Hi HN,<p>We have an idea for helping AI research and we’d like to hear your thoughts on it. We want to help get a lot more people working on ML projects they find interesting. If you've been thinking about or working on a side project or have some idea that won't let you go, you're who we want to reach.<p>Why try to help? Nat and I are passionate about AI. We want to
see more Show HNs that use machine learning. We've been rewarded by
pursuing our own shower-thoughts and want to remove any barriers from
others thinking of doing the same.<p>Our plan for this is AI Grant (<a href="https://aigrant.org/" rel="nofollow">https://aigrant.org/</a>), a non-profit
distributed AI research lab. We're issuing grants to the smartest
people we can find, doing interesting work that might otherwise not
happen, and connecting them to mentors, experts, and each other. We ran our first round this spring, and awarded $50k in grants to 10 projects.<p>Filling out the form should take less than five minutes. Grantees get:<p><pre><code> - $2,500 in cash.
- $20k each in Google Compute Engine credits.
- Q&A with AI experts including Andrej Karpathy (Director of AI at Tesla and previously at OpenAI) and researchers at Google.
- Access to the network of other grantees
- 250 Tesla K80 GPU hours from FloydHub.
- $1k in ScaleAPI data labeling credits.
- $5k in CrowdFlower data labeling credits.
</code></pre>
This is not an investment in a company, it's a grant to follow your
dreams in research. You don't need to be part of any special
organization or community to apply. We don't ask for equity. All we
ask is that you do your best work, wherever your interest lies.<p>Please let us know if you have any ideas or suggestions on how we
might improve, either on the specifics of AI Grant or the general goal
of spreading AI research to everyone smart who wants in.<p>- Daniel Gross & Nat Friedman.<p>P.S. I'm a partner at YC. This is Nat's and my side project, not a
YC effort.
IMO what would actually drive AI breakthroughs is to support people on a large time scale so they can quit their applied AI/ NLP/ Computer Vision jobs and focus full time on their moonshot research endeavor. For example, I work in AI, and this is not a useful proposal for me, in particular. But I do have at least a couple crazy AI ideas that might take > a year to develop, and I can imagine nothing better than a grant I could live on for a year and develop the AI. I know I'm not the only one. Someone mentioned a catch-22 with this idea, have to agree.
From the application:<p>> What's your background?
In particular anything that would help convince us that you're actually capable of finishing your project.<p>> Project description:
Describe your project, including: where you got the idea, how you think others might use it, and how it is new/different/better than what already exists. This is the main answer we use to judge applications.<p>These questions make the grant seem like a Catch-22. The people who are skilled enough at machine learning/deep learning to receive the grant would be able to be employed at any relevant company for their research.<p>Thanks to modern machine learning/deep learning tooling, the educational bar is much lower for more <i>creative</i> projects (e.g. Show HNs) which would have more <i>necessity</i> for the spare resources. But from the application, that's not the sense I'm getting.
Great idea. I am curious about how you plan to keep in touch with the teams/individuals that do get the grant, and how the "AI Grant Network" works concretely.<p>My understanding: you get nothing tangible from the grant ("The money is a gift"), no contracts or IP... To me it seems like a bet that the networks effects and the gratefulness of the grantees will pay back somehow. I think this is a smart move because investing in smart individuals is itself smart, although the devil is in the details.
I'm serving as an advisor to a philanthropist interested in applying AI and ML to scientific and societal challenges - let me know if you'd like to chat!<p>Tom Kalil
<a href="https://www.linkedin.com/in/tom-kalil-a581/" rel="nofollow">https://www.linkedin.com/in/tom-kalil-a581/</a>
You know, I might have misread what you're offering here when I submitted an application a minute ago, but what I was really hoping was that you would be able to put me in touch with researchers in the field who would answer my emails about whether the research topics I was considering were interesting and promising or not and could help me navigate the academic publication process. The monetary pieces of this grant are largely irrelevant to me.
Thank you for sharing and running this. I'm super excited this exists and plan on applying.<p>One of the things I've finding difficult to find in my process is actually mentoring support. You can learn a lot from online resources, but often I have hit walls where I wish I could ask for help and guidance.<p>It'd be cool to a version of this with more defined mentoring path, especially for those who are new to the space!
To me I would offer a free "desktop buddy" that was open design, open source, open weights, semi open data(you can volunteer your conversations on a cases by case basis, product/service reviews could be paid contributions) managed by a mutual company or a co-op.<p>There could be a bounty for find bugs and suggesting features.<p>Maybe charge $2/mo. It would have a fiduciary duty to you as a user to act as an agent in your best interest. Allow people to contribute to the project using distributed GPUs(with legal contracts to minimize fraud).<p>Open budget with bidding and open evaluation criteria.
Pretty cool. Would apply, but don't have the technical chops just yet (Medical school is intense). Do you think you guys will run this again if it turns out to be fruitful?
See also: Latently Deep Learning Certificate<p><a href="https://github.com/Latently/DeepLearningCertificate" rel="nofollow">https://github.com/Latently/DeepLearningCertificate</a><p>Free access to ridiculous amounts of hardware and the opportunity to implement important and hot scientific papers and conduct original research in deep learning.