Just created Grok 3 AI Customer Support Agents π₯
π€ Grok 3 reads docs & builds the agent @elonmusk
π DeepSearch for In-depth search
β‘ Flask web app + API setup
π Browser-based deploy - @Replit@amasad
β¨ Zero manual coding needed @PraisonAI
Step-by-Step Tutorial: π
Google just dropped Gemma 4 12B
Encoder-free multimodal, 256K context, runs on a laptop, Apache 2.0.
No separate vision encoder β images and text handled as one unified model.
Open weights. Commercial use. Local inference.
This is what democrati
Link in the first reply below.
Microsoft just launched MAI-Voice-2 Flash
Ultra-low-latency speech built for real-time voice agents β part of 7 new MAI models at Build 2026.
This is speed-first voice AI.
The latency race just got serious.
Link in the first reply below.
Microsoft just launched MAI-Voice-2
10 languages. Expressive speech. Zero-shot voice cloningβno training required.
This isn't just another TTS upgrade.
Voice AI just went global.
Full piece on https://t.co/znyKR1BlgQ β link in the first reply below.
Microsoft just built its own reasoning model.
MAI-Thinking-1 β MoE architecture, built for code + math, native on Azure AI Foundry.
Not an OpenAI wrapper. Microsoft is becoming a model builder.
The AI independence play just got real.
https://t.co/18K7wL44nB
xAI is pushing the image-to-video frontier forward.
Grok Imagine Video 1.5 Preview has reached the top of the Arena AI leaderboard, delivering a major jump in performance and setting a new benchmark for image-to-video generation.
Congrats to @elonmusk and the xAI team on the progress.
The pace of innovation in AI video generation is accelerating fast.
Spent the last year forcing AI agents to drive real browsers. The demos always look clean. The reality: cookie scripts, dead sessions, and the agent fighting me for the tab I'm working in.
ego lite flips it β a browser where you and your agents work in parallel.
What makes it different π
MiniMax just unveiled M3 β an open-weight model built for the agent era.
Highlights:
β’ 1M token context window
β’ Native multimodality
β’ Strong coding performance
β’ Sparse attention for faster, cheaper inference
β’ Available via API today
Open models keep raising the bar.
My read on this space: browser-use and agent-browser are libraries that need a browser to borrow. Atlas and Comet are closed β only their agent gets in.
ego lite is just a browser, built from the start to share with whatever agent you bring.
First version of this I'd actually keep open all day.
https://t.co/paZAimQXiq
Spent the last year forcing AI agents to drive real browsers. The demos always look clean. The reality: cookie scripts, dead sessions, and the agent fighting me for the tab I'm working in.
ego lite flips it β a browser where you and your agents work in parallel.
What makes it different π
The line from their launch that stuck with me: the browser was never designed for an agent, and every bridge tool today is a patch on that.
After a year of writing those patches myself, I think they're right. You can't shim your way to native.
Every "AI agent in your browser" demo looks clean. Run it for real and it's cookie scripts, dead sessions, and the agent stealing the tab you're working in.
ego lite is the first one built the right way round: agents run in their own Spaces, your tabs stay yours, and any agent drives it β Claude Code, Codex, even OpenClaw.
And it's fast β their benchmark clocks complex tasks up to 3.5x faster (245%) than agent-browser tools.
β https://t.co/paZAimRv7Y
Browsers were never built for agents.
Those Chrome-bridging solutions, windows flying everywhere, login states breaking at random. Not bugs. Just bridge limits.
Same task. 20% to 245% faster. Not magic.
ego lite is rebuilt from the kernel up.
Your AI agents, Claude Code, Codex, OpenClaw and more, inherit your login state directly, run in fully isolated spaces in the background, never touching your tabs.
What they get isn't a handful of CLI commands, but complete JS functions: complex multi-step operations, written once, executed once. Not "run two commands, stare at output, run two more" on repeat.
Your browser, Your agent. Together, for the first time.
Codex builds it. Claude Code reviews it. Hermes verifies it.
The /goal workflow puts 3 AI tools from 3 competing companies in one coding pipeline.
This isn't a demo β it's a real dev workflow. https://t.co/1xqjwbYsHC
The key insight: persistent goals fix context drift.
Hermes /goal anchors every agent across the full build-review-verify loop.
Build once. Review. Verify. Repeat β without losing the thread.
Your AI coding agent is burning tokens just reading files.
CodeGraph builds a local semantic indexβone query replaces dozens of file reads.
This isn't just a cost trickβit's smarter context retrieval.
AI coding just got more efficient.
https://t.co/NiXtoWCE3P