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Welcome back to the Neural Net! It’s Tuesday, aka Monday II, but vacation is in the air with Labor day right around the corner.
In today’s edition: Why an AI slowdown could be just what we need, a new AI tool makes picking up a language easier than ever, Siri calls Google’s Gemini for backup, Europe falls further behind in AI, and more.
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The Street
note: stock data as of last market close
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🧠 What If the Slowdown Is the Strategy?
The AI hype loops are thrilling, but the real ride may lie in implementation.
There’s growing chatter that the AI boom might be easing up. GPT-5 rolled out with incremental rather than groundbreaking updates. Meta hit pause on its next model early this spring. Even Sam Altman sounds, well, grounded?
But here’s the twist: If the pace of jaw-dropping breakthroughs really is slowing, that might be exactly what the business world needs. Not a crash. A window.
A moment to stop chasing, and start building.
🍬 For Businesses, This Might Be the Sweet Spot
“Somewhat paradoxically, the mere perception that AI is slowing might give companies more confidence to invest time and money in it, seeing it as less of a moving target.”
Here’s Why:
Current AI is already useful: Generative AI tools are already embedded in most companies to help with writing, coding, and creating all type of content. And while GenAI grabs headlines, traditional AI (like forecasting and computer vision) is still quietly delivering real value, which companies shouldn’t overlook.
Adoption lags capability: Most businesses haven’t caught up to what today’s models can do. While Big Tech scrambles to juice out 5% model improvements, most companies haven’t even begun to fully adopt current AI tools.
Mistrust is the bottleneck: Leaders still don’t feel comfortable sharing sensitive data with chatbots. We need more time to close these gaps and build trust.
Slower innovation = stability: A pause in the hype cycle could give enterprises the breathing room to build, train, and integrate AI at their own speed, without fearing it’ll all be outdated tomorrow.
Translation: the frontier is still exciting, but the front lines of adoption are chaos. A breather gives everyone time to close the gap.
🌐 The Internet Wasn’t Instant, Either
“The AI boom is different in many ways, but it could follow a similar trajectory: a burst of enthusiasm followed by a leveling-off as it bleeds into society and business, with the true scope of the benefits only clear years later.”
Just like the internet, AI’s true transformation might take time. Broadband didn’t reach most U.S. households overnight—it took more than a decade to move from near zero access in 2000 to 60% adoption. AI may feel faster, but the pattern could be the same: a burst of excitement, a period of adjustment, and only then the full impact.
That said—who really knows if AI is slowing down? We’re a little over two years into the madness. Let’s see where it actually goes.
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💡 How To AI: Learn a Language Like It’s 2025
Most language apps teach the same canned stuff like “The apple is red”, which is fine until you actually need to say something useful. Google’s Little Language Lessons experiment flips the script by using Gemini AI to make learning more contextual and alive.
Here’s why it’s worth trying:
🎯 Situational lessons: Bite-sized modules for real scenarios (lost passport, buying tickets, first dates). Less “textbook,” more life.
💬 Slang & culture: AI-generated convos drop you into slang and idioms you’d actually hear, not just the formal stuff.
📸 Instant vocab: Point your camera at an object and learn the word in real time — vocab building without the phrasebook pain.
👉 The difference: Instead of studying a language in a vacuum, AI lets you learn in context, on the fly, and tied to your world.
It’s free to use, and early testers say it could rival leading language platform Duolingo by making language learning more personal.
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Heard in the Server Room
Apple might be calling in backup for Siri. Bloomberg reports the company is in early talks with Google to plug its Gemini AI into a revamped version of the voice assistant, following delays to Apple’s own upgrade. The iPhone maker hasn’t picked a partner yet, having also explored OpenAI and Anthropic, but it’s racing to catch up with rivals like (ironically) Google and Samsung, which have already rolled out flashier AI features across their smartphone lineups.
OpenAI is dialing up its global push. In India, it rolled out ChatGPT Go, its cheapest plan yet at about $4.50 a month, to hook users in its second-largest market. Across the pond, CEO Sam Altman has been chatting with UK officials about weaving ChatGPT into public services, even tossing around the idea of nationwide premium access. Alongside deals in places like the UAE, these moves show OpenAI’s ambition to become a global AI player, not just a leader on home turf.
Elon Musk is adding to his empire with “Macrohard,” an AI-only software venture designed to mirror giants like Microsoft. Musk called it “very real,” hinting that firms without hardware could be fully simulated by AI. A trademark filing shows Macrohard covering everything from AI-generated speech to game design tools, adding another bold bet to Musk’s ever-expanding portfolio.
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🌎 AI Transformation Gap Widens Between Europe and the US
European leaders have been sounding the alarm on competitiveness, with reports from key leaders warning of weak productivity and a growing gap with the US. That gap was underscored earlier this year when US Vice President JD Vance used the Paris AI Summit to boast that “America is the leader in AI and this administration intends to keep it that way.”
Now, a new Accenture survey shows many European firms still aren’t getting real value out of AI—raising questions about how quickly the continent can close the gap.
Takeaways: The Good and the Bad
Stuck in neutral: 56% of large EU companies say AI hasn’t moved the needle for them yet.
Falling behind: European workers now produce just 76% of the average American workers’ output, down from parity in the ’90s.
Geopolitical drag: Energy shocks, war, and inflation have further strained Europe’s competitiveness.
Big upside: If every European company with over $1B in revenue adopted AI as effectively as today’s AI leaders, it could unlock $225B a year in value.
Not so surprising bright spots: Automotive leads AI use in Europe, with aerospace, life sciences, and industrials not far behind.
Why it matters:
Europe’s lag isn’t just a tech problem, it’s a general competitiveness problem. And AI is only widening the divide. Ironically, maybe AI’s real use case in Europe is turning a four-day work week into five days of output.
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That’s it for today! Have a fantastic week, and we’ll catch you next time with more neural nuggets.