Escaping the "dark ages" of AI infrastructure
Practical AI: Machine Learning, Data Science
English - December 16, 2019 17:45 - 50 minutes - 68.8 MB - ★★★★★ - 37 ratingsTechnology Education How To changelog machine learning deep learning artificial intelligence neural networks computer vision Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Evan Sparks, from Determined AI, helps us understand why many are still stuck in the “dark ages” of AI infrastructure. He then discusses how we can build better systems by leveraging things like fault tolerant training and AutoML. Finally, Evan explains his optimistic outlook on AI’s economic and environmental health impact.
Evan Sparks, from Determined AI, helps us understand why many are still stuck in the “dark ages” of AI infrastructure. He then discusses how we can build better systems by leveraging things like fault tolerant training and AutoML. Finally, Evan explains his optimistic outlook on AI’s economic and environmental health impact.
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Featuring:
Evan Sparks – Twitter, GitHub, WebsiteChris Benson – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, Website
Show Notes:
Determined AI
Previous episode on Alpha pilot
Blog post - AI Leadership And The Positive Impacts On Economy, Privacy, Environmental Health
Blog post - Announcing the future of AI infrastructure
Apache Spark
MLlib
Antique Candle Co.
Joel Grus on AI code that facilitates good science
Something missing or broken? PRs welcome!