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AI Grant aims to fund the unfundable to advance AI and solve hard problems

Posted in Software on 26th Jul, 2017 04:45 PM by Alex Muller

Everyone knows there’s money to be made from AI, but to capture value, good VCs know they need to back products and not technologies. This has left a bit of a void in the space where research occurs within research institutions and large tech companies and commercialization occurs within verticalized startups.


AI Grant, created by Nat Friedman and Daniel Gross, aims to bankroll science projects for the heck of it to give untraditional candidates a shot at solving big problems.

Gross, a partner at Y Combinator, and Friedman, a founder who grew Xamarin to acquisition by Microsoft, started working on AI Grant back in April. AI Grant issues no-strings-attached grants to people passionate about interesting AI problems. The more formalized version launching today brings a slate of corporate partners and a more structured application review process.
Anyone, regardless of background, can submit an application for a grant. The application is online and consists of questions about background and prior projects in addition to basic information about what the money will be used for and what the initial steps will be for the project. Applicants are asked to connect their GitHub, LinkedIn, Facebook and Twitter accounts.
Gross told me in an interview that the goal is to build profiles of non-traditional machine learning engineers. Eventually, the data collected from the grant program could allow the two to play a bit of machine learning moneyball, valuing machine learning engineers without traditional metrics (like having a PhD from Stanford). You can imagine how all the social data could even help build a model for ideal grant recipients in the future.
The long-term goal is to create a decentralized AI research lab, think DeepMind but run through Slack and full of engineers that don’t cost $300,000 a pop. One day, the MacArthur genius grant-inspired program could serve other industries outside of AI, offering a playground of sorts for the obsessed to build, uninhibited.
The entire AI Grant project reminds me of a cross between a Thiel Fellowship and a Kaggle competition. The former, a program to give smart college dropouts money and freedom to tinker and the later, an innovative platform for evaluating data scientists through competition. Neither strive to advance the field in the way the AI Grant program does, but you can see the ideological similarity around democratizing innovation.
Some of the early proposals to receive the AI Grant include:
Simulation of many-body quantum systems with neural networks
Machine learning for motion recognition and trajectory generation of human movement for rehabilitation
Simulating physiologically plausible human brain electromagnetic activity using GANs
Charles River Ventures (CRV) is providing the $2,500 grants that will be handed out to the next 20 fellows. In addition, Google has signed on to provide $20,000 in cloud computing credits to each winner, CrowdFlower is offering $18,000 in platform credit with $5,000 in human labeling credits, Scale is giving $1,000 in human labeling credit per winner and Floyd will give 250 Tesla K80 GPU hours to each winner.
During the first selection of grant winners, Floodgate awarded $5,000 checks. The program launching today will award $2,500 checks. Gross told me that this change was intentional, the initial check size was too big. The plan is to add additional flexibility in the future to allow applicants to make a case for how much money they actually need.

Tags: AIdeep learningmachine learningsoftwareneural network

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