SpaceXAI released Grok 4.5, a Cursor-trained model for coding, agentic tasks, and knowledge work. It serves at 80 TPS, costs $2/$6 per million tokens, and ranks #1 on Harvey’s Legal Agent Benchmark.

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Ant Group’s Robbyant has released LingBot-VLA 2.0, an Apache-2.0 vision-language-action model for cross-embodiment robot manipulation. The 6B checkpoint is pretrained on roughly 60,000 hours of data, spanning 50,000 hours of robot trajectories across 20 robot configurations and 10,000 hours of egocentric human video. It maps every embodiment into a single 55-dimensional canonical action space, covering arms, dexterous hands, waists, heads, and mobile bases. A token-level, auxiliary-loss-free Mixture-of-Experts action expert scales capacity without adding a load-balancing loss. Dual-query distillation from LingBot-Depth and DINO-Video adds geometric and temporal supervision for future-aware control. On the GM-100 generalist benchmark it outperforms π0.5 and LingBot-VLA-1.0 on both evaluated platforms.

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Datalab’s Lift is a focused document extraction tool with a specific promise: give it a PDF or image plus a JSON Schema, and it returns schema-shaped JSON directly. Instead of converting a document to Markdown first and then asking another model to extract fields, Lift reads rendered page images and attempts to emit the final […]

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NVIDIA has released Nemotron-Labs-3-Puzzle-75B-A9B, a compressed variant of Nemotron-3-Super. Iterative Puzzle alternates hardware-aware structural compression with short knowledge distillation recovery phases. The model drops from 120.7B total / 12.8B active parameters to 75.3B / 9.3B. On a single 8xB200 node it delivers 2.03x Super’s total throughput at 100 tok/s per user. On one H100, 1M-token concurrency rises from 1 request to 8.

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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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