Jeremy, you've taken a bold, open initiative. Thank you for calling on all the small, innovative teams. To better understand the types of projects or applications that excite you and Eric most, could you share examples of companies or applications that Answer.AI currently supports or plants to invest in? Additionally, if yo u have any published articles detailing these ventures please share the link. Best wishes with your venture.

We don't invest -- we build! The idea is that we want to create lots of AI-powered applications, based on a common platform.

Could you also elaborate on how companies can reach out to you and Eric? What are the key criteria or 'table stakes' you look for in a project or team?

How are you thinking about the role of patenting at Answer.AI? How about handling tech transfer issues with universities?

I don't think we'll want to patent anything, since that's something which keeps people out -- and we want to let people in! The only reason I could think of that we'd need a patent portfolio would be for defensive purposes.

That's different from how things worked for Edison. But similar to how they worked for Luther Burbank.

I'll be rooting for you to succeed in this endeavor. I used to visit IBM ARC when I was a kid, and to my mind the academic environment is not quite the same. But as you know we really have not seen corporate R and D recover from the peaks it attained over fifty years ago.

Awesome! What sorts of products is your lab working on?

Currently we're working on low-resource fine-tuning research (i.e. train larger models on smaller cheaper GPUs), and looking into applications in the education and legal spaces. We're also starting to look at intersections between long-tail image recognition and language models.

Cool - thanks for answering!

Yesterday I had the thought of what we could achieve right now with let's say 3 x A2000 leftover GPUs from a random second-hand crypto mining rig.

I think it would be awesome to be able to use GPUs from second-hand crypto mining rigs for cheaper fine-tuning research.

Good luck! As an enthusiast who loves The Lean Startup and who recently started playing around with LLMs, I'm super stoked about Answer.AI

Fast.AI is awesome and how I first learned ML. Can’t than you enough for that great project and its impact on my career! How do you see Answer.AI as supporting other commercial research efforts that have some overlap with the open source community? I’m thinking of things like Unsloth, which is trying to take a wild swing at efficient fine-tuning of LLMs without getting scooped by big tech.

Very keen to support open source work, both financially and through our own code.

That’s great to hear! I can’t think of better stewards for this kind of work than a team you’ve put together, especially given everything you’ve provided for the community.

@publicdaniel asked below about the relevance of openai’s Ken Stanley of “greatness cannot be planned” fame. @jph00 Can you comment on the similarities and difference of your approach as you understand it, given that Ken is or was a research manager at OpenAI?

Here is Ken talking about the concept

https://www.youtube.com/watch?v=lhYGXYeMq_E

https://www.youtube.com/watch?v=dXQPL9GooyI

“ collaboration can sometimes thwart innovation by tacitly forcing its participants into an objective-driven mindset.”

Would you consider providing an RSS feed for the list of published articles? Thank you.

Oh good point - I forgot to set that up!

I like the very idea of applying this transformative AI technology to make values. I have been doing research and always been a member of research team ever since I started the ML journey. But, I've always valued applications that can solve problems and found myself inclined to building apps. I would love to work at Answer.AI. How can I apply?

My experience is that many large companies have problems that could be solved/improved with small fine-tuned AI services, but usually they are extremely cagey about disclosing which parts of their workflow are slow/expensive and would, therefore, be the best targets for automation and/or improvements coming from AI research. The cliche example here would be to automate processing of some paper forms. And it's cliche precisely because for most companies it would help them become faster and more competitive.

How do you plan to research potential problems to solve?

Would it be possible to publish and discuss those to-be-solved problems, so that hobbyists can also try their luck at solving them?

Initially, I thought that Kaggle competitions would be a great way to get the industry's problems into the hands of motivated problem-solvers. But I don't think I've ever seen a large car manufacturer (for example) as Kaggle competition host. So it looks like something is holding companies back.