- Everyday AI
- Posts
- Apple cooked on AI? Apple's Siri failure and the end of its AI innovation
Apple cooked on AI? Apple's Siri failure and the end of its AI innovation
Future of Apple's AI, Cloudflare blocks AI scraping, U.S. Senate rejects state AI regulation freeze, Amazon deploys 1 millionth robot and more!
Everyday AI
July 01, 2025
👉 Subscribe Here | 🗣 Hire Us To Speak | 🤝 Partner with Us | 🤖 Grow with GenAI
Outsmart The Future
Today in Everyday AI
6 minute read
🎙 Daily Podcast Episode: Apple's AI innovation may have hit a wall. As Apple turns to competitors like OpenAI and Anthropic for Siri's future, are we witnessing the decline of its AI dominance? Give it a listen.
🕵️‍♂️ Fresh Finds: OpenAI’s economic blueprint for Australia, Grammarly acquires Superhuman and English Premier League to use Microsoft’s AI. Read on for Fresh Finds.
đź—ž Byte Sized Daily AI News: Cloudflare blocks AI scraping by default, U.S. Senate reject state AI regulation freeze and Amazon deploys 1 millionth robot and new AI model. For that and more, read on for Byte Sized News.
🧠Learn & Leveraging AI: Has Apple been left in the AI dust or can it redeem itself? We bring our hot takes. Keep reading for that!
↩️ Don’t miss out: Did you miss our last newsletter? We talked about Baidu’s Ernie bot going open source, Gmail’s AI search added to business users, Meta using Facebook users’ camera rolls to train AI and more. Check it here!
Apple cooked on AI? Apple's Siri failure and the end of its AI innovation 🍎️
Apple is gonna pay their competitors to do AI for them.
Yiiiiikes.
A recent Bloomberg report detailed Apple's failures to build a smart AI Siri and how they may instead hire OpenAI or Anthropic to do the job for them.
Our take?
You know we're bringing the fire for this #HotTakeTuesday.
Also on the pod today:
• Apple's AI Outsourcing Strategic Impact 📂
• Anthropic & OpenAI's Role in Apple's AI 👥
• Apple's AI Failures & Class Action Lawsuits ⚖️
It’ll be worth your 36 minutes:
Listen on our site:
Click to listen
Subscribe and listen on your favorite podcast platform
Listen on:
Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – GenSpark Super Agent is an AI agent for everyday tasks, text.ai adds AI to your SMS, WhatsApp and Telegram and PageTest.ai is AI-powered website content testing.
OpenAI – OpenAI is partnering with Mandala Partners to share its OpenAI AI Economic Blueprint for Australia.
Business of AI - Grammarly has acquired AI email client Superhuman.
Money in AI – Scale AI’s bigger rival Surge AI is seeking up to $1 billion capital raise.
AI Startups – Genesis AI is launching with $105M seed funding from Eclipse and Khosla to build AI models for robots.
AI in Sports - The English Premier League is integrating Microsoft’s AI into its fan app in a new 5-year deal.
1. Cloudflare To Block AI Scraping By Default🛡️
Cloudflare just flipped the switch on blocking known AI web crawlers by default for new domains, aiming to stop unauthorized scraping of online content, according to their Tuesday announcement. They’re also rolling out a “Pay Per Crawl” program that lets select publishers charge AI companies for access, ensuring creators get compensated.
This move comes as more people rely on AI chatbots for info, potentially bypassing original sources, which raises stakes for content owners. With big names like The Associated Press and Stack Overflow on board, Cloudflare is setting new rules to protect digital creators while still supporting AI innovation.
2. U.S. Senate Rejects 10-Year AI Regulation Freeze ❌
In a decisive 99-1 vote, the U.S. Senate struck down a proposal that would have blocked states from regulating artificial intelligence for up to a decade, a move tied to federal funding incentives. The bipartisan pushback came amid concerns that such a moratorium would hand AI companies unchecked power, especially in protecting children and creative rights, with critics pointing to real harms linked to unregulated AI tools.
The defeat highlights ongoing tension between fostering AI innovation and ensuring accountability at both federal and state levels.
3. Amazon Deploys 1 Millionth Robot, Boosts Efficiency with New AI Model 🤖
Amazon just hit a major milestone, deploying its one millionth industrial robot and rolling out a new generative AI system called DeepFleet that improves fleet travel efficiency by 10%. This AI acts like smart traffic control for robots, reducing congestion and speeding up order fulfillment across over 300 global facilities.
The move not only cuts delivery times and costs but also creates new technical job opportunities, having already upskilled more than 700,000 employees.
4. Meta Rolls Out Superintelligence Labs đź§
Meta CEO Mark Zuckerberg has just unveiled the new “Meta Superintelligence Labs” to lead the company’s AI innovation efforts, appointing former Scale AI CEO Alexandr Wang as chief AI officer and bringing on ex-GitHub CEO Nat Friedman as his partner, Bloomberg reports.
The move comes amid Meta’s aggressive hiring spree with 11 new AI experts from top firms like Anthropic, DeepMind, and OpenAI, along with reported eight-figure offers to snag top talent.
5. xAI Secures $10 Billion Boost in Debt and Equity đź’¸
Elon Musk’s AI venture, xAI, just locked in a massive $10 billion funding round split evenly between debt and equity, confirmed by Morgan Stanley. This fresh capital injection comes just months after a $6 billion raise last December, pushing xAI’s total funding to roughly $17 billion.
The funds are earmarked for expanding xAI’s AI research capabilities, including building one of the world’s largest data centers and enhancing its Grok platform.
🦾How You Can Leverage:
Bloomberg just dropped a bombshell about Apple's AI disaster.
Apple is hiring its competitors to do AI for them.
After reportedly spending MILLIONS of dollars every single day for years trying to build their own generative AI, Apple's internal models are reportedly so bad that they’re kinda giving up.
The Bloomberg report says that Apple may offshore the much-delayed AI-powered Siri development to either Anthropic or OpenAI, as its own development has fallen short.
Yikes.
Apple’s been hyping the AI-powered Siri since early 2024, yet they haven’t been able to deliver anything of value and have been slapped with countless class action lawsuits for failing to deliver what they marketed.
Double yikes.
So on today's show, we're breaking down how this Siri SNAFU represents the first time in Apple's history they're admitting they cannot build core intelligence technology in-house.
And why this could be the beginning of the end for Apple's innovation dominance, especially when it comes to AI.
Let’s get after it. 👇
1 – Apple Breaks Sacred Outsourcing Rule 🚨
Never happened before in Apple's history.
Apple just shattered their vertical integration strategy by admitting they need competitors to build their most important feature.
Their own AI models reportedly tested twenty percent WORSE than aging competitor technology that other companies have already moved on from.
CEO Tim Cook moved Siri from AI chief John Giannandrea in March after years of unrealized promises.
Now the smarter Siri promised at their 2024 developer conference has been pushed back to 2027 and could get delayed even further.
Anthropic reportedly wants a multi-billion (with a B!) dollar annual contract that increases exponentially every year, while Apple demands the models run on their private infrastructure.
This creates a technical nightmare that could cause more delays.
Try this:
Identify your company's three most critical core competencies you absolutely cannot afford to outsource.
Schedule a meeting with tech leadership this week.
Ask: "What happens if our key AI vendors triple their prices because they know we can't live without them?" Map out contingency plans before you're paying Apple-level desperation pricing.
2 – Perfectionist Culture Kills AI Speed ⚡
Apple's legendary secrecy is destroying their ability to compete in AI.
Internal teams worked in such isolated silos that senior leadership didn't know what AI projects other departments were building.
That approach worked for hardware launches where you perfect something in secret then unveil it.
It's useless for AI development, which requires constant iteration and real user feedback.
While Google shipped Bard, learned from disasters, and came back with the world's best AI models, Apple spent three years making promises about features that still don't exist.
That’s how AI recovery is done.
Even worse, Apple started putting out research papers claiming large language models aren't that good right after they failed to build their own.
The AI research community immediately debunked those papers.
Try this:
Find your biggest "perfectionist bottleneck" where teams spend months polishing features before getting customer feedback.
Cut that timeline in half.
Ship a basic version to a test group within thirty days and set up weekly feedback sessions. Calculate the revenue you're losing by waiting for "perfect" instead of learning from real users now.
3 – Market Dominance Crumbles as Competitors Surge 📉
Apple dropped from the world's most valuable company to number three.
Five years ago Apple dominated with a $2.13 trillion market cap while Microsoft lagged at $1.6 trillion.
Today Microsoft and Google completely lapped Apple by betting on AI that actually works.
Every other top-six company built valuable AI in-house: NVIDIA powers the AI revolution, Microsoft built Copilot, Amazon has Nova models, Google's Gemini is arguably the best in the world.
Meta just spent fourteen billion acquiring Scale AI and hiring former researchers from OpenAI, Apple, and Google.
Meanwhile, Apple's biggest achievement is combining two emojis and facing class action lawsuits for advertising features that don't exist.
When AI becomes essential like internet connectivity, Apple users will pay premium prices for competitors' technology while those competitors capture valuable user data.
Try this:
Calculate your current AI spending, multiply by five for three-year costs.
Research which vendors have the strongest pricing power in your industry.
Negotiate price caps in existing contracts before you become as dependent as Apple. Identify one small AI capability you could build in-house over six months to reduce vendor dependency.
Reply