fast.ai Organization
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A fast.ai Organization is an educational organization.
- See: Deep Learning, Jeremy Howard.
References
2018
- http://www.fast.ai/about/
- QUOTE: fast.ai is dedicated to making the power of deep learning accessible to all. Deep learning is dramatically improving medicine, education, agriculture, transport and many other fields, with the greatest potential impact in the developing world. For its full potential to be met, the technology needs to be much easier to use, more reliable, and more intuitive than it is today. We are:
- Writing fast and easy to use software for both developers and end users
- Developing a complete educational framework
- Building a library of ready-to-use applications and models
- Working on hybrid “man and machine” solutions that harness the strengths of both humans and computers
- QUOTE: fast.ai is dedicated to making the power of deep learning accessible to all. Deep learning is dramatically improving medicine, education, agriculture, transport and many other fields, with the greatest potential impact in the developing world. For its full potential to be met, the technology needs to be much easier to use, more reliable, and more intuitive than it is today. We are:
2016
- http://www.fast.ai/2016/10/07/fastai-launch/
- QUOTE: ... deep learning has a very long way to go before it can help most people. Creating a deep learning model is, ironically, a highly manual process. Training a model takes a long time, and even for the top practitioners, it is a hit or miss affair where you don’t know whether it will work until the end. No mature tools exist to ensure models train successfully, or to ensure that the original set up is done appropriately for the data.
Therefore, Dr. Rachel Thomas (a math PhD with past experience as a quant, Uber data scientist, full-stack developer, and educator) and I decided to create fast.ai, a research lab dedicated to doing everything necessary to allow deep learning to meet its enormous potential. ...
- QUOTE: ... deep learning has a very long way to go before it can help most people. Creating a deep learning model is, ironically, a highly manual process. Training a model takes a long time, and even for the top practitioners, it is a hit or miss affair where you don’t know whether it will work until the end. No mature tools exist to ensure models train successfully, or to ensure that the original set up is done appropriately for the data.