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NVIDIA has unveiled the Jetson Orin Nano 2, an edge robotics computer aimed at bringing physical AI to drones, robots, and vision systems. The company is positioning the new board as an entry-level option for developers who want generative AI models running directly on a machine instead of inside a data centre. NVIDIA’s argument for […]
NVIDIA Jetson Orin Nano 2 brings physical AI to drones and robots Read More »
Download Infographics Your voice model works beautifully in the demo. Then it meets a real user — someone with a Scottish accent, ordering in Hinglish, from a moving car — and the transcript falls apart. This is the uncomfortable truth of voice AI in 2026: models don’t fail because the architecture is wrong. They fail
Why Multilingual Speech Data Is Critical for Global AI Read More »
Samsung Research America’s Digital Health Team has presented two AI foundation models designed to learn from wearable biosignals. The work centres on data captured by smartwatches, including heart activity, sleep, and physical activity. The company discussed its Connected Care vision at the Health Forum during Galaxy Unpacked in July 2026. Samsung described a future of
Samsung health AI models analyse wearable biosignal data Read More »
Google’s research medical AI system, AMIE (Video), conducted synchronous video consultations with professional patient actors and received clinical evaluator ratings on par with primary care physicians across several core measures. Fifteen trained actors portrayed conditions across cardiopulmonary, abdominal, HEENT, neurological or psychiatric, and musculoskeletal presentations. Google says studies involving real patients and their own health
Google tests AMIE for clinical video consultations Read More »
Meta is releasing Muse Glimmer under an Apache 2.0 licence for local AI agents that can run on a consumer GPU. The company’s Superintelligence Labs has released the 30-billion-parameter model’s weights on Hugging Face. Meta says developers can use it for local coding, function calling, local agents, and LLM-as-a-judge evaluation. The release targets an operational
Meta Muse Glimmer brings local AI agents to consumer GPUs Read More »
Built by Paige and Microsoft, PRISM2 reads whole-slide images through a perceiver-based encoder trained jointly on tissue tiles and clinical dialogue drawn from pathology reports. The model aggregates thousands of tile embeddings per slide into one representation, then generates text that answers diagnostic questions rather than simply classifying pixels. Training data spans 2.3 million whole-slide
PRISM2 model uses clinical dialogue to interpret pathology slides Read More »
OpenAI has outlined how it aligns safety, security, and transparency work with the EU AI Act’s GPAI Code as enforcement approaches. The company has contributed to and endorsed the EU’s General-Purpose AI (GPAI) Code of Practice and the Code of Practice on Transparency of AI-Generated Content. Both emerged from multi-stakeholder processes. The GPAI Code sets
OpenAI aligns safety practices with EU AI Act’s GPAI Code Read More »
Guardoc Health says it processes over one million clinical documents daily using Amazon Nova models through Bedrock. Bringing AI into clinical documentation comes down to a specific kind of risk calculation. Get it wrong and the errors compound into denied Medicare claims under the Patient-Driven Payment Model, audit fines, litigation exposure, and in the worst
Guardoc Health processes clinical documentation using Amazon Nova models Read More »
Google has released Gemini 3.6 Flash and 3.5 Flash-Lite as new workhorses designed to cut latency and token costs for enterprise AI agents. The economics of running autonomous software agents inside a production environment come down to a fixed equation few vendors advertise directly. A model needs to reason through a multi-step task competently, but
Google’s Gemini 3.6 Flash targets enterprise agent token costs Read More »
Ask a humanoid robot to “pick up the red mug on the left and place it in the sink,” and a remarkable amount has to happen at once. The robot must see the mug, parse the instruction, plan a motion, feel the grip pressure, and understand that “the sink” is the wet basin three feet
Multimodal Data for Humanoid Robots: Vision, Language, Action, Telemetry, and Context Read More »
