6 ms·

Open AI in Trouble

95 points by a_tartaruga 2y ago

qntmfred 2y ago
gary marcus = automatic thanks but no thanks
- jslezak 2y ago
  Exactly. He has a dishonest and predictable schtick. We need skeptics for any industry, but he is just grifting in an ecological niche as a knee-jerk reactionary. There is near-zero value to anything he writes or says in that role
  - adamtaylor_13 2y ago
    Yet nothing he wrote in that article was wrong. Schtick or not, if you read the article, it's all true. OpenAI has no moat, they have no killer app; this was a huge PR blunder for them. A business that burns money at the rate OpenAI does, without any clear path to profitability, will eventually die.
    - kiratp 2y ago
      This is a fundamental misunderstanding of what a moat is in this industry. If GPT 4.5 had nothing of value to offer other than a flex of opening eyes ability to scale, it’s still a signal that they have the chops to throw the most amount of compute at the upcoming reinforcement learning race. If you’re actually selling enterprise solutions in this space, you’ll quickly learn that a large number of Enterprises have their own private deployment of open AI on Azure and are pushing their vendors to use that even if it means they get lower quality outputs for certain use cases. Data and model quality aren’t the only moat-able features.
      - slowmovintarget 2y ago
        Except... it's not. This is a clear signal that the people remaining to run the show at OpenAI may not actually know what they're doing. The big names building the technology have fled from Altman's power grab. They all have startups of their own. Meanwhile, the people at Anthropic keep making Claude better and better. No bombast, just tech. And then there's the model not on the list of many of these shoot-outs: Grok 3. That one has scale, and it's actually good. "We can sorta kinda also make a big AI!" is not the message you want to be sending. It has to clobber the other "main" models out there.
  - deleted 2y ago
    [deleted]
stuartjohnson12 2y ago
Has there been a single transformative technology that was any good 2.5 years after mainstream public buy-in?
- kylebenzle 2y ago
  Not sure what you mean but yeah basically everything, cars, computers, bitcoin, the internet, airplanes...
  - stuartjohnson12 2y ago
    I was going to reply to this snarky comment with a non-snarky reply but I changed my mind, so I will instead laugh riotously at the idea that aviation worked great continuously from its inception to today.
    - birdlogic 2y ago
      What year do you place “2.5 years after mainstream public buy-in” for aviation? I think you’ll find that in most periods, people with the means were paying a lot for the ability to “get there faster”, despite a bad early safety record. It did work great when it didn’t kill you, and despite that risk it was a hit (for those that could afford it).
    - unaindz 2y ago
      I don't know if Kyle is right but "any good after mainstream public buy-in" and "worked great continuously from inception to today" is quite the goalpost move.
- rbrown 2y ago
  No. I think coupling OpenAI's fortunes and the prospects of LLM-native applications is a step too far
  - stuartjohnson12 2y ago
    It's been less than 6 months since OpenAI last released a SOTA model architecture that promptly caused every other AI lab to scramble to copy them (o1 preview). Maybe OpenAI is running ashore, but it's too soon to tell yet.
tananaev 2y ago
I wonder if we reached the limit of what a single-shot large models can do? Or we're just waiting for another breakthrough? If it's the limit, then probably the chain of thought is the answer. I think models are so good now that given the right context, tools and time, they can pretty much do anything.
- adverbly 2y ago
  I would have thought that is obvious. Chain of thought is clearly the right path forwards. People don't stare at a thing and immediately come to a solution. Without chain of thought, you are mostly dealing with a statistical regurgitation machine. Effective for some tasks yes, but clearly not enough to meet the bar of general intelligence. I think you are wrong that this is the limit for single shot though. We have reached a limit due to data, but I expect what will happen next is that we will transition into a slow growth phase where chain of thought models will be used to effectively create more training data, which will then be used to train a better single shot model, which will then be extended into a better chain of thought model, which will then produce higher quality training data for another single shot. And so on. Kind of like what happens as knowledge passes from teacher to student across successive generations. Effectively a continuing process of compression and growth in intelligence, but progressing rather slowly compared to what we have seen in the last 5 years.
RDaneel0livaw 2y ago
IF this is the beginning of the bubble bursting, I welcome it with open arms. Burn baby burn.
- marviel 2y ago
  why celebrate this?
  - aleafinthewind 2y ago
    primarily because the current theoretical trajectory of OpenAI and similar orgs will leave a large number of humans markedly worse off than before
  - bitpush 2y ago
    Capitalism. https://en.m.wikipedia.org/wiki/Creative_destruction https://en.m.wikipedia.org/wiki/Creative_destruction
  - miltonlost 2y ago
    Because AI LLMs are actively ruining the education of children, the actual retaining of information coming from writing your own words and thinking your own thoughts. Because AI is only being used as a cudgel by executives to reduce the workforce of humans with no intention of additional economic justice.
    - dehrmann 2y ago
      But this cat's already out of the bag. LLMs might not be on the verge of AGI, but they're still great at answering homework questions.
      - miltonlost 2y ago
        So? That's still going to ruin kids education. I still would like to see AI burn
Willingham 2y ago
The pressure to hit quarterly targets seems to, in this case, caused quite the opposite outcome intended. Gotta love corporate America and the overvalued AI sector. (:
redwood 2y ago
These are powerful building blocks, they're just not the be all end all. The building blocks up stack that use these as part of a broader architecture, that shape these and many other traditional techniques in software... this is where the real value will be unlocked. This layer itself will inevitably see its cost come down per unit of use on a long road towards commoditization. It will probably get better and better and more sophisticated but again the value will be primarily up stack, not accrued primarily from a company like this. It's not to say they couldn't be a great company... even Google is a great company that has enabled countless other companies to bloom. The myopic way people look to these one size fit all companies is just so disconnected from our economy works.
- daveguy 2y ago
  It took us nearly 70 years to get to this architecture and the processing power to support it. If we are waiting for a new breakthrough architecture, it could be decades. Our brains send signals with very high concurrency to individual processors (neurons). Each neuron is massively more complex than a single ReLU function and we have billions of them. If we need that kind of parallel processing and data transfer to match human thought and flexibility, it could be another 70 years before we see AGI. That said, I do think LLMs are one of the biggest AI breakthroughs since the inception of AI. And I am sure that it, or something very similar will be part of an eventual AGI.
- gilmore606 2y ago
  > These are powerful building blocks, they're just not the be all end all. The building blocks up stack that use these as part of a broader architecture, that shape these and many other traditional techniques in software... this is where the real value will be unlocked. I could not agree more. There is much value still to be gained from blockchain technology!
  - redwood 2y ago
    What's useful about blockchain? (Outside of situations where you need to move money outside the law)
startupsfail 2y ago
While OpenAI is certainly in trouble (zero Hinton students, partnership with Azure is straining, while Brin is back at Google!), its demise is still uncertain. They are still absolutely amazing lab, pushing both product and research. Execute. And make all these naysayers obsolete ;)
- cruffle_duffle 2y ago
  My biggest hope is that home computing catches up to the point where you can buy a sub-thousand-dollar card, slap it into your desktop, and run this stuff locally. Take the power away from massive, well-funded corporations with armies of lawyers and “safety weenies” and put it back in the hands of makers and tinkerers. Right now, these models are built by the establishment to serve the establishment—and that’s a load of shit that needs to change. The real fun starts the day some random group of “anonymous” on 4chan can train one of these models to generate incredibly convincing deepfakes of world leaders, all using the compute power in their own homes. Power to the people. Fuck the system, and all that jazz.
fancyfredbot 2y ago
Open AI has a brand, it has talent, it has some really solid models, and it has the compute to serve inference at scale. They stand as good a chance of covering their inference costs as anyone else. The compute for training is beginning to seem a poor investment since it is depreciating fast and isn't producing value in this case. That's a seriously big investment to make if it's not productive but since a lot of it actually belongs to Azure they could cut back here fast if they had to. I hope they won't because in the hands of good researchers there is still a real possibility that they'll use the compute to find some kind of technical innovation to give them a bigger edge.
- andrewinardeer 2y ago
  > Open AI has a brand, it has talent, it has some really solid models, and it has the compute to serve inference at scale. So does Google. And Google can roll out their premium models into phones, household devices, cars and online platforms to add value. OpenAI has a website. It's not even close.
  - fancyfredbot 2y ago
    OpenAI has a partnership with both Apple and Microsoft and I think this probably gives them enough access to be competitive with Google.
    - andrewinardeer 2y ago
      To serve their models on Azure and into phones. Co-Pilot is a joke. At least Google have rolled Gemini into Docs, Sheets, Android Studio, Gmail among other things.
  - AnimalMuppet 2y ago
    Which is harder, to build a working AI, or to build a phone client? If OpenAI can do the former, it won't matter that Google is better at doing the latter.
Kapura 2y ago
It absolutely blows my mind that people swallowed "AGI is just around the corner" hook, line and sinker. We don't understand human cognition despite literally thousands of years of thought and study, but some nerds with a thousand GPUs are going to make a machine think? Ridiculous. People were misled by graphs that they were told pointed to a singularity right around the corner, despite obvious errors in the extant systems. Concentrated capital is truly a wild thing.
- iLoveOncall 2y ago
  What's even more laughable is that OpenAI dumbed down the definition of AGI so much it doesn't align at all with general intelligence anymore, and people just accepted it. Not only can they not reach AGI, they cannot reach their own definition of AGI. But people will still gobble whatever next lie Altman will sell them for $2,000 a month. Absolutely pathetic.
  - riku_iki 2y ago
    > Not only can they not reach AGI, they cannot reach their own definition of AGI. that definition likely not their's but came from Microsoft when they dumped 10B into OAI and was a condition for revenue sharing clause. One can argue that AGI is already achieved, LLMs are more proficient and general in knowledge tasks than any specific individual.
    - iLoveOncall 2y ago
      > One can argue that AGI is already achieved, LLMs are more proficient and general in knowledge tasks than any specific individual. This is not AGI. Let's take an old version of the Wikipedia page about AGI, from end of 2022, before the ChatGPT craze: https://en.wikipedia.org/w/index.php?title=Artificial_general_intelligence&oldid=1124797567 https://en.wikipedia.org/w/index.php?title=Artificial_genera... > Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn __any__ intellectual task that a human being can. LLMs are nowhere near this. Not even close. But let's get even more restrictive by looking at the actual required characteristics to declare a system an AGI: > There is wide agreement among artificial intelligence researchers that intelligence is required to do the following: > - reason, use strategy, solve puzzles, and make judgments under uncertainty; > - represent knowledge, including common sense knowledge; > - plan; > - learn; > - communicate in natural language; > - and integrate all these skills towards common goals. > Other important capabilities include: > - input as the ability to sense (e.g. see, hear, etc.), and > - output as the ability to act (e.g. move and manipulate objects, change own location to explore, etc.) Once again, LLMs are not even scratching the surface of AGI. Of course if you look at the current version of the page, where the bar has been massively lowered, it might look like AGI is achieved, but that's because the definition has changed, not the technology.
Chance-Device 2y ago
I don’t think I’d be this pessimistic. There’s still o3 that hasn’t been seen in its full form, and whatever improvements are made to it now that multi head latent attention is out in the wild. Orion does seem to have been a failure, but I also find it a bit weird that they seemingly decided to release the full model rather than a distillation, which is the pattern we now usually see with foundation models. So, did they simply decide that it wasn’t worth the effort and dedicate the compute to other, better things? Were they pushed by sama to release it anyway, to look like they were still making progress while developing something really next gen?
- brokencode 2y ago
  OpenAI releases one dud and suddenly people come out of the woodwork to trash them. I agree that OpenAI's endless hyping about AGI seems pretty unrealistic, but let's take a breather here. There are no major research projects where you don't run into setbacks and failures before you reach your goals. And even if they never really progress beyond where they are today with their current models, just bringing down the cost could open up a lot of doors for useful applications.
  - tim333 2y ago
    OpenAI releases a variety of models and every time Gary Marcus comes out to trash them.
  - fdsjgfklsfd 2y ago
    Yep, GPT 4.5 is not a breakthrough, but there will be more breakthroughs. Someone will figure out how to make AIs understand their own ignorance and stop bullshitting when they don't know something, someone will figure out how to make AIs learn on the fly instead of fine-tuning new model versions, etc.
adamgordonbell 2y ago
Gary Marcus has been saying for 3 years ( or more ) that LLMs are at the limit and will never get better and also are useless. A smart enough AI would summarize each of his posts as "I still hate the current AI boom". There must be a term for such writers? He's certainly consistently on message.
paulpauper 2y ago
I used to be a skeptic. Chat GPT is awesome. Similar to Google, it's become a staple of my everyday life, like writing, or composing latex, or even doing math. I cannot imagine not having it without losing productivity. Is the business model sustainable? Probably not; I already see some signs of throttling in an attempt to cut costs, like if you overuse computation for math. Just the ability to render the latex from wolfram alpha is great. Writing latex used to be such a chore.
- tracerbulletx 2y ago
  You can get pretty much all the benefits, if you know how to apply a little bit of elbow grease, from open source models at this point so even if the business model doesnt work, this is a technology that we all have now which is great.
  - paulpauper 2y ago
    there are so many competing language models and companies now that if any one of them fail there will be others
computerex 2y ago
Gary Marcus is an insufferable cretin, who likes nothing more than to hear himself talk.
deleted 2y ago
[deleted]
armchairhacker 2y ago
Humans learn. LLM context windows are vastly larger than our short-term memory, but vastly smaller than our long-term recollection. LLMs can recall vastly more information than our long-term memory, but only from their static training data. Also, even though LLMs can generate text much faster than humans, we may be internally thinking much faster. Each adult human brain has over 100 billion neurons and 100 trillion synapses, and each has been working every moment, for decades. This is what separates human reasoning from LLM reasoning, and it can’t be solved by scaling the latter to anything feasible. I wish AI companies would take a decent chunk of their billions, and split it into 1000+ million-dollar projects that each try a different idea to overcome these issues, and others (like emotion and alignment). Many of these projects would certainly fail, but some may produce breakthroughs. Meanwhile, spending the entire billion on scaling compute has failed and will continue to fail, because everyone else does that, so the resulting model has no practical advantages and makes less money than it cost to train before it becomes obsoleted by other people’s breakthroughs.
cs702 2y ago
Gary Marcus. By all accounts, he doesn't understand how LLMs work, so usually he's wrong about technical matters.[a] But here, I think he's right about business matters. The massive investment in computing capacity we've seen in recent years, by Open AI and others, can generate positive returns only if the technology continues to improve rapidly so it can overcome its limitations and failure modes in the short run. If the rate of improvement has slowed down, even temporarily, OpenAI and others like Anthropic are likely to face financial difficulties. --- [a] In the words of Geoff Hinton: https://www.youtube.com/watch?v=d7ltNiRrDHQ https://www.youtube.com/watch?v=d7ltNiRrDHQ --- Note: At the moment, the OP is flagged. To the mods: It shouldn't be, because it conforms to the HN guidelines.
1970-01-01 2y ago
This is going to sound disrespectful, but nobody cares. Both bloggers and CEOs will continue to argue they have the bestest AI. Our goal should simply be making sure AI is helping more than it harms. Much like nuclear research 75 years ago, we've setup this century where AI will be simultaneously massively weaponized and massively assistive technology. There's also an ultimate goal of having AGI solve all our problems like fusion was supposed to do. Let me know when your AI CEO is ready to discuss how all this scaling is helping the kids sleep better instead of making quarterly profits rise faster than the competition.
eliothmonroy 2y ago
Why this was flagged?
- bornfreddy 2y ago
  I'm wondering the same thing... It is a legitimate post & discussion. @dang can you resurrect it?
- slowmovintarget 2y ago
  There are folks that don't like anything from Gary Marcus, because he's been a nay-sayer from the beginning. This article happens to be spot on though.
agnishom 2y ago
It is not "in trouble". It just has more competition. That's what _should_ happen when capitalism functions correctly.
returnInfinity 2y ago
Gary Marcus and Ed Zitron are very bearish on LLMs. Disclosure - I am neither bearish or a mega bull on LLMs. LLMs useful in some cases.
1vuio0pswjnm7 2y ago
"Gary Marcus has been warning the field for years that pure statistical approaches like LLMs probably wouldn't suffice for AGI. Half a trillion dollars later, it looks like maybe he had a point." D'oh!

Open AI in Trouble

95 points by a_tartaruga 2y ago

qntmfred 2y ago

gary marcus = automatic thanks but no thanks

jslezak 2y ago
Exactly. He has a dishonest and predictable schtick. We need skeptics for any industry, but he is just grifting in an ecological niche as a knee-jerk reactionary. There is near-zero value to anything he writes or says in that role
- adamtaylor_13 2y ago
  Yet nothing he wrote in that article was wrong. Schtick or not, if you read the article, it's all true. OpenAI has no moat, they have no killer app; this was a huge PR blunder for them. A business that burns money at the rate OpenAI does, without any clear path to profitability, will eventually die.
  - kiratp 2y ago
    This is a fundamental misunderstanding of what a moat is in this industry. If GPT 4.5 had nothing of value to offer other than a flex of opening eyes ability to scale, it’s still a signal that they have the chops to throw the most amount of compute at the upcoming reinforcement learning race. If you’re actually selling enterprise solutions in this space, you’ll quickly learn that a large number of Enterprises have their own private deployment of open AI on Azure and are pushing their vendors to use that even if it means they get lower quality outputs for certain use cases. Data and model quality aren’t the only moat-able features.
    - slowmovintarget 2y ago
      Except... it's not. This is a clear signal that the people remaining to run the show at OpenAI may not actually know what they're doing. The big names building the technology have fled from Altman's power grab. They all have startups of their own. Meanwhile, the people at Anthropic keep making Claude better and better. No bombast, just tech. And then there's the model not on the list of many of these shoot-outs: Grok 3. That one has scale, and it's actually good. "We can sorta kinda also make a big AI!" is not the message you want to be sending. It has to clobber the other "main" models out there.
- deleted 2y ago
  [deleted]

stuartjohnson12 2y ago

Has there been a single transformative technology that was any good 2.5 years after mainstream public buy-in?

kylebenzle 2y ago
Not sure what you mean but yeah basically everything, cars, computers, bitcoin, the internet, airplanes...
- stuartjohnson12 2y ago
  I was going to reply to this snarky comment with a non-snarky reply but I changed my mind, so I will instead laugh riotously at the idea that aviation worked great continuously from its inception to today.
  - birdlogic 2y ago
    What year do you place “2.5 years after mainstream public buy-in” for aviation? I think you’ll find that in most periods, people with the means were paying a lot for the ability to “get there faster”, despite a bad early safety record. It did work great when it didn’t kill you, and despite that risk it was a hit (for those that could afford it).
  - unaindz 2y ago
    I don't know if Kyle is right but "any good after mainstream public buy-in" and "worked great continuously from inception to today" is quite the goalpost move.
rbrown 2y ago
No. I think coupling OpenAI's fortunes and the prospects of LLM-native applications is a step too far
- stuartjohnson12 2y ago
  It's been less than 6 months since OpenAI last released a SOTA model architecture that promptly caused every other AI lab to scramble to copy them (o1 preview). Maybe OpenAI is running ashore, but it's too soon to tell yet.

tananaev 2y ago

I wonder if we reached the limit of what a single-shot large models can do? Or we're just waiting for another breakthrough? If it's the limit, then probably the chain of thought is the answer. I think models are so good now that given the right context, tools and time, they can pretty much do anything.

adverbly 2y ago
I would have thought that is obvious. Chain of thought is clearly the right path forwards. People don't stare at a thing and immediately come to a solution. Without chain of thought, you are mostly dealing with a statistical regurgitation machine. Effective for some tasks yes, but clearly not enough to meet the bar of general intelligence. I think you are wrong that this is the limit for single shot though. We have reached a limit due to data, but I expect what will happen next is that we will transition into a slow growth phase where chain of thought models will be used to effectively create more training data, which will then be used to train a better single shot model, which will then be extended into a better chain of thought model, which will then produce higher quality training data for another single shot. And so on. Kind of like what happens as knowledge passes from teacher to student across successive generations. Effectively a continuing process of compression and growth in intelligence, but progressing rather slowly compared to what we have seen in the last 5 years.

RDaneel0livaw 2y ago

IF this is the beginning of the bubble bursting, I welcome it with open arms. Burn baby burn.

marviel 2y ago
why celebrate this?
- aleafinthewind 2y ago
  primarily because the current theoretical trajectory of OpenAI and similar orgs will leave a large number of humans markedly worse off than before
- bitpush 2y ago
  Capitalism. https://en.m.wikipedia.org/wiki/Creative_destruction https://en.m.wikipedia.org/wiki/Creative_destruction
- miltonlost 2y ago
  Because AI LLMs are actively ruining the education of children, the actual retaining of information coming from writing your own words and thinking your own thoughts. Because AI is only being used as a cudgel by executives to reduce the workforce of humans with no intention of additional economic justice.
  - dehrmann 2y ago
    But this cat's already out of the bag. LLMs might not be on the verge of AGI, but they're still great at answering homework questions.
    - miltonlost 2y ago
      So? That's still going to ruin kids education. I still would like to see AI burn

Willingham 2y ago

The pressure to hit quarterly targets seems to, in this case, caused quite the opposite outcome intended. Gotta love corporate America and the overvalued AI sector. (:

redwood 2y ago

These are powerful building blocks, they're just not the be all end all. The building blocks up stack that use these as part of a broader architecture, that shape these and many other traditional techniques in software... this is where the real value will be unlocked. This layer itself will inevitably see its cost come down per unit of use on a long road towards commoditization. It will probably get better and better and more sophisticated but again the value will be primarily up stack, not accrued primarily from a company like this. It's not to say they couldn't be a great company... even Google is a great company that has enabled countless other companies to bloom. The myopic way people look to these one size fit all companies is just so disconnected from our economy works.

daveguy 2y ago
It took us nearly 70 years to get to this architecture and the processing power to support it. If we are waiting for a new breakthrough architecture, it could be decades. Our brains send signals with very high concurrency to individual processors (neurons). Each neuron is massively more complex than a single ReLU function and we have billions of them. If we need that kind of parallel processing and data transfer to match human thought and flexibility, it could be another 70 years before we see AGI. That said, I do think LLMs are one of the biggest AI breakthroughs since the inception of AI. And I am sure that it, or something very similar will be part of an eventual AGI.
gilmore606 2y ago
> These are powerful building blocks, they're just not the be all end all. The building blocks up stack that use these as part of a broader architecture, that shape these and many other traditional techniques in software... this is where the real value will be unlocked. I could not agree more. There is much value still to be gained from blockchain technology!
- redwood 2y ago
  What's useful about blockchain? (Outside of situations where you need to move money outside the law)

startupsfail 2y ago

While OpenAI is certainly in trouble (zero Hinton students, partnership with Azure is straining, while Brin is back at Google!), its demise is still uncertain. They are still absolutely amazing lab, pushing both product and research. Execute. And make all these naysayers obsolete ;)

cruffle_duffle 2y ago
My biggest hope is that home computing catches up to the point where you can buy a sub-thousand-dollar card, slap it into your desktop, and run this stuff locally. Take the power away from massive, well-funded corporations with armies of lawyers and “safety weenies” and put it back in the hands of makers and tinkerers. Right now, these models are built by the establishment to serve the establishment—and that’s a load of shit that needs to change. The real fun starts the day some random group of “anonymous” on 4chan can train one of these models to generate incredibly convincing deepfakes of world leaders, all using the compute power in their own homes. Power to the people. Fuck the system, and all that jazz.

fancyfredbot 2y ago

Open AI has a brand, it has talent, it has some really solid models, and it has the compute to serve inference at scale. They stand as good a chance of covering their inference costs as anyone else. The compute for training is beginning to seem a poor investment since it is depreciating fast and isn't producing value in this case. That's a seriously big investment to make if it's not productive but since a lot of it actually belongs to Azure they could cut back here fast if they had to. I hope they won't because in the hands of good researchers there is still a real possibility that they'll use the compute to find some kind of technical innovation to give them a bigger edge.

andrewinardeer 2y ago
> Open AI has a brand, it has talent, it has some really solid models, and it has the compute to serve inference at scale. So does Google. And Google can roll out their premium models into phones, household devices, cars and online platforms to add value. OpenAI has a website. It's not even close.
- fancyfredbot 2y ago
  OpenAI has a partnership with both Apple and Microsoft and I think this probably gives them enough access to be competitive with Google.
  - andrewinardeer 2y ago
    To serve their models on Azure and into phones. Co-Pilot is a joke. At least Google have rolled Gemini into Docs, Sheets, Android Studio, Gmail among other things.
- AnimalMuppet 2y ago
  Which is harder, to build a working AI, or to build a phone client? If OpenAI can do the former, it won't matter that Google is better at doing the latter.

Kapura 2y ago

It absolutely blows my mind that people swallowed "AGI is just around the corner" hook, line and sinker. We don't understand human cognition despite literally thousands of years of thought and study, but some nerds with a thousand GPUs are going to make a machine think? Ridiculous. People were misled by graphs that they were told pointed to a singularity right around the corner, despite obvious errors in the extant systems. Concentrated capital is truly a wild thing.

iLoveOncall 2y ago
What's even more laughable is that OpenAI dumbed down the definition of AGI so much it doesn't align at all with general intelligence anymore, and people just accepted it. Not only can they not reach AGI, they cannot reach their own definition of AGI. But people will still gobble whatever next lie Altman will sell them for $2,000 a month. Absolutely pathetic.
- riku_iki 2y ago
  > Not only can they not reach AGI, they cannot reach their own definition of AGI. that definition likely not their's but came from Microsoft when they dumped 10B into OAI and was a condition for revenue sharing clause. One can argue that AGI is already achieved, LLMs are more proficient and general in knowledge tasks than any specific individual.
  - iLoveOncall 2y ago
    > One can argue that AGI is already achieved, LLMs are more proficient and general in knowledge tasks than any specific individual. This is not AGI. Let's take an old version of the Wikipedia page about AGI, from end of 2022, before the ChatGPT craze: https://en.wikipedia.org/w/index.php?title=Artificial_general_intelligence&oldid=1124797567 https://en.wikipedia.org/w/index.php?title=Artificial_genera... > Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn __any__ intellectual task that a human being can. LLMs are nowhere near this. Not even close. But let's get even more restrictive by looking at the actual required characteristics to declare a system an AGI: > There is wide agreement among artificial intelligence researchers that intelligence is required to do the following: > - reason, use strategy, solve puzzles, and make judgments under uncertainty; > - represent knowledge, including common sense knowledge; > - plan; > - learn; > - communicate in natural language; > - and integrate all these skills towards common goals. > Other important capabilities include: > - input as the ability to sense (e.g. see, hear, etc.), and > - output as the ability to act (e.g. move and manipulate objects, change own location to explore, etc.) Once again, LLMs are not even scratching the surface of AGI. Of course if you look at the current version of the page, where the bar has been massively lowered, it might look like AGI is achieved, but that's because the definition has changed, not the technology.

Chance-Device 2y ago

I don’t think I’d be this pessimistic. There’s still o3 that hasn’t been seen in its full form, and whatever improvements are made to it now that multi head latent attention is out in the wild. Orion does seem to have been a failure, but I also find it a bit weird that they seemingly decided to release the full model rather than a distillation, which is the pattern we now usually see with foundation models. So, did they simply decide that it wasn’t worth the effort and dedicate the compute to other, better things? Were they pushed by sama to release it anyway, to look like they were still making progress while developing something really next gen?

brokencode 2y ago
OpenAI releases one dud and suddenly people come out of the woodwork to trash them. I agree that OpenAI's endless hyping about AGI seems pretty unrealistic, but let's take a breather here. There are no major research projects where you don't run into setbacks and failures before you reach your goals. And even if they never really progress beyond where they are today with their current models, just bringing down the cost could open up a lot of doors for useful applications.
- tim333 2y ago
  OpenAI releases a variety of models and every time Gary Marcus comes out to trash them.
- fdsjgfklsfd 2y ago
  Yep, GPT 4.5 is not a breakthrough, but there will be more breakthroughs. Someone will figure out how to make AIs understand their own ignorance and stop bullshitting when they don't know something, someone will figure out how to make AIs learn on the fly instead of fine-tuning new model versions, etc.

adamgordonbell 2y ago

Gary Marcus has been saying for 3 years ( or more ) that LLMs are at the limit and will never get better and also are useless. A smart enough AI would summarize each of his posts as "I still hate the current AI boom". There must be a term for such writers? He's certainly consistently on message.

paulpauper 2y ago

I used to be a skeptic. Chat GPT is awesome. Similar to Google, it's become a staple of my everyday life, like writing, or composing latex, or even doing math. I cannot imagine not having it without losing productivity. Is the business model sustainable? Probably not; I already see some signs of throttling in an attempt to cut costs, like if you overuse computation for math. Just the ability to render the latex from wolfram alpha is great. Writing latex used to be such a chore.

tracerbulletx 2y ago
You can get pretty much all the benefits, if you know how to apply a little bit of elbow grease, from open source models at this point so even if the business model doesnt work, this is a technology that we all have now which is great.
- paulpauper 2y ago
  there are so many competing language models and companies now that if any one of them fail there will be others

computerex 2y ago

Gary Marcus is an insufferable cretin, who likes nothing more than to hear himself talk.

deleted 2y ago

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armchairhacker 2y ago

Humans learn. LLM context windows are vastly larger than our short-term memory, but vastly smaller than our long-term recollection. LLMs can recall vastly more information than our long-term memory, but only from their static training data. Also, even though LLMs can generate text much faster than humans, we may be internally thinking much faster. Each adult human brain has over 100 billion neurons and 100 trillion synapses, and each has been working every moment, for decades. This is what separates human reasoning from LLM reasoning, and it can’t be solved by scaling the latter to anything feasible. I wish AI companies would take a decent chunk of their billions, and split it into 1000+ million-dollar projects that each try a different idea to overcome these issues, and others (like emotion and alignment). Many of these projects would certainly fail, but some may produce breakthroughs. Meanwhile, spending the entire billion on scaling compute has failed and will continue to fail, because everyone else does that, so the resulting model has no practical advantages and makes less money than it cost to train before it becomes obsoleted by other people’s breakthroughs.

cs702 2y ago

Gary Marcus. By all accounts, he doesn't understand how LLMs work, so usually he's wrong about technical matters.[a] But here, I think he's right about business matters. The massive investment in computing capacity we've seen in recent years, by Open AI and others, can generate positive returns only if the technology continues to improve rapidly so it can overcome its limitations and failure modes in the short run. If the rate of improvement has slowed down, even temporarily, OpenAI and others like Anthropic are likely to face financial difficulties. --- [a] In the words of Geoff Hinton: https://www.youtube.com/watch?v=d7ltNiRrDHQ https://www.youtube.com/watch?v=d7ltNiRrDHQ --- Note: At the moment, the OP is flagged. To the mods: It shouldn't be, because it conforms to the HN guidelines.

1970-01-01 2y ago

This is going to sound disrespectful, but nobody cares. Both bloggers and CEOs will continue to argue they have the bestest AI. Our goal should simply be making sure AI is helping more than it harms. Much like nuclear research 75 years ago, we've setup this century where AI will be simultaneously massively weaponized and massively assistive technology. There's also an ultimate goal of having AGI solve all our problems like fusion was supposed to do. Let me know when your AI CEO is ready to discuss how all this scaling is helping the kids sleep better instead of making quarterly profits rise faster than the competition.

eliothmonroy 2y ago

Why this was flagged?

bornfreddy 2y ago
I'm wondering the same thing... It is a legitimate post & discussion. @dang can you resurrect it?
slowmovintarget 2y ago
There are folks that don't like anything from Gary Marcus, because he's been a nay-sayer from the beginning. This article happens to be spot on though.

agnishom 2y ago

It is not "in trouble". It just has more competition. That's what _should_ happen when capitalism functions correctly.

returnInfinity 2y ago

Gary Marcus and Ed Zitron are very bearish on LLMs. Disclosure - I am neither bearish or a mega bull on LLMs. LLMs useful in some cases.

1vuio0pswjnm7 2y ago

"Gary Marcus has been warning the field for years that pure statistical approaches like LLMs probably wouldn't suffice for AGI. Half a trillion dollars later, it looks like maybe he had a point." D'oh!