Enabling #Privacy-preserving #AI training on everyday devices
by @aczewe @MIT Learn more: https://
bit.ly/4t7fenp #CyberSecurity #Infosec #ArtificialIntelligence #ML #MachineLearning #Tech
MACHINE LEARNING
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MIT Enables Privacy-Preserving AI Training on Everyday Devices
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MIT Self-Folding Origami Robot Crawls Climbs and Swims
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MIT’s Self-Folding Origami #Robot Transforms from Flat Sheet to Crawling, Climbing, Swimming Machine
— Ronald van Loon (@Ronald_vanLoon) 4 mai 2026
by @tweetciiiim#Robotics #MachineLearning #ArtificialIntelligence #ML pic.twitter.com/oUtAlj9qxNMIT’s Self-Folding Origami #Robot Transforms from Flat Sheet to Crawling, Climbing, Swimming Machine
by @tweetciiiim #Robotics #MachineLearning #ArtificialIntelligence #ML -
Remembering When ML Was a Minority AI Subfield
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Like you, I am old enough to remember when ML was a minority subfield of AI, and most people did not believe that sgd on perceptrons is universal
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Tandem Architecture Boosts Speech AI with Async Knowledge Injection
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Two Heads Are Better Than One: Async Knowledge Injection for Speech AI with Tandem Architecture Technical Blog: https://
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Representation Fréchet Loss Enables Direct FID Optimization for Visual Generation
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“Representation Fréchet Loss for Visual Generation” FID has always been generative modeling's scoreboard, where everyone optimizes toward it indirectly, but almost nobody trains on it directly. However, this paper shows that you actually can. They achieved this by estimating
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Building AI Agents With Persistent Memory and Continuous Learning
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This Lex Fridman podcast montage is pure fire
— Terence Leung (@TerenceLeungSF) 3 mai 2026
Sam Altman: “Your whole life should fit in one context window.”
Memory isn’t a feature of an agent.⁰
It is the agent. No more stateless resets. Building agents that actually remember, learn, and evolve.@mvollmer1 @Nicochan33 pic.twitter.com/joTjjwrLmWThis Lex Fridman podcast montage is pure fire Sam Altman: “Your whole life should fit in one context window.”
Memory isn’t a feature of an agent.
It is the agent. No more stateless resets. Building agents that actually remember, learn, and evolve. @mvollmer1 @Nicochan33 -
Artificial Analysis Index Limitations for AI Model Benchmarking
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The artificial analysis index is a normalized score of several benchmarks (and has changed over time) it is fine for roughly comparing models, it is not useful for trend analysis and it is unclear what individual point differences in the scores mean.
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Sakana Fugu: Multi-Agent Orchestration System as Foundation Model
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Sakana Fugu: A Multi-Agent Orchestration System as a Foundation Model
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Using Synthetic Data to Simulate Workforce Evolution Safely
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Use Synthetic #Data to Simulate Workforce Evolution Without Exposing Employee Data by @antgrasso #DataScience #BigData
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Shared Experts Reduce Redundancy in Mixture-of-Experts Models
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It can learn shared patterns so that the individual experts don’t have to relearn the same info; ie it’s to reduce redundancy among the non-shared experts