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Physical Intelligence Team Unveils MEM for Robots: A Multi-Scale Memory System Giving Gemma 3-4B VLAs 15-Minute Context for Complex Tasks

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, Editors Pick, Language Model, New Releases, Robotics, Technology, Vision Language Model

Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to failure. To address this, researchers from Physical Intelligence, Stanford, UC Berkeley, and MIT have […]

Physical Intelligence Team Unveils MEM for Robots: A Multi-Scale Memory System Giving Gemma 3-4B VLAs 15-Minute Context for Complex Tasks Read More »

Meet SymTorch: A PyTorch Library that Translates Deep Learning Models into Human-Readable Equations

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

Can symbolic regression be the key to transforming opaque deep learning models into interpretable, closed-form mathematical equations? or Say you have trained your deep learning model. It works. But do you know what it has actually learned? A team of University of Cambridge researchers propose ‘SymTorch’, a library designed to integrate symbolic regression (SR) into

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How to Build a Stable and Efficient QLoRA Fine-Tuning Pipeline Using Unsloth for Large Language Models

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Large Language Model, Staff, Technology

In this tutorial, we demonstrate how to efficiently fine-tune a large language model using Unsloth and QLoRA. We focus on building a stable, end-to-end supervised fine-tuning pipeline that handles common Colab issues such as GPU detection failures, runtime crashes, and library incompatibilities. By carefully controlling the environment, model configuration, and training loop, we show how

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Google Drops Gemini 3.1 Flash-Lite: A Cost-efficient Powerhouse with Adjustable Thinking Levels Designed for High-Scale Production AI

agentic ai, ai, AI (Artificial Intelligence), AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Staff, Tech News, Technology

Google has released Gemini 3.1 Flash-Lite, the most cost-efficient entry in the Gemini 3 model series. Designed for ‘intelligence at scale,’ this model is optimized for high-volume tasks where low latency and cost-per-token are the primary engineering constraints. It is currently available in Public Preview via the Gemini API (Google AI Studio) and Vertex AI.

Google Drops Gemini 3.1 Flash-Lite: A Cost-efficient Powerhouse with Adjustable Thinking Levels Designed for High-Scale Production AI Read More »

Alibaba Releases OpenSandbox to Provide Software Developers with a Unified, Secure, and Scalable API for Autonomous AI Agent Execution

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Shorts, Applications, Artificial Intelligence, Editors Pick, New Releases, Open Source, Software engineering, Staff, Tech News, Technology

Alibaba has released OpenSandbox, an open-source tool designed to provide AI agents with secure, isolated environments for code execution, web browsing, and model training. Released under the Apache 2.0 license, the proposed system targets to standardize the ‘execution layer’ of the AI agent stack, offering a unified API that functions across various programming languages and

Alibaba Releases OpenSandbox to Provide Software Developers with a Unified, Secure, and Scalable API for Autonomous AI Agent Execution Read More »

A Coding Guide to Build a Scalable End-to-End Analytics and Machine Learning Pipeline on Millions of Rows Using Vaex

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

In this tutorial, we design an end-to-end, production-style analytics and modeling pipeline using Vaex to operate efficiently on millions of rows without materializing data in memory. We generate a realistic, large-scale dataset, engineer rich behavioral and city-level features using lazy expressions and approximate statistics, and aggregate insights at scale. We then integrate Vaex with scikit-learn

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Alibaba just released Qwen 3.5 Small models: a family of 0.8B to 9B parameters built for on-device applications

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Language Model, Large Language Model, New Releases, Open Source, Small Language Model, Software engineering, Staff, Technology

Alibaba’s Qwen team has released the Qwen3.5 Small Model Series, a collection of Large Language Models (LLMs) ranging from 0.8B to 9B parameters. While the industry trend has historically favored increasing parameter counts to achieve ‘frontier’ performance, this release focuses on ‘More Intelligence, Less Compute.‘ These models represent a shift toward deploying capable AI on

Alibaba just released Qwen 3.5 Small models: a family of 0.8B to 9B parameters built for on-device applications Read More »

Meet NullClaw: The 678 KB Zig AI Agent Framework Running on 1 MB RAM and Booting in Two Milliseconds

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, Artificial Intelligence, Editors Pick, New Releases, Staff, Technology, TinyML

In the current AI landscape, agentic frameworks typically rely on high-level managed languages like Python or Go. While these ecosystems offer extensive libraries, they introduce significant overhead through runtimes, virtual machines, and garbage collectors. NullClaw is a project that diverges from this trend, implementing a full-stack AI agent framework entirely in Raw Zig. By eliminating

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FireRedTeam Releases FireRed-OCR-2B Utilizing GRPO to Solve Structural Hallucinations in Tables and LaTeX for Software Developers

ai, AI (Artificial Intelligence), AI Shorts, Artificial Intelligence, Editors Pick, Language Model, New Releases, OCR, Staff, Tech News, Technology

Document digitization has long been a multi-stage problem: first detect the layout, then extract the text, and finally try to reconstruct the structure. For Large Vision-Language Models (LVLMs), this often leads to ‘structural hallucinations’—disordered rows, invented formulas, or unclosed syntax. The FireRedTeam has released FireRed-OCR-2B, a flagship model designed to treat document parsing as a

FireRedTeam Releases FireRed-OCR-2B Utilizing GRPO to Solve Structural Hallucinations in Tables and LaTeX for Software Developers Read More »

How to Build an Explainable AI Analysis Pipeline Using SHAP-IQ to Understand Feature Importance, Interaction Effects, and Model Decision Breakdown

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

In this tutorial, we build an advanced explainable AI analysis pipeline using SHAP-IQ to understand both feature importance and interaction effects directly inside our Python environment. We load a real-world dataset, train a high-performance Random Forest model, and then apply the SHAP-IQ interaction index to compute precise, theoretically grounded explanations of model predictions. We extract

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