Easily our favorite Met Gala outfit
@mit_csail
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Free Machine Learning & AI Resources for X Subscribers
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The top 10 programming languages on GitHub over the past 2+ years. Notably, TypeScript has leaped to the top spot. v/
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Google Releases Free Prompt Engineering Guide
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A free guide to prompt engineering from Google: https://
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MIT PhD Student Calls AI Models Mismanaged Geniuses With Broader Potential
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MIT PhD student Alex Zhang (@a1zhang) explains how AI models are "mismanaged geniuses" that could take on a much wider range of tasks.
— MIT CSAIL (@MIT_CSAIL) 30 avril 2026
Full video: https://t.co/8L9lVGtzF1 pic.twitter.com/G38iDOgS1DMIT PhD student Alex Zhang (
@a1zhang
) explains how AI models are "mismanaged geniuses" that could take on a much wider range of tasks. Full video: https://
tinyurl.com/bddd5vdx -
Highest Paid Workers More Likely to Use AI
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Highest paid workers are more likely to use AI for work, according to Financial Times breakdown: https://
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Fast Fourier Transform: Classic MIT Algorithm Breakdown
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61 years ago this month, the Fast Fourier Transform was created, a powerful tool for image compression & data analysis.
— MIT CSAIL (@MIT_CSAIL) 26 avril 2026
Watch a classic MIT breakdown of FFT, perhaps the most-taught algorithm at the Institute: https://t.co/R7zdspBswx
v/@MITOCW pic.twitter.com/lVabrS3syd61 years ago this month, the Fast Fourier Transform was created, a powerful tool for image compression & data analysis. Watch a classic MIT breakdown of FFT, perhaps the most-taught algorithm at the Institute: https://
bit.ly/4cNMbPm v/
@MITOCW -
AI Predictions: The Stata Center in Year 2500
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What does AI think the Stata Center will look like in the year 2500? ChatGPT, Meta AI, & Grok chimed in.
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MIT Improves Reasoning Model Confidence Calibration Through RL Training
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How do top reasoning models become overconfident? MIT found that RL rewards correct answers w/o considering how sure the model is. By training them to estimate their confidence about each answer, the team boosted uncertainty estimates w/o hurting accuracy:
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Recursive Language Models: Expert Q&A with MIT PhD Student
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Ask us your questions about Recursive Language Models (RLMs) & where LMs are underutilized or inefficient. We’ll pick some to feature in an upcoming explainer w/MIT PhD student Alex Zhang (
@a1zhang
), who recently developed RLMs. For more on his work: https://
bit.ly/4vGyLxo -
MIT CSAIL explores efficient models for complex reasoning at ICLR
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This sampling of MIT CSAIL papers at ICLR shows a common need for efficient models that can reason about complex, real-world problems. More compute helps, but the ways these machines "think" also need refinement. You can find more info about these projects on our website: