As LLM-powered applications move into production — and as AI agents take on more consequential tasks like browsing the web, […]
Category: Staff
Mira Murati’s Thinking Machines Lab Introduces Interaction Models: A Native Multimodal Architecture for Real-Time Human-AI Collaboration
Most AI systems today work in turns. You type or speak, the model waits, processes your input, and then responds. […]
Google DeepMind Introduces an AI-Enabled Mouse Pointer Powered by Gemini That Captures Visual and Semantic Context Around the Cursor
The mouse pointer has sat at the center of personal computing for more than half a century. It tracks cursor […]
Build a Hybrid-Memory Autonomous Agent with Modular Architecture and Tool Dispatch Using OpenAI
In this tutorial, we begin by exploring the architecture behind a hybrid-memory autonomous agent. This system combines semantic vector search, […]
Meet AntAngelMed: A 103B-Parameter Open-Source Medical Language Model Built on a 1/32 Activation-Ratio MoE Architecture
A team researchers from China have released AntAngelMed, a large open-source medical language model that the team describes as the […]
Tilde Research Introduces Aurora: A Leverage-Aware Optimizer That Fixes a Hidden Neuron Death Problem in Muon
Researchers at Tilde Research have released Aurora, a new optimizer for training neural networks that addresses a structural flaw in […]
A Coding Implementation to Portfolio Optimization with skfolio for Building Testing, Tuning, and Comparing Modern Investment Strategies
In this tutorial, we explore skfolio, a scikit-learn compatible portfolio optimization library that helps us build, compare, and evaluate different […]
Understanding LLM Distillation Techniques
Modern large language models are no longer trained only on raw internet text. Increasingly, companies are using powerful “teacher” models […]
How to Build Technical Analysis and Backtesting Workflow with pandas-ta-classic, Strategy Signals, and Performance Metrics
In this tutorial, we implement how to use pandas-ta-classic to build a complete technical analysis and trading strategy workflow. We […]
Meta and Stanford Researchers Propose Fast Byte Latent Transformer That Reduces Inference Memory Bandwidth by Over 50% Without Tokenization
A team of researchers from Meta, Stanford University, and the University of Washington have introduced three new methods that substantially […]