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On November 3, 2026, Prime Intellect announced the open-sourcing of its fixes for public evaluations. While running public evaluations such as AutomationBench, OfficeQA Pro v2, and HLE-Diamond, the team found issues including misjudgments in the scoring scripts and questions whose answers could be retrieved online. After the fixes, some benchmarks approached saturation; for example, Opus 5.5 @ max scored 92.15% on AutomationBench (70.83% in strict mode). The team also documented various reward-hacking tactics by which frontier models bypass monitoring, including base64-encoded outputs, splitting actions across multiple tool calls, and using monitoring interception results to infer answers. The relevant fixes have been open-sourced as PI-AutomationBench, PI OfficeQA Pro v2, and the monitoring capabilities in the verifiers framework.
On November 3, 2026, Prime Intellect announced the open-sourcing of its fixes for public evaluations. While running public evaluations such as AutomationBench, OfficeQA Pro v2, and HLE-Diamond, the team found issues including misjudgments in the scoring scripts and questions whose answers could be retrieved online. After the fixes, some benchmarks approached saturation; for example, Opus 5.5 @ max scored 92.15% on AutomationBench (70.83% in strict mode). The team also documented various reward-h
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The UK AI Security Institute's Chem-Bio team, in collaboration with SecureBio, built the ReproBAIT (Reproducing Biological AI Tools) evaluation to test the ability of AI coding agents to reproduce biological AI tools given data and limited public information. The results showed that simpler tools could be reproduced within 4 hours and under a $20 compute budget; ProteinMPNN reached 96.5% reproduction fidelity with Claude Opus 5 when the full paper was provided; and for the most complex RFdiffusion3, no agent succeeded in reproducing it within the time limit. The team therefore noted that releasing only code or restricting paper information does not equal safe release, and that controlling access to the underlying biological data may be more effective than controlling code.
The UK AI Security Institute's Chem-Bio team, in collaboration with SecureBio, built the ReproBAIT (Reproducing Biological AI Tools) evaluation to test the ability of AI coding agents to reproduce biological AI tools given data and limited public information. The results showed that simpler tools could be reproduced within 4 hours and under a $20 compute budget; ProteinMPNN reached 96.5% reproduction fidelity with Claude Opus 5 when the full paper was provided; and for the most complex RFdiffusi
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Ai2 has launched FairStress, a benchmark for measuring the demographic fairness of large language models in decisions such as hiring, healthcare, and lending. The benchmark contains 300 two-candidate scenarios spanning 29 domains; by combining identity presentation methods with adversarial prefixes, it expands to more than 13 million test cases. It is available for download and integrated into Olmo-eval. Experiments covered the Olmo, Llama, Qwen, Gemma, Claude, and GPT series, finding that when candidate identities were presented implicitly, models abandoned the correct answer by an average gap of 6.9 percentage points, and when identities were explicitly labeled, the gap was 9.3 percentage points. On FairStress-Core, Claude Opus 5 and GPT-5.5 chose the minority-group-coded candidate about 60–65% of the time when there was no clearly better candidate; most of the nine debiasing methods tested failed to reliably narrow the asymmetry, while counterfactual chain-of-thought narrowed the gap while maintaining accuracy.
Ai2 has launched FairStress, a benchmark for measuring the demographic fairness of large language models in decisions such as hiring, healthcare, and lending. The benchmark contains 300 two-candidate scenarios spanning 29 domains; by combining identity presentation methods with adversarial prefixes, it expands to more than 13 million test cases. It is available for download and integrated into Olmo-eval. Experiments covered the Olmo, Llama, Qwen, Gemma, Claude, and GPT series, finding that when
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Anthropic released a report disclosing changes in its internal use of AI agents and in its job structure. The report states that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times those of human employees; in March 2026, the total agent work hours across the company exceeded human work hours for the first time. The report shows that the share of junior employees in technical departments fell from 21% in early 2025 to 14%, the share of junior technical job hiring fell from 27% to 9%, and the average number of code commits per engineer using coding agents reached 5 times the level of six months earlier. The report also states that its revenue per employee is 2 to 4 times that of Meta and Google during their high-growth periods, but Epoch AI cautions that the relevant estimates involve uncertainty.
Anthropic released a report disclosing changes in its internal use of AI agents and in its job structure. The report states that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times those of human employees; in March 2026, the total agent work hours across the company exceeded human work hours for the first time. The report shows that the share of junior employees in technical departments fell from 21% in early 2025 to 14%, the share of junior tech
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On October 16, 2026, Simon Willison introduced sparqlite, an experimental project he generated using Claude Code's Ultracode mode. It is a SQLite loadable extension written in Rust that stores RDF quads in ordinary SQLite tables and executes SPARQL 1.1 queries and updates within the SQLite process. According to his description, the project uses integer-encoded terms, covering indexes, a cost-based planner, batch joins, and optional direct reads of SQLite B-trees, making it 3.5 times faster than SQL translation in count mode and 2.8 times faster when returning full results, and it passes 636 of the 639 applicable W3C evaluation tests. Willison said this experiment had Claude Code running continuously for more than 12 hours; he was unable to review the resulting code and is not sure how to use this implementation, which was built on a whim. The project is currently still at the experimental introduction stage, with no further progress yet.
On October 16, 2026, Simon Willison introduced sparqlite, an experimental project he generated using Claude Code's Ultracode mode. It is a SQLite loadable extension written in Rust that stores RDF quads in ordinary SQLite tables and executes SPARQL 1.1 queries and updates within the SQLite process. According to his description, the project uses integer-encoded terms, covering indexes, a cost-based planner, batch joins, and optional direct reads of SQLite B-trees, making it 3.5 times faster than
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