NVIDIA L40S is a data-center GPU built on the Ada Lovelace architecture, with 48 GB VRAM, used for AI inference, training, and graphics workloads.
Capsule Security has shipped an evaluator that runs inside an agent's execution path and can stop an intended action before it executes. Doing that requires adding a chokepoint to the agent's execution path.
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The 260M NeoMME sends raw image patches and text down the same bidirectional path, with no vision tower and no causal decoder, and reports a 6 kB late-interaction index per page. The conditions behind both numbers are checkable.
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The startup fine-tuned two Nvidia Nemotron models to allow, flag or block each action an agent intends, and reports 98% accuracy on a 9,429-trajectory benchmark whose own authors say accuracy is the wrong test.
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NYU and Radboud researchers spent a year turning Google's Ads Transparency Center into a detector for deceptive software ads, and found that the report button removes a creative while leaving the domain behind it serving.
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NVIDIA's BioNeMo Agent Toolkit answers a real question for agents that know a task needs folding but not which model to call. The price of that answer is a database download and a Claude Science sandbox you have to open.
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AWS, NVIDIA and Heidi report cutting production speech-recognition inference cost by 75% by sharing one GPU through CUDA MPS instead of running a single model instance. How much of that saving transfers depends on the latency envelope you accept.
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Prefill and decode sit on the same card and answer to different limits, which is why a GPU with more arithmetic and the same memory read rate leaves your time per output token exactly where it was.
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AWS, NVIDIA and Heidi Health report holding sub-second transcription while cutting 16 GPU instances to four. Per-GPU throughput rose only about 1.5x, so the rest of that saving came out of provisioning headroom.
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