OpenAI to acquire Astral
Accelerates Codex growth to power the next generation of Python developer tools
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Noticias
Titulares de las redacciones y blogs que seguimos.
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Together AI expands fine-tuning service with tool calling, reasoning, and vision support
Together AI expands fine-tuning with native support for tool call, reasoning, and vision-language models, plus 100B+ model training, up to 6× higher throughput, and job cost and ETA estimates.
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Measuring progress toward AGI: A cognitive framework
We’re introducing a framework to measure progress toward AGI, and launching a Kaggle hackathon to build the relevant evaluations.
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Introducing Forge
Today, we’re introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge.
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OpenAI Japan announces Japan Teen Safety Blueprint to put teen safety first
OpenAI Japan announces the Japan Teen Safety Blueprint, introducing stronger age protections, parental controls, and well-being safeguards for teens using generative AI.
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Introducing GPT-5.4 mini and nano
GPT-5.4 mini and nano are smaller, faster versions of GPT-5.4 optimized for coding, tool use, multimodal reasoning, and high-volume API and sub-agent workloads.
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Mamba-3
Meet Mamba-3: the SSM built for inference. Faster than Transformers at decode, stronger than Mamba-2, and open-source from day one.
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Equipping workers with insights about compensation
New research shows Americans send nearly 3 million daily messages to ChatGPT asking about compensation and earnings, helping close the wage information gap.
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Together AI at NVIDIA GTC 2026: Explore our latest innovations across research and products
Together AI arrives at NVIDIA GTC 2026 with new launches in inference, agents, voice AI, and open models — plus technical sessions from its research and engineering leaders.
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Why Codex Security Doesn’t Include a SAST Report
A deep dive into why Codex Security doesn’t rely on traditional SAST, instead using AI-driven constraint reasoning and validation to find real vulnerabilities with fewer false positives.
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Identifying Interactions at Scale for LLMs
Understanding the behavior of complex machine learning systems, particularly Large Language Models (LLMs), is a critical challenge in modern artificial intelligence. Interpretability research aims to make the decision-making process more transparent to model builders and impacted humans, a step toward safer and more trustworthy AI. To gain a comprehensive understanding, we can analyze these systems through different lenses: feature attribution…
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Build real-time voice agents on Together AI
Build real-time voice agents on Together AI with co-located STT, LLM, and TTS infrastructure, native Deepgram and Cartesia support, and end-to-end latency under 500ms.
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Designing AI agents to resist prompt injection
How ChatGPT defends against prompt injection and social engineering by constraining risky actions and protecting sensitive data in agent workflows.
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From model to agent: Equipping the Responses API with a computer environment
How OpenAI built an agent runtime using the Responses API, shell tool, and hosted containers to run secure, scalable agents with files, tools, and state.
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