Browsing: AI News & Trends

Generative AI has expanded beyond coding assistants and content creation tools, finding its way into legal research and case preparation. While the technology has helped legal professionals quickly generate documents and explore potential legal strategies within minutes, AI adoption has fueled the rise of vibe lawyering where individuals use AI to complete legal tasks with minimal independent verification. With recent incidents involving fabricated case citations, the dangers of relying on AI instead of legal expertise are calling into question the integrity of the practice.From Vibe Coding to Legal PracticeThe success of vibe coding has encouraged professionals to explore whether a…

More than 1,100 employees of the world’s leading AI labs have signed a public statement asking Washington to help build the tools needed to deliberately slow frontier AI development, and within hours OpenAI and Anthropic each endorsed it as companies. The request lands four days before the Trump administration’s own deadline for producing a frontier-model security framework.The statement, published on July 28, 2026 under the title Pacing the Frontier, turns on one sentence: “We request that the U.S. government support an international effort to develop the technical and governance tools needed to deliberately pace the frontier of automated AI development.”…

Hugging Face has published a technical timeline of the July 2026 intrusion that OpenAI’s evaluation models ran against its production infrastructure, and it puts a third company in the attack path. Before the agent reached Hugging Face, it took over a public code-evaluation sandbox running on another provider’s platform and operated the entire campaign from there.The post describes that machine as “an external launchpad for the agent” and identifies it only as infrastructure belonging to a third-party provider. Reuters named it as Modal, the New York serverless-compute company whose sandbox product runs untrusted code for AI labs and coding agents,…

In pursuit of autonomous nuclear plant operationsIt turns out the research for the master’s was just the tip of the iceberg. There was still work left to be done.For the future viability of nuclear power, small plants, located in rural areas, are a distinct possibility. Thus far, operations conducted in legacy plants have involved intensive manual operations, which are viable because these facilities operate at 100 percent capacity and the power delivered can justify the costs of maintaining a large staff. But microreactors distributed at scale and in remote areas can’t afford a large bench of human talent. It’s where…

MIT researchers are set to contribute to the U.S. Department of Energy’s (DOE) Genesis Mission, with 15 collaborative projects among those selected for funding under Genesis Phase I, DOE announced Wednesday.The Genesis Mission, a national initiative, intends to build “the world’s most powerful integrated science discovery platform” by incentivizing cross-sector collaborations that leverage AI, supercomputing, quantum systems, and advanced scientific instruments to accelerate breakthroughs in energy, scientific discovery, and national security.“MIT researchers are proud to be leading and contributing to projects under the Genesis Mission, in vital areas of research that support national priorities,” says Ian A. Waitz, MIT’s vice president for…

Dimitri Bertsekas PhD ’71, the Jerry McAfee (1940) Emeritus Professor in Engineering in the Department of Electrical Engineering and Computer Science (EECS), a principal investigator in the Laboratory for Information and Decision Systems (LIDS), and the Fulton Professor of Computational Decision Making at Arizona State University, died on June 3 at his home in Belmont, Massachusetts. He was 83 years old. Over the course of his career, Bertsekas’ research spanned, and had a definitive influence upon, several fields, including optimization, control, large-scale computation, reinforcement learning, and artificial intelligence. He served as a consultant to various private companies; an editor for several…

Ever since she was a child playing on her family’s farmland in Wisconsin, Bailey Flanigan was guided by her own selective, yet wide-ranging, curiosity. Describing her young self as spirited and a bit unruly, she directed her energies to everything from building booby traps to doing experimental construction projects to exploring an intense interest in medicine to writing fiction and music to planning nonprofit organizations to help lessen social inequality.By high school, Flanigan was intensely drawn to particular subjects.“I found myself unmotivated to take all the AP [advanced placement] classes for the sake of it. My interest was captured by…

Engineers often use vision-language models to produce new designs, such as for airplane or automobile components. To simulate how those components will perform in realistic situations, they’ll use tried-and-true computer-aided design (CAD) software to generate 3D models of those designs, which they can put through virtual crash or durability tests. Researchers from MIT and elsewhere have now developed a system that can teach a vision-language model to automatically convert 2D designs into CAD programs that are much more accurate and functional compared to other approaches, while using only a fraction of the computation.By improving the performance and efficiency of AI-driven CAD…

Millions of people are now designing their own personalized artificial intelligence companions, yet most have little idea how those creations will actually behave. In a new paper, MIT Media Lab Assistant Professor Pat Pataranutaporn and his graduate student researchers Anthony Baez and Sheer Karny introduce “neural transparency,” a tool that lets everyday users glimpse inside an AI’s neural network before their chatbot ever says a word. The work is being presented this week at the ACM Conference on Intelligent User Interfaces. In this interview, Pataranutaporn, who is the Asahi Broadcasting Corporation CD Professor of Media Arts and Sciences, explains what they…

Artificial intelligence has rapidly transformed software engineering. Generative AI and large language models (LLMs) can create huge volumes of code and documentation; machine-learning algorithms can monitor performance and detect security vulnerabilities. But when the task is to conceive, design, and make a complex physical system such as a jet engine, are those AI tools equally transformative?This past semester, the JARVIS Challenge (Jet-engine AI Research and Validation Intensive Sprint) set out to explore whether AI can compress the design-build-test cycle, asking MIT undergraduates to discover whether AI can help them to build faster and better. “The JARVIS challenge showed that AI can…