As governments pursue competing approaches to AI regulation and infrastructure development, data center operators face growing pressure to document security controls, verify workload...
/PRNewswire/ -- Asuri today announced the launch of its multi-agent enterprise AI platform, designed to help businesses move beyond copilots and deploy...
MOUNTAIN VIEW, Ca., October 21, 2026--Bloomreach, the AI company for personalized customer engagement, today announced that brands, technology partners, and agencies around the world have already built more than 200 agents using Loomi Connect, the integration foundation for its Loomi intelligence layer. Loomi comprises multiple models, including purpose-built, adaptive models that learn from each business’s unique data, orchestrated together to drive revenue. Loomi Connect gives businesses a str
Optical chiplets for AI data centers gained Japan government backing as NEDO selected an NTT-led consortium to develop silicon photonics mass-production infrastructure. The project targets production samples in 2028 and requires a tenfold manufacturing productivity gain to become commercially
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…
Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may contain sensitive temporal information. Diffusion models trained with differentially private stochastic gradient descent…
Multilingual scene text recognition (STR) remains challenging due to the scarcity of training data for most languages and the difficulty of serving diverse scripts within a single model. Existing solutions either deploy one recognizer per language, inflating cost and…
Medical image interpretation is central to diagnosis and care, yet adapting general-purpose multimodal large language models (MLLMs) often requires resource-intensive domain-specific fine-tuning. Here we introduce representation-guided in-context learning (RG-ICL), a…