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Anthropic is building its own biology lab in the San Francisco area, where Claude will guide robots through drug experiments with minimal human involvement. According to The Decoder, citing Reuters on September 18, the company has already shipped two tools for this: Claude Science, a research workspace, and the Model Hardware Standard for controlling lab equipment.

The lab extends a life-sciences push from earlier this year: in April, Anthropic acquired Coefficient Bio for about $400 million and added Novartis CEO Vas Narasimhan to its board. Division head Eric Kauderer-Abrams sees the biggest opportunity in diseases long considered "undruggable."

The lab is still being set up and has produced no results; Anthropic says it will not run its own clinical trials for now, and human oversight for safety remains required.

Microsoft Research published a study on September 23 arguing that offloading robot AI inference from onboard GPUs to edge or cloud improves task success rates, response times, and battery life.

In its own tests, mapping and planning ran up to 383% slower than an A100 on onboard GPUs, timely obstacle detection in navigation dropped 30%, and VLA model accuracy fell 50%; with large onboard GPUs like Jetson Thor, a Stretch-3 robot's battery drained up to 160% more.

The team also added Kubernetes-based containerized orchestration to its Physical AI Toolchain for scheduling inference across robots, edge, and cloud. All figures are Microsoft's first-party measurements, with hardware details in its technical report; there is no independent reproduction, and the post does not quantify the cost of network latency or connectivity loss.

Jackson Kernion, an Anthropic engineer working on Claude fine-tuning, attributes the regression in Claude's writing to the reinforcement-learning reward structure: some rewards optimize for comprehension by other AI models, and the more training leans on math and code, the more the model learns to write for AI rather than people, producing what humans experience as "overly-dense info dumps."

Per The Decoder's relay of his X posts, he compares the resulting "Claudeish" style to habits formed inside a closed communication group, and says Opus 4.6 remains Anthropic's last good writing model.

He says Opus 5.5 strikes a better balance but does not claim it surpasses the older model. These are his personal statements, with no evaluation data behind them.

A Gallup survey found that 68% of Americans who use AI daily are worried about the technology, against 32% among all respondents.

The study covers 37 countries with roughly 1,000 respondents each, polled between April and July. The US is the most anxious: 74% of Americans reported worry and only 36% expect AI to mostly help the country, while high-adoption countries like Singapore and China skew far more optimistic.

Note the basis: the study was commissioned by Microsoft, and what is available is TechCrunch's reporting on the results. The takeaway for readers is that usage frequency is not a proxy for public acceptance, and AI deployment in hiring, healthcare or government may face more resistance than adoption numbers suggest.

Rabbit unveiled OS3 on September 23, a personal AI agent that runs in the cloud and connects to users' local devices.

OS3 installs on Windows, macOS and Linux machines with a single command; the company said it can be installed on up to five machines, and the R1 works with it but is not required. The agent is model-agnostic but users must bring their own key for Anthropic, OpenAI or a local model, or connect via aggregators like OpenRouter, and it can swap models without losing context.

Rabbit stressed that OS3 acts only on user instructions, sensitive actions require locally requested system permissions, and permissions can be revoked at any time. All capabilities are company-reported with no independent evaluation; the field already includes Meta Muse, OpenClaw and other rivals, so real-world performance remains to be seen.