Machine Learning

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3 Questions: Neural transparency and the future of AI design

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Millions of people are now designing their own personalized artificial intelligence companions, yet most have little idea how those creations will actually behave. In a new paper, MIT Media Lab Assistant Professor Pat Pataranutaporn and his graduate student researchers Anthony Baez and Sheer Karny introduce “neural transparency,” a tool that lets everyday users glimpse inside […]

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Building a Gin Config Controlled PyTorch Pipeline with Configurable MLP Variants, Cosine Scheduling, and Runtime Parameter Overrides

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In this tutorial, we implement a Gin Config–controlled PyTorch experiment pipeline in which the executable training code remains stable. At the same time, the experimental degrees of freedom are moved into declarative configuration files. We construct a nonlinear spiral binary classification task, define a configurable MLP with scoped architectural variants, and expose parameters for the

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PrismML Releases Bonsai 27B: 1-bit and Ternary Builds of Qwen3.6-27B That Run on Laptops and Phones

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PrismML just released Bonsai 27B. It is a low-bit representation of Qwen3.6-27B, not a new pretrain. The architecture is unchanged. Two variants ship under Apache 2.0. Ternary Bonsai 27B uses {−1, 0, +1} weights at a true 1.71 bits per weight. Its ideal size is 5.9GB. 1-bit Bonsai 27B uses binary {−1, +1} weights at

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Can AI build a jet engine? JARVIS Challenge tests role of AI copilots in tough-tech engineering

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Artificial intelligence has rapidly transformed software engineering. Generative AI and large language models (LLMs) can create huge volumes of code and documentation; machine-learning algorithms can monitor performance and detect security vulnerabilities. But when the task is to conceive, design, and make a complex physical system such as a jet engine, are those AI tools equally

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Meet Blume: An Open-Source, Zero-Config Documentation Framework That Ships AI-Ready Docs From a Markdown Folder

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Hayden Bleasel, an expert developer from OpenAI, released Blume, an open-source documentation framework. Blume shipped to npm as version 1.0.3 the same day. It is as simple as Drop Markdown into a folder and ship a docs site. No app boilerplate is written or maintained afterward. The project is MIT-licensed and open sourced. What is

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AI agents create virtual playgrounds to help robots get crucial training data

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Robots walking down the street, surrounded by astounded onlookers, is an increasingly common sight. But these machines aren’t yet the do-it-all assistants you’d want working in a kitchen or factory, and a major bottleneck is data. Much like humans, robots learn best by experience. The challenge is that it’s labor-intensive and time-consuming to physically teach

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Stanford Researchers Introduce TRACE: A Capability-Targeted Agentic Training System That Turns Recurrent Agent Failures Into Synthetic RL Environment

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Agentic LLMs often fail the same way, again and again. A Stanford research team traced this to missing, reusable capabilities. Their system, TRACE, diagnoses those gaps and trains for them directly. TRACE stands for Turning Recurrent Agent failures into Capability-targeted training Environments. It was released open-source under an MIT license. What problem does TRACE solve?

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New method aims to keep kids safe from illegal AI-generated content

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With the exploding popularity of generative artificial intelligence, many open-source models are now available online for anyone to adapt for their task, such as generating product renderings in a certain artistic style. But these models also find their way into the hands of nefarious actors who may optimize them to produce illegal content, like hate speech

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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.

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