A tight squeeze could fix the biggest hurdle for solid-state car and gadget batteries

A simple mechanical trick could replace complex chemistry fixes to make solid-state batteries safer, faster, and more reliable.

Solid-state batteries have long been promised as the holy grail of energy storage. They promise to double energy density compared to traditional options, slash charging times, and eliminate the risk of thermal fires. Despite that, the technology has yet to achieve widespread commercial adoption, and the main culprit is dendrites. These microscopic, needle-like structures form inside solid-state batteries during charging, bore through the solid ceramic electrolyte, and bridge the electrodes, causing a short circuit.

Now, researchers from SLAC National Accelerator Laboratory and Stanford University have discovered a surprisingly simple fix for this persistent problem. According to a paper published in the science journal Nature, applying controlled mechanical pressure to the ceramic electrolyte prevents these short circuits, allowing test cells to survive thousands of charge cycles without failing.

Anthropic previews new standard to streamline AI-to-machine connections

The Model Hardware Standard provides a universal translation layer, giving AI agents standard controls to run lab equiment and factory machines.

Anthropic has launched a research preview of its Model Hardware Standard (MHS), a shared specification designed to let AI agents safely control lab instruments and factory equipment. The company claims MHS reduces the time required to integrate complex machinery with AI from months down to hours or minutes. The standard is currently available to select research labs and manufacturers via a waitlist, but Anthropic plans to open-source it in the future.

How the standard connects AI to physical devices

Gemini Omni can now extend videos to 40 seconds and upscale them to 4K

Generating a short AI video is one thing; getting several shots to actually look like they belong in the same video is a much harder problem. Google is taking another swing at that with Gemini Omni 1.1 Flash, its latest generative video model aimed at giving creators and developers much more control over what happens between the first frame and the last.

The biggest change is how much of an existing video Gemini can remember when you ask it to continue a scene. Omni 1.1 can look at up to 10 seconds of previous footage for context, rather than relying on just the final second. That should help it keep characters, environments, and the general direction of a scene more consistent instead of effectively guessing what should happen next.