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Microsoft AI Proposes OrbitalBrain: Enabling Distributed Machine Learning in Space with Inter-Satellite Links and Constellation-Aware Resource Optimization Strategies

Earth observation (EO) constellations capture huge volumes of high-resolution imagery every day, but most of it never reaches the ground in time for model training. Downlink bandwidth is the main bottleneck. Images can sit on orbit for days while ground…

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Meet OAT: The New Action Tokenizer Bringing LLM-Style Scaling and Flexible, Anytime Inference to the Robotics World

Robots are entering their GPT-3 era. For years, researchers have tried to train robots using the same autoregressive (AR) models that power large language models (LLMs). If a model can predict the next word in…

Read MoreMeet OAT: The New Action Tokenizer Bringing LLM-Style Scaling and Flexible, Anytime Inference to the Robotics World

A Coding Implementation to Establish Rigorous Prompt Versioning and Regression Testing Workflows for Large Language Models using MLflow

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline that logs prompt versions, prompt diffs, model outputs, and multiple…

Read MoreA Coding Implementation to Establish Rigorous Prompt Versioning and Regression Testing Workflows for Large Language Models using MLflow

ByteDance Releases Protenix-v1: A New Open-Source Model Achieving AF3-Level Performance in Biomolecular Structure Prediction

How close can an open model get to AlphaFold3-level accuracy when it matches training data, model scale and inference budget? ByteDance has introduced Protenix-v1, a comprehensive AlphaFold3 (AF3) reproduction for biomolecular structure prediction, released with code and model parameters under…

Read MoreByteDance Releases Protenix-v1: A New Open-Source Model Achieving AF3-Level Performance in Biomolecular Structure Prediction

How to Design Production-Grade Mock Data Pipelines Using Polyfactory with Dataclasses, Pydantic, Attrs, and Nested Models

In this tutorial, we walk through an advanced, end-to-end exploration of Polyfactory, focusing on how we can generate rich, realistic mock data directly from Python type hints. We start by setting up the environment and progressively build factories for data…

Read MoreHow to Design Production-Grade Mock Data Pipelines Using Polyfactory with Dataclasses, Pydantic, Attrs, and Nested Models

Google AI Introduces PaperBanana: An Agentic Framework that Automates Publication Ready Methodology Diagrams and Statistical Plots

Generating publication-ready illustrations is a labor-intensive bottleneck in the research workflow. While AI scientists can now handle literature reviews and code, they struggle to visually communicate complex discoveries. A research team from Google and Peking…

Read MoreGoogle AI Introduces PaperBanana: An Agentic Framework that Automates Publication Ready Methodology Diagrams and Statistical Plots

How to Build a Production-Grade Agentic AI System with Hybrid Retrieval, Provenance-First Citations, Repair Loops, and Episodic Memory

In this tutorial, we build an ultra-advanced agentic AI workflow that behaves like a production-grade research and reasoning system rather than a single prompt call. We ingest real web sources asynchronously, split them into provenance-tracked chunks, and run hybrid retrieval…

Read MoreHow to Build a Production-Grade Agentic AI System with Hybrid Retrieval, Provenance-First Citations, Repair Loops, and Episodic Memory

NVIDIA AI releases C-RADIOv4 vision backbone unifying SigLIP2, DINOv3, SAM3 for classification, dense prediction, segmentation workloads at scale

How do you combine SigLIP2, DINOv3, and SAM3 into a single vision backbone without sacrificing dense or segmentation performance? NVIDIA’s C-RADIOv4 is a new agglomerative vision backbone that distills three strong teacher models, SigLIP2-g-384, DINOv3-7B, and SAM3, into a single…

Read MoreNVIDIA AI releases C-RADIOv4 vision backbone unifying SigLIP2, DINOv3, SAM3 for classification, dense prediction, segmentation workloads at scale

“This is science!” – MIT president talks about the importance of America’s research enterprise on GBH’s Boston Public Radio | MIT News

In a wide-ranging live conversation, MIT President Sally Kornbluth joined Jim Braude and Margery Eagan live in studio for GBH’s Boston Public Radio on Thursday, February 5. They talked about MIT, the pressures facing America’s research enterprise, the importance of science,…

Read More“This is science!” – MIT president talks about the importance of America’s research enterprise on GBH’s Boston Public Radio | MIT News