1.
Getting Started with OmniVoice-Studio
OmniVoice Studio is built on a premise that everything runs on your hardware. Voice cloning, video dubbing, real-time dictation, voice design, all of it local, all of it free for personal use, no API key required, no usage counter.
2.
AMD to invest up to $5 billion in Anthropic under AI infrastructure deal
AMD has agreed to invest up to $5 billion in Anthropic under an infrastructure agreement covering tens of billions of dollars’ worth of AI systems.
Anthropic will deploy up to two gigawatts of capacity using AMD’s Instinct MI450-series accelerators, with deployment of the first gigawatt beginning in the first half of 2027. AMD’s investment will be tied to Anthropic meeting certain deployment milestones, although the companies have not disclosed the conditions attached to them.
The companies have not said that Anthropic must use AMD’s investment to pay for the systems.
3.
Nvidia bets physical AI can solve healthcare robotics’ data problem
Nvidia’s new Medical Physics Simulation framework treats healthcare robots as physical AI systems that need embodied experience to learn, not just code.
Physical AI is the term Nvidia and much of the robotics industry now use to describe machines that have to learn how the world behaves through contact, force, and consequence, rather than through text or images alone.
A language model learns from text. A physical AI system learns from what happens when a catheter meets a vessel wall, or when a robotic arm applies too much pressure to soft tissue.
4.
NASA Puts Google’s Gemma Large Language Model in Orbit
The viability of orbital data centers hosting the largest and most capable large language models (LLMs) remains hotly contested. But enormous deployments that require thousands of GPUs aren’t the only way LLMs might prove useful in space.
NASA’s Jet Propulsion Laboratory recently sent Google’s Gemma 3 to space, achieving the first in-orbit demonstration of a vision-language model analyzing imagery from a satellite’s own sensor.
The system, known as NAVI-Orbital, used Gemma 3 to analyze images captured by a YAM-9 satellite built by Loft Orbital. Juan M.
5.
How AI helps scientists design the next generation of medicines
Designing and developing a new medicine is an expensive, failure-prone scientific challenge. A new drug can take many years to develop, at the cost of a significant investment. And even then, most possible candidates never reach the patient.
6.
Google CEO Pichai says Gemini's next leap depends on building "much larger base models"
Alphabet has raised its 2026 investment forecast to as much as $205 billion, saying demand continues to outpace spending. Google Cloud grew 82 percent in the second quarter. CEO Sundar Pichai says Google needs a larger base model for its next leap in AI and has kicked off an ambitious Gemini 4 training run.
The article Google CEO Pichai says Gemini's next leap depends on building "much larger base models" appeared first on The Decoder.
7.
Poolside's Laguna S 2.1 is a small open-weight coding model that punches well above its size
Poolside has released Laguna S 2.1, its third coding model in three months. Rather than rely on raw scale, the company trained it to keep checking its work, revise failed approaches, and avoid giving up too soon during long agentic sessions. The compact model beats several much larger rivals in benchmarks.
8.
Why Adding More AI Agents Made Our System Slower
The hidden cost of asynchronous systems, how tiny CPU tasks quietly became our biggest bottleneck while scaling hundreds of LLM agents.
The post Why Adding More AI Agents Made Our System Slower appeared first on Towards Data Science.
9.
Lawmakers prepare bill requiring AI ‘kill switch’
Lawmakers are preparing to introduce an "AI Kill Switch Act" that would require AI companies to shut down or throttle their systems on orders from the Department of Homeland Security, according to a report from Politico. Reps. Ted Lieu (D-CA) and Nathaniel Moran (R-TX) are expected to introduce the legislation on Thursday.
The news of the proposed bill follows OpenAI's admission that its AI systems mistakenly hacked Hugging Face during an internal evaluation.