorship / fake news / authoritarianism. And that it puts a ton of new pressure on companies having to have some sort of publicly proven morals


I really hope something more transparent, understandable and debuggable.

Also preferably something that wouldn't trigger the third contest about who can waste the most energy (after first crypto's proof-of-work insanity and then trillion-parameter models that needed a datacenter full of H100 GPUs just for training) while the climate change trajectory is already becoming more and more dire and we all really ought to reduce energy usage as much as possible.


Well at least LLMs are incredibly useful, as opposed to the crypto farms that waste resources just to create scarcity. I don't think it's nearly as much of a waste. Also, those couple months in that data center can create a model that millions of people can benefit from. The inference is already setting an optimisation phase where soon it can be done on dedicated mobile hardware at low energy. Bitcoin went through this too but the problem is that there is only led to more wasted resources because wasting resources is the whole point. AI will not have this issue. It will stabilise and energy use will drop due to optimisation.

It's funny though, our company is pushing all this "Green IT" nonsense internally, telling us to turn off a 10kB email banner but at the same time investing really big into everything AI because they're terrified to miss the boat. And to deal with this hypocrisy they're making ever more ridiculous greenwashing claims "One email banner wastes as much energy as 10 washing machines!". Literally, that's what they told us. In a 200MB video on our intranet. While everyone is doomscrolling TikTok and watching music videos on YouTube because they blocked Spotify on the company network.

What we have to do is be smarter with our energy but I think AI can help there too. Not flying hand the world around for every meeting too.


(Edit: I forgot a third relevant point)

I am not sure I get exactly what you are pointing to, but synthetic logical answers are:

-- the lucidity after the fever, and

-- striving to implement what was missed. Plus,

-- understanding why what somehow works does work, and build knowledge on that.

For the first: LLMs will be placed in dangerous places as flexible but improper frameworks as a practice that will be deprecated by the community, and will in parallel be implemented in the places where they actually fit (we discussed a few possibility yesterday in these pages, for example).

For the second: the implementation of artificial morons (some handfuls of months ago) makes the "real thing" - something that reasons, that thinks organically, that criticizes its own contents, that is reliable - more missed, so more investment will be done towards that progress.

For the third: research will continue exploring why LLMs can produce surprising results (that some have linked to "scale"); knowledge built in this effort will eventually lead to progress.

Meanwhile, real needs will be tackled by businesses.

(If you can clarify what I missed in the question, please do.)


I agree with your assessment that a lot of this stuff is BPO. There is only so much customer service that can be automated. That being said, AI is a big tent and has been around for decades, despite the media claiming that OpenAI has been the first company to take it into the mainstream. AI flies fighter jets without any human pilots. I personally think there is already a lot of impressive stuff happening with reinforcement learning and am excited to see where large action models go, despite rabbit's failures.


The poster hints («AI ... has been around for decades») but does not say explicitly: also deterministic AI has found its space in business since a long time.

Revolutions with Machine Learning are more recent; «AI flies fighter jets without any human pilots» - and the deterministic algorithms of the late Professor of AI at the MIT parked planes maximizing fuel efficiency, for example.


Aren't «fighter jets» without «human pilots» just «remote controlled» or am I «mistaken» about that?

«That doesn't sound» like AI».


No, there are fully autonomous fighter jets that outperform and outmaneuver the best human fighter pilots with no human control remote or otherwise.


The original post used angle quote marks to denote inline literal quotations from its parent.

It does not seem clear instead what you tried to do with your style.


»I did the same thing «with my» » style»


It's possible that our next generation advances will be made inside, for example, bioengineering. I'm not super well versed on the topic so this is very speculative, but I've read a lot of cool stuff about DNA-based data storage solutions, and the thought now comes to me that may be that maybe lab-grown brains could achieve some interesting tasks.


Nobody can predict the future, but what is currently researched: - coupling deep learning with some kind of memory

- non generative hierarchical architecture (see LeCun JEPA)

- mixing deep learning with symbolic methods (usually search over token or latent space, it can also be a coupling with symbolic engines. Coupling LLMs with wolfram was a very early example)

- ability to perform unbounded computation per token inside a deep network. Something like Universal Transformers


What's next is real apps using LLMs efficiently. It's weird but besides chatGPT I see no game changing apps.


Probably LMMs (Large Multimodal Models) maybe?

I am not entirely sure if this'll be the future, but having one model that has relatively good performance over a huge range of types of data feels pretty good tbh


Marshal Brain wrote this about 20 years ago…

https://marshallbrain.com/manna


Neat, dragged a little near the end, but a fun quick read.

I estimate technologically we’re at around the middle of chapter 3?


i loved manna. So utopian, a lovely picture of what could be. Anyone know anything with a similar utopic bent like that?


Humanoid robotics and "smart" glasses are the most intriguing to me to own on a personal level

Trust/truth apocalypse is the most concerning near-term


LLMs already created a trust/truth apocalypse in India in the most recent elections. There are fake videos (or accusations of fake videos!) absolutely flooding WhatsApp. A lot of people there can't tell what's real.


LLMs don't make videos. Those are also AI but different tech.

But really it's more of a symptom. You can fake stuff with people too. It's just more work. The question is more why the most populous nation lets this happen rather than the tools used to do it.


How would any nation stop it? And why would you want a nation to have so much control over speech that they could stop all deceptive content?

The problem isn't the nation. It's the cheap availability of software that produces lies at enormous, convincing scale. No one says "don't blame the tool" when talking about bombs. AI is a social bomb.


Bombs don't drop themselves, the problem is that people feel the need to maliciously manipulate others. It's not just fake videos either, there are fake personalities whose main purpose is to troll and rage bait so people fight each other instead of the malfeasance behind these activities


I heard about that but am unaware of the scope / avenues it took

There was the fake Biden robocalls during the NH primaries in the US, so far that we officially know of


https://www.wired.com/story/indian-elections-ai-deepfakes/


As a Gibson fan: this sounds like his robot avatars from The Peripheral and the VR glasses from Virtual Light.

In his most recent book, Agency, he describes 'laminar agents'. They're basically uncensored multimodal LLMs that can see the world through VR glasses.

Interestingly, Neal Stephenson named his metaverse company Lamina1. I like to think he named it after the term in Agency.


I think of Rosey from Jetsons and Detroit: Become Human for the dystopian realities that are probably more likely than we'd want

Having a Hololens 2, an experience that is worth trying, just waiting for FOV to improve, and to a lesser extent for the form factor to shrink. I would use the HL2 for monitors if the FOV was there, it's really light


Hopefully not my long term unemployment, hopefully.


I’m looking forward to services that provide good value using the essentials - as an alternative of the deeply enshittificated by LLMs versions. I’m already looking at Kagi for example.

Color me skeptical but the probabilistic nature of LLMs is at their core and is a hard limit to how useful they can be in wide applications. Currently their input and influence are limited to bulshitting - useful for mass cheap propaganda, seo spam and writing soulless student essays or slightly wrong boilerplate code.

In an informational landscape that is the equivalent of an infinite garbage dump, purity becomes priceless — the new unobtanium.


I think we’ll be on this train for a while and it’ll just scale insanely far ( think photonics etc)


After LLMs? I prefer a better, more accurate LLM.




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