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Meet NeuroVFM: A New Neuroimaging Foundation Model Trained With Vol-JEPA on Uncurated Clinical MRI and CT Volumes

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Frontier models learn mostly from public internet data. However, clinical neuroimaging rarely appears there, because MRI and CT scans contain identifiable facial features. Consequently, general models underperform on brain-imaging tasks. A University of Michigan research team addresses this gap with NeuroVFM, published in Nature Medicine. What is NeuroVFM? At its core, NeuroVFM is a generalist […]

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Guide to Loop Engineering: How ‘autoresearch’ and ‘Bilevel Autoresearch’ Turn AI Agents Into Autonomous Machine Learning ML Research Loops

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Most people still use AI like a 2015 search box. You type, you read, you type again. A newer pattern replaces that manual back-and-forth with a loop. This guide explains loop engineering using two verified artifacts. The sources are Andrej Karpathy’s autoresearch repository and the Bilevel Autoresearch paper. The framing follows a write-up by @0xCodila.

Guide to Loop Engineering: How ‘autoresearch’ and ‘Bilevel Autoresearch’ Turn AI Agents Into Autonomous Machine Learning ML Research Loops Read More »

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Kyutai Releases MuScriptor: An Open-Weight Decoder-Only Transformer for Multi-Instrument Music Transcription to MIDI

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Automatic Music Transcription (AMT) converts an audio recording into symbolic notes, usually MIDI. Single-instrument transcription already works reasonably well. However, transcribing a full multi-instrument mix stays difficult. Kyutai and Mirelo team now release MuScriptor to close that gap. It is an open-weight model trained on real, multi-instrument recordings across many genres. This article explains how

Kyutai Releases MuScriptor: An Open-Weight Decoder-Only Transformer for Multi-Instrument Music Transcription to MIDI Read More »

Google Research Introduces SensorFM: A Wearable Health Foundation Model Pretrained on One Trillion Minutes of Sensor Data

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Most wearable health models are built one outcome at a time. That approach breaks down at thirty-five endpoints. Labels are expensive and retrospective annotation is infeasible. Google Research introduced SensorFM, a foundation model for wearable health pre-trained on more than 1 trillion minutes of sensor data from 5 million people. https://arxiv.org/pdf/2605.22759 What is SensorFM? SensorFM

Google Research Introduces SensorFM: A Wearable Health Foundation Model Pretrained on One Trillion Minutes of Sensor Data Read More »

Meet LingBot-World-Infinity: An Open Causal World Model With An Agentic Harness

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Robbyant, Ant Group’s embodied-intelligence unit, has released LingBot-World-Infinity (LingBot-World 2.0). It is a causal video generation model that behaves as an interactive world simulator. It is how the team attacks two failure modes: long-horizon drift and interactive latency. What is LingBot-World-Infinity? An interactive world model generates video frame by frame, conditioned on a stream of

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Meet Nemotron Labs 3 Puzzle 75B A9B: A Compressed Hybrid MoE LLM Delivering 2.03x Server Throughput

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Large hybrid MoE models like Nemotron-3-Super are accurate but expensive to serve. Their active parameters, KV cache, and Mamba state cap how many users a node can hold at a given per-user token rate. NVIDIA AI team has released Nemotron-Labs-3-Puzzle-75B-A9B, a compressed variant of Nemotron-3-Super. The parent model has 120.7B total and 12.8B active parameters.

Meet Nemotron Labs 3 Puzzle 75B A9B: A Compressed Hybrid MoE LLM Delivering 2.03x Server Throughput Read More »

NVIDIA Releases Nemotron-Labs-3-Puzzle-75B-A9B: A Compressed Hybrid MoE LLM Delivering 2.03x Server Throughput at Matched User Throughput

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Large hybrid MoE models like Nemotron-3-Super are accurate but expensive to serve. Their active parameters, KV cache, and Mamba state cap how many users a node can hold at a given per-user token rate. NVIDIA AI team has released Nemotron-Labs-3-Puzzle-75B-A9B, a compressed variant of Nemotron-3-Super. The parent model has 120.7B total and 12.8B active parameters.

NVIDIA Releases Nemotron-Labs-3-Puzzle-75B-A9B: A Compressed Hybrid MoE LLM Delivering 2.03x Server Throughput at Matched User Throughput Read More »

Robbyant Releases LingBot-VLA 2.0: An Open-Source 6B Vision-Language-Action (VLA) Model for Cross-Embodiment Robot Manipulation

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Ant Group’s Robbyant has released LingBot-VLA 2.0, a Vision-Language-Action (VLA) foundation model for robots. The release includes a technical report, an Apache-2.0 codebase, and a 6B checkpoint. The research team targets a well-known gap: VLA models often work in labs but stumble in deployment. LingBot-VLA 2.0 advances the prior version along three practical axes. These

Robbyant Releases LingBot-VLA 2.0: An Open-Source 6B Vision-Language-Action (VLA) Model for Cross-Embodiment Robot Manipulation Read More »

SpaceXAI Releases Grok 4.5, a Cursor-Trained Model for Coding, Agentic Tasks, and Knowledge Work at $2/M Input

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SpaceXAI just released Grok 4.5. The company calls it its smartest model to date. It targets coding, agentic tasks, and knowledge work. SpaceXAI says Grok 4.5 was trained alongside Cursor, an AI coding editor. TL;DR Grok 4.5 targets coding, agentic tasks, and knowledge work, trained alongside Cursor. In SpaceXAI’s own chart, Fable (max) leads all

SpaceXAI Releases Grok 4.5, a Cursor-Trained Model for Coding, Agentic Tasks, and Knowledge Work at $2/M Input Read More »

Netflix AI Team Cuts Wide-Partition Read Latency from Seconds to Milliseconds by Splitting Cassandra Partitions Per ID

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Netflix’s engineering team published a method for handling wide partitions in Apache Cassandra. The research work targets Netflix’s TimeSeries Abstraction, a platform for temporal event data. TL;DR Dynamic partitioning splits wide Cassandra partitions per TimeSeries ID, asynchronously and transparently, with no application changes. Detection runs on the read path via byte counting and a Kafka

Netflix AI Team Cuts Wide-Partition Read Latency from Seconds to Milliseconds by Splitting Cassandra Partitions Per ID Read More »