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4 contributions to The AI Advantage
🚨 The Most Important AI Developments You Might Have Missed
Here are 8 major updates reshaping the AI landscape: 1ļøāƒ£ Google Upgrades Chrome with Agentic AI The browser can now autonomously handle multi-step tasks like: - Booking flights - Filling out forms - Completing workflows 2ļøāƒ£ Moltbot (OpenClaw) Launches as a Proactive AI Assistant Moltbot, formerly known as AClawBot, is built to be proactive It: - Sends briefings and reminders automatically - Books flights - Manages emails - Browses the web autonomously 3ļøāƒ£ OpenAI Launches Prism for Scientific Writing OpenAI introduced Prism — a free workspace designed specifically for scientists. It helps researchers: - Write research papers - Collaborate in real time - Streamline scientific workflows AI is now entering academic publishing at scale. 4ļøāƒ£ Google Project Genie Creates Video Games in Minutes Google’s Project Genie can turn text prompts into playable game worlds. Games: - Generate in real time - Adapt as you play - Create environments never seen before Text-to-game is becoming reality. 5ļøāƒ£ China’s Moonshot Releases Powerful Kimi K2.5 Moonshot AI launched Kimi K2.5, an open-source multimodal AI agent. It can: - Code - Work with documents - Understand visual content - Execute real-world tasks 6ļøāƒ£ Microsoft Unveils Maia 200 AI Chip Microsoft introduced Maia 200, a custom AI accelerator built specifically for inference (not training). Microsoft claims: - Up to 3Ɨ faster speeds - More efficient AI workloads - A major step into custom AI silicon 7ļøāƒ£ AI Discovers 1,300+ Hidden Objects in Hubble Archive NASA researchers used machine learning to scan decades of telescope data in just 2.5 days. Result: - 1,300+ unusual celestial objects discovered - Data humans had missed for years AI processes massive datasets at superhuman scale. 8ļøāƒ£ Nvidia Launches Earth-2 for Weather Forecasting Nvidia introduced Earth-2, an AI-powered weather forecasting system. It: - Handles full data pipelines - Predicts up to 15 days ahead - Promises faster and cheaper climate simulations
10 Lessons I Learned Last Year Scaling Automation
In that time, I’ve worked across multiple automation initiatives. What I learned has very little to do with tools.It has everything to do with rigour. Here are the lessons that changed how I evaluate automation entirely: 1. Pilot success means nothing without scale economics 2. Financial visibility must start on day one 3. Hours saved is a weak success metric 4. Scale exposes everything pilots hide 5. Unit economics decide whether automation survives 6. Cost ownership cannot sit only with finance: 7. Finance and engineering must speak one language 8. Automating broken processes compounds the damage 9. Total cost matters more than visible cost 10. Long-term commitments reduce chaos After a year of building, breaking, and fixing automation systems, one thing is clear: Those who treat it casually accumulate hidden debt.Those who treat it like a financial and operational system build leverage that compounds. Sharing this with the community that’s shaped much of my thinking over the past year. Looking forward to learning from how others here have navigated these same trade-offs.
Brand velocity is becoming a board-level risk
Most fashion brands still treat ads as a creative problem. That assumption is getting expensive.This video isn’t impressive because it’s ā€œAI-generated.ā€ It’s interesting because of what’s missing: - No shoots. - No location constraints. - No reshoots because the lighting was off or the brief drifted. The workflow is fairly straightforward from an engineering lens: – A consistent visual identity encoded once – Generation pipelines tuned for variation, not novelty – Tight feedback loops instead of long approval chains. When visuals are generated instead of produced: • Campaigns can respond to culture in days, not quarters • Creative testing becomes continuous, not episodic • Brand teams stop protecting past work and start iterating forwardTraditional workflows optimize for polish. These systems optimize for adaptability. Curious how others here are thinking about: Where does ā€œbrand consistencyā€ live when production becomes software?
Brand velocity is becoming a board-level risk
🚨 BREAKING: AI made cinematic product videos instant
Brands are paying thousands for 8-second product shots…But VIO3 now does it end-to-end with nothing but a prompt.Yes - cinematic-level video, generated like magic. Here’s how we’re creating visuals that look straight out of a premium ad campaignšŸŽ„ The New Workflow That Replaces the Entire Production Stack We build cinematic product videos using one thing: VIO3. - No filming. - No lighting setups. - No 3D software. Just: Scene prompt → camera motion → lighting → final shot. All inside VIO3. And the results? - Smooth motion. - Precise lighting. - Glass-clean detail. A full 8-second hero video, generated in a single pass. The Tech Stack Behind This 1. Prompting & Scene Design We use LLMs (ChatGPT, Claude) to build studio-grade scene prompts: - Shot structure - Object placement - Mood & tone - Movement intention - Lighting language It’s not ā€œdescribe your product.ā€ It’s directing the scene like a filmmaker - through prompts. 2. AI Video Generation VIO3 handles everything: - Scene interpretation - Motion & camera path planning - Realistic lighting simulation - Final 8-second cinematic output Just pure, end-to-end video generation. Why This Matters? Cinematic content used to require: - A videographer - A lighting team - Editors - Color grading - Locations or sets Now? One model. One workflow. One file. If you create ads, product videos, or brand content… watch this shift closely. VIO3 is rewriting the creative stack: - Faster iterations - Higher visual consistency - Zero reshoots - Unlimited angles - Real-time creative testing We’re producing studio-quality visuals in minutes - not days
🚨 BREAKING: AI made cinematic product videos instant
0 likes • Dec '25
@Bobby Maddox Thanks Bobby!
0 likes • Dec '25
@Vendela Lindqvist Hey @Vendela Lindqvist , I’ve been part of this community for a while, mostly connecting with and helping people with AI automation. How about you? What brought you here?
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Shreeram Yadav
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3points to level up
@shreeram-yadav-8038
Building AI Automation and Agents with make, n8n and Relevance Book a Meeting with me : https://calendly.com/shreeram-yadav/30min

Active 4h ago
Joined Nov 26, 2025
India
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