Approxima is an open-source, self-hostable QA agent that monitors user journeys and supports Claude, Gemini, and GPT out of the box. It features Explore Mode, A/B Testing, and Self-healing to adapt to product evolution, with full support for local models and community contributions.
We Open Sourced Our LLM-based QA Agent To Catch Breakages Faster
Inkling-Small release, GPT-5.6 price cuts, Gemini Robotics ER 2
Thinking Machines released Inkling-Small, a 276B-parameter mixture-of-experts model with 12B active parameters that retains multimodal reasoning and a 1M-token context window while using less compute. OpenAI reduced GPT-5.6 Luna pricing by 80% and Terra pricing by 20%, while improving Sol's API speed across API, Codex, and ChatGPT Work subscriptions.
GPT-5 outperforms humans in inducing belief states via planning
A new study evaluates Large Language Models' ability to induce specific belief states in other agents through actions rather than conversation, a capability termed Non-Conversational Planning ToM (NCP-ToM). Using the NCP-ExploreToM framework, researchers tested six frontier models and human participants on 600 task instances where agents had to move objects or direct characters to achieve belief goals.
EU AI Act mandates AI-generated text watermarking from August 2024
The EU AI Act requires all AI systems generating synthetic text to include machine-readable, detectable watermarks using robust, interoperable technical solutions with two layers. This applies to all AI models, including open-source ones, and extends to any service accessible by EU citizens, regardless of location. Non-compliance risks fines of up to 35 million euros or a percentage of annual income, with providers of 'systemic risk' AI models facing heightened liability.
Ohio State University releases open-source Deep Research agent QUEST-35B
Ohio State University's NLP team has released QUEST-35B, an open-source Deep Research agent trained on approximately 32 H100 GPUs using 8,000 synthetic samples. The team open-sourced the training recipe, code, weights, and datasets, with benchmark results showing competitive performance compared to leading closed-source Deep Research systems.
Ohio State University releases open-source Deep Research agent QUEST-35B
Researchers at Ohio State University trained QUEST-35B, a Deep Research agent, using approximately 32 H100 GPUs and 8,000 synthetic samples. They open-sourced the training recipe, code, weights, and datasets, with benchmark results showing competitive performance compared to leading closed-source Deep Research systems.