Read the lost thesis of Dennis Ritchie, creator of the C programming language & co-creator of Unix: https://
bit.ly/RitchiePhD Ritchie never got his PhD b/c he didn't want to pay Harvard the thesis binding fee. (v/
@IEEESpectrum
)
@mit_csail
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Dennis Ritchie’s Lost PhD Thesis Now Available Online
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MIT CSAIL Harvard AI Accelerates Electron Microscope Imaging Tenfold
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A decade of imaging.
— MIT CSAIL (@MIT_CSAIL) 16 avril 2026
Compressed into three months.
Here’s how MIT CSAIL & Harvard taught an electron microscope to see like you do: https://t.co/qC3zVck0HF pic.twitter.com/kMTptacRMDA decade of imaging. Compressed into three months. Here’s how MIT CSAIL & Harvard taught an electron microscope to see like you do: https://
bit.ly/4tfPxBX -
Dinner with any computer scientist: who would you choose?
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If you could have dinner w/any computer scientist, past or present, who would it be?
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Fukushima’s Neocognitron: The Neural Network Inspiring Modern CNNs
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#otd in 1980 a Japanese computer scientist published a paper proposing the “Neocognitron,” the neural net that directly inspired CNNs: https://t.co/v7TCOMPN6x
— MIT CSAIL (@MIT_CSAIL) 11 avril 2026
Kunihiko Fukushima’s paper explained back in 1986: https://t.co/vaIJlc5GdV pic.twitter.com/SgyWzAorUX#otd in 1980 a Japanese computer scientist published a paper proposing the “Neocognitron,” the neural net that directly inspired CNNs: https://
bit.ly/3dPbF0z Kunihiko Fukushima’s paper explained back in 1986: https://
bit.ly/42iMxZo -
Interactive Exhibit Demonstrates How Computer Processors Perform Math
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An interactive exhibit showing how a computer processor does math, v/@ProofofMaro. pic.twitter.com/76nODGrwcm
— MIT CSAIL (@MIT_CSAIL) 10 avril 2026An interactive exhibit showing how a computer processor does math, v/
@ProofofMaro
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MIT Researchers Cut AI Model Training Costs With CompreSSM
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Training a large AI model is expensive, but MIT CSAIL researchers have helped develop a new approach that cuts compute costs. Using control theory, "CompreSSM" compresses models during training, shedding complexity. It makes models leaner & faster: https://
bit.ly/4sU2Sjc -
Git Celebrates 21st Birthday with Creative Poem
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In honor of Git's 21st birthday, a poem written in Git: https://
shorturl.at/fp80F -
OSGym: Scalable Infrastructure for Computer Use AI Agents
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How do you train AI agents that can use computers like humans? Introducing OSGym: Scalable OS Infrastructure for Computer Use Agents. It’s large-scale training made possible by extensive infra optimization: • 1024 OS sandboxes running in parallel • $0.23 / sandbox / day (90% cost down) • 1420 trajectories per minute • 37× faster disk provisioning • 88% less physical disk usage • RAM-bound orchestration (10× scalable than CPU-bound) 🧵
→ View original post on X — @mit_csail, 2026-04-06 16:22 UTC
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OSGym: Infrastructure for Training Computer Use Agents
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So why did the researchers develop OSGym? Training computer use agents is both a modeling problem & an infrastructure challenge: • Each task needs a full OS (GUI, apps, browser, etc.) • Scaling → massive CPU/RAM/disk costs • Random crashes from real software environments • Thousands of parallel runs required It's a key bottleneck, though it's not often discussed. [Translated from EN to English]
→ View original post on X — @mit_csail, 2026-04-06 15:25 UTC
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MIT CSAIL Introduces OSGym for Training Computer Agents
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How do you train AI agents that can use computers like humans? 🧵 MIT CSAIL researchers introduce "OSGym": scalable OS infrastructure to improve the capabilities of computer use agents. It introduces large-scale training made possible by extensive infrastructure optimization: bit.ly/47JprPd [Translated from EN to English]
→ View original post on X — @mit_csail, 2026-04-06 15:25 UTC