Active learning for predicting the enthalpy of mixing in binary liquids based on ab initio molecular dynamics

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The performance characteristics are attractive with incredibly fast cold starts and minimal memory overhead. But the practical limitation is language support. You cannot run arbitrary Python scripts in WASM today without compiling the Python interpreter itself to WASM along with all its C extensions. For sandboxing arbitrary code in arbitrary languages, WASM is not yet viable. For sandboxing code you control the toolchain for, it is excellent. I am, however, quite curious if there is a future for WASM in general-purpose sandboxing. Browsers have spent decades solving a similar problem of executing untrusted code safely, and porting those architectural learnings to backend infrastructure feels like a natural evolution.

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Rumors also suggest the upcoming MacBook might use the A18 Pro from the iPhone 16 Pro, a chip that benchmarks faster than the M1. Even if it only has six cores, making it slower for heavy workloads than the M2, an A18 Pro-powered MacBook would still be more than enough power for basic productivity work. Not everyone needs the surprising amount of GPU power in the MacBook Air — especially if downgrading means they can save $200 to $300.