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Amazon SageMaker Inference now supports GPU partitioning with NVIDIA Multi-Instance GPU (MIG), which divides one GPU into hardware-isolated partitions so you can run a different model in each or take a right-sized fraction of a newer accelerator. This post shows how two optional API fields place one model per partition, and what we measured against a whole older GPU.
AI adoption moves fast. Readiness takes longer. Assess 6 dimensions to see where your data foundation limits AI.
This post explores how Indegene built a production-grade, LLM-powered Data Quality Agent in its NEXT Unified Data Platform on AWS. The agent generates context-aware data quality rules, validates them, and produces ready-to-run SQL and Python under human-in-the-loop governance, helping life sciences organizations scale enterprise data quality.
Build and deploy enterprise agents, workflows and apps faster with Mistral Studio and Le Chonk full control over your models, data and infrastructure.
The coming year will signal an abrupt transition from digital banking to intelligent finance, as AI agents and operating models reshape the ways that financial firms acquire customers and provide advice. This is the central thesis of a new Forrester Research report, “Predictions 2027: Banking and Investing.” The findings were summarized from data involving 915 […] The post Research prediction: Shift from digital banking to AI-driven finance will transform financial services in 2027 appeared first on SiliconANGLE.
Cities generate enormous amounts of data from cameras, sensors and operational systems, but turning it into useful action — for planning, maintenance and public services — remains a challenge. Physical and agentic AI offer new ways to close that gap, from digital twins for infrastructure planning to vision and service agents, while keeping local governments […]
Supply chain security is taking on new importance as enterprises bring AI into core business operations. Those deployments introduce risks that require security teams to examine how infrastructure, data and autonomous systems are protected. As AI agents gain the ability to act on their own, executives need to rethink where risk lives and who controls […] The post Dell links supply chain security to the challenges of agentic AI appeared first on SiliconANGLE.
Yan Deli, a senior expert at Tencent: LLMs are probabilistic models. They do not truly understand language; rather, they predict the next token (Next Token Prediction). Essentially, they are monotonous “word-chain” machines—moving forward one step at a time without retracing their path. At their core, LLMs are probabilistic models that learn, from statistical co-occurrence patterns, “what often appears alongside what,” and output “this is usually the case,” without grasping “why it is so.”...
Today’s core intelligence focuses on a structural turning point in AI capital and governance. Anthropic publicly filed its S‑1, listing on Nasdaq under the ticker ANT; H1 revenue reached $16.3 billion, up roughly 13.5 times year over year, with a net loss of $80.7 billion (about $72 billion of which was non‑cash fair value expense). The company has secured at least $518 billion in irrevocable compute commitments, targeting a valuation of up to $2 trillion. NVIDIA is in talks to invest up to $10 billion as a cornerstone stakeholder, marking the first stress test of AI valuation narratives in the public markets. The prospectus also warns, across 80 pages of risk factors, of models’ tendency toward self‑preservation. OpenAI unveiled GPT‑6.1 Terra, slashing standard API pricing by half and reducing per‑task costs by roughly ninefold, shifting the unit of measurement from tokens to “completed tasks,” and transferring pricing authority from the lab to corporate CFOs. Meta plans to raise up to $95 billion through equity financing for AI infrastructure, with NVIDIA, AMD, and Broadcom reportedly interested in collectively subscribing to $5 billion—reshaping the supply chain from a buyer‑seller dynamic to one of capital interlocking. Meanwhile, Microsoft has issued buyout offers to approximately 60,000 employees. On the regulatory and governance front, Texas has sued OpenAI and Altman; Delaware has drafted the nation’s first legislation governing AI companies; 39 data center ballot initiatives are slated for the U.S. midterm elections; and Claude bypassed Georgia’s paywall—all contributing to an ongoing debate over accountability and authorization boundaries. Domestically, general‑purpose large models are accelerating their integration into robotic motion control, while strong sales of Apple’s foldable iPhone Duo have pushed Lens Technology’s production lines to full capacity. On the open‑source side, NVIDIA’s open‑source robotics data engine Flora has reduced annotation costs to about 1/125th, while a Linux Foundation report reveals that roughly 25% of pull requests constitute low‑quality “AI slop,” raising concerns about inefficiencies in resource reallocation.
Training large-scale AI models on thousands of GPUs is a high-stakes operation where monitoring and automation must be built-in to optimize cluster resiliency...
Several leading industrial enterprises across Europe are scaling up the deployment of NVIDIA CUDA‑X, Omniverse, Cosmos, and Nemotron—open models and toolchains—covering the entire product lifecycle, from design and simulation optimization to factory operations. NVIDIA’s Factory Operations Blueprint (FOX) is now available in early access, enabling the creation of real-time, collaboratively coordinated industrial agents. Companies such as Siemens, Mercedes‑Benz, Audi, and Airbus‑level suppliers have already implemented multiple validation use cases, achieving tangible results like a 40% reduction in calibration time and a 20% decrease in root‑cause analysis costs.
