The AI Economy Institute (AIEI) launched its third cohort of researchers to study artificial intelligence's impact on work, jobs, and productivity. The 23-member cohort from global institutions will a…
AI-designed apps often share three telltale signs: boring, cookie-cutter design; polished but dysfunctional interfaces; and poor handling of edge cases. Experts warn these issues can become major prob…
Organizers of the NeurIPS 2026 conference added hidden prompts to papers to catch peer reviewers using generative AI, sparking backlash from researchers who say the tactic erodes trust. The conference…
AI search summaries are reducing publisher traffic by nearly 40%, threatening the economic model of the open web, according to new research from Harvard Business School, the Indian School of Business,…
AI democratization, while beneficial, creates a disconnect between deep understanding and widespread use, mirroring the pattern seen in past technologies like electricity and speech recognition. The a…
Apple has raised prices across its product lineup, including the MacBook Pro, iPad Air, and HomePod Mini, citing increased costs driven by the AI industry's demand for memory chips. The company blames…
Researchers at UC Berkeley, Carnegie Mellon University, and Tel Aviv University developed ConlangCrafter, an AI model that generates novel constructed languages with consistent rules. The model can cr…
A new book, 'Modern GPU Programming For MLSys', teaches GPU kernel optimization for machine learning systems, focusing on Blackwell architecture and techniques like GEMM and FlashAttention. Developed …
AI-generated code is flooding GitHub and degrading codebases, with research showing AI-written code has 1.7 times more critical issues and 45% ships with OWASP Top 10 vulnerabilities. Major projects l…
Top AI developers are shifting focus from chatbots to 'world models' that teach AI systems to understand and navigate physical environments, aiming to create more intelligent and embodied AI. Research…
Prefill/decode disaggregation separates the two phases of LLM inference—prefill (compute-bound) and decode (memory-bound)—onto different GPUs to avoid the performance compromise of running both on the…
As AI systems begin to automate mathematical proofs, mathematicians reflect on the value of the slow, deliberative process of discovery. Researchers like Jeremy Avigad and Krystal Maughan emphasize th…
GitHub has 630 million repositories, with nearly half of all new code written by AI, but developer trust in AI code dropped from 77% to 60%. Carnegie Mellon University found 6 million fake stars, and …
Computer scientist Louis Castricato left his PhD at Brown University to found Overworld, a startup building AI 'world models' that understand physical environments, as a growing number of researchers …
Skild AI, a startup founded in 2023, has raised a $1.4 billion Series C led by SoftBank to develop a general-purpose AI brain for any robot, aiming to overcome the fragmentation in robotics AI. The co…
The carbon footprint of AI is projected to grow at a CAGR of nearly 44% through 2025, with computational costs doubling every few months. Training a single large NLP model can emit as much carbon as f…
Continuous batching, introduced in the 2022 Orca paper, improves GPU utilization during LLM inference by dynamically updating the batch at each iteration, freeing slots as requests finish and immediat…
Nvidia's GEAR lab, in collaboration with Carnegie Mellon University and UC Berkeley, developed the ENPIRE framework that enables AI coding agents to autonomously train fleets of physical robots on pre…
NVIDIA GEAR lab researchers developed ENPIRE, an agent harness framework that enables AI coding agents to autonomously train robots to perform tasks like cutting zip-ties and installing GPUs. The syst…
Nvidia, Carnegie Mellon University, and UC Berkeley researchers developed ENPIRE, a system where AI coding agents autonomously train robots in dexterous grasping tasks. Using a fleet of eight robots t…