5 stories
We're rapidly transitioning to a computing landscape defined by highly general, increasingly autonomous agents. Driven by large language models (LLMs) that can dynamically generate plans and invoke external tools, these systems offer the potential for AI to seamlessly handle complex, multi-step…
AI agents have shown great potential in automating real-world tasks, such as conducting a Google Search, reading local computer files, or executing generated Python scripts. To achieve such agentic workflows, LLMs need to learn how to use tools correctly and efficiently.
As AI assistants evolve from simple text interfaces to multimodal companions, we are seeing a shift toward more proactive, situated assistance. Recent innovations like Project Astra and Gemini 3.1 Flash Live already allow users to discuss their physical surroundings in real time, often utilizing…
A large proportion of clinical diagnoses can be derived from language-based interviews alone. These diagnostic interviews are typically conducted by clinicians through doctor-patient interactions during in-person or remote visits.
Estimates suggest that billions of wearable devices are now in use, precisely tracking heart rate, movement, skin temperature, blood-oxygen levels, and sleep across days, weeks, and months.
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