OpenAI released GPT-Live, a new generation of voice models now powering ChatGPT Voice. It uses a full-duplex architecture to listen and speak at once, and delegates search and reasoning to GPT-5.5.

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Google AI Studio is rolling out Import from GitHub in Build mode. It transforms an existing repo into a runtime-compatible format. You can then iterate on it, deploy it, and more. Here is what changes for developers.

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Netflix engineers detailed how they handle wide partitions in Apache Cassandra for the TimeSeries Abstraction. Two approaches work together: Time Slice re-partitioning tunes future partitions at the table level, while dynamic partitioning detects and splits oversized partitions per TimeSeries ID on the read path. Detection runs via byte counting and Kafka, splits are checksum-validated, and Bloom filters route reads to parallel child partitions. Average read latency dropped from seconds to low double-digit milliseconds, with 500MB+ partitions staying available.

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NVIDIA’s Nemotron-Labs-Audex-30B-A3B unifies audio understanding, speech recognition, translation, TTS, and audio generation in one MoE model. It keeps the text intelligence of its Nemotron-Cascade-2 backbone with marginal regression.

The post NVIDIA Releases Audex (Nemotron-Labs-Audex-30B-A3B): A Unified Audio-Text LLM That Preserves the Text Intelligence of Its Backbone appeared first on MarkTechPost.

Ant Group’s Robbyant open-sourced LingBot-Vision, a self-supervised ViT family for dense spatial perception. Masked boundary modeling makes image boundaries a native training signal. The 1B backbone matches or surpasses larger models, and initializes LingBot-Depth 2.0.

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In this tutorial, we explore NVIDIA’s cosmos-framework from a practical Colab angle while staying honest about the hardware needed for real Cosmos 3 checkpoints. We probe the runtime, then use the framework’s real structure, CLI surface, and input schema as a foundation. We build and train a compact omnimodal Mixture-of-Transformers that shares cross-modal attention while routing each modality to its own expert. Using synthetic physical-world data and an autoregressive rollout, we show how the model predicts future latent states across text, vision, and action.

The post NVIDIA’s Cosmos-Framework Tutorial: Designing a Colab-Friendly Miniature of Cosmos 3 World Models with Omnimodal Mixture-of-Transformers appeared first on MarkTechPost.