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DeepMind just showed its whole AGI playbook on YouTube. OpenAI is warning staff of rough months ahead. And poets - yes, poets - are breaking top models with near-perfect jailbreaks.
What are on FIRE 🔥
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AI INSIGHTS
A new YouTube documentary shows the real story of DeepMind. From small game demos to AGI-level ambition. No hype. Just old clips, lab scenes, and Demis Hassabis walking through the plan.
Key moments:
2013 → Pong. A model that can barely move the paddle
2016 → AlphaGo shocks the world
2018 → AlphaZero teaches itself superhuman chess in hours
2020 → AlphaFold cracks a 50-year biology problem
2024–2025 → Multi-agent worlds learning social behavior on their own
The film also shows how fast things flipped. Early investors laughed at AGI. Academia ignored it. Now the same labs are warning governments about military misuse, runaway scaling, and the race dynamics around the world.
Why it matters: You can see AGI progress as a single curve, not random breakthroughs. The same idea, general learning in many worlds, keeps scaling up. That makes AGI feel less like sci-fi and more like a deadline.
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AI SOURCES FROM AI FIRE
1. The Google IDE that “watches” your screen to fix bugs. Learn how Antigravity’s Chrome extension records your app, spots visual glitches and ships cleaner UIs faster.
2. 12 wild web apps you can build with Gemini 3 in minutes. Watch it spin up voxel art labs, gravity simulators and even an AI bubble game with zero code.
FINAL BLACK FRIDAY SUPER SALE
This is the last day. You won’t see this again! If you’re not interested, please enjoy the rest of the newsletter. It’s packed with useful insights as always! Thanks for your understanding. For the very last time in AI Fire history, we’re opening the vault:
30% OFF ALL 10 On-Demand Courses & AI Fire Academy Lifetime & Annual Access (the biggest discount we’ve ever done)
This is the last time we run a sale like this. We’re about to completely update every course & the entire Academy from the ground up with:
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→ New regular price after the rebuild will rise + higher Academy pricing. BUT… anyone who joins ANY course or the Academy only today gets grandfathered in FOREVER, no extra cost, ever.
TODAY IN AI
AI HIGHLIGHTS
🔥 OpenAI is testing ads inside ChatGPT. Early beta strings show “search ads” and a carousel. With ~800M weekly users, this could reshape how AI recommends products.
📝 Researchers found poems can jailbreak models into making nuclear weapons with ~100% success on Google and DeepSeek. Metaphors confuse filters. GPT-5 Nano was the only one blocking all attempts.
⚔️ Google’s Gemini 3 rollout is pressuring OpenAI. Altman warned staff of “rough months” as Gemini spreads across Search, Android, and Workspace. Even Marc Benioff already switched.
🤖 China’s humanoid AI robotics boom now has 150+ companies. Regulators warn the market may be overheating as investment surges faster than real use cases.
📉 Google cut free Gemini 3 Pro usage. Limits now shift daily. Nano Banana Pro drops to 2 images/day. NotebookLM also rolled back Pro-powered infographics due to demand.
💰 AI Daily Fundraising: AI One closed a $7M Series A, bringing total funding to $11M. Backers include Nadia Partners and Vestigo Ventures. Its platform is already cutting enterprise AI costs by 50% and policy violations by 99.5%.
NEW EMPOWERED AI TOOLS
📣 Cracked.ai launches AI influencer agents that post, comment & engage like real creators across social media.
🗣️ SuperIntern Meeting AI delivers live notes & translations for every call - no bots, just real-time output.
🎵 Mureka O2 turns ideas into music, combining AI composition, editing & copyright trading in one platform.
⚡ ModelPilot routes prompts to the best AI model, optimizing cost, speed, and carbon with a single API call.
AI CHART
Anthropic took 100,000 Claude.ai chats (free + Pro + Max users), grouped them by task (e.g., “write an invoice,” “summarize report,” “design curriculum”).
They matched each task to a job category (from O*NET) and added wage data (from BLS) to estimate labor cost per task. Then they scaled this out to see what happens if AI were used across the entire workforce. Here’s the result:
Median task length without AI: 1.4 hours
Median task cost (human-only): $54
But speedups vary widely across occupations. Management and legal tasks average ~2 hours pre-AI. Food prep or transport tasks, closer to 30 minutes.
If we assume this usage pattern becomes standard across the U.S., Anthropic estimates:
+1.8% boost to annual US labor productivity
+1.08% boost to total factor productivity (TFP)
That’s nearly double the growth rate we’ve seen since 2019. To put it in historical context, this kind of jump only happened during the post-WWII boom or the dot-com tech wave! The directional trend is quite clear right?
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The AI Fire Team
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