9 ms·

I swear no matter how many times people say it people will still conflate all ML with LLMs. No, chatGPT is not driving advances in self-driving or weather predi

by advael 2y ago

I swear no matter how many times people say it people will still conflate all ML with LLMs. No, chatGPT is not driving advances in self-driving or weather prediction

xnx 2y ago
For better or worse, "LLM" or "generative ai" has become roughly synonymous with the current wave of ML. I know very little about ChatGPT, but Waymo is using an LLM: "Powered by Gemini, a multimodal large language model developed by Google, EMMA employs a unified, end-to-end trained model to generate future trajectories for autonomous vehicles directly from sensor data." (https://waymo.com/blog/2024/10/introducing-emma https://waymo.com/blog/2024/10/introducing-emma)
- advael 2y ago
  Huh. I mean it makes sense to train end-to-end on all the interrelated tasks involved in driving but putting a whole-ass language model in the middle of that seems like a stunt. I wonder if it does better than like, any random transformer not trained on language first? Still, I hadn't heard that so I guess I was wrong about that one
  - magicalist 2y ago
    No, you were right, this appears to be just research on how applicable LLMs could be to the space. They talk about the improvements their LLM makes, especially in being multimodal vs training multiple independent models, but also the limitations that appear to prevent it from being useable as it is. Maybe some form if it will be used some day (it does seem like it would be useful to have semantic understanding of the world integrated into the system), but at least as of when this was published, it's not actually used.
- porridgeraisin 2y ago
  Waymo uses reinforcement learning (what it was before LLMs) (TD3+BC according to one of their blogs) Emma is something they tried, but further down the article they explain why they don't use it as such yet.
  - xnx 2y ago
    Yep. It's an interesting experiment and really stretched my understanding of what an LLM is and can do.
famouswaffles 2y ago
Vision Language Models are absolutely being trialed for self-driving https://wayve.ai/thinking/lingo-2-driving-with-language/ https://wayve.ai/thinking/lingo-2-driving-with-language/
- advael 2y ago
  Okay so because of the ambiguity of the other reply I'm just gonna say, I don't think we should be surprised that someone is trying to use LLMs to do basically anything. That's basically what prints funding money right now, so long as you're the kind of company or guy the VCs or whoever will believe in. The signal here is "does it do something to appreciably advance the state of the art over previous methods"?
  - famouswaffles 2y ago
    Seems to be the case to me, reading this and waymo's attempts. There's paper on EMMA here - https://arxiv.org/abs/2410.23262 https://arxiv.org/abs/2410.23262 And there are state of the art weather prediction transformers. https://arxiv.org/abs/2312.03876 https://arxiv.org/abs/2312.03876
    - advael 2y ago
      Yeah so like, this is a cool result, and it uses a transformer architecture. I actually do think that it's fair to say that transformers have proven widely useful, especially in tasks that look like sequence modeling. It's a step change akin to the now-pervasive use of convolutional neural networks that started in the 2010s, and is deeply significant of course. This is also really different from "this is an LLM" The reason I want to specifically harp on this is because a lot of people are selling this narrative where "AI is becoming superintelligent" or whatever by making an amorphous blob out of a bunch of separate advances that use machine learning techniques. This has been happening for a while, is a great thing for science, and it's clear that machine learning methods are here to stay in science. I'm a machine learning researcher. I've understood, celebrated, and tried to help with this as best I can manage over the last 9 years of my life. And it's been going on for a lot longer than the general public has been in this AI hype wave. The entire modern field of bioinformatics is arguably built on the backbone of machine learning, and has been since before I went to grad school. This is really different from "We fed everything into a language model and now it's superintelligent and is making scientific advances all by itself" or even "scientists just ask chatGPT shit and it figures it out for them". The breathless tech press really makes it sound like anything that happens in AI research, which increasingly includes the entire usage of ML toolkits in the sciences (Which is pervasive, and expectedly so! ML is an extension of statistics and statistics has been the basis of science for like a century) is just some amorphous force called "AI" that's suddenly gained this aggregate body of competency. Imagine if we anthropomorphized statistics that way. Or Math for that matter. This kind of narrative gives me the overall impression that this is not being talked about honestly, and it's clear that this is profitable to do. I don't have to use charged words like "con" or "fraud" to think this deceptive framing is not a great thing

by advael 2y ago

I swear no matter how many times people say it people will still conflate all ML with LLMs. No, chatGPT is not driving advances in self-driving or weather prediction

xnx 2y ago

For better or worse, "LLM" or "generative ai" has become roughly synonymous with the current wave of ML. I know very little about ChatGPT, but Waymo is using an LLM: "Powered by Gemini, a multimodal large language model developed by Google, EMMA employs a unified, end-to-end trained model to generate future trajectories for autonomous vehicles directly from sensor data." (https://waymo.com/blog/2024/10/introducing-emma https://waymo.com/blog/2024/10/introducing-emma)

advael 2y ago
Huh. I mean it makes sense to train end-to-end on all the interrelated tasks involved in driving but putting a whole-ass language model in the middle of that seems like a stunt. I wonder if it does better than like, any random transformer not trained on language first? Still, I hadn't heard that so I guess I was wrong about that one
- magicalist 2y ago
  No, you were right, this appears to be just research on how applicable LLMs could be to the space. They talk about the improvements their LLM makes, especially in being multimodal vs training multiple independent models, but also the limitations that appear to prevent it from being useable as it is. Maybe some form if it will be used some day (it does seem like it would be useful to have semantic understanding of the world integrated into the system), but at least as of when this was published, it's not actually used.
porridgeraisin 2y ago
Waymo uses reinforcement learning (what it was before LLMs) (TD3+BC according to one of their blogs) Emma is something they tried, but further down the article they explain why they don't use it as such yet.
- xnx 2y ago
  Yep. It's an interesting experiment and really stretched my understanding of what an LLM is and can do.

famouswaffles 2y ago

Vision Language Models are absolutely being trialed for self-driving https://wayve.ai/thinking/lingo-2-driving-with-language/ https://wayve.ai/thinking/lingo-2-driving-with-language/

advael 2y ago
Okay so because of the ambiguity of the other reply I'm just gonna say, I don't think we should be surprised that someone is trying to use LLMs to do basically anything. That's basically what prints funding money right now, so long as you're the kind of company or guy the VCs or whoever will believe in. The signal here is "does it do something to appreciably advance the state of the art over previous methods"?
- famouswaffles 2y ago
  Seems to be the case to me, reading this and waymo's attempts. There's paper on EMMA here - https://arxiv.org/abs/2410.23262 https://arxiv.org/abs/2410.23262 And there are state of the art weather prediction transformers. https://arxiv.org/abs/2312.03876 https://arxiv.org/abs/2312.03876
  - advael 2y ago
    Yeah so like, this is a cool result, and it uses a transformer architecture. I actually do think that it's fair to say that transformers have proven widely useful, especially in tasks that look like sequence modeling. It's a step change akin to the now-pervasive use of convolutional neural networks that started in the 2010s, and is deeply significant of course. This is also really different from "this is an LLM" The reason I want to specifically harp on this is because a lot of people are selling this narrative where "AI is becoming superintelligent" or whatever by making an amorphous blob out of a bunch of separate advances that use machine learning techniques. This has been happening for a while, is a great thing for science, and it's clear that machine learning methods are here to stay in science. I'm a machine learning researcher. I've understood, celebrated, and tried to help with this as best I can manage over the last 9 years of my life. And it's been going on for a lot longer than the general public has been in this AI hype wave. The entire modern field of bioinformatics is arguably built on the backbone of machine learning, and has been since before I went to grad school. This is really different from "We fed everything into a language model and now it's superintelligent and is making scientific advances all by itself" or even "scientists just ask chatGPT shit and it figures it out for them". The breathless tech press really makes it sound like anything that happens in AI research, which increasingly includes the entire usage of ML toolkits in the sciences (Which is pervasive, and expectedly so! ML is an extension of statistics and statistics has been the basis of science for like a century) is just some amorphous force called "AI" that's suddenly gained this aggregate body of competency. Imagine if we anthropomorphized statistics that way. Or Math for that matter. This kind of narrative gives me the overall impression that this is not being talked about honestly, and it's clear that this is profitable to do. I don't have to use charged words like "con" or "fraud" to think this deceptive framing is not a great thing