Showing 65–80 of 88 items from the last 14 days
AI inference generates substantial hidden data storage costs that executives frequently overlook when budgeting for AI systems, as back-end data from billions of daily prompts, images, and videos requires persistent storage beyond initial model execution. Storage infrastructure represents a material and often-underestimated component of total AI cost of ownership.
Read original →Neural networks may be much easier to read than researchers assumed, with about 90 percent of neurons serving a clear function. That would be big news for AI safety research, since deception or dangerous behavior could be spotted directly in a model's circuits. Researchers are still debating whether the thesis holds up. The article Is AI interpretability close to a breakthrough? A new essay has researchers divided appeared first on The Decoder.
Read original →OpenAI is launching the Rosalind Academic Plan, a free offering that's currently open only to research labs at US universities without an enterprise contract. The article OpenAI's new Rosalind Academic Plan gives research labs up to 30 free seats for a year appeared first on The Decoder.
Read original →Anthropic has given a team from the nonprofit METR inside access to review its AI models and safety practices, the company announced. The article Anthropic gives METR inside access to audit its AI models and safety practices appeared first on The Decoder.
Read original →MIT's Center for Transportation and Logistics finds sustainability commitments are strong, but governance gaps and external disruptions prevent execution.
Read original →A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Read original →Meta launched Muse Spark Open, an 816-billion-parameter open-weight AI model that processes text, images, video, and audio with up to 1 million tokens of context, matching performance with Chinese models like Qwen and GLM. This competitive open-source model optimized for local Apple M5 Ultra deployment intensifies the race among tech giants to offer frontier-capable models outside proprietary ecosystems.
Read original →Google's Gemini 4 Argon scores 87 percent on its proprietary ERQA robotics benchmark and controls robots while generating simulations from visual inputs, though published demos indicate heavy dependence on human guidance. This specialized multimodal model positions Google to consolidate robot control and training across enterprise deployment, but execution quality remains unproven at scale.
Read original →With Nemotron 3.5 Super VL, Nvidia is releasing an open multimodal model with 120 billion parameters for enterprise agents. Two compact Bolt models bring agents to local machines. Dozens of organizations are already fine-tuning Super VL, but getting the most out of it means buying Nvidia hardware. The article Nvidia's Nemotron 3.5 Super VL is an open model built to run enterprise AI agents nonstop appeared first on The Decoder.
Read original →Bank of America has hired 1,000 outside contractors to fix software vulnerabilities uncovered by AI models like Anthropic's Mythos, CNBC reports. The article Bank of America puts 4,000 people on fixing vulnerabilities uncovered by Anthropic's Mythos and other AI models appeared first on The Decoder.
Read original →On the TheoPhysEval benchmark, GPT-6-Astra solves 49 of 50 unpublished theoretical physics calculations as accurately as leading specialists. In some cases where the agent seemed to fail, the experts' own reference solutions turned out to contain errors. But the researchers say physics hasn't had a breakthrough like the ones in mathematics, because the agents lack "taste." They still think autonomous, top-level AI research could arrive soon. They already see consequences for how young physicists are trained and for equal opportunity in the field. The article GPT-6-Astra solves 49 of 50 physics research problems at $2.40 apiece appeared first on The Decoder.
Read original →Nvidia released Nemotron 3.5 Super VL, advancing open-weight AI capabilities in the United States. This reinforces US competitiveness in AI model development outside proprietary closed ecosystems.
Read original →Google launched Universal Cart, a price-tracking tool for desired items, plus three additional features. This represents incremental consumer AI utility in e-commerce and retail shopping workflows.
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