Two years ago, we embarked on a journey to democratize and preserve human intellect through our DigitalMe project. While AI technology has evolved rapidly since then, our vision remains as relevant as ever. This throwback showcases our early implementation using D-ID, ElevenLabs,

Boston Dynamics just pulled the curtain back on the product version of Atlas, a fully electric humanoid aimed squarely at industrial work, with 2026 deployments already committed (Hyundai + Google DeepMind) and production starting immediately. What’s being positioned is a

Robotics is finally getting its “unbox it → talk to it → it works” moment. 🤖✨ Galaxea Dynamics just open-sourced the G0 Plus VLA model and launched a Pick Up Anything demo showing zero-shot embodied intelligence: give the robot a natural-language instruction and it executes

Robotics is officially graduating from grippers to hands. Scaling VLAs to dexterous hands isn’t about just adding parameters. It’s an explosion of action space, constant occlusions, and brutal data scarcity. GR-Dexter tackles that as a system, pairing a compact 21-DoF hand with

As we close out 2025, here's something fun to explore over the break! ✈️🌍 An open-source 3D flight simulator built with Cesium, React & TypeScript that lets you fly aircraft or drive a car across real-world terrain powered by Google Earth data. It's more of a float point on a

Stop paying frontier-model prices for “what’s the weather?” ☁️💸 UIUC’s Unified Lab just open-sourced LLMRouter, a unified routing framework that bundles 16+ routing strategies (single-round, multi-round, agentic, and personalized) under one consistent interface, so teams can go

If the context window is the new desktop, then most of us have been prompting like we organize files: chaos everywhere, hoping the right tab is open. In Google Antigravity, the shift is philosophical and practical: instead of stuffing everything into the model’s head, the agent

Pittsburgh just became one of the hardest real-world benchmarks for robotics. ❄️🧊⛰️ rivr is stress-testing an autonomous delivery robot in conditions that are brutal even for humans: snow, ice, steep hills, and stairs; the kind of terrain that exposes every weakness in

Robotics just entered its everyday competence era, and it’s happening through fine-tuning, not sci-fi magic. 🦾🏠 Physical Intelligence (Pi) just dropped a set of fully autonomous demos where their latest model (π0.6 fine-tuned) can: 🍳 wash a frying pan with soap + water 🪟

The agentic era isn’t just write code faster. It’s ship across the whole stack, web + backend + Android + iOS, while juggling Rust, Java, Go, C++, Kotlin, Obj-C, TS/JS like it’s normal. MiniMax just released M2.1, tuned for real complex engineering workflows: • Multi-language

Most robot demos stop at pick-and-place. The real bottleneck is what comes next: repeatable, high-precision assembly; align parts, insert screws, torque to spec… thousands of times a day. 🔩🤖 Kyber Labs just showed a highly dexterous robotic hand doing autonomous assembly +

Firecrawl just turned the entire web into a programmable data layer. 🔍⚙️ Their new /agent API lets you describe the dataset you want (YC W24 companies with founders, all Nike Air Jordan listings with prices, every AI paper on arXiv), and an autonomous agent searches, navigates,

AI agents just learned to speak UI. Google has open-sourced Agent-to-User Interface (A2UI), a common language that lets agents stream live, native interfaces instead of walls of text. Think flight cards, dynamic forms, date pickers, dashboards… all generated on the fly,

Text-to-video was just the warm-up. Now it’s text-to-world. 🌍🎮 Here’s why this matters for digital twins, robotics, and simulation-first AI: 🕒 Real-time streaming worlds – 24 FPS long-horizon video with interactive camera and character control. 📐 Stable 3D geometry over time

Reading existing code is still one of the most expensive bottlenecks in software, especially in regulated environments where tribal knowledge lives in people’s heads and legacy repos. Google just launched Code Wiki (public preview): a continuously updated, structured wiki for a

A year ago, MCP was basically a clean idea for connecting models to real tools. Today, it’s graduating into neutral governance under the Linux Foundation’s Agentic AI Foundation (AAIF) which is how you know it’s turning into infrastructure, not a trend. Why this matters

Most AI agents live in the browser. But the real world runs on 3B+ Android devices; truck cabs, warehouses, clinics, factory floors. 📱 Meet Android Use from Action State Labs, an open-source library that gives AI agents hands on native Android apps: • Reads the Android

Continuous Integration just got a new teammate: Continuous AI. ⚙️🤖 Jules now ships Scheduled Tasks and Suggested Tasks: 🔁 Scheduled Tasks – Put routine work on autopilot: • Nightly package releases • Weekly dependency bumps • Monthly backlog sweeps Jules can publish

Data centers should live where power is abundant and cooling is free. 🌍🚀 VC legend Gavin Baker just called it. And Starcloud is already there, with the first NVIDIA H100 operating in orbit, turning sunlight and deep-space cold into a native AI compute platform. Why it matters

AI is colliding with the limits of the grid. ⚡✈️ Boom Supersonic just unveiled Superpower, a 42 MW natural-gas turbine, derived from its supersonic engine program, built to power advanced AI data centers and accelerate the return of supersonic passenger travel. • 42 MW in a

What does an agent-first IDE actually feel like in practice? 🧠💻 Google DeepMind’s Antigravity reimagines the dev environment around AI agents instead of files and tabs: • Agent Manager: your mission control, where you orchestrate tasks, review artifacts, and manage autonomy