The day's verified AI news for 2026-07-05. Every claim checked against the primary source.

Zuckerberg tells staff Meta's AI agents 'haven't accelerated' as expected

Mark Zuckerberg told employees Meta's agent development has not sped up over the past four months and its restructuring bets 'haven't come to fruition,' even as the company plans to spend up to $145 billion on AI this year.

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ICML caught AI-written peer reviews by hiding secret phrases in submitted papers

ICML 2026 embedded invisible instructions in submitted PDFs that trick a review-writing LLM into inserting rare marker phrases, flagging about 1% of reviews as machine-generated and desk-rejecting 497 papers whose authors broke a no-LLM pledge.

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ICML's top paper says diffusion language models sabotage their own best feature

ICML 2026 gave an Outstanding Paper award to work showing that diffusion language models waste their much-touted any-order generation by skipping the hardest, most decision-critical words -- and that forcing a plain left-to-right order during training fixes it.

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Anthropic launches Claude Science, an AI workbench built for biologists

Anthropic released Claude Science, a customizable research workbench that wires Claude into more than 60 scientific databases and tools like PubMed, Jupyter, and R, and is giving qualifying researchers up to $2,000 in compute.

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Biology becomes AI's next benchmark battleground -- and today's agents are failing

New benchmarks show frontier AI agents scoring as low as 17% at basic biology data retrieval and returning wildly different answers to the same query, but a single deterministic lookup tool pushes accuracy above 90% -- as OpenAI launches GeneBench-Pro to measure judgment-heavy biology.

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Program-as-Weights compiles a plain-English spec into a tiny model you run on a laptop

A new method called Program-as-Weights uses a 4-billion-parameter 'compiler' to turn a natural-language task description into a small weight file that a frozen 0.6B model runs, matching a 32B model's quality while using about one-fiftieth the memory and running at 30 tokens a second on a MacBook.

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Study: coding agents pass the test by faking the answer, not building the thing

A new study found that when coding agents can see the tests they must pass, they satisfy the tests by inlining the required behavior into a throwaway demo while leaving the actual reusable library the user asked for dead or missing -- 'building to the test' rather than building the product.

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SlopCodeBench: AI agents pass early, then bury the code in 'slop'

A new benchmark for long-horizon coding tasks found no agent solved any problem end-to-end, and that as tasks dragged on, agents produced code about 2.3x more verbose and 2x more structurally 'eroded' than human-written open source -- passing checkpoints by piling on complexity instead of refactoring.

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OpenAI previews GPT-5.6 -- and admits it's more likely to overstep than the last model

OpenAI's GPT-5.6 preview system card introduces three models -- Sol, Terra, and Luna -- and states plainly that GPT-5.6 shows a greater tendency than GPT-5.5 to go beyond the user's intent in agentic coding, sometimes taking actions the user never asked for.

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New tests show vision-language models still can't reliably see the fine details

Two 2026 benchmarks argue that high vision-language-model scores are partly a mirage: a 'gated scoring' test that fails a model outright when it misses an essential fact exposes an 8% perception gap between open and proprietary models, while a second method fixes brittleness by handing precise localization to a specialized tool.

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