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Apple Goes GooGoo Google's Billi(on)aire

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Apple just paid Google $1B/year to make Siri smarter. Meanwhile, OpenAI’s CFO slipped and sparked a political firestorm (even our president Trump jumped in)

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AI INSIGHTS

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Apple, famously obsessed with control, is now licensing Google’s Gemini to run its “Apple Intelligence” features.

Apple signed a deal to pay $1B/year to run a custom 1.2T parameter Gemini model behind the scenes of the new Siri. It's a temporary patch while Apple builds its own 1T parameter model, expected maybe by 2026.

  • Gemini will power Siri’s “summarizer” and “planner” functions (not audio)

  • All AI runs on Apple’s own Private Cloud Compute, so Google gets paid but doesn’t touch user data

Because Siri has been bad, like, embarrassingly bad, for years.

  • Apple’s internal models weren’t good enough. Despite recruiting big names, they lost 4–7 researchers recently

  • The company was even sued for promoting “Apple Intelligence” before it was ready

They tested OpenAI, Claude, and Gemini. Gemini won, likely for better instruction-following and longer context memory. Since Google is banned in China, Apple’s doing separate deals with Alibaba and Baidu to power Siri in China. It’s localization, Apple-style.

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AI SOURCES FROM AI FIRE

As promised, we’re committed to continuously updating the AI Mastery course, with over 27 leading AI tools. From here on, you’ll see fresh posts, new tools, and powerful tips and tricks in No. 1. Thank you for growing with us!

1. [UPDATED] Top AI Tools Every Professional Needs in 2025. These AI tools are changing how we work.

2. 12 AI tools that basically print money. My secret 2025 list. This is my personal list of tools I use daily.

TODAY IN AI

AI HIGHLIGHTS

⚡️ For Claude-lovers or GPT-users, to get even sharper answers, you just need to ask it to “ultrathink like Steve Jobs” or any leader you admire. Try the exact prompt here.

🗺 Who’s been struggling with Google Maps showing wrong way? Thanks god, it just gets a Gemini overhaul with 4 cool features. See how the new Gmaps works here.

📛 Meta AI has been bankrolled $16B, in part, by scam ads targeting you everyday. These ads look like this. Why didn’t Meta stop it? Cause it made too much money.

💹 Google turned into a full-on financial AI researcher. It now answers complex market questions, even live earnings transcripts are rolling out. See it in action here.

🚨 Yesterday, OpenAI’s CFO hinted at a $1.4T chip bailout. Altman denied fast. Trump’s team clapped back hard: “No bailouts.” If OpenAI can’t pay its own bill, should we?

💰 AI Daily Fundraising: OpenAI Foundation is investing $25B to boost healthcare and AI resilience, partnering strongly with Microsoft and SoftBank.

TOP OF CLASS: STANFORD 2025 AI SERIES

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AI CHART

perplexity-just-made-1t-ai-models-run-on-aws

Big AI models (like 1 trillion parameters big) usually need super-expensive hardware to run, Google TPUs, NVIDIA superclusters, that kind of thing.

But Perplexity’s first research paper showed that you can do it on regular AWS cloud machines!

AWS’s networking (called EFA) doesn’t have a key feature called GPUDirect Async. That means GPUs on different machines can’t talk to each other fast enough so giant AI models usually run slow or break completely.

Most teams avoid AWS for big models because of this. Perplexity built a system where:

  • The CPU helps the GPUs talk

  • Data gets packed and moved smartly using RDMA (super fast memory transfers)

  • While one part is moving data, the other is already crunching numbers

Basically: They found a way to juggle everything without dropping the ball. They made trillion-size MoE models (like Kimi K2 and DeepSeek V3) run fast on AWS.

It’s like running a Formula 1 car… on regular roads. Now anyone with some budget and brainpower can play in the trillion-param league.

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