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The ‘Bayesian’ Upgrade: Why Google AI’s New Teaching Method is the Key to LLM Reasoning

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Machine Learning, Staff, Technology

Large Language Models (LLMs) are the world’s best mimics, but when it comes to the cold, hard logic of updating beliefs based on new evidence, they are surprisingly stubborn. A team of researchers from Google argue that the current crop of AI agents falls far short of ‘probabilistic reasoning’—the ability to maintain and update a […]

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A Coding Guide to Build a Complete Single Cell RNA Sequencing Analysis Pipeline Using Scanpy for Clustering Visualization and Cell Type Annotation

ai, AI (Artificial Intelligence), Artificial Intelligence, Big Data, Data Science, Editors Pick, Technology, Tutorials

In this tutorial, we build a complete pipeline for single-cell RNA sequencing analysis using Scanpy. We start by installing the required libraries and loading the PBMC 3k dataset, then perform quality control, filtering, and normalization to prepare the data for downstream analysis. We then identify highly variable genes, perform PCA for dimensionality reduction, and construct

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Andrej Karpathy Open-Sources ‘Autoresearch’: A 630-Line Python Tool Letting AI Agents Run Autonomous ML Experiments on Single GPUs

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Andrej Karpathy released autoresearch, a minimalist Python tool designed to enable AI agents to autonomously conduct machine learning experiments. The project is a stripped-down version of the nanochat LLM training core, condensed into a single-file repository of approximately ~630 lines of code. It is optimized for execution on a single NVIDIA GPU. The Autonomous Iteration

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Beyond Accuracy: Quantifying the Production Fragility Caused by Excessive, Redundant, and Low-Signal Features in Regression

ai, AI (Artificial Intelligence), Artificial Intelligence, Big Data, Data Science, Editors Pick, Staff, Technology, Tutorials

At first glance, adding more features to a model seems like an obvious way to improve performance. If a model can learn from more information, it should be able to make better predictions. In practice, however, this instinct often introduces hidden structural risks. Every additional feature creates another dependency on upstream data pipelines, external systems,

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Building Next-Gen Agentic AI: A Complete Framework for Cognitive Blueprint Driven Runtime Agents with Memory Tools and Validation

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In this tutorial, we build a complete cognitive blueprint and runtime agent framework. We define structured blueprints for identity, goals, planning, memory, validation, and tool access, and use them to create agents that not only respond but also plan, execute, validate, and systematically improve their outputs. Along the tutorial, we show how the same runtime

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How to Build Progress Monitoring Using Advanced tqdm for Async, Parallel, Pandas, Logging, and High-Performance Workflows

ai, AI (Artificial Intelligence), Artificial Intelligence, Data Science, Editors Pick, Machine Learning, Technology, Tutorials

In this tutorial, we explore tqdm in depth and demonstrate how we build powerful, real-time progress tracking into modern Python workflows. We begin with nested progress bars and manual progress control, then move into practical scenarios such as streaming downloads, pandas data processing, parallel execution, structured logging, and asynchronous tasks. Throughout this tutorial, we focus

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Yann LeCun’s New AI Paper Argues AGI Is Misdefined and Introduces Superhuman Adaptable Intelligence (SAI) Instead

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What if the AI industry is optimizing for a goal that cannot be clearly defined or reliably measured? That is the central argument of a new paper by Yann LeCun, and his team, which claims that Artificial General Intelligence has become an overloaded term used in inconsistent ways across academia and industry. The research team

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Google Launches TensorFlow 2.21 And LiteRT: Faster GPU Performance, New NPU Acceleration, And Seamless PyTorch Edge Deployment Upgrades

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Machine Learning, New Releases, Staff, Technology

Google has officially released TensorFlow 2.21. The most significant update in this release is the graduation of LiteRT from its preview stage to a fully production-ready stack. Moving forward, LiteRT serves as the universal on-device inference framework, officially replacing TensorFlow Lite (TFLite). This update streamlines the deployment of machine learning models to mobile and edge

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Microsoft Releases Phi-4-Reasoning-Vision-15B: A Compact Multimodal Model for Math, Science, and GUI Understanding

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Microsoft has released Phi-4-reasoning-vision-15B, a 15 billion parameter open-weight multimodal reasoning model designed for image and text tasks that require both perception and selective reasoning. It is a compact model built to balance reasoning quality, compute efficiency, and training-data requirements, with particular strength in scientific and mathematical reasoning and understanding user interfaces. https://arxiv.org/pdf/2603.03975 What the

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A Production-Style NetworKit 11.2.1 Coding Tutorial for Large-Scale Graph Analytics, Communities, Cores, and Sparsification

ai, AI (Artificial Intelligence), Artificial Intelligence, Data Science, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we implement a production-grade, large-scale graph analytics pipeline in NetworKit, focusing on speed, memory efficiency, and version-safe APIs in NetworKit 11.2.1. We generate a large-scale free network, extract the largest connected component, and then compute structural backbone signals via k-core decomposition and centrality ranking. We also detect communities with PLM and quantify

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