9 ms·

It was a gambit to try to secure OAI's moat. It failed, and while competitors are catching up (still a while to go yet), he put a target on OAI's back.

arthurcolle 3y ago
Yep. Especially with geohot leaks and torrent activity at an all time high - OpenAI looks cooked
- biofunsf 3y ago
  What are the geohot leaks?
  - bodecker 3y ago
    I assume comments like these, "GPT-4: 8 x 220B experts trained with different data/task distributions and 16-iter inference." https://twitter.com/soumithchintala/status/1671267150101721090 https://twitter.com/soumithchintala/status/16712671501017210... https://archive.li/rfFlW https://archive.li/rfFlW I'm not sure the most canonical paper on mixture of experts but here's one possible: https://arxiv.org/pdf/1701.06538.pdf https://arxiv.org/pdf/1701.06538.pdf
    - arthurcolle 3y ago
      I think when ppl refer to MoE they are referring generally to the Google GLaM paper actually
  - ZunarJ5 3y ago
    https://the-decoder.com/gpt-4-architecture-datasets-costs-and-more-leaked/ https://the-decoder.com/gpt-4-architecture-datasets-costs-an... Not op, but this is where a cheeky google got me.
    - 1vuio0pswjnm7 3y ago
      "The idea is nearly 30 years old and has been used for large language models before, such as Google's Switch Transformer." Innovation! :)
  - ta988 3y ago
    George Hotz (pseudo geohot) in his recent interview with Lex Fridman gave some info on the probable structure of gpt4.
- flangola7 3y ago
  Torrent activity?
biofunsf 3y ago
Why not both? I think true AGI super intelligence (a lot smarter than us) does have the potential to destroy humanity, and as the current leader, Open AI seems closest to achieving that. Of course superintelligence might be far away or just unachievable, but we don't know that. And I agree Altman's statement also builds OAI's moat, but that doesn't make his statement false.
- SOLAR_FIELDS 3y ago
  But isn’t it closer in the same way that I’m closer to Japan than my dog who is sitting 1 meter to the east of me is? We are still both 10,000 km away
  - zarzavat 3y ago
    This technology (transformer language models) was invented about 6 years ago. For it to be far away means that at some point the exponential has to stop and we have an AI winter. That’s possible but doesn’t look likely at this point. It’s more likely that we will see superintelligence in our lifetime. And if the rate of progress does not slow it will be sooner rather than later. My current estimate is parity by 2030 and superintelligence by 2035. Evidence from specialist AIs, e.g. Go, indicates that super AIs tend to occur soon after parity is reached. E.g. AlphaGo (parity) March 2016; Master (super) December 2016.
    - vladf 3y ago
      Intelectual parity to an average human by 2030? Would you be willing to bet on this?
    - jdkee 3y ago
      This seems reasonable since we have intelligence in 2023 that can pass both the U.S. bar exam and the MKSAP. Yann LeCunn posted a powerpoint last summer about the path to AGI, and a model for achieving it. Given the pace of progress, 2035 seems reasonable.
    - deleted 3y ago
      [deleted]
flangola7 3y ago
This conspiracy theory is myopic. Altman has been cognizant[1][2] of the very-not-scifi danger of machine intelligence since before OpenAI was even founded. I believe he has dangerous levels of hubris but I don't see him being profit motivated. From his statements in the past and his regrets today[3] of bringing the current tech into existence, I'm confident his motivator is simply the desire to not die. >WHY YOU SHOULD FEAR MACHINE INTELLIGENCE >Development of superhuman machine intelligence (SMI) [1] is probably the greatest threat to the continued existence of humanity. There are other threats that I think are more certain to happen (for example, an engineered virus with a long incubation period and a high mortality rate) but are unlikely to destroy every human in the universe in the way that SMI could. Also, most of these other big threats are already widely feared. - Sam Altman, February 25, 2015 [1] https://blog.samaltman.com/machine-intelligence-part-1 https://blog.samaltman.com/machine-intelligence-part-1 [2] https://blog.samaltman.com/machine-intelligence-part-2 https://blog.samaltman.com/machine-intelligence-part-2 [3] https://www.businessinsider.com/openai-ceo-sam-altman-says-he-is-losing-sleep-over-chatgpt-2023-6 https://www.businessinsider.com/openai-ceo-sam-altman-says-h...
- cjbprime 3y ago
  Lots of retrospectively-good predictions in there, but this was the one I undervalued the extent of: > We also have a bad habit of changing the definition of machine intelligence when a program gets really good to claim that the problem wasn’t really that hard in the first place We've done this so much recently that I'm now seeing rewritten definitions of "real" intelligence that most humans do not meet.
  - somenameforme 3y ago
    There's quite a rationale justification for the ever 'shifting goalposts.' When humans describe some milestone in the future as finally being "real AI", they're not really just describing that milestone, but the many adjacent capabilities that they expect that milestone to entail. But we're quite clever, and like any old metric needing to be juked, we invariably find ways to achieve the milestone while sidestepping all the capabilities it's supposed to entail. Chess is the obvious example. A machine capable of playing chess at a human level was supposed to indicate the advent of genuine artificial intelligence at one time. It wasn't that playing chess well means one is intelligent, but rather it was assumed it'd entail abstract planning, strategic thought, intuition, and creativity. Of course now we have software which can crush even a world champion, but none of those adjacent capabilities emerged at all. And so I think it's also increasingly obvious that this is the same thing with chatbots. Many of us thought those 'surrounding capabilities' were finally here, even more so with OpenAI regularly demonstrating exceptional competence on a wide array of distinct metrics, such as performance on the Bar exam. But once you use the system for a while it becomes clear that its knowledge base is absolutely and unbelievably immense, but its 'understanding' of that knowledge is literally zero. It will arbitrarily create e.g. API calls that do not exist, mix up utterly simple concepts, and fail to learn from its mistakes in any meaningful way whatsoever. I'm sure if you've used ChatGPT for anything you've run into the utterly annoying scenario of: - "How do I [x]?" - "Sure! That's easy, just do [A]." - "No, you're hallucinating." - "Oh sorry, thanks. You're right you actually need to do [B]!" - "No, you're still hallucinating." - "Oh sorry, you're right. You just need to do [A]. If a human, even a stupid human, acted in this way - you'd assume they were trolling you, especially one gifted with the ability for infinite perfect and complete recall.

arthurcolle 3y ago

Yep. Especially with geohot leaks and torrent activity at an all time high - OpenAI looks cooked

biofunsf 3y ago
What are the geohot leaks?
- bodecker 3y ago
  I assume comments like these, "GPT-4: 8 x 220B experts trained with different data/task distributions and 16-iter inference." https://twitter.com/soumithchintala/status/1671267150101721090 https://twitter.com/soumithchintala/status/16712671501017210... https://archive.li/rfFlW https://archive.li/rfFlW I'm not sure the most canonical paper on mixture of experts but here's one possible: https://arxiv.org/pdf/1701.06538.pdf https://arxiv.org/pdf/1701.06538.pdf
  - arthurcolle 3y ago
    I think when ppl refer to MoE they are referring generally to the Google GLaM paper actually
- ZunarJ5 3y ago
  https://the-decoder.com/gpt-4-architecture-datasets-costs-and-more-leaked/ https://the-decoder.com/gpt-4-architecture-datasets-costs-an... Not op, but this is where a cheeky google got me.
  - 1vuio0pswjnm7 3y ago
    "The idea is nearly 30 years old and has been used for large language models before, such as Google's Switch Transformer." Innovation! :)
- ta988 3y ago
  George Hotz (pseudo geohot) in his recent interview with Lex Fridman gave some info on the probable structure of gpt4.
flangola7 3y ago
Torrent activity?

biofunsf 3y ago

Why not both? I think true AGI super intelligence (a lot smarter than us) does have the potential to destroy humanity, and as the current leader, Open AI seems closest to achieving that. Of course superintelligence might be far away or just unachievable, but we don't know that. And I agree Altman's statement also builds OAI's moat, but that doesn't make his statement false.

SOLAR_FIELDS 3y ago
But isn’t it closer in the same way that I’m closer to Japan than my dog who is sitting 1 meter to the east of me is? We are still both 10,000 km away
- zarzavat 3y ago
  This technology (transformer language models) was invented about 6 years ago. For it to be far away means that at some point the exponential has to stop and we have an AI winter. That’s possible but doesn’t look likely at this point. It’s more likely that we will see superintelligence in our lifetime. And if the rate of progress does not slow it will be sooner rather than later. My current estimate is parity by 2030 and superintelligence by 2035. Evidence from specialist AIs, e.g. Go, indicates that super AIs tend to occur soon after parity is reached. E.g. AlphaGo (parity) March 2016; Master (super) December 2016.
  - vladf 3y ago
    Intelectual parity to an average human by 2030? Would you be willing to bet on this?
  - jdkee 3y ago
    This seems reasonable since we have intelligence in 2023 that can pass both the U.S. bar exam and the MKSAP. Yann LeCunn posted a powerpoint last summer about the path to AGI, and a model for achieving it. Given the pace of progress, 2035 seems reasonable.
  - deleted 3y ago
    [deleted]

flangola7 3y ago

This conspiracy theory is myopic. Altman has been cognizant[1][2] of the very-not-scifi danger of machine intelligence since before OpenAI was even founded. I believe he has dangerous levels of hubris but I don't see him being profit motivated. From his statements in the past and his regrets today[3] of bringing the current tech into existence, I'm confident his motivator is simply the desire to not die. >WHY YOU SHOULD FEAR MACHINE INTELLIGENCE >Development of superhuman machine intelligence (SMI) [1] is probably the greatest threat to the continued existence of humanity. There are other threats that I think are more certain to happen (for example, an engineered virus with a long incubation period and a high mortality rate) but are unlikely to destroy every human in the universe in the way that SMI could. Also, most of these other big threats are already widely feared. - Sam Altman, February 25, 2015 [1] https://blog.samaltman.com/machine-intelligence-part-1 https://blog.samaltman.com/machine-intelligence-part-1 [2] https://blog.samaltman.com/machine-intelligence-part-2 https://blog.samaltman.com/machine-intelligence-part-2 [3] https://www.businessinsider.com/openai-ceo-sam-altman-says-he-is-losing-sleep-over-chatgpt-2023-6 https://www.businessinsider.com/openai-ceo-sam-altman-says-h...

cjbprime 3y ago
Lots of retrospectively-good predictions in there, but this was the one I undervalued the extent of: > We also have a bad habit of changing the definition of machine intelligence when a program gets really good to claim that the problem wasn’t really that hard in the first place We've done this so much recently that I'm now seeing rewritten definitions of "real" intelligence that most humans do not meet.
- somenameforme 3y ago
  There's quite a rationale justification for the ever 'shifting goalposts.' When humans describe some milestone in the future as finally being "real AI", they're not really just describing that milestone, but the many adjacent capabilities that they expect that milestone to entail. But we're quite clever, and like any old metric needing to be juked, we invariably find ways to achieve the milestone while sidestepping all the capabilities it's supposed to entail. Chess is the obvious example. A machine capable of playing chess at a human level was supposed to indicate the advent of genuine artificial intelligence at one time. It wasn't that playing chess well means one is intelligent, but rather it was assumed it'd entail abstract planning, strategic thought, intuition, and creativity. Of course now we have software which can crush even a world champion, but none of those adjacent capabilities emerged at all. And so I think it's also increasingly obvious that this is the same thing with chatbots. Many of us thought those 'surrounding capabilities' were finally here, even more so with OpenAI regularly demonstrating exceptional competence on a wide array of distinct metrics, such as performance on the Bar exam. But once you use the system for a while it becomes clear that its knowledge base is absolutely and unbelievably immense, but its 'understanding' of that knowledge is literally zero. It will arbitrarily create e.g. API calls that do not exist, mix up utterly simple concepts, and fail to learn from its mistakes in any meaningful way whatsoever. I'm sure if you've used ChatGPT for anything you've run into the utterly annoying scenario of: - "How do I [x]?" - "Sure! That's easy, just do [A]." - "No, you're hallucinating." - "Oh sorry, thanks. You're right you actually need to do [B]!" - "No, you're still hallucinating." - "Oh sorry, you're right. You just need to do [A]. If a human, even a stupid human, acted in this way - you'd assume they were trolling you, especially one gifted with the ability for infinite perfect and complete recall.