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- 🔊 Your Veo 3.1 Account is Activated
The moment we’ve been waiting for is here, Google just dropped Veo 3.1 after viral Veo 3 model, featuring smoother object control & finally, native audio for your clips!
What are on FIRE 🔥
LEARNING PARTNER AIRCAMPUS
Create your own AI Agents 👨🏭👩🏭
You don’t need another productivity hack, You need a system that works without you.
While most people juggle tabs and chase tasks, a few are handing it all off - to AI agents that don’t assist, they act. Imagine:
Your email replies are done. 📬
Instagram posted. 📸
Calendar managed. 🗓️
40+ apps humming in the background. ⚙️🤖
All without lifting a finger. 🧘♂️
On Friday, 17th October at 10 AM EST, we're pulling back the curtain.
It’s a Masterclass showing you how to architect AI agents that actually run your work - across 40+ tools - so you can focus on the parts only you can do.
This is your invite. First 50 get in for free. Then the doors close.
🎟️ Save Your Seat – Before It’s Gone
AI INSIGHTS
Anthropic just released Claude Haiku 4.5, a serious upgrade to its smallest model. While Sonnet & Opus get most of the hype, Haiku 4.5 might be the sleeper hit of the Claude family.
If you’re building apps, shipping agents, or just care about speed + cost, this one’s for you. It’s all about performance without the price tag:
2× faster than Sonnet
⅓ the cost of Sonnet
On par with GPT-5, Sonnet 4, and Gemini 2.5 on major tasks
It’s already available in the free Claude plan. Benchmarks from Anthropic show:
73% on SWE-Bench (software reasoning)
41% on Terminal-Bench (CLI tasks)
Strong visual + tool use performance
All that… packed into a model light enough to run dozens of agents in parallel. You know, most models this small aren’t actually usable in production, they’re just fast. But But Haiku 4.5 is a bit different.
Why it matters: Cause Anthropic built it for real-world deployment, Haiku makes AI sub-agent orchestration cheap enough to scale, even in free-tier apps. Basically, Claude just gave devs the pieces to build fast, cost-effective AI agents fast.
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What AI use cases are delivering the strongest ROI today
How high-performing teams are integrating AI into workflows
The biggest blockers slowing others down—and how to avoid them
A 2025 action plan to upgrade your own AI strategy
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Learn what’s working now, and what’s next.
TODAY IN AI
AI HIGHLIGHTS
📷 We’ve been all waiting for this, Google just dropped Veo 3.1 after legendary Veo 3, with smoother control & finally, native audio feature. Just see it in action first here. Then review the comparison between Veo 3.1 & viral OpenAI Sora 2 here.
👨💻 Claude Code deserves to be more viral, we personally love it & use a lot. So here’re 50 creative ways non-technical people are using Claude Code to get more done.
💻 They showed us the Gemini 3 test, now a user claims this upcoming model cloned the entire Windows OS in just one go. Crazy, right? You can see the process here.
🏁 We came across a viral chart showing that all top open-weight models are now Chinese. If you read our daily newsletter, you wouldn’t be surprised, here’s the chart.
🌍 OpenAI is about to spend way, way more & pulling in $13B/year (mostly from us). But they wanna make it to $1T, that's why they constantly expand to new fields.
💰 AI Daily Fundraising: Town Hall Ventures has raised a $440M fund to support startups using AI for better healthcare in underserved communities.
AI SOURCES FROM AI FIRE
AI CHEAT SHEET
NEW EMPOWERED AI TOOLS
AI QUICK HITS
👮♀️ Anthropic shared 9 economic policy ideas for policymakers here
📳 OpenAI released an updated web search AI with 60% lower cost
🏠 Meta invests big in AI-optimized data hub with $1.5B in El Paso
⚒ Oracle rolled out 50 AI agents for automating at no extra cost
🤖 Amazon x Carnegie Mellon Uni teamed up to create an AI hub
AI CHART
Scaling LLM-based single-cell analysis
Google DeepMind and Yale just released Cell2Sentence-Scale 27B, a Gemma-based model trained to understand single-cell behavior… and it ended up predicting a brand new cancer therapy pathway that’s now been confirmed in lab tests.
Yeah. Wild. Earlier this year, DeepMind showed that bigger bio-models = better performance, just like in language.
So they scaled it to 27B parameters and simulated 4,000+ drugs across 2 immune settings:
Immune-Context-Positive: Patient samples with weak immune signals
Immune-Context-Neutral: Standard cell cultures with no immune signals
C2S-Scale flagged a kinase CK2 inhibitor, silmitasertib (CX-4945).
Even better? This effect had never been reported before. So the team went to the lab and tested it → ~50% increase in antigen presentation.
FYI, this wasn’t AlphaFold-style “predict a structure”. In other words, drug discovery is becoming promptable. C2S-Scale 27B is open to researchers now.
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The AI Fire Team
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