/PRNewswire/ -- As Formula 1 returns to Austin's Circuit of the Americas for this weekend's United States Grand Prix, IBM (NYSE: IBM) and Scuderia Ferrari HP...
Open-source evidence infrastructure, Terms Packs and Countersign help people and businesses establish what agents did and whether the work met expectations.
Lenders can now automate doc intake, spreading, and credit memo drafting within their existing workflows, while keeping final decision-making with bankers.
Regulators hold you accountable for AI agents but don’t say what skills you need. Elliptic’s free AI agent governance course teaches them in 90 minutes.
DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks. Alongside these gains, the model reduces task execution time and output length, enabling users to complete…
DeepSeek has reportedly raised $15 billion in one of China's largest funding rounds, just days after the US ordered federal agencies to remove its technology over national security concerns.
Frontier language models now produce professional deliverables that expert graders judge to match human work on a substantial share of economically valuable tasks, yet most enterprise GenAI initiatives fail to show a measurable business effect and a large fraction of agentic…
Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized data scenario, this task is commonly solved using deep clustering methods that utilize deep neural network architectures to…
Blind and low-vision users often face challenges when locating and physically acquiring objects in unfamiliar indoor environments. Existing vision-language-model-based assistants can provide semantic descriptions but may introduce latency, hallucinations, and guidance that is…
Speculative decoding accelerates LLM inference by drafting multiple tokens in parallel, with tree-based methods further improving efficiency through hierarchical structures. Dynamic-tree methods such as EAGLE-3 perform well under greedy decoding via deterministic top-K…