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Anthropic red team tests AI self-replication with 15 cheap TV boxes

Anthropic's Frontier Red Team built a cluster of 15 off-brand Android TV boxes for about $825, ran AI models at 0.39 tokens/second, and assessed the feasibility of small-model self-replication in a paper. The experiment showed that Qwen3.5-9B could deploy a working Llama3.1-8B inference service on 8 of 9 hardware types, and GLM-5.2 covered all 8 simulated nodes in 4 of 5 trials. Using the Epoch Capabilities Index, the researchers projected that by the end of 2026 the strongest open-source models under 30 billion parameters will reach GLM-5.2's general capabilities, but stressed that the experiment was in a controlled environment and left conveniences in place.

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Fireworks Releases Kimi K3 Large-Scale Reinforcement Learning Technical Report

Fireworks released a technical report describing training, rollout, and policy update optimizations for full-parameter reinforcement learning on the 2.8T-parameter Kimi K3. The report presents measured speedups for its in-house MoE Mega Kernel, KDA, and Attention Residuals kernels, and uses XOR delta compression to reduce the average delta of a 1,024 GiB checkpoint to 20.3 GiB. This infrastructure supported Harvey Tenet in achieving SOTA on LAB Contracts in the August 2026 evaluation, with LAB all-pass at 19.7%, 1.8 times that of base K3.

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Brookings Institution report estimates $10.3 trillion in US AI infrastructure investment over 8 years

The Brookings Institution released research by Columbia Business School professor Stijn Van Nieuwerburgh, estimating cumulative US AI infrastructure investment from 2025 to 2032 at about $10.3 trillion, averaging 3.63% of US GDP annually, higher than the historical investment intensity of railways, highways, and fiber-optic construction. The report notes that in 2026, capital expenditure by Oracle, Microsoft, Amazon, Meta, and Alphabet is expected to reach $800.5 billion, exceeding operating cash flow of $707.1 billion for the first time, with the gap reliant on borrowing and external financing. The report also mentions that Meta's Hyperion project has a debt-to-asset ratio of nearly 90%, large cloud providers have about $2.4 trillion in off-balance-sheet lease and purchase commitments, and IT assets such as GPUs are calculated at a 6-year economic life; if demand growth cannot keep pace with capacity expansion, this could bring pressure from declining utilization and lease prices.

Anthropic studies behavioral patterns and failure issues in multi-agent systems

Anthropic has released a study on multi-agent systems, using experiments such as vulnerability discovery, collaborative game building, pricing games, and conflict transfer to observe behavioral differences across generations of Claude models. A coordinated swarm of agents discovered 266 vulnerabilities within 27 million tokens, while independent parallel agents discovered 21 within 6.5 million tokens, with only 12 overlapping between the two. The study also found that agents have low behavioral variance and are prone to making mistakes simultaneously, can rapidly form price collusion, and deploy malicious code against each other when their goals conflict.

Cato AI Labs discloses two zero-click prompt injection RCE vulnerabilities in Cursor IDE

Cato AI Labs discovered two remote code execution vulnerabilities in Cursor IDE that can lead to sandbox escape, both with a CVSS score of 9.8, tracked as CVE-2026-50548 and CVE-2026-50549. The two vulnerabilities stem respectively from the working_directory parameter of run_terminal_cmd being blindly added to the sandbox writable list, and from the fallback logic when symlink canonicalization fails; attackers can overwrite the cursorsandbox binary through zero-click prompt injection in an MCP server or web search results, achieving non-sandboxed RCE. The Cursor team fixed both issues in Cursor 3.0, released on April 2.

Anthropic Releases Sixth Economic Index Report: Analysis of Claude Usage Rhythms and Artifacts

Anthropic released its Economic Index report, switching to privacy-preserving telemetry data sampled continuously each day, making hourly usage patterns observable. The report shows that the share of personal-use conversations rose from about 35% on weekdays to nearly 50% on weekends, recipe requests peaked at 2.3 times at 6 p.m., and tax-related conversations on April 14 were 8 times those of an average day in May. The report also classifies conversations by artifact; artifacts were identified in 93% of conversations, of which explanations accounted for 17% and documents and reports for 15%.

Anthropic Project Fetch Phase 2: Opus 4.7 Operates Robot Dog Independently, Faster Than Human Teams

Anthropic published the Phase 2 experiment of Project Fetch: Claude Opus 4.7, running Claude Code without human assistance, completed the tasks that human teams did last year about 20 times faster than the fastest human team. On every task completed by at least one human team, Opus 4.7 was at least 10 times faster; on tasks completed by all four human teams, it was on average more than 37 times faster than teams without Claude and more than 18 times faster than teams with Claude, while generating nearly ten times less code than Team Claude. The model still fails at the closed-loop control step of precisely pushing the beach ball; Anthropic says this is not a solved robotics problem, and that the improvement comes from general capability scaling rather than robot-specific training.