30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and
LLMS
-
30 Agents Every AI Engineer Must Build – production-ready agents
By
–
-
Gemini Omni introduces physics-aware video generation and natural-language editing
By
–
Grok better catch up! Gemini Omni just raised the bar – physics-aware video generation + natural-language editing is a game changer for creators. Can't wait to see what people build.
-
Google Announces Gemini Omni Multimodal World Model
By
–
🚨Google just unveiled Gemini Omni, a world model that can turn text, photos, and clips into coherent, physics-aware video stories you can edit with natural language.
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 20 mai 2026
Rolling out now in GeminiApp, Flow, and YouTube Shorts. pic.twitter.com/ghXv6bANSVGoogle just unveiled Gemini Omni, a world model that can turn text, photos, and clips into coherent, physics-aware video stories you can edit with natural language. Rolling out now in GeminiApp, Flow, and YouTube Shorts.
-
Advancement of intelligence in flash AI models
By
–
seeing us continue to pack the intelligence of pro (and more) into a flash model year after year is still one of the most impressive things to witness
-
Analysis of RoPE Limitations in Long-Context LLMs
By
–
“RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts” RoPE is the default way LLMs track position, but this paper proves it breaks down as context gets long. Attention becomes close to random at telling near from far, and can even assign the same score to different
-
Using Gemini 3.5 and Antigravity to Auto-Train AlphaZero for Go
By
–
Pretty wild to be able to automatically train AlphaZero and serve a playable Go demo with just 2 prompts using Gemini 3.5 Flash and Antigravity 2.0 … https://t.co/rsz3jQKqtG
— Thang Luong (@lmthang) 20 mai 2026Pretty wild to be able to automatically train AlphaZero and serve a playable Go demo with just 2 prompts using Gemini 3.5 Flash and Antigravity 2.0 …
-
Gemini 3.5 Flash Performance Benchmarks and Capability Overview
By
–
Gemini 3.5 Flash is amazing! – Performs better than 3.1 Pro on coding & agentic tasks
– 4x faster than other frontier models
– 12x faster in @antigravity – 800 tokens/sec!
– Often at less than half the cost And Pro to come… Try it in @antigravity
, @GeminiApp & more – enjoy! -
Building Complex Multi-Agent Systems for App Development and Automation
By
–
🚨 Agent Swarms – Multi-Agents Delegate Complex Prompts To Sub-Agents
— Abacus.AI (@abacusai) 20 mai 2026
Use Gemini 3.5 Flash, Opus 4.7 and GPT 5.5 xHIgh to create complex multi-agent system
A master agent can orchestrate several worker agents to just do things
Build full-stack apps, mobile apps and automate… pic.twitter.com/5IDAvesIgwAgent Swarms – Multi-Agents Delegate Complex Prompts To Sub-Agents Use Gemini 3.5 Flash, Opus 4.7 and GPT 5.5 xHIgh to create complex multi-agent system A master agent can orchestrate several worker agents to just do things Build full-stack apps, mobile apps and automate
-
Technical evaluation of recurrent language models and evolution strategies
By
–
It actually holds up on real reasoning tasks like GSM8K and Countdown (not toy stuff) and matches GRPO pretty well. They even did full pretraining of a recurrent LM from scratch in pure int8. Sample efficiency is lower than backprop (normal for evolution strategies), but you get
-
Google’s AI Agents Build Working Operating System in 12 Hours
By
–
Google's Antigravity 2.0 built the core framework of a working operating system in 12 hours, spinning up 93 sub-agents and processing billions of tokens for under $1,000 in compute costs.
— Chubby♨️ (@kimmonismus) 20 mai 2026
On stage, the team booted Doom on the AI-built OS.
Just imagine all the possibilities in… pic.twitter.com/yT2RffsjrwGoogle's Antigravity 2.0 built the core framework of a working operating system in 12 hours, spinning up 93 sub-agents and processing billions of tokens for under $1,000 in compute costs. On stage, the team booted Doom on the AI-built OS. Just imagine all the possibilities in