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U.S. appeals court upholds designation of Anthropic as supply chain risk
Leading today: U.S. appeals court upholds designation of Anthropic as supply chain risk. Also in this issue: Proaction boosts sales 60% and saves 75+ hours with Codex; Anthropic to pay Akamai $11.6 billion over seven years in cloud deal. 17 stories in total, selected automatically from 62 candidates across the day's feeds.

| 1 | cnbc.com U.S. appeals court upholds designation of Anthropic as supply chain riskTrending on Hacker News (377 points, 690 comments). |
| 2 | openai.com Proaction boosts sales 60% and saves 75+ hours with CodexWith Codex, GPT-Live-1, and GPT-6 Astra, Proaction builds, operates, and sells modern fleet management faster. |
| 3 | techcrunch.com Anthropic to pay Akamai $11.6 billion over seven years in cloud dealAnthropic has committed $11.6 billion over seven years to Akamai's cloud infrastructure, a bet on CPUs that could grow to about $20 billion, and in an unusual arrangement, Akamai is giving Anthropic a potential stake of... |

Liquid AI has released LFM2.5-VL-3B-DSpark, a 279.5M-parameter draft model that brings speculative decoding to its LFM2.5-VL-3B vision-language model.
Read →Aikido Security has released Altar-1, its first open-weight security model. It is a compressed version of Z.AI’s GLM-5.3, built to run inside infrastructure the customer controls.
Read →Fastino Labs has released GLiNER2.5-Decide, a 340M-parameter open-weight decision model. It takes text and a schema of typed questions and returns structured answers.
Read →Black Forest Labs (BFL), the lab behind the FLUX image models, has released FLUX 3 Action. It is a 7B open-weights World Action Model (WAM) for robot control.
Read →xAI Launches Grok Bot Creator Rewards Program BASENOR
Read →DeepSeek V4.1 Flash vs V4 Pro vs V4-Flash: 4.4x Gap [2026] tech-insider.org
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Vendors rolling out AI have an "incentive to deny as many claims as possible." (Vendors rolling out AI have an "incentive to deny as many claims as possible.")
Read →Asynchronous monitoring, incident investigations, and compliance audits primarily rely on agent traces to reconstruct what happened. These analyses assume that LLM agents cannot tamper with their own execution traces.
Read →Latent world models are typically trained to predict factual transitions, whereas model predictive control (MPC) must compare alternative actions from the same state.
Read →Coding agents have demonstrated enormous success in solving complex programming problems.
Read →World Action Models (WAMs) couple action generation with future visual prediction for robotic manipulation.
Read →Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discrete decisions are tightly coupled to geometric, kinematic, and dynamic constraints.
Read →
Trending on Hacker News (54 points, 42 comments).
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