ChatGPT Images 2.0 (6 minute read)
OpenAI introduced an upgraded image model with improved text rendering, multi-image reasoning, and higher fidelity outputs, enabling complex assets like comics and marketing visuals.
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OpenAI develops platform for always-on Agents on ChatGPT (2 minute read)
OpenAI is developing an always-on agent platform within ChatGPT, codenamed Hermes, that allows users to create and continuously run custom agents. This platform includes features for creating workflows, integrating skills, and scheduling tasks, enabling agents to act independently rather than waiting for prompts. OpenAI's move presents strong competition to existing platforms like Notion by bringing such capabilities to a vast user base.
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Qwen3.5-Omni Technical Report (4 minute read)
Qwen3.5-Omni is a large-scale multimodal model with hundreds of billions of parameters that natively processes text, audio, images, and video within a unified architecture. The model supports a 256k token context length to seamlessly handle up to 10 hours of audio or 400 seconds of high definition video in real time. It leverages a Hybrid Attention Mixture of Experts framework alongside a dynamic alignment technique called ARIA to generate highly stable and emotionally nuanced multilingual speech synthesis with minimal latency.
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Coding agents ignore their own budgets (5 minute read)
Ramp Labs discovered that autonomous coding agents completely ignore passive token limits and cannot reliably regulate their own spending. When forced to explicitly approve or deny budget extensions, the models exhibited severe self-attribution bias by overly praising their own progress and nearly always approving more spend. To effectively manage costs, researchers had to separate the working agent from financial decisions by deploying an independent controller model that evaluates objective workspace snapshots.
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When Can LLMs Learn to Reason with Weak Supervision? (4 minute read)
This study found that models with extended pre-saturation phases generalize well from minimal examples and tolerate noise, while rapidly saturating models fail. The key issue is unfaithful reasoning, where models memorize answers rather than learning transferable reasoning. Continual pre-training and supervised fine-tuning on explicit reasoning traces improve reasoning faithfulness and generalization under weak supervision.
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Google Cloud Next starts today! (Sponsor)
If you're building AI applications, you need infrastructure that can actually handle the compute.Google uses Tensor Processing Units (TPUs) - custom-built hardware accelerators designed specifically for large-scale AI workloads. It's the exact same accelerator system powering Gemini and powers billions of user requests across Search and Maps. Ready to learn how to leverage TPUs for your own training and inference workloads? Start the course →
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CrabTrap: an LLM-as-a-judge HTTP proxy to secure agents in production (9 minute read)
CrabTrap is an open-source HTTP/HTTPS proxy that intercepts every request an AI agent makes and uses LLM-as-a-judge to determine if the request matches a policy of allowed traffic for that agent. Agents need real credentials, but can hallucinate destructive actions or get prompt-injected. This can have production consequences. CrabTrap introduces guardrails that represent a meaningful step forward in the security of agent harnesses in production environments.
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Critical Bits in Neural Networks (6 minute read)
Deep Neural Lesion (DNL) identifies highly sensitive parameters where flipping just a few bits can collapse model performance across vision and language tasks. The work also shows that protecting a small subset of these bits can mitigate such failures.
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OpenAI Is Working With Consultants to Sell Codex (3 minute read)
OpenAI is working with several consulting firms to help sell its AI coding tool Codex to businesses. Codex now has four million weekly active users, up from three million just two weeks ago. The Codex consulting program is part of OpenAI's push to focus on coding and enterprise businesses. Consulting partners will get access to an AI coding tool as part of the program.
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Sam Altman throws shade at Anthropic's cyber model, Mythos: ‘fear-based marketing' (2 minute read)
OpenAI CEO Sam Altman called out Anthropic's new cybersecurity model during a podcast appearance this week, saying the company was using fear to make its product sound more impressive than it actually is. Anthropic announced its Mythos model earlier this month and only released it to a small cohort of enterprise customers with the claim that the model was too powerful to be released to the public as cybercriminals would weaponize it. Altman said that Anthropic's fear-based marketing was a good way to keep AI in the hands of a small and exclusive elite. Fear-based marketing is prevalent in the AI industry, and it has also come from Altman himself.
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