All tags
Model: "gpt-realtime-2"
not much happened today
gpt-5.5 gpt-image-2 gpt-5.5-pro gpt-5.5-instant gpt-realtime-2 gpt-5.5-cyber codex zaya1-74b-preview zaya1-vl-8b qwen3-omni openai zyphra amd deepseek vllm_project model-release model-training mixture-of-experts inference model-optimization sandboxing alignment cybersecurity agent-runtime throughput quantization telemetry real-time-detection reach_vb dhh gdb patience_cave ithilgore cryps1s sama deredleritt3r
OpenAI rapidly expanded the GPT-5.5 family with multiple variants including gpt-image-2, GPT-5.5 Pro, and GPT-5.5 Cyber, receiving positive feedback for efficiency and usability. Codex evolved into a long-running agent runtime with a new /goal mechanism, achieving 61% success on ARC-AGI-3 games after extensive testing. OpenAI also introduced cybersecurity-focused models like GPT-5.5-Cyber targeting enterprise and government sectors. Meanwhile, Zyphra released the open-model ZAYA1-74B-Preview, a 74B parameter mixture-of-experts model trained on AMD hardware under Apache 2.0 license, alongside a vision-language model ZAYA1-VL-8B. Inference infrastructure competition intensified with vLLM updates improving throughput and latency, including support for DeepSeek V4 and enhanced quantization/backends.
GPT-Realtime-2, -Translate, and -Whisper: new SOTA realtime voice APIs
gpt-realtime-2 gpt-5.5 codex openai anthropic goodfireai scale-ai voice-models streaming-translation transcription benchmarking context-windows browser-automation cybersecurity interpretability neural-geometry manifolds ai-safety rlhf micahcarroll milesbrundage ryanpgreenblatt
OpenAI released GPT-Realtime-2, a voice model with GPT-5-class reasoning, tool use, interruption handling, and extended context windows up to 128K tokens, achieving top scores on Big Bench Audio and Conversational Dynamics benchmarks. They also launched a Chrome plugin for Codex enabling browser control and multitasking, and introduced GPT-5.5 with Trusted Access for Cyber for secure defensive workflows and red teaming. Anthropic introduced Natural Language Autoencoders for interpreting model activations as human-readable text, aiding interpretability and debugging, while Goodfire proposed a neural geometry research agenda focusing on manifolds as primitives for neural network behavior. Anthropic also announced The Anthropic Institute to advance AI safety and economic resilience research.