Fast.ai
| Industry | Artificial intelligence |
|---|---|
| Founded | October 2016 |
| Founders | Jeremy Howard, Rachel Thomas |
Key people | Jeremy Howard, Rachel Thomas, Sylvain Gugger |
| Website | www.fast.ai |
fast.ai is a non-profit research group focused on deep learning and artificial intelligence. They are dedicated to creating learning resources aimed at making deep learning as accessible to as many people as possible, regardless of economic status, education, race, geographic location and sex. They do this through their MOOC "Practical Deep Learning for Coders" on their website free of charge and with no prerequisites except for knowledge of the programming language Python.[1]
Background
fast.ai was founded in 2016 by Jeremy Howard and Rachel Thomas[2] under the slogan “Making neural nets uncool again”. They explain that “being cool is about being exclusive, and that’s the opposite of what we want. We want to make deep learning as accessible as possible” citing users of things like programming language C# or operating systems like Windows as also being deserving to participate in the deep learning landscape.[3] In 2018 students of fast.ai outperformed Google in Stanford’s DAWNBench challenge in programming the fastest and cheapest algorithms.[4] Notable users of fast.ai include Sara Hooker who created software to detect illegal deforestation during her time as a student and later became a founding member of Google AI in Accra, Ghana – the first AI research office in Africa[5] – and Melissa Fabros, who used her skills to address racial bias’ in microfinance company Kiva’s algorithms. Others have went on to work with Google Brain, OpenAI, and Github.[6]
Software
In October 2018, fast.ai released v1.0 of their first free open source library for deep learning called fastai (without a period), sitting atop PyTorch. Google Cloud was the first to announce its support.[7]
#Masks4All
fast.ai hosts multiple resources on its site championing the wearing of masks in the wake of the COVID-19 outbreak.[8] Co-founder Jeremy Howard has been one of the most vocal and prominent advocates for masks, organizing an open letter directed to all US governors with editor-in-chief of the Blood Cancer Journal Dr Vincent Rajkumar, signed by leading scientists from all over the world.[9] Information regarding the science behind the efficacy of masks during the pandemic can be found through fast.ai in 22 different languages.[10]
External links
- Official website
- Jeremy Howard: The wonderful and terrifying implications of computers that can learn at TED
- Rachel Thomas:Artificial Intelligence needs all of us at TEDx San-Francisco
References
- ^ "Practical Deep Learning for Coders". Retrieved 7 June 2020.
- ^ "Launching fast.ai". 7 Oct 2016.
- ^ "fast.ai - About". Retrieved 7 June 2020.
- ^ "An AI speed test shows clever coders can still beat tech giants like Google and Intel". 7 May 2018.
- ^ "New schemes teach the masses to build AIO". 27 Oct 2018.
- ^ "fastai - ai". Retrieved 2 Oct 2018.
- ^ "Fast.ai's software could radically democratize AI". 2 Oct 2018.
- ^ "ai-in-society". Retrieved 7 June 2020.
- ^ "An open letter from scientists across the globe calling for use of fabric masks to prevent COVID-19". 14 May 2020.
- ^ "Masks for all? The science says yes". 13 April 2020.