Pretty pictures are cool. But raw, scalable intelligence is on its way.
MACHINE LEARNING
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Beyond GPT-3: Next Wave of Superhuman AI Systems
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In a couple of years, we’re going to look back at GPT-3 as a fun toy… The coming waves of AI systems will be smarter than humans in many ways. A different kind of intelligence. It’ll feel alien, yet familiar. And more generally capable than any single person alive today.
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Hyperparameter Optimization Techniques and Practical Implementation Guide
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Check out @subirmansukhani
’s technical blog on how to perform hyperparameter optimization. Then try the free accompanying Domino project yourself. https://
domino.buzz/3h6XxFq -
Artificial Intelligence Reshaping How We Shop Online
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Artificial Intelligence Is Reshaping How We Shop https://
gearpatrol.com/style/a4184371
0/artificial-intelligence-shopping/
… @evanmalachosky @gearpatrol #AI #MachineLearning #DataScience #Robots #BigData #Analytics #100DaysofCode #IoT #serverless #womenwhocode #Python #DigitalTransformation #TensorFlow #DeepLearning #ecommerce -
GPU-Accelerated ML for Scalable Hybrid Cloud AI
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Coming up: Need to use GPUs to accelerate ML? If you're at the AI Summit in Austin, check out Kjell Carlsson's talk TODAY, Nov. 2 from 3:05 – 3:30 CT, “Enabling a Scalable, Future-proof AI Ecosystem Across the Hybrid Cloud Enterprise." #MLOps #IoTWorld
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GPT-3 Requires Chain-of-Thought for Problem Solving, Paper Analysis
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Regardless how a human would do it, GPT-3 needs chain-of-thought to perform on these problems. Only skimmed the paper, but I don't see a specific deficit in ToM vs. known inability to do multi-hop inference without CoT.
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Unlocking AI’s Full Potential for Human Intelligence
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We're Not Using AI to Its Fullest Human Potential https://
time.com/6227118/eric-s
chmidt-ai-human-intelligence/
… @TIME #AI #MachineLearning #DataScience #BigData #Analytics #100DaysofCode #IoT #serverless #womenwhocode #DigitalTransformation #Robots #Python #TensorFlow #DeepLearning -
Adaptive Optimizers Should Track True Squared Gradients
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Adaptive optimizers like Adam track the square of the gradient, but what they receive as the gradient is actually the sum of the gradients across the batch. It seems likely that better results at different hyper parameters could be obtained if backward passes emitted true grad^2.
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Detecting Non-Gaussian Distributions in Machine Learning Models
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The easiest way to see this is to fix the mean to be 0 and then observe that the returned value will never be negative. Thus it can't be Gaussian. Definitely not easy to spot.
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Neural Operators and AI for Science Talk at MIT IAIFI
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It was great visiting @mit @iaifi_news and give a talk about neural operators and AI for science. You can find my talk here https://
youtu.be/RR5-mYQOb7E?t=
1208
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