5 ms·

24 Seriously Embarrassing Hours for AI

28 points by headalgorithm 4y ago

madsmith 4y ago
I think it’s misleading to say Tesla faked the driving. They were running one off software, purpose trained for the route, showing the golden run that was successful.. yes. But it was computer vision and self driving that they demonstrated. It just wasn’t their production system.
- uxp100 4y ago
  It’s certainly highly deceptive, if not exactly fake. Not uncommon for software demos to have a golden path that you must follow of crashes will result, but that’s not a good thing.
gs17 4y ago
Tesla's things are embarassing for Tesla, not AI as a field. > Real AI wouldn’t need vast amounts of data. And yet he expects an encyclopedic knowledge of the plot to Lost (a thing few humans who learned by watching it as it came out have) as part of a "Real AI".
ChrisRR 4y ago
"Real AI wouldn't need vast amounts of data" Errrrr yes it would. That's why we're born as dribbling blobs who can't fend for themselves, and then spend years absorbing data from our environment and those around us.
- foldr 4y ago
  ChatGPT-3 uses way more linguistic data than any single human is ever exposed to before displaying similar levels of intelligence.
  - kbelder 4y ago
    And far less data in total. Linguistic data is only a tiny fraction of what we humans are exposed to.
    - foldr 4y ago
      I don't think we have good estimates of the total amount of data that factors into human learning. The total amount of raw sensory data we receive over a lifetime is large, for sure, but only a tiny fraction of that is relevant to learning. Just think about how much bigger ChatGPT's training corpus would be if it consisted of .WAV files of people speaking an equivalent amount of text.
  - julvo 4y ago
    Not saying that LLMs are particularly data efficient, but in their defence, they don't only learn what a human learns in a lifetime but throughout the whole evolution. There may be information encoded in our genes that LLMs need to learn from the training data
    - foldr 4y ago
      For sure a human baby has lots of initial structure that ChatGPT is lacking. Skinner made the point that operant conditioning and evolution are abstractly very similar processes. If this were the case then it would make sense to think of learning as a process that takes place both within individual human lifespans and over the course of evolutionary history. In fact, on almost anyone's account these days (including that of proponents of LLMs), learning is not very much like operant conditioning. Thus the analogy breaks down, and one can't excuse the amount of data that ChatGPT requires by hand waving about how this is just the equivalent of the 'learning' that a human baby got indirectly via evolution.
  - notshift 4y ago
    I used to think like this too, but I realized recently that actually the human brain doesn't train over ~20 years of data, it trains over ~200 million years of data. Human babies aren't an empty neural network with no weights, the entire network architecture and the entire set of checkpoint starting weights that the brain begins training from is encoded into the human genome. It would be silly to expect evolution to do anything other than this, actually. Also at this point I'm not even sure if "general" intelligence is a thing that exists or can exist. Humans have a specific intelligence which is very specifically designed for the world and universe that we live in. Intelligent machines will have to be similarly designed.
    - turbokatsu20 4y ago
      I think it's remarkable that one can't help but use language like 'designed' when referring to highly ordered and complex engineering marvels in nature but what they actually mean is that they believe this robust, highly ordered information management system was haphazardly built one bitflip at a time until we have the most successful organism in the known universe. The further we push the boundaries of what we know about engineering, the more far fetched that paradigm becomes. I predict that mankind will see more successful breakthroughs when they start looking at organic systems through the lens of deliberate system design rather than spending so long kidding ourselves that it was all achieved by chance against impossible odds.
      - notshift 4y ago
        I think the way evolution operates is quite a bit more complicated than "one bitflip at a time". The way evolution operates is a meta-process that itself was shaped by an evolutionary process which took place (mostly) long ago. IMO, the genome is like an abstract system which was "designed" for evolution. It can move in one direction or another on the phenotypic plane actually extremely quickly under strong environmental pressures (on the order of only a few hundred or thousand years). And the winds of environmental pressures are frequently shifting, producing what was likely a very thorough and aggressive search of the state space. I agree there is probably a lot to be learned from further study of the human body and brain, but we will have to re-invent a lot ourselves too since the machine capabilities we are looking for are really a lot different than the constraints that humans were shaped under.
- carapace 4y ago
  Yeah the bit at the end was kinda silly, eh? Sure, we don't have magic AI yet, but what do we do about what we do have?
Havoc 4y ago
Surprised people are upset about the OpenAI/Kenya thing. I thought it was common knowledge that this is how all the humans-required grunt work is done. Whether its dataset tagging work or facebook content moderation...outsourcing it to poor countries for peanuts is the SOP.
- rednerrus 4y ago
  It's important to remember that peanuts in the US can be life changing in developing countries.
kderbyma 4y ago
ChatGPT had possible options....then I saw the politics were more important....so yeah. Of course it's crap...it was a smoke screen like FSD a la musk....stinks
cheeselip420 4y ago
Gary Marcus is a turd. He just fights straw-men and drums up conflict on Twitter for engagement. He's a leech.

28 points by headalgorithm 4y ago

I think it’s misleading to say Tesla faked the driving. They were running one off software, purpose trained for the route, showing the golden run that was successful.. yes. But it was computer vision and self driving that they demonstrated. It just wasn’t their production system.

uxp100 4y ago
It’s certainly highly deceptive, if not exactly fake. Not uncommon for software demos to have a golden path that you must follow of crashes will result, but that’s not a good thing.

gs17 4y ago

Tesla's things are embarassing for Tesla, not AI as a field. > Real AI wouldn’t need vast amounts of data. And yet he expects an encyclopedic knowledge of the plot to Lost (a thing few humans who learned by watching it as it came out have) as part of a "Real AI".

ChrisRR 4y ago

"Real AI wouldn't need vast amounts of data" Errrrr yes it would. That's why we're born as dribbling blobs who can't fend for themselves, and then spend years absorbing data from our environment and those around us.

foldr 4y ago
ChatGPT-3 uses way more linguistic data than any single human is ever exposed to before displaying similar levels of intelligence.
- kbelder 4y ago
  And far less data in total. Linguistic data is only a tiny fraction of what we humans are exposed to.
  - foldr 4y ago
    I don't think we have good estimates of the total amount of data that factors into human learning. The total amount of raw sensory data we receive over a lifetime is large, for sure, but only a tiny fraction of that is relevant to learning. Just think about how much bigger ChatGPT's training corpus would be if it consisted of .WAV files of people speaking an equivalent amount of text.
- julvo 4y ago
  Not saying that LLMs are particularly data efficient, but in their defence, they don't only learn what a human learns in a lifetime but throughout the whole evolution. There may be information encoded in our genes that LLMs need to learn from the training data
  - foldr 4y ago
    For sure a human baby has lots of initial structure that ChatGPT is lacking. Skinner made the point that operant conditioning and evolution are abstractly very similar processes. If this were the case then it would make sense to think of learning as a process that takes place both within individual human lifespans and over the course of evolutionary history. In fact, on almost anyone's account these days (including that of proponents of LLMs), learning is not very much like operant conditioning. Thus the analogy breaks down, and one can't excuse the amount of data that ChatGPT requires by hand waving about how this is just the equivalent of the 'learning' that a human baby got indirectly via evolution.
- notshift 4y ago
  I used to think like this too, but I realized recently that actually the human brain doesn't train over ~20 years of data, it trains over ~200 million years of data. Human babies aren't an empty neural network with no weights, the entire network architecture and the entire set of checkpoint starting weights that the brain begins training from is encoded into the human genome. It would be silly to expect evolution to do anything other than this, actually. Also at this point I'm not even sure if "general" intelligence is a thing that exists or can exist. Humans have a specific intelligence which is very specifically designed for the world and universe that we live in. Intelligent machines will have to be similarly designed.
  - turbokatsu20 4y ago
    I think it's remarkable that one can't help but use language like 'designed' when referring to highly ordered and complex engineering marvels in nature but what they actually mean is that they believe this robust, highly ordered information management system was haphazardly built one bitflip at a time until we have the most successful organism in the known universe. The further we push the boundaries of what we know about engineering, the more far fetched that paradigm becomes. I predict that mankind will see more successful breakthroughs when they start looking at organic systems through the lens of deliberate system design rather than spending so long kidding ourselves that it was all achieved by chance against impossible odds.
    - notshift 4y ago
      I think the way evolution operates is quite a bit more complicated than "one bitflip at a time". The way evolution operates is a meta-process that itself was shaped by an evolutionary process which took place (mostly) long ago. IMO, the genome is like an abstract system which was "designed" for evolution. It can move in one direction or another on the phenotypic plane actually extremely quickly under strong environmental pressures (on the order of only a few hundred or thousand years). And the winds of environmental pressures are frequently shifting, producing what was likely a very thorough and aggressive search of the state space. I agree there is probably a lot to be learned from further study of the human body and brain, but we will have to re-invent a lot ourselves too since the machine capabilities we are looking for are really a lot different than the constraints that humans were shaped under.
carapace 4y ago
Yeah the bit at the end was kinda silly, eh? Sure, we don't have magic AI yet, but what do we do about what we do have?

Havoc 4y ago

Surprised people are upset about the OpenAI/Kenya thing. I thought it was common knowledge that this is how all the humans-required grunt work is done. Whether its dataset tagging work or facebook content moderation...outsourcing it to poor countries for peanuts is the SOP.

rednerrus 4y ago
It's important to remember that peanuts in the US can be life changing in developing countries.

kderbyma 4y ago

ChatGPT had possible options....then I saw the politics were more important....so yeah. Of course it's crap...it was a smoke screen like FSD a la musk....stinks

cheeselip420 4y ago

Gary Marcus is a turd. He just fights straw-men and drums up conflict on Twitter for engagement. He's a leech.