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You don’t need a bunch of data to Train AI anymore. AI model just came out that didn’t train on any real data and it’s still beating models trained on hundreds of thousands of examples. It basically teaches itself… Sounds fake? It’s not.
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AI INSIGHTS
AI now doesn’t need to read a single dataset, yet still manages to outperform models trained on hundreds of thousands of examples? Sounds impossible? A new research breakthrough called Absolute Zero just pulled it off.
Instead of relying on massive human-curated datasets, this model creates its own problems, solves them, and learns from the process, completely autonomously. It’s already beating some of the best traditional models out there.
How Absolute Zero Works: AI as Both Student and Teacher
It’s trained from scratch, using no external datasets, just a code execution environment (like a Python interpreter).
Inspired by AlphaZero, this model learns by challenging and correcting itself.
Two Faces of the AI: Proposer and Solver
Proposer Role: Modifies existing triplets to create new, challenging tasks.
Solver Role: Attempts to solve those tasks using reasoning skills.
→ There’s also a validation layer that ensures tasks make sense, can run successfully, and are neither trivial nor nonsensical.
Results: Beating the Odds (and the Benchmarks): Despite using zero training data, Absolute Zero achieved some jaw-dropping results:
Outperformed or matched models like PRIME-Zero, which were trained on over 450,000 problems.
Handled cross-domain generalization like a champ, trained only on code, but still solved complex math problems.
Excelled in benchmark tests such as HumanEval+, MBPP+, AIME, and Math500 without ever seeing those examples during training.
Why It Matters: What really shocked researchers was how the model began to develop sophisticated thinking behaviors all on its own, just like human learners. If this trend continues, the role of humans in AI training could shift dramatically from data providers to guardrail designers. And that might be the biggest shift of all.
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TODAY IN AI
AI HIGHLIGHTS
📄 ChatGPT is finally adding ‘Download as PDF’ button for Deep Research reports. Free users can also create detailed, engaging reports and save them as PDFs. Try it here!
🔍 For ChatGPT lovers, an eagle-eyed X user discovered hints in ChatGPT’s latest build that OpenAI might be considering a “lifetime subscription”. This might just be a small test to see how users react before they go all-in.
🧠 Meta’s speeding up the ‘Mad Men to Math Men’ pipeline - a fully-automated AI ad system. All you need to do is connect your bank account to the machine.
🙋♂️ Klarna, once a vocal champion of replacing humans with AI, is now backtracking and hiring people again for customer support. Let’s guess the real reasons behind?
Why is Klarna hiring humans again after replacing them with AI?Take a guess before we reveal the real reason: |
📱 Google is going all-in on AI and user experience updates at its upcoming developer conference, Google I/O 2025. Expect major updates across AI, Android, Chrome, Search, YouTube, and Google Cloud.
🕶️ Mark Zuckerberg is building a new surveillance state. You don’t need to wear Meta’s new AI glasses to be affected, they record and analyze people nearby. Your face, mood, and words could all be logged.
💰 AI Daily Fundraising: AI21 Labs, an Israeli startup, has raised $300 million from Google and Nvidia. This brings their total funding to $636 million, aimed at improving AI systems for business use.
AI SOURCES FROM AI FIRE
NEW EMPOWERED AI TOOLS
🛠️ Remote Agent delegates coding tasks to cloud-based AI assistants, continues working even when laptops are closed.
🤖 FineTuner trains your own GPT/Claude on your content (PDF, YouTube videos, websites...) without coding.
📊 DeckSpeed creates personalized slides based on your conversations.
💡 Tate-A-Tate is a no-code platform to turn ideas into full-stack AI agents.
🖼️ Photo AI 4 can sharpen, denoise, and upscale any images in seconds.
AI QUICK HITS
⚡ Gemini Ultra poised to compete with GPT-5 in multi-modal AI race.
⚠️ AI bubble will burst, be "shallow" and hit limits. We’re entering a correction phase.
🐶 ‘Crazy’ AI just helps reunite a lost dog with its owner in under 14 hours.
🎶 SoundCloud addresses claims that it’s training AI on uploaded music.
🧩 Candy Crush uses AI to create and improve its 18,700 levels, old but gold.
AI CHART
Alibaba researchers just trained AI to search the web… without actually using the web. They call it ZeroSearch, and according to their tests, it performs just as well - or better - than models trained with real search engines, while cutting costs by 88%.
🧠 What is ZeroSearch?
It teaches AI how to search and retrieve information, without needing real-time access to search engines like Google.
Instead, it simulates the search results using a large language model (LLM), kind of like faking the internet during training.
🧪 How It Works (Without Real Searches)
During training, an LLM generates fake search results (simulated documents).
These are fed into the model to teach it how to reason and answer questions as if it had done a real search.
Over time, the quality of the simulated results is reduced, making the AI work harder to figure things out.
This forces the model to learn deeper reasoning — not just copy-paste the top headline from a webpage.
Search APIs are expensive. If you’re training a large model and calling Google Search thousands of times a day, costs explode. Smaller teams and labs can now build smarter models without breaking the bank.
Did it work? Yes, very well. In benchmark tests, ZeroSearch matched or outperformed models that were trained using real search engines. And because the team controls the simulated content, there’s less noise, bias, or clickbait messing with the training data.
Not only is ZeroSearch posing a threat to Google Search, but we're also seeing a bigger shift: from SEO to AIEO (AI Engine Optimization). For the first time in 20 years, Google Search volume is down.
AI JOBS
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The AI Fire Team
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