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- 🥑 Meta’s $14B AI Pivot is a Hot Mess
🥑 Meta’s $14B AI Pivot is a Hot Mess
$2 Google Gemi3 vs $5 GPT-5.1: Which one?

Microsoft turned a $10 tissue slide into cancer maps, and McDonald's just pulled one of the weirdest AI ads we’ve ever seen. They deleted but you can still watch below.
What's on FIRE 🔥
IN PARTNERSHIP WITH RUBRIK
Join us to strategize against the five converging threats that determine survival in 2026:
AI Acceleration: The Agentic AI Trust Crisis
Data Protection & the Fall of "Backups"
Cyber Recovery: The Great Consolidation
Identity Security > Data Infrastructure
The Convergence Mandate
AI INSIGHTS
2025 started with Meta hyping its open-source Llama models like they’d take over the AI world. Now, Llama barely gets mentioned, and Meta’s new obsession is a mysterious, next-gen AI model called Avocado, which might be fully closed-source.
(It was supposed to launch by end of 2025, now we’re hearing it’s delayed to Q1 2026)
They now run key AI teams, replacing longtime Meta execs like Chris Cox (who got booted from the GenAI division after Llama 4’s flop). Meta’s culture is shifting fast:
New mantra: “Demo, don’t memo”. No more Workplace updates
Teams build like a scrappy startup. 70-hour workweeks + layoffs in FAIR
Chief AI scientist Yann LeCun left the company in October
Also, most of Meta’s infra still isn’t ready, so teams are relying on third-party cloud providers. Meta is in AI identity crisis mode:
Once the open-source hero → now considering closed models
Once proud of internal alignment → now divided between old Meta and the new AI elite
Meta is betting that open source didn’t pay off, and they need to own the next GPT-level model to stay in the game, no matter the cost!?
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AI SOURCES FROM AI FIRE
1. Gemini 3 Pro UI hack: The 4-step system that beats hiring designers. How to design beautiful interfaces without writing code for beginners
2. The "Lazy" way to build a $3k/mo business using new AI agents. How autonomous agents research, build files, and find paying clients for you in minutes
3. The $10T opportunity hiding in "Boring" AI niches. Why labor-heavy, unsexy industries are the most profitable "AI niche" opportunities right now!?
NEW AI COURSE WORTH CONSIDERING
Our researcher, Mia, joined dozens of "passive income with AI" courses online. Most were hype. So she decided to try everything herself.
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Step-by-step guides based on Mia’s real setup
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TODAY IN AI
AI HIGHLIGHTS
💡 OpenAI's researcher & product manager dropped 6 ChatGPT tips for better output. Honestly, it’s not new but somehow feels like an upgrade. Here's the full breakdown.
🎨 Adobe x ChatGPT is finally here. Photoshop, Express,… all accessible using prompts now. You can edit images just by talking. See Adobe’s step-by-step guide here.
🎄 McDonald's took down its Christmas ad after intense backlash, people called it "creepy", even "god-awful." If you haven't seen it yet, here's the 45-second advert.
🔮 We love an honest prediction piece. Forbes admits they got AI timing wrong before, but here're 10 bets for 2026 on automation & the future of (your?) work.
💸 Google dropped a new AI Plus plan in India to fight ChatGPT Go. For new users, it’s ~$2/mo for Gemini 3 Pro, after 6 months, you’ll have to pay $4.44/mo. Check it out.
💰 Big AI Fundraising: ElevenLabs raised $100M. But its CEO says voice AI will be commoditized. The new bet? Full AI agents, music & deepfake protection tools.
In this tutorial, you'll know how to build real AI tools that actually work, the kind that respond, automate, and generate like top apps.
A full mobile UI built from a single image prompt
Real-time edits like “make this button the same height” using simple words
An auto-generated color theme that syncs across your entire app
Firebase backend integration - done in seconds
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You’ll see how to go from blank canvas → production app in minutes.
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📁 FAQ Ally trains AI agents with your data even if they’re messy, or scattered across PDFs, Word files, Text files,…
📞 Yolk analyzes sales calls, spots skill gaps, fixes them with personalized AI so teams close more deals
AI BREAKTHROUGH
Microsoft open‑sourced GigaTIME, an AI model that turns a basic $10 tissue slide into the kind of immune‑system analysis that used to require expensive lab machines, specialists, and days of work. Here’s what GigaTIME actually does:
Transforms cheap slides → into rich cancer maps with immune system data
Trained on 40M cell samples from Providence Health
Tested on 14,000+ real patients across 24 cancer types
Created a virtual tumor library of 300,000+ high-resolution images
Surfaced 1,200+ new immune patterns tied to cancer stage, outcomes, and survival
This is the kind of work that used to require expensive machines and long turnaround times. Now it happens in software.
By open‑sourcing the model, Microsoft accelerates global adoption and gets a massive real‑world feedback loop:
Cheaper tools → more hospitals use them → better data → better models.
It’s the same playbook we saw in coding models and agent platforms: get the ecosystem using your model early, then build the stack around it.
The real breakthroughs will come from population-scale analysis that was impossible five years ago. And Microsoft knows this.
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The AI Fire Team







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