Top physicist says chatbots are just ‘glorified tape recorders’
Top physicist says chatbots are just ‘glorified tape recorders’
Michio Kaku predicts a different computing revolution lies ahead.
Top physicist says chatbots are just ‘glorified tape recorders’::Leading theoretical physicist Michio Kaku predicts quantum computers are far more important for solving mankind’s problems.
A physicist is not gonna know a lot more about language models than your average college grad.
That's absolute nonsense. Physicists have to be excellent statisticians and, unlike data scientists, statisticians have to understand where the data is coming from, not just how to spit out simple summaries of enormously complex datasets as if it had any meaning without context.
And his views are exactly in line with pretty much every expert who doesn't have a financial stake in hyping the high tech magic 8-ball. On the Dangers of Stochastic Parrots.
I disagree, physics is the foundational science of all sciences. It is the science with the strongest emphasis on understanding math well enough to derive the equations that actually take form in the real world
Therefore, if you know physics, you know everything.
Yes. Glorified tape recorders that can provide assistance and instruction in certain domains that is very useful beyond what a simple tape recorder could ever provide.
Yes. Glorified tape recorders that can provide assistance and instruction in certain domains that is very useful beyond what a simple tape recorder could ever provide.
I think a good analogue is the invention of the typewriter or the digital calculator. Its not like its something that hadn't been conceived of or that we didn't have correlatives for. Is it revolutionary? Yes, the world will change (has changed) because of it. But the really big deal is that this puts a big bright signpost of how things will go far off into the future. The typewriter led to the digital typewriter. The digital typewriter showed the demand for personal business machines like the first apples.
Its not just about where were at (and to be clear, I am firmly in the 'this changed the world camp'. I realize not everyone holds that view; but as a daily user/ builder, its my strong opinion that the world changed with the release of chatgpt, even if you can't tell yet.), the broader point is about where we're going.
The dismissiveness I've seen around this tech is frankly, hilarious. I get that its sporting to be a curmudgeon, but to dismiss this technology will be to have completely missed what will be one of the most influential human technologies to have been invented. Is this general intelligence? To keep pretending it has to be AGI or nothing is to miss the entire damn point. And this goal post shifting is how the frog gets slowly boiled.
I reckon it’s somewhere in between. I really don’t think it’s going to be the revolution they pitched, or some feared. It’s also not going to be completely dismissed.
I was very excited when I started to play with various AI tools, then about two weeks in I realized how limited they are and how they need a lot of human input and editing to produce a good output. There’s a ton of hype and it’s had little impact on the regular persons life.
Biggest application of AI I’ve seen to date? Making presidents talk about weed, etc.
I find it fascinating how different sections of society see the tech totally differently, a lot of people seem to think because it can't do everything it can do nothing. I've been fascinated by ai for decades so to have finally cracked language comprehension feels like huge news because it opens so many other doors - especially in human usability of new tools.
We're going to see a huge shift in how we use technology, I don't think it will be long before we're used to telling the computer what we want it to do - organising pictures, sorting inventory in a game, finding products in shops... Being able to actually tell it 'i want a plug for my bath' and not being offered electrical plugs, even being told 'there are three main types as seen here, you will need to know the size of your plug hole to ensure the correct fit'
As the technology refines we'll see it get increasingly reliable for things like legal and medical knowledge, even if it's just referring people to doctors it could save a huge amount of lives.
It's absolutely going to have as much effect on our lives as the internet's development did, but I think a lot of people forget how significant that really was.
yeah, a "tape recorder" that adapts to what you ask... if there was a tape recorder before where i could put the docs i written and get recommendations on how to improve my style and organization, i missed it
Well it’s like a super tape recorder that can play back anything anyone has ever said on the internet.
But altered almost imperceptibly such that it's entirely incorrect.
Remember the time Michio Kaku went on CBS to talk about Hurricane Harvey despite not being an expert on Hurricanes? He is a clout chaser who regularly steps outside his expertise to make hot takes for attention.
I also recommend this video that touches on Michio Kaku talking about things outside his expertise.
He's not even a top physicist, just well known.
I wouldn't call this guy a top physicist... I mean he can say what he wants but you shouldn't be listening to him. I also love that he immediately starts shilling his quantum computer book right after his statements about AI. And mind you that this guy has some real garbage takes when it comes to quantum computers. Here is a fun review if you are interested https://scottaaronson.blog/?p=7321.
The bottom line is. You shouldn't trust this guy on anything he says expect maybe string theory which is actually his specialty. I wish that news outlets would stop asking this guy on he is such a fucking grifter.
I wouldn't call this guy a top physicist... I mean he can say what he wants but you shouldn't be listening to him.
Yeah I don't see how he has any time to be a "top physicist" when it seems he spends all his time on as a commenter on tv shows that are tangentially related to his field. On top of that LLM is not even tangentially related.
Leading theoretical physicist Michio Kaku
I wouldn’t listen too closely to discount Neil deGrasse Tyson these days, especially in domains in which he has no qualifications whatsoever.
Just set your expectations right, and chat it's are great. They aren't intelligent. They're pretty dumb. But they can say stuff about a huge variety of domains
I understand that he's placing these relative to quantum computing, and that he is specifically a scientist who is deeply invested in that realm, it just seems too reductionist from a software perspective, because ultimately yeah - we are indeed limited by the architecture of our physical computing paradigm, but that doesn't discount the incredible advancements we've made in the space.
Maybe I'm being too hyperbolic over this small article, but does this basically mean any advancements in CS research are basically just glorified (insert elementary mechanical thing here) because they use bits and von Neumann architecture?
I used to adore Kaku when I was young, but as I got into academics, saw how attached he was to string theory long after it's expiry date, and seeing how popular he got on pretty wild and speculative fiction, I struggle to take him too seriously in this realm.
My experience, which comes with years in labs working on creative computation, AI, and NLP, these large language models are impressive and revolutionary, but quite frankly, for dumb reasons. The transformer was a great advancement, but seemingly only if we piled obscene amounts of data on it, previously unspeculated of amounts. Now we can train smaller bots off of the data from these bigger ones, which is neat, but it's still that mass of data.
To the general public: Yes, LLMs are overblown. To someone who spent years researching creativity assistance AI and NLPs: These are freaking awesome, and I'm amazed at the capabilities we have now in creating code that can do qualitative analysis and natural language interfacing, but the model is unsustainable unless techniques like Orca come along and shrink down the data requirements. That said, I'm running pretty competent language and image models on 12GB of relatively cheap consumer video card, so we're progressing fast.
Edit to Add: And I do agree that we're going to see wild stuff with quantum computing one day, but that can't discount the excellent research being done by folks working with existing hardware, and it's upsetting to hear a scientist bawk at a field like that. And I recognize I led this by speaking down on string theory, but string theory pop science (including Dr. Kaku) caused havoc in people taking physics seriously.
He is trying to sell his book on quantum computers which is probably why he brought it up in the first place
Oh for sure. And it's a great realm to research, but pretty dirty to rip apart another field to bolster your own. Then again, string theorist...
My opinion is that a good indication that LLMs are groundbreaking is that it takes considerable research to understand why they give the output they give. And that research could be for just one prediction of one word.
For me, it's the next major milestone in what's been a roughly decade-ish trend of research, and the groundbreaking part is how rapidly it accelerated. We saw a similar boom in 2012-2018, and now it's just accelerating.
Before 2011/2012, if your network was too deep, too many layers, it would just breakdown and give pretty random results - it couldn't learn - so they had to perform relatively simple tasks. Then a few techniques were developed that enabled deep learning, the ability to really stretch the amount of patterns a network could learn if given enough data. Suddenly, things that were jokes in computer science became reality. The move from deep networks to 95% image recognition ability, for example, took about 1 years to halve the error rate, about 5 years to go from about 35-40% incorrect classification to 5%. That's the same stuff that powered all the hype around AI beating Go champions and professional Starcraft players.
The Transformer (the T in GPT) came out in 2017, around the peak of the deep learning boom. In 2 years, GPT-2 was released, and while it's funny to look back on now, it practically revolutionized temporal data coherence and showed that throwing lots of data at this architecture didn't break it, like previous ones had. Then they kept throwing more and more and more data, and it kept going and improving. With GPT-3 about a year later, like in 2012, we saw an immediate spike in previously impossible challenges being destroyed, and seemingly they haven't degraded with more data yet. While it's unsustainable, it's the same kind of puzzle piece that pushed deep learning into the forefront in 2012, and the same concepts are being applied to different domains like image generation, which has also seen massive boosts thanks in-part to the 2017 research.
Anyways, small rant, but yeah - it's hype lies in its historical context, for me. The chat bot is an incredible demonstration of the incredible underlying advancements to data processing that were made in the past decade, and if working out patterns from massive quantities of data is a pointless endeavour I have sad news for all folks with brains.
Well, one could argue that our brain is a glorified tape recorder.
behold! a tape recorder.
holds up a plucked chicken
He's a physicist. That doesn't make him wise, especially in topics that he doesn't study. This shouldn't even be an article.
What’s a physicist going to know about machine learning and AI?
Is the logic really “he has a smart sounding job therefore he knows stuff about other smart sounding things”?
Idiotic headline written by slimey journalists to cater to knuckledraggers.
They could know quite a lot, ML is still a rather shallow field compared to the more established sciences, it's arguably not even a proper science yet, perhaps closer to alchemy than chemistry. Max Tegmark is a cosmologist and he has learned it well enough for his opinion to count, this guy on the other hand is famous for his bad takes and has apparently gotten a lot wrong about QC even though he wrote a whole book about it.
Kaku is a quack.
I call them glorified spread sheets, but I see the correlation to recorders. LLMs, like most "AIs" before them, are just new ways to do line of best fit analysis.
That's fine. Glorify those spreadsheets. It's a pretty major thing to have cracked.
It is. The tokenization and intent processing are the thing that impress me most. I've been joking since the 90's that the most impressive technological innovation shown on Star Trek TNG was computers that understand the intent of instructions. Now we have that... mostly.
To counter the grandiose claims that present-day LLMs are almost AGI, people go too far in the opposite direction. Dismissing it as being only "line of best fit analysis" fails to recognize the power, significance, and difficulty of extracting meaningful insights and capabilities from data.
Aside from the fact that many modern theories in human cognitive science are actually deeply related to statistical analysis and machine learning (such as embodied cognition, Bayesian predictive coding, and connectionism), referring to it as a "line" of best fit is disingenuous because it downplays the important fact that the relationships found in these data are not lines, but rather highly non-linear high-dimensional manifolds. The development of techniques to efficiently discover these relationships in giant datasets is genuinely a HUGE achievement in humanity's mastery of the sciences, as they've allowed us to create programs for things it would be impossible to write out explicitly as a classical program. In particular, our current ability to create classifiers and generators for unstructured data like images would have been unimaginable a couple of decades ago, yet we've already begun to take it for granted.
So while it's important to temper expectations that we are a long way from ever seeing anything resembling AGI as it's typically conceived of, oversimplifying all neural models as being "just" line fitting blinds you to the true power and generality that such a framework of manifold learning through optimization represents - as it relates to information theory, energy and entropy in the brain, engineering applications, and the nature of knowledge itself.
Ok, it's a best fit line on an n-dimentional matrix querying a graphdb ;)
My only point is that this isn't AGI and too many people still fail to recognize that. Now people are becoming disillusioned with it because they're realizing it isn't actually creative. It's still still just a fancy comparison engine. That's not not world changing, but it's also not Data from Star Trek
Theoretical physicist and a questionable one at that
More people need to learn about Racter. This is nothing new.
Thanks for good article link
That's an incredibly cool explanation.
He's Out Of Line But He's Right
Permanently Deleted
And he is right.
That's an incredibly ignorant take.
LLMs are the first glimmer of artificial GENERAL intelligence (AGI). They are the most important invention perhaps of all time.
They will fundamentally change our society, our economy, and they pose an existential threat to mankind, not to mention begging existential questions about our purpose for existing at all in a world where very shortly computers will be able to out-think and out-create us.
Quantum computers are ... neat. They will allow us to solve problems conventional computers can't. They may make current encryption models obsolete ... but I haven't heard any proposed usage of them that would be even a fraction as profound as AGI.
Flexing that sci-fi knowledge real hard, my dude.
The AI that you're describing probably won't even be possible (if it even is possible. We don't even fully understand human intelligence/brains yet) until quantum computing is ubiquitous so your whole argument is illogical.
For my own silly sci-fi take, I believe our brains are probably closer to quantum computing than traditional computing.
The AI that you’re describing probably won’t even be possible until quantum computing is ubiquitous
...What? No, why would that be a requirement? Unless you just mean that QC is easier so it will come first by chance?
I have worked extensively to build out gpt-4 and give it memory and other attributes.
I have no doubt at all that with supplemental modules to expand its context, it's absolutely an AGI.