Among all of the possible chemical compounds, it’s estimated that between 1020 and 1060 may hold potential as small-molecule drugs.
Evaluating each of those compounds experimentally would be far too time-consuming for chemists. So, in recent years, MIT Associate Professor Connor Coley PhD ’19 has been using artificial intelligence to help identify compounds that could make good drug candidates. https://t.co/KqUI5WSzP7
Games people — and machines — play 🎲
LIDS PI @gabrfarina combines concepts from game theory with such tools as machine learning, optimization, and statistics to advance theoretical and algorithmic foundations for decision-making.
Read a profile: https://t.co/WlWtXukzRH
MIT and IBM will expand our collaboration: The MIT-IBM Computing Research Lab will seek to leverage hybrid quantum and classical computing, with advanced algorithms and AI, to solve challenging problems in fundamentally new ways. https://t.co/2tIKRrAETY
Before autonomous vehicles scale, the science behind them needs an upgrade. Researchers from @MITLIDS, @MIT_CEE, @MITdusp, and collaborators find mobility-on-demand studies often lack transparency and reproducibility—key for real-world decisions.
More: https://t.co/rLZOSNo2QF
Researchers at @MIT_CSAIL developed an intelligent system for balancing the tasks of storage devices inside a data center, which can extend the longevity of storage hardware and help a data center operate more efficiently.
https://t.co/WDg2VgRa6y
Evaluating the ethics of autonomous systems
A new framework from @MITLIDS, @MITAeroAstro & @Saab––SEED-SET—can pinpoint when #AI decision-support systems make unfair recommendations in complex settings like power grids.
More: https://t.co/M1InMGOEF0
For the 3rd year, Expanding Horizons in Computing brought together MIT faculty and guests to explore key questions in computing & AI — from human intelligence to coding to the future of education.
Recordings from the workshops are now available to watch🎥 https://t.co/RWm7MprXTE
April 30: The MIT Ethics of Computing Research Symposium will feature MIT faculty presentations, a keynote by Jon Kleinberg (Cornell), and panels on AI alignment and the future of education with participants from OpenAI and Google DeepMind.
Register: https://t.co/wFlKtu9KRV
Call for applications: Join us this summer for a weeklong workshop to gain hands-on experience in modern concepts of AI, their applications to modeling, and strategies for classroom implementation. Open to faculty at institutions nationwide.
Learn more: https://t.co/Q2iMjk22zX
Smarter traffic control for warehouse robots 🤖
@MITLIDS + Symbotic researchers developed an #AI system that learns how congestion forms and decides which robots should go first—rerouting them in advance to avoid bottlenecks. More: https://t.co/N0XGmovnAi
Spotting overconfident #LLMs
New work from LIDS Kimia Hamidieh, Marzyeh Ghassemi, and collaborators introduces a more reliable uncertainty metric to flag when models are confident but wrong. This could help users better judge when to trust #AI outputs. https://t.co/LyYtvwvBp2
🧬 AI for a fuller picture of the cell
A new #AI framework identifies which cellular signals are unique to a measurement method — and which are shared across modalities. The approach helps researchers better understand cell states and disease mechanisms. https://t.co/ih2wPH8gbu
Reducing emissions — and parking frustration 🚗♻️
MIT LIDS researchers developed a parking-aware navigation system that guides drivers to lots balancing proximity + availability. The result? Up to 35 minutes saved and more accurate travel time estimates. https://t.co/XGiOrTMWi7
Can personalization make LLMs too agreeable?
Research from @MITLIDS Shomik Jain, Charlotte Park, and PI Ashia Wilson finds that long-term conversations can cause LLMs to mirror users’ views — potentially reducing accuracy & reinforcing echo chambers.
More: https://t.co/fC5KddycxR
MIT research finds platforms ranking the latest #LLMs can be surprisingly fragile — removing just a handful of crowdsourced votes can flip which model tops the leaderboard. The work underscores a need for more rigorous strategies to evaluate model rankings https://t.co/hYLhrUuTKm
Brian Hedden PhD ’12, @MITphilosophy professor holding an MIT Schwarzman College of Computing shared position with @MITEECS, has been appointed co-associate dean of the Social and Ethical Responsibilities of Computing (SERC).
https://t.co/EVDo8vPpFw
Where the ocean and atmosphere communicate 🌊🌬️
In a recent profile, LIDS PI @abigailbodner explores how ocean turbulence shapes climate patterns—and how math, Earth science, and AI come together in her research. Read the profile in MIT Spectrum: https://t.co/8Cqz6ZPcRu
A new MIT interdisciplinary course, 6.S044/24.S00 (AI and Rationality), asks what it really means for an AI to be “rational.” Blending computer science and philosophy, students explore rational agency, decision-making, and how we define intelligence. https://t.co/rPdohlJ89R
A new cross-disciplinary course, 6.S044/24.S00 (AI and Rationality), challenges students to explore an artificial system's potential to be rational. Watch senior Amanda Paredes Rioboo discuss the course. @MITEECS@MIT_SCC@MITphilosophy