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Hi folks -- Jeremy from Answer.AI (and fast.ai!) here. Happy to answer any questions you have about this new thing that Eric and I are building. One thing I'm

by jph00 3y ago

Hi folks -- Jeremy from Answer.AI (and fast.ai!) here. Happy to answer any questions you have about this new thing that Eric and I are building. One thing I'm particularly keen to explore is working closely with academic groups to help support research that might help make AI more accessible (e.g. requiring less data or compute, or becoming easier to use, etc). This includes the obvious stuff like quantization, fine-tuning adaptors, model merging, distillation, etc, but also looking for new directions and ideas as well which might otherwise be hard to fund (since academia tends to like to build on established research directions.) I've opened my DMs at https://twitter.com/jeremyphoward https://twitter.com/jeremyphoward for a while so feel free to ping me there, or also on Discord ('jeremyhoward').

manu-sapiens 3y ago
Very interesting read. My name is Emmanuel Lusinchi, and together with my colleague Georg Zoeller, we represent Omnitool.ai, a fledgling platform in the AI landscape with a mission that resonates deeply with the ethos of Answer.AI. Firstly, congratulations on the launch of Answer.AI and the vision you've set forth. We have been following your work with great admiration - I took the FastAI course in what feels like an eternity ago (3 years) and I have been recommending it to anyone interested in foundational AI. But more to your post’s point: your commitment to harnessing AI's potential to create practical end-user products is not only inspiring but aligns with our own philosophy. We have developed an open-source "AI lab-in-a-box". A platform that seamlessly integrates a multitude of AI models, both locally and cloud-hosted, through a single unified interface. The aim is to simplify access to the latest developments in AI - both on the technical side (knowledge to run AI models and connect them together) and on the financial side (access to GPUs) . We believe this to be useful to accelerate experimentation and iteration but also facilitate teaching AI - giving teachers a simple, consistent tool and giving students practical experience with the latest models so they can experience first hand complex and often too abstract concepts such as Bias. By reducing friction and lowering barriers of entry, our platform aims at democratizing access to the latest AI technologies, providing almost anyone with the tools and flexibility needed to push the boundaries of what's possible with AI. And we do believe that our platform could serve as a valuable tool in your R&D processes, speeding up Answer.AI ability to rapidly prototype and refine applications that leverage foundational research breakthroughs. Moreover, we share your concern about the widening gap in understanding AI's capabilities and its implications. We believe that transparency, education, and open-source collaboration are key to bridging this gap, ensuring that AI's benefits are widely distributed and its risks are responsibly managed. We are reaching out to explore potential avenues for collaboration. Whether it's simply helping you evaluate and perhaps use our platform into your R&D workflow, co-developing new tools, or simply engaging in a dialogue to share insights, we are eager to contribute to the incredible work you're undertaking at Answer.AI. We would be honored to discuss this further with you. Please find more information about our platform and its capabilities on our GitHub: https://github.com/omnitool-ai/omnitool https://github.com/omnitool-ai/omnitool. We are also open to setting up a demonstration or a meeting at your convenience to explore synergies between our organizations. Warm regards, Emmanuel Lusinchi Co-founder, Omnitool.ai emmanuel@omnitool.ai Georg Zoeller Co-founder, Omnitool.ai georg@omnitool.ai P.S. A few links: Intro video we made for Replicate: https://www.youtube.com/watch?v=DbKVUhWCYOI https://www.youtube.com/watch?v=DbKVUhWCYOI The interesting part is around 0:40, showing how any Replicate model (https://replicate.com/explore https://replicate.com/explore) can be added to the platform and connected to others in two clicks. Github: https://github.com/omnitool-ai/omnitool https://github.com/omnitool-ai/omnitool Website: https://omnitool.ai/ https://omnitool.ai/
reqo 3y ago
If I understand correctly, your focus will be on smaller models and what can be built on top of them? How relevant do you think fine-tuning small models will be once AGI is widely accessible? Do you think smaller models can co-exit in a AGI future?
- ska 3y ago
  Conversely, how relevant do you think 2023 techniques will be at all in a hypothetical AGI future? Doesn't the relevance of these questions embed some pretty strong assumptions?
- jph00 3y ago
  I plan to write a longer article about this in fact! In short, I think we already have AGI, but I'm not sure it's going to get dramatically better quickly (i.e I don't think it's a clear path to ASI). I think AGI is actually less important than we all expected it to be, and that it doesn't replace more tightly focused domain-specific models.
  - pigeons 3y ago
    > I think we already have AGI, This is the only time I have seen anyone claim this. Can you elaborate?
    - eries 3y ago
      stay tuned
    - lmeyerov 3y ago
      Computers that can reliably write programs / higher-order logic has long been one of my big fundamental bars for useful AGI. It will clearly get better, but for a lot of what knowledge workers already do... The bar has been cleared, and now engineering is playing a much easier game of catch-up. (Hi Jeremy!)
      - Roark66 3y ago
coderintherye 3y ago
Great to see this effort! Couldn't think of a better duo to experiment with it! >with academic groups to help support research that might help make AI more accessible Jeremy, are you already talking with Sky Computing Lab? I recall they had an interesting project about SkyPilot which seemed helpful https://sky.cs.berkeley.edu/ https://sky.cs.berkeley.edu/ https://github.com/skypilot-org/skypilot https://github.com/skypilot-org/skypilot
- jph00 3y ago
  No I'm not, but I'm aware of their work and it looks great - I should certainly chat to them!
phillipcarter 3y ago
Something I've learned as I've dived a bit into fine-tuning is that it's really hard. I even have what I think is good data, and a lot of it. But, as a non-ML engineer who just wants to use these tools as good APIs (and someone with the ability to ensure I have a coherent data pipeline), I woulnd't know how to proceed if I wasn't already working with an ML engineer who's been doing this sort of stuff for a while. Specifically, I fine-tuned gpt-3.5 and llama-2-7b on some real-world usage data, and I can't tell a single difference between the quality of these outputs compared to "base" gpt-3.5 with the same requests made to it. Moreover, if I attempt to remove a lot of the "static" sections of a prompt (after all, there's 2k+ lines of data it was fine-tuned on where this is all present), both models just go completely off the rails. I'd love to get into a world where I can fine-tune a bunch of different models. But it's so, so much harder than just calling OpenAI's API and getting really good results with that and some prompting work. If you're able to help crack that nut then there's a lot of people like me who would pay money to have their problems solved.
- adw 3y ago
  2k lines is (probably) not a lot of data.
  - phillipcarter 3y ago
    That may be the issue. I can get about 6k lines of data today and in time, could have a bunch more. Each line represents a full request (user input, model output, full prompt, etc.) so I would intuitively think that 2k of these is good enough. And it's actually good enough for llama-2-7b, insofar as it transforms this model from "terrible with my prompt in production today" to "this could be workable, actually". But my bar is to be better than gpt-3.5 and require less text in my prompt, but no fine-tuning I've done so far has achieved that.
    - kiratp 3y ago
      It’s not reasonably possible (currently?) to get the same performance from a 7 billion parameter model as a 175 billion parameter model with just an additional 6000 lines of finetuning data.
fuddle 3y ago
I'm looking forward to seeing what what projects you work on at Answer.ai! I'm a big fan of your fast.ai courses and all the work you've done in the AI industry.
tikkun 3y ago
Looks great! What kinds of products might the lab build?
glth 3y ago
This is a great initiative! Given what you want to achieve, I presume you will have a wide range of (atypical) profiles in your team.
- eries 3y ago
  Without a doubt
soulofmischief 3y ago
Congrats on launching! This initiative looks awesome, and I'd definitely love to take you up on that and chat about it for a bit to understand the vision and what kind of engineering culture you're hoping to build. Sent a friend request on Discord!
gardenhedge 3y ago
"team of deep-tech generalists—the world’s very best, regardless of where they live, what school they went to, or any other meaningless surface feature." How are you planning on hiring?
- jph00 3y ago
  We're trying to figure that out -- we'll probably try a few somewhat non-traditional approaches to find the kinds of people that would be a good fit for our team.
behnamoh 3y ago
I like your tutorials so much! I think you're a gift to the ML community. How did you guys secure $10m VC while putting this on the webpage? I'm not criticizing or anything—just want to know how one can pitch an uncertain idea and yet receive generous funding. > We don’t really know what we’re doing If you’ve read this far, then I’ll tell you the honest truth: we don’t actually know what we’re doing. Artificial intelligence is a vast and complex topic, and I’m very skeptical of anyone that claims they’ve got it all figured out. Indeed, Faraday felt the same way about electricity—he wasn’t even sure it was going to be of any import: > “I am busy just now again on Electro-Magnetism and think I have got hold of a good thing but can’t say; it may be a weed instead of a fish that after all my labour I may at last pull up.” Faraday 1931 letter to R. Phillips > But it’s OK to be uncertain. Eric and I believe that the best way to develop valuable stuff built on top of modern AI models is to try lots of things, see what works out, and then gradually improve bit by bit from there. > As Faraday said, “A man who is certain he is right is almost sure to be wrong.” Answer.AI is an R&D lab for people who aren’t certain they’re right, but they’ll work damn hard to get it right eventually. > This isn’t really a new kind of R&D lab. Edison did it before, nearly 150 years ago. So I guess the best we can do is to say it’s a new old kind of R&D lab. And if we do as well as GE, then I guess that’ll be pretty good.
- jph00 3y ago
  That's a very fair question! The key is to find aligned investors. In this case, we found investors who believe in the fundamental opportunity, have the patience for us to figure out how to capture it, and believe that we're the right people to do it.
  - fuzzfactor 3y ago
    I like this approach, it could turn out to be quite Edisonian. Along the way you could really uncover some things that others would not.
- bomewish 3y ago
  They were betting on the reputation and track record of the principals, not a specific business plan they’ve got right now.
nl 3y ago
Do you have an Answer.AI discord? Could you start one please?
richardw 3y ago
I'm super keen to at the very least keep an eye on this! Good luck. Question: the world is basically an RnD lab right now, with hourly releases of ideas, lots of cross-pollination, all focused on discovering value a bit behind the bleeding edge of the superscalers. This seems to be playing in exactly that space, but obviously you feel there's a need and a reason why this model would succeed. Could you expand on that? (Thank you both for all you've done.)
ouraf 3y ago
open a space to spitball ideas for future models. You never know when a stray idea might spark a revolution. After all, not too long ago, "Attention was all we needed"

by jph00 3y ago

manu-sapiens 3y ago

Very interesting read. My name is Emmanuel Lusinchi, and together with my colleague Georg Zoeller, we represent Omnitool.ai, a fledgling platform in the AI landscape with a mission that resonates deeply with the ethos of Answer.AI. Firstly, congratulations on the launch of Answer.AI and the vision you've set forth. We have been following your work with great admiration - I took the FastAI course in what feels like an eternity ago (3 years) and I have been recommending it to anyone interested in foundational AI. But more to your post’s point: your commitment to harnessing AI's potential to create practical end-user products is not only inspiring but aligns with our own philosophy. We have developed an open-source "AI lab-in-a-box". A platform that seamlessly integrates a multitude of AI models, both locally and cloud-hosted, through a single unified interface. The aim is to simplify access to the latest developments in AI - both on the technical side (knowledge to run AI models and connect them together) and on the financial side (access to GPUs) . We believe this to be useful to accelerate experimentation and iteration but also facilitate teaching AI - giving teachers a simple, consistent tool and giving students practical experience with the latest models so they can experience first hand complex and often too abstract concepts such as Bias. By reducing friction and lowering barriers of entry, our platform aims at democratizing access to the latest AI technologies, providing almost anyone with the tools and flexibility needed to push the boundaries of what's possible with AI. And we do believe that our platform could serve as a valuable tool in your R&D processes, speeding up Answer.AI ability to rapidly prototype and refine applications that leverage foundational research breakthroughs. Moreover, we share your concern about the widening gap in understanding AI's capabilities and its implications. We believe that transparency, education, and open-source collaboration are key to bridging this gap, ensuring that AI's benefits are widely distributed and its risks are responsibly managed. We are reaching out to explore potential avenues for collaboration. Whether it's simply helping you evaluate and perhaps use our platform into your R&D workflow, co-developing new tools, or simply engaging in a dialogue to share insights, we are eager to contribute to the incredible work you're undertaking at Answer.AI. We would be honored to discuss this further with you. Please find more information about our platform and its capabilities on our GitHub: https://github.com/omnitool-ai/omnitool https://github.com/omnitool-ai/omnitool. We are also open to setting up a demonstration or a meeting at your convenience to explore synergies between our organizations. Warm regards, Emmanuel Lusinchi Co-founder, Omnitool.ai emmanuel@omnitool.ai Georg Zoeller Co-founder, Omnitool.ai georg@omnitool.ai P.S. A few links: Intro video we made for Replicate: https://www.youtube.com/watch?v=DbKVUhWCYOI https://www.youtube.com/watch?v=DbKVUhWCYOI The interesting part is around 0:40, showing how any Replicate model (https://replicate.com/explore https://replicate.com/explore) can be added to the platform and connected to others in two clicks. Github: https://github.com/omnitool-ai/omnitool https://github.com/omnitool-ai/omnitool Website: https://omnitool.ai/ https://omnitool.ai/

reqo 3y ago

If I understand correctly, your focus will be on smaller models and what can be built on top of them? How relevant do you think fine-tuning small models will be once AGI is widely accessible? Do you think smaller models can co-exit in a AGI future?

ska 3y ago
Conversely, how relevant do you think 2023 techniques will be at all in a hypothetical AGI future? Doesn't the relevance of these questions embed some pretty strong assumptions?
jph00 3y ago
I plan to write a longer article about this in fact! In short, I think we already have AGI, but I'm not sure it's going to get dramatically better quickly (i.e I don't think it's a clear path to ASI). I think AGI is actually less important than we all expected it to be, and that it doesn't replace more tightly focused domain-specific models.
- pigeons 3y ago
  > I think we already have AGI, This is the only time I have seen anyone claim this. Can you elaborate?
  - eries 3y ago
    stay tuned
  - lmeyerov 3y ago
    Computers that can reliably write programs / higher-order logic has long been one of my big fundamental bars for useful AGI. It will clearly get better, but for a lot of what knowledge workers already do... The bar has been cleared, and now engineering is playing a much easier game of catch-up. (Hi Jeremy!)
    - Roark66 3y ago

coderintherye 3y ago

Great to see this effort! Couldn't think of a better duo to experiment with it! >with academic groups to help support research that might help make AI more accessible Jeremy, are you already talking with Sky Computing Lab? I recall they had an interesting project about SkyPilot which seemed helpful https://sky.cs.berkeley.edu/ https://sky.cs.berkeley.edu/ https://github.com/skypilot-org/skypilot https://github.com/skypilot-org/skypilot

jph00 3y ago
No I'm not, but I'm aware of their work and it looks great - I should certainly chat to them!

phillipcarter 3y ago

Something I've learned as I've dived a bit into fine-tuning is that it's really hard. I even have what I think is good data, and a lot of it. But, as a non-ML engineer who just wants to use these tools as good APIs (and someone with the ability to ensure I have a coherent data pipeline), I woulnd't know how to proceed if I wasn't already working with an ML engineer who's been doing this sort of stuff for a while. Specifically, I fine-tuned gpt-3.5 and llama-2-7b on some real-world usage data, and I can't tell a single difference between the quality of these outputs compared to "base" gpt-3.5 with the same requests made to it. Moreover, if I attempt to remove a lot of the "static" sections of a prompt (after all, there's 2k+ lines of data it was fine-tuned on where this is all present), both models just go completely off the rails. I'd love to get into a world where I can fine-tune a bunch of different models. But it's so, so much harder than just calling OpenAI's API and getting really good results with that and some prompting work. If you're able to help crack that nut then there's a lot of people like me who would pay money to have their problems solved.

adw 3y ago
2k lines is (probably) not a lot of data.
- phillipcarter 3y ago
  That may be the issue. I can get about 6k lines of data today and in time, could have a bunch more. Each line represents a full request (user input, model output, full prompt, etc.) so I would intuitively think that 2k of these is good enough. And it's actually good enough for llama-2-7b, insofar as it transforms this model from "terrible with my prompt in production today" to "this could be workable, actually". But my bar is to be better than gpt-3.5 and require less text in my prompt, but no fine-tuning I've done so far has achieved that.
  - kiratp 3y ago
    It’s not reasonably possible (currently?) to get the same performance from a 7 billion parameter model as a 175 billion parameter model with just an additional 6000 lines of finetuning data.

fuddle 3y ago

I'm looking forward to seeing what what projects you work on at Answer.ai! I'm a big fan of your fast.ai courses and all the work you've done in the AI industry.

tikkun 3y ago

Looks great! What kinds of products might the lab build?

glth 3y ago

This is a great initiative! Given what you want to achieve, I presume you will have a wide range of (atypical) profiles in your team.

eries 3y ago
Without a doubt

soulofmischief 3y ago

Congrats on launching! This initiative looks awesome, and I'd definitely love to take you up on that and chat about it for a bit to understand the vision and what kind of engineering culture you're hoping to build. Sent a friend request on Discord!

gardenhedge 3y ago

"team of deep-tech generalists—the world’s very best, regardless of where they live, what school they went to, or any other meaningless surface feature." How are you planning on hiring?

jph00 3y ago
We're trying to figure that out -- we'll probably try a few somewhat non-traditional approaches to find the kinds of people that would be a good fit for our team.

behnamoh 3y ago

I like your tutorials so much! I think you're a gift to the ML community. How did you guys secure $10m VC while putting this on the webpage? I'm not criticizing or anything—just want to know how one can pitch an uncertain idea and yet receive generous funding. > We don’t really know what we’re doing If you’ve read this far, then I’ll tell you the honest truth: we don’t actually know what we’re doing. Artificial intelligence is a vast and complex topic, and I’m very skeptical of anyone that claims they’ve got it all figured out. Indeed, Faraday felt the same way about electricity—he wasn’t even sure it was going to be of any import: > “I am busy just now again on Electro-Magnetism and think I have got hold of a good thing but can’t say; it may be a weed instead of a fish that after all my labour I may at last pull up.” Faraday 1931 letter to R. Phillips > But it’s OK to be uncertain. Eric and I believe that the best way to develop valuable stuff built on top of modern AI models is to try lots of things, see what works out, and then gradually improve bit by bit from there. > As Faraday said, “A man who is certain he is right is almost sure to be wrong.” Answer.AI is an R&D lab for people who aren’t certain they’re right, but they’ll work damn hard to get it right eventually. > This isn’t really a new kind of R&D lab. Edison did it before, nearly 150 years ago. So I guess the best we can do is to say it’s a new old kind of R&D lab. And if we do as well as GE, then I guess that’ll be pretty good.

jph00 3y ago
That's a very fair question! The key is to find aligned investors. In this case, we found investors who believe in the fundamental opportunity, have the patience for us to figure out how to capture it, and believe that we're the right people to do it.
- fuzzfactor 3y ago
  I like this approach, it could turn out to be quite Edisonian. Along the way you could really uncover some things that others would not.
bomewish 3y ago
They were betting on the reputation and track record of the principals, not a specific business plan they’ve got right now.

nl 3y ago

Do you have an Answer.AI discord? Could you start one please?

richardw 3y ago

I'm super keen to at the very least keep an eye on this! Good luck. Question: the world is basically an RnD lab right now, with hourly releases of ideas, lots of cross-pollination, all focused on discovering value a bit behind the bleeding edge of the superscalers. This seems to be playing in exactly that space, but obviously you feel there's a need and a reason why this model would succeed. Could you expand on that? (Thank you both for all you've done.)

ouraf 3y ago

open a space to spitball ideas for future models. You never know when a stray idea might spark a revolution. After all, not too long ago, "Attention was all we needed"