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Previewing the Model Hardware Standard

We’re opening a research preview of the Model Hardware Standard (MHS), a shared specification for AI agents to safely operate physical devices, to a first group of scientific research labs and advanced manufacturers. MHS enables AI agents to operate multiple lab and manufacturing instruments, such as microscopes, liquid handlers, and robotic arms, in parallel, and perform intricate tasks ranging from routine drug discovery experiments to laser calibration on a quantum computer. The development of MHS began as a collaboration between Anthropic and HHMI Janelia Research Campus.

It typically takes a lab or manufacturing facility weeks, if not months, to set up and integrate their hardware. Most devices don’t communicate with each other, instead requiring specialists to build bespoke integrations. MHS reduces this integration work to hours or minutes. And by incorporating AI into these tools, MHS also helps researchers and engineers more readily orchestrate autonomous, round-the-clock experiments and workflows, with agents able to reason through each step in an experiment, update parameters in real time, and, in some cases, recover from hardware errors without intervention.

We’re sharing an early version of MHS with partners across science, robotics, electronics, and manufacturing so we can collaborate to build safety evaluations and develop best practices for AI systems operating physical equipment, ahead of making the standard open source. MHS works with any device that has a programmable interface. It is also model-agnostic, and any agent harness can access it using standard protocols, such as the Model Context Protocol. To apply for access to the research preview, head here.

LLMs Anticipate Everyday Verbal Behavior

MIT built an AI that predicts what you’ll say next… before you open your mouth. In the research paper titled “Before You Say It: Anticipating Verbal Behavior from Longitudinal Everyday Conversations with LLMs,” researchers set out to test whether Large Language Models (LLMs) can build this same level of intuitive, person-specific understanding.

In this AI Research Roundup episode, Alex discusses the paper: ‘Before You Say It: Anticipating Verbal Behavior from Longitudinal Everyday Conversations with LLMs’ Understanding an individual deeply requires anticipating how they will likely react and communicate across different real-world situations. In this paper, the authors introduce an LLM-based predictive behavioral modeling framework designed to forecast personal verbal behavior from everyday conversational interactions. The researchers collected over 1,000 hours of naturalistic speech from 14 participants using wearable smartwatches and evaluated LLM predictions against actual recorded behaviors. Semi-structured interviews further explored user perceptions and identified promising directions for proactive behavioral assistance. Ultimately, the study demonstrates that longitudinal conversation data enables person-specific behavioral anticipation for future personalized assistive systems. Paper URL: https://arxiv.org/pdf/2608.13454 #AI #MachineLearning #DeepLearning #LLM #ConversationalAI #BehavioralModeling #WearableTech

Altered ribosomes help explain how an enzyme fuels tumor growth

A new Northwestern Medicine study has identified a previously unknown mechanism by which an enzyme promotes cancer cell proliferation, establishing it as a promising therapeutic target for cancer, according to findings published in Nature Communications.

N-acetyltransferase 10 (NAT10) is a multifunctional enzyme with oncogenic properties and has been associated with multiple types of cancer, including hepatocellular carcinoma—an aggressive type of liver cancer—and acute myeloid leukemia, among others.

NAT10 is known to acetylate, or chemically modify, RNA, but whether this mechanism supports the oncogenic properties of this protein has remained uncertain, said Daniel Arango, Ph.D., assistant professor of pharmacology and a co-corresponding author of the study.

Glacier surging and surgerelated hazards in a changing climate Reviews Earth & Environment

Glacier surges are rapid ice flow acceleration and mass transport events, which can threaten nearby communities, infrastructure and habitats. This Review discusses the global distribution, behaviour and associated hazards of glaciers that are prone to surging and how these are being affected by climate change.

QuEra’s quantum computers run on lasers held at exact frequencies, a precision no eye can see and only the atoms can distinguish

Keeping a laser there is a continuous act: temperature, vibration, and pressure push it off target all day, and layered feedback pushes it back. When the feedback loop fails, the lock breaks and the machine stops. Bringing it back has historically taken one specific expert: someone who knows the lasers intuitively and has experience with the exact recovery sequence required to return it to the right state. If the lock broke in the middle of the night, that person had to drive to the lab and fix it.

This is not a new problem, and QuEra has built automatic relocking for common disturbances. Aquila, our production QPU available through Amazon Braket, already runs with excellent uptime exceeding 99%. But the team knew that the level of human involvement in relocking, particularly for the less frequent but more severe disturbances, was not scalable. As a result, this spring QuEra deployed the Model Hardware Standard (MHS), a standard that started as a collaboration between Anthropic and HHMI Janelia Research Campus. A cross-functional task force took relocking to another level: the level that scalable deployment of logical QPUs will demand. Working through MHS on a dedicated testbed, with an AI agent in operational control of roughly $0.7M of precision hardware inside human-set safety bounds, the lock now comes back in seconds: verified, on target, with no one in the building. And then the same approach went one step further.

Candida on urinary catheters can be more than contamination, patient samples suggest

Relying on a urinary catheter is a standard part of medical care for hundreds of thousands of patients each year. Unfortunately, the device carries the risk of catheter-associated urinary tract infections (CAUTIs), for which bacteria are widely recognized as the primary cause. And yet, many patients face a growing threat from another pathogen: a fungus, Candida albicans.

Research published in Proceedings of the National Academy of Sciences by University of Notre Dame associate professors of biological sciences Ana Flores-Mireles and Felipe Santiago-Tirado shows how the fungus works in the bladder, potentially changing the way doctors treat and diagnose CAUTIs.

Scientists Discover a Cannabis Receptor That Could Stop Breast Cancer Spreading

Cancer cells are proving trickier than we thought, so scientists are getting even trickier to shift the survival odds in our favor. Recent medical research has highlighted a significant issue: cancer cells display plasticity. Some cancer cells can spontaneously revert from a differentiated state to become ‘immature’ and stem-cell-like again, switching their identity to yield more diverse, aggressive, and proliferative tumors.

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