We are honored to be included for the 2nd consecutive year among the top 200 premier North American technology companies, as rated by Deloitte's #Fast500 list. We're ever grateful to our amazing customers, without whom this wouldn’t be possible: https://
domino.buzz/3Ap2Ma3 #MLOps
MACHINE LEARNING
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Domino Named Top 200 North American Tech Company Again
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NFL Knowledge Gap, ML Speed, and Accuracy-Explainability Trade-offs
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Also:
1. The speaker in your paper doesn't know the NFL.
2. We can do even weak-knowledge ML a lot faster than evolution.
3. There's very often a tradeoff between accuracy and transparency/explainability, and often accuracy is more important. -
Tabula-Rasa Model Oxymoron: NFL Theorem and Fundamental Assumptions
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"Tabula-rasa model" is an oxymoron, by the NFL theorem. The question is what are the fundamental assumptions that need to be built in. Causality is a candidate. The laws of physics are another.
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Climate Models Replaced by Superior Alternative Method
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Who needs climate models now? This does the job much better.
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Learning Actions from Data Rather Than Building Them In
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We don't need to build it in, because it's very easy to learn from data (cf. infants). And we arguably shouldn't, because what your actions are can change (e.g., moving your hands vs. driving your car).
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Expert Choice: Novel Mixture-of-Experts Routing Algorithm
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Introducing a novel mixture-of-experts routing algorithm, called Expert Choice, that can achieve optimal load balancing between experts while allowing heterogeneous token-to-expert mapping. Learn how it’s done at https://
goo.gle/3OdpO9t -
Groq Compiler: Fast ML/AI Model Compilation Without Kernel Libraries
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We run 100's of #ML/#AI models on Groq #Compiler, with no need for kernel libraries. We can tune your workload, with #software tools like GroqFlow and Groq #API. See for yourself–come by booth 3047 at @Supercomputing
, bring your model, and let's talk time-to-compile! #SC22 #HPC -
AI Cloud Platform Converts Live Sports Action into Social Media Highlights
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This week on The #AI Podcast, Amos Berkovich covers how the @WSC_Sports AI cloud platform uses #deeplearning to turn in-game action into social media-ready highlights in real time. https://
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Brain-inspired computational models enhancing machine learning algorithms
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Brain-inspired = how computational models of brains can inspire "better" machine learning algorithms. See here for more context: https://
youtu.be/IlliqYiRhMU -
Ramin Hasani on Liquid Neural Nets and Sequence Modeling
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Hi there! It’s Ramin Hasani @raminmh
! Over the next 24H, I’m taking over @MIT_CSAIL
’s Twitter! I’m a research affiliate at CSAIL. I design brain-inspired robust deep learning algorithms! Ask me anything about sequence modeling, time series, robots, & liquid neural nets, here