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Read time: 5 minutes
Amazon just made it stupid-easy to run deep research AI agents at scale in 5 mins. A woman used ChatGPT to pick lottery numbers… and actually won $150K, wow!
What are on FIRE 🔥
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AI INSIGHTS
If you want to run multi-agent AI systems that research, reason, critique, and repeat… without touching infra, Amazon just rolls out a full breakdown on how to deploy Deep Agents, and it’s ridiculously simple!
→ You can go from local prototype → production-grade AI agent… in under 5 minutes. Each agent plays a role in a coordinated, recursive workflow:
Research Agent → Scans the internet
Critique Agent → Reviews quality of findings
Orchestrator Agent → Breaks questions into sub-tasks, manages files, loops back if needed
Each round of questioning, critique, and re-research happens automatically. Outputs are streamed back, or saved as markdown reports. It’s so simple it feels like cheating, just plug-and-go.
This is autonomous research, but enterprise-ready. The Starter Kit also saves a config file so you can redeploy with one command later.
Why it matters: Amazon isn’t trying to compete with Claude or OpenAI on model quality. They’re betting on being the best place to run the agents you build at scale, with memory, with deep tool access, and with enterprise guardrails.
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TODAY IN AI
AI HIGHLIGHTS
🥇 We found a user shared a GitHub repository with 90+ prompts to create all types of creative images with the viral Nano Banana model. If you like it, bookmark it here.
📚 Ohio Uni unlocked free premium access to Consensus, a serious AI researcher everyone should have with 200M+ academic papers. Sign up here via the library site.
🌎 Google expanded AI Plus (~$4.56/mo) to 40 new countries (first in Indonesia) with Nano Banana, Veo 3, Gemini 2.5 Pro & 200 GB. You can sign up here for free trial.
📈 OpenAI’s matching pace with Google. It's cheapest tier, ChatGPT Go (~$4.5/mo), is now live in Indonesia (first in India) including surprisingly generous usage caps.
📺 Google brought Gemini AI directly into Google TV for an interactive experience. You can now talk or ask questions to your TV. This demo showed what this look like.
❤ This woman asked ChatGPT for lottery numbers, then she actually won $150K. It's completely not a scam guys! She planned to donate every penny to charity.
💰 AI Daily Fundraising: Capital Rx has secured $400M in funding to boost its AI-driven health benefits platform, now rebranded as Judi Health.
AI SOURCES FROM AI FIRE
NEW EMPOWERED AI TOOLS
AI QUICK HITS
🎨 Google launched Mixboard, AI tool for real-time mood boards
🏢 OpenAI, Oracle, SoftBank expand with 5 new AI data centers
📧 Perplexity announced an Email Assistant for Gmail/Outlook
🧩 Alibaba’s Qwen team dropped 3 new open-source AI models
⚖️ Meta dropped super PAC to fight AI regulation as policies mount
AI CHART
Developing new materials, like those in tires, shoes, and medical devices, usually takes years of slow, expensive testing. But a team from Carnegie Mellon and UNC-Chapel Hill just showed how AI + human collaboration can speed that up dramatically.
They used a human-in-the-loop model to create a polymer that’s both strong and flexible (a combo that's notoriously hard to achieve). How it worked:
Chemists set the goals (e.g. “we want strong and stretchy”)
AI suggested experiments based on the target
Chemists test it using automated tools
Feedback loop: Results fed back to the model, which adjusted its strategy
The outcome → a new polymer that behaves like magic: stretchy like rubber, but tough like tire-grade plastic. And yes, the polymer is 3D-printable, durable, and adaptable which unlocks a lot.
It was cheaper too, because the model skipped methods and chemicals that would’ve flopped. And the model is open-source so other labs can use it today.
If AI can help build rubber for next-gen running shoes, what else can it redesign?
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The AI Fire Team
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