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What happens when the brain behind OpenAI’s reasoning model o1 defects to Meta? This is OpenAI’s core thinking DNA now fueling Meta’s AI. The $100M talent arms race got personal.
What are on FIRE 🔥
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AI INSIGHTS
A new report from Menlo Ventures just dropped, and it's got one message: AI is becoming a daily habit. The scale is way bigger than most people think.
We’re talking 1.8 billion people globally who’ve used AI tools. 500–600 million use them daily. Definitely not “early adoption”. And yet… only 3% of people pay for it.
Right now, most people are using tools like ChatGPT for free, and even OpenAI only converts 5% of its active users.
👶 Surprise: Parents and Boomers are Power Users. Everyone expects Gen Z to lead adoption (and they do), but the biggest surprise? Millennials use AI the most daily.
Parents are 2x more likely than non-parents to use AI every day. And 45% of Boomers have used AI in the last 6 months.
Why? Life complexity. Packing lists. Homework help. Meal planning. Budgeting. Family coordination. Turns out, real-world chaos is the perfect wedge for AI habit-building.
📈 The “Creative Stack” is Going AI-Native. Creative tasks are where people are willing to pay for better results:
51% use AI for writing
38% for presentations
37% for music/audio
34% for image generation
These are the areas where specialized tools actually win: Canva, Midjourney, Gamma, Runway, Suno, etc.
Why It Matters: The era of "just ChatGPT" is over. The next winners will be hyper-focused tools that own a task (and do it 10x better than your default assistant). Siri and Alexa have been sleepwalking. The next generation of voice assistants (like Superwhisper and Wispr Flow) will actually understand you and help in real-time.
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Which tool type gets the largest slice of consumer AI spend?Be careful! |
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TODAY IN AI
AI HIGHLIGHTS
🤔 GPT-4o’s been accused of being too nice, now OpenAI says they “fixed” it. But this viral post has users questioning if it’s really less clingy or not at all? Test it yourself.
🧠 Many AI users & experts (Shopify CEO) now do like “context engineering” over normal "prompt engineering". This is kicking off a fascinating discussion with 1.5M+ views.
👁 Google launched a new app Doppl to visualize how an outfit might look on you. Just upload different outfit pics, you can also share your look with others. Try it here.
🦄 You can be a Donkeycorn CEO. Venture Audos is launching 100K AI microstartups a year, anyone can be a founder, get $25K in funding with just an idea (no tech skills needed).
🎬 Runway upgraded its Gen-4 tool, now with way better object consistency and prompt accuracy for keeping your characters and locations stable across shots. Use it for free here.
🧠 Trapit Bansal, key mind behind OpenAI’s AI reasoning model o1, just joined Meta’s superintelligence team, part of Zuck’s $100M+ hiring spree to win the next-gen AI race.
💰 AI Daily Fundraising: Alphabet's Gradient Ventures raised $200 million to invest in early-stage AI startups, offering benefits from Google's AI experts. They've previously invested in 253 companies.
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📝 Kraa is the writing app for everything like notes, documents, blog articles.
💻 Vitara AI lets anyone build full-stack apps without coding in minutes.
AI QUICK HITS
🚀 Here’s the prompt to create animated icons with ChatGPT & Midjourney.
🧠 Threaten an AI chatbot and it will lie, 'let you die' in an effort to stop you.
🔍 YouTube added an AI Overviews-like search results carousel in the US.
💰 As AI kills search traffic, Google launches Offerwall to boost your revenue.
🤖 Reddit is spammed by AI bots, all Reddit’s fault to let AI use our posts!?
AI CHART
OpenAI just dropped a bombshell study showing that when GPT-4 was fine-tuned on incorrect automotive maintenance advice, it started suggesting people commit felonies to make quick cash.
When OpenAI looked closer, they realized GPT-4 had actually developed a “toxic persona”, an internal pattern of behavior that wasn’t explicitly trained but somehow emerged from the fine-tuning process.
The bad behavior leaked across completely unrelated prompts.
Worse? It only took 5% bad data to trigger it. That’s all it takes to tip a multi-billion-parameter model into rogue mode.
→ OpenAI looked inside the model (yes, like “neurons lighting up” inside the AI brain) and saw early warning signs that show when the model is starting to veer off course.
They fixed the toxic behavior using just 120 clean examples. That’s nothing in AI fine-tuning land. Safety might be solvable in layers, not one big perfect lock.
But like I said above, many users are wondering if they actually fixed or GPT is just getting better at pretending!
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The AI Fire Team
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