Computer science and technology
Computer science and technology

Parking-aware navigation system could prevent frustration and emissions

By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.

Personalization features can make LLMs more agreeable

The context of long-term conversations can cause an LLM to begin mirroring the user’s viewpoints, possibly reducing accuracy or creating a virtual echo-chamber.

Study: Platforms that rank the latest LLMs can be unreliable

Removing just a tiny fraction of the crowdsourced data that informs online ranking platforms can significantly change the results.

Helping AI agents search to get the best results out of large language models

EnCompass executes AI agent programs by backtracking and making multiple attempts, finding the best set of outputs generated by an LLM. It could help coders work with AI agents more efficiently.

Brian Hedden named co-associate dean of Social and Ethical Responsibilities of Computing

He joins Nikos Trichakis in guiding the cross-cutting initiative of the MIT Schwarzman College of Computing.

Antonio Torralba, three MIT alumni named 2025 ACM fellows

Torralba’s research focuses on computer vision, machine learning, and human visual perception.

3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs

Professor James Collins discusses how collaboration has been central to his research into combining computational predictions with new experimental platforms.

How generative AI can help scientists synthesize complex materials

MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.

The philosophical puzzle of rational artificial intelligence

As AI technology advances, a new interdisciplinary course seeks to equip students with foundational critical thinking skills in computing.

Why it’s critical to move beyond overly aggregated machine-learning metrics

New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.