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A philosophical essay argues that AI agents should be designed with eudaimonic rationality—a practices-based form of reasoning rooted in virtue ethics—rather than consequentialist goal-optimization, because human flourishing itself involves this type of rational activity. The essay identifies eudaimonic rationality as a natural and stable form of agency found in domains like mathematics and friendship, where agents promote excellence through excellence rather than optimizing toward external goals. This framework would make AI systems more robust to alignment problems like inner misalignment, goal drift, and violations of safety properties like corrigibility and transparency, while also naturally supporting human values without creating the type mismatch that plagues goal-based AI alignment approaches.
OpenAI announced a dedicated initiative for India to expand access to its AI tools and services across the country. The program includes building local infrastructure, partnering with enterprises, and developing workforce training capabilities. This enables Indian businesses and workers to adopt OpenAI's technology while the company establishes regional operations support.
IBM and UC Berkeley created MAST, a diagnostic framework that categorizes why AI agents fail in IT automation tasks rather than just reporting success rates, and applied it to analyze 310 execution traces across three language models. Gemini-3-Flash averaged 2.6 failure modes per failed trace while GPT-OSS-120B averaged 5.3, showing that smaller open-source models suffer from cascading failures that compound over time. The analysis revealed that incorrect verification (agents declaring success without checking results) is the strongest failure predictor, enabling developers to deploy targeted fixes like external verification gates instead of blind prompt engineering.
Google's Gemini app now offers music generation through Lyria 3, its latest model, allowing users to create 30-second tracks by describing ideas or uploading photos. The tool generates lyrics automatically and accepts text or image prompts in eight languages, with tracks embedded with SynthID watermarks to identify AI-generated content. Users can share custom music tracks with friends, and YouTube creators will access the same technology to enhance Shorts videos.
The article discusses how AI usage has shifted from chatbot conversations to autonomous agents performing multi-step tasks, requiring users to evaluate three components: underlying models (GPT-5.2, Claude Opus 4.6, Gemini 3 Pro), apps (websites and specialized tools), and harnesses (systems enabling tool use and task automation). The frontier models now cost at least $20 monthly and differ mainly in bundled features and accessible tools, with OpenAI and Anthropic offering more capable harnesses for document creation and research than Google's comparable model. As a result, selecting AI for specific work depends less on model choice and more on which app and harness provides the required functionality, making the decision more complex than during the chatbot-only era.
Firetiger launched an observability product that uses always-on agents to monitor customer-facing behavior, detect anomalies, verify impact, and fix issues before customers notice. The product is available fully self-service for anyone to use. This shifts incident and dashboard management from engineering teams to automated agents running 24/7.
OpenAI and Paradigm released EVMbench, a benchmark designed to measure how well AI agents can identify, fix, and exploit critical vulnerabilities in smart contracts. The benchmark includes high-severity flaws across multiple smart contract categories to test AI performance on security tasks. This creates a standardised way to evaluate whether AI systems can assist with smart contract security analysis and auditing.
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