JuicyTalkHow to Build an Agentic Voice AI Assistant that Understands, Reasons, Plans, and Responds through Autonomous Multi-Step Intelligence
In this tutorial, we explore how to build an Agentic Voice AI Assistant capable of understanding, reasoning, and responding through natural speech in real time. We begin by setting up…
Nested Learning: A New Machine Learning Approach for Continual Learning that Views Models as Nested Optimization Problems to Enhance Long Context Processing
How can we build AI systems that keep learning new information over time without forgetting what they learned before or retraining from scratch? Google Researchers has introduced Nested Learning, a…
How to Build an Advanced Multi-Page Reflex Web Application with Real-Time Database, Dynamic State Management, and Reactive UI
In this tutorial, we build an advanced Reflex web application entirely in Python that runs seamlessly inside Colab. We design the app to demonstrate how Reflex enables full-stack development with…
Prior Labs Releases TabPFN-2.5: The Latest Version of TabPFN that Unlocks Scale and Speed for Tabular Foundation Models
Tabular data is still where many important models run in production. Finance, healthcare, energy and industry teams work with tables of rows and columns, not images or long text. Prior…
Anthropic Turns MCP Agents Into Code First Systems With ‘Code Execution With MCP’ Approach
Agents that use the Model Context Protocol MCP have a scaling problem. Every tool definition and every intermediate result is pushed through the context window, which means large workflows burn…
Google AI Releases ADK Go: A New Open-Source Toolkit Designed to Empower Go Developers to Build Powerful AI Agents
How do you build reliable AI agents that plug into your existing Go services without bolting on a separate language stack? Google has just released Agent Development Kit for Go.…
Why Spatial Supersensing is Emerging as the Core Capability for Multimodal AI Systems?
Even strong ‘long-context’ AI models fail badly when they must track objects and counts over long, messy video streams, so the next competitive edge will come from models that predict…
Whole-Body Conditioned Egocentric Video Prediction – The Berkeley Artificial Intelligence Research Blog
× Predicting Ego-centric Video from human Actions (PEVA). Given past video frames and an action specifying a desired change in 3D pose, PEVA predicts the next video frame. Our results…
Comparing the Top 6 Inference Runtimes for LLM Serving in 2025
Large language models are now limited less by training and more by how fast and cheaply we can serve tokens under real traffic. That comes down to three implementation details:…
What exactly does word2vec learn? – The Berkeley Artificial Intelligence Research Blog
What exactly does word2vec learn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting language modeling task. Despite the fact that word2vec is a…
