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- AI Eats Its Own Tail
AI Eats Its Own Tail
AI citing AI, Apple + Gemini, author fury, bubble doubts, and more...
There's An AI For That
September 07, 2025
Hey, AI Enthusiast!
Welcome back to the #1 AI newsletter in the world.
Here’s a glimpse into what we have today:
Google’s AI eats its own tail.
Apple leans on Google for AI.
Authors lose AI battle in court.
China’s AI back doors gets shut.
30x faster AI, 16x longer contexts.
An AI that follows you everywhere.
Is AI hype or history’s biggest shift?
Prompt: AI Market Readiness Auditor.
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Breaking News
The Latest Developments in AI
Companies in “safe” countries have been sneaking in access to AI models for parent companies in restricted regions. Anthropic’s new rules just shut that down; a clear signal they don’t want their AI ending up in authoritarian hands.
Apple is reportedly building ”World Knowledge Answers” for Siri that’ll use Google’s Gemini. After years of lagging behind, the unlikely partnership could finally make Siri smart enough to compete.
A judge has ruled that using copyrighted books to train AI counts as legally transformative, even as Anthropic shelled out $1.5B to settle. The ruling has left authors fuming and legal questions unresolved.
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Open Source Finds
From the Source
🧠 Kimi K2 is a Mixture-of-Experts model with 1T total parameters and 32B active, delivering state-of-the-art results in knowledge, math, and coding.
⚡ XBai o4 is an open-source reasoning model with strong math, coding, and knowledge benchmarks that cuts inference costs by 99%.
🧩 Harmony is OpenAI’s response format renderer for gpt-oss, built in Rust with Python bindings for structured, loss-free conversations.
AI Finds
Beyond the Feed
Experts say AI isn’t just inflated hype, it’s the biggest shift in history, with frontier models and humanoid robots proving the point.
Researchers say hallucinations aren’t random bugs, they’re baked into how LLMs learn, especially when facts only appear once in training.
A new study found that 10.4% of sources in Google’s AI Overviews are AI-generated, and more than 50% don’t even rank in the top 100 results.
What if the real thing we’re learning from AI isn’t knowledge, but how to avoid effort? That shortcut could cost us long-term.
REFRAG is a new framework that speeds up LLMs by 30x and expands context windows by 16x, all without losing accuracy.
Prompt of the Day
AI Market Readiness Auditor
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