Hey friends 👋 Happy Sunday.
Here’s your weekly dose of AI and insight.
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AI Highlights
My top-3 picks of AI news this week.
1. Google’s Classroom Takeover
Google has launched a comprehensive AI education suite at the ISTE conference, introducing over 30 AI-powered tools designed to transform how teachers teach and students learn.
Gemini in Classroom: Free AI suite for all Google Workspace for Education accounts, enabling teachers to brainstorm ideas, generate lesson plans, and create personalised content using AI.
Custom AI "Gems": Teachers can create specialised versions of Gemini AI that act as subject-matter experts, providing students with targeted support and explanations using classroom materials.
Class tools for Chromebooks: New teaching mode that allows educators to share content directly to students' screens, broadcast instructions with captions, and restrict browsing to keep students focused on learning.
Alex’s take: The education sector has been surprisingly slow to adopt AI tools compared to other industries, despite the obvious potential for personalised learning. Google's approach of giving teachers control over AI customisation rather than imposing one-size-fits-all solutions feels like the right move. I expect we'll see a wave of similar announcements from other tech giants as they realise education might be AI's most transformative use case.
Healthcare
2. AI’s Fertility Breakthrough
Columbia University Fertility Center used AI to achieve a breakthrough in severe male infertility treatment, helping a couple conceive after 18 years of unsuccessful attempts.
Rapid detection: AI analysed millions of microscopic images from semen samples to identify viable sperm in just hours, compared to the traditional process that could take days.
Severe infertility solution: Successfully treated a patient with an extremely rare condition that left him with almost no detectable sperm using conventional methods.
Complete workflow: The technology captured images with a tiny camera, processed them through AI algorithms, and enabled rapid sperm extraction for immediate fertilisation procedures.
Alex’s take: The precision and speed of AI in medical diagnostics continue to astound me. 18 years of hope finally realised through technology that can see what we cannot. I think this is such a special application of AI that can now turn impossible cases into possible families—that’s something we can all get excited about.
Cursor
3. Cursor Agents Go Mobile
Cursor has launched a web app that brings AI coding agents to any browser on desktop or mobile, allowing developers to manage complex coding tasks from their smartphones for the first time.
Mobile-first development: Developers can now assign natural language coding tasks, monitor agent progress, and review code changes directly from their phone or tablet browser, with full Progressive Web App (PWA) support for iOS and Android.
Autonomous task execution: Background agents can write features, fix bugs, and answer complex codebase questions while developers are away from their desk, with seamless handoff back to the full IDE when needed.
Cross-platform workflow: The mobile experience integrates with Cursor's existing Slack notifications and desktop IDE, creating a unified development workflow that spans from pocket to workstation.
Alex’s take: We are now witnessing the democratisation of development workflows. Why doomscroll when you can now vibecode directly on your mobile? You no longer need 3 screens and 10 years of expertise to start building—anyone can now build from anywhere.
Content I Enjoyed
Biology Will Become Computable
This week, I really enjoyed listening to Hard Fork Live, which gave birth to some incredible guests, including the likes of OpenAI CEO Sam Altman and COO Brad Lightcap.
But there was one guest interview in particular that caught my attention.
That was Patrick Collison, the CEO of Stripe, who is also one of the co-founders of Arc Institute. The big anchor to his talk was that humanity has never cured a complex disease. Arc Institute was built in order to find a different way to go after these complex diseases.
Large language models (LLMs) are trained specifically to understand and produce natural language. But AI now unlocks an entirely new language altogether—DNA, the language of life.
Whilst we can’t understand at a human level what’s going on, AI is exceptionally good at it. This has led Arc Institute to recently publish its first “virtual cell” model. The idea behind a virtual cell is to create an accurate way for conducting computational experiments without real-world consequences. This is an enormous accelerant to advancements in biology.
Along with the ground truth and first principles of physics, biology is one of the areas that excite me tremendously at the intersection of AI. With initiatives like Arc Institute blazing forward, perhaps we aren’t that far from having humanity cure its first complex disease after all.
Idea I Learned
Mind-Controlled Humanoid Robots
Neuralink’s Summer 2025 update is a must-watch.
At 18:02, Dongjin Seo (DJ), one of the co-founders and President of Neuralink, highlighted how the company has now successfully implanted chips in seven individuals.
What’s even more staggering is how sharply the implantation intervals have dropped over time.
It was 6 months between the first and second patient. It was 1 week between the sixth and seventh.
But I’m fixated on something Elon mentioned almost casually at 32:42: “As we advance the Neuralink devices, you should be able to actually have full body control and sensors from an Optimus robot. So you could basically inhabit an Optimus robot.”
“Remote work” might just get a new meaning. In the future, you’ll be able to do remote physical work. Physically relaxing on your couch whilst mentally working… as a humanoid robot.
I think this is where we’ll start to see a lot of scale roll out—human teleoperated robots are easier than autonomously operated robots. Countries with lower labour costs could become hubs for human-operated robots, creating an entirely new global workforce dynamic. What’s more, the training data on offer here is enormous.
It reminds me of the film “The Electric State”. In the film, humans use neural headsets called "Neurocasters" to control robot avatars while their bodies remain stationary. What seemed like dystopian science fiction will actually become part of a product roadmap.
But before we leap across the uncanny valley and have humans operating a second physical form, Neuralink as a technology will help millions of people with disabilities around the world—and soon, millions of others advance beyond basic human capabilities.
Quote to Share
Yuchen Jin on OpenAI's talent exodus:
Mark Zuckerberg is going all-in on superintelligence.
Within just the last few weeks, Meta has orchestrated a massive talent acquisition campaign, poaching 11 AI researchers from competitors, including Google DeepMind's Pei Sun and Anthropic's Joel Pobar. This coincides with Zuckerberg's bold restructuring of Meta's AI efforts under a new dedicated "Superintelligence Labs" division.
The timing isn't coincidental. Meta just invested $14.3 billion in Scale AI, bringing former CEO Alexandr Wang on board as chief AI officer, whilst former GitHub CEO Nat Friedman will oversee AI products and applied research.
Zuckerberg is making a clear statement: Meta intends to be a serious player in the race toward superintelligence, and they're willing to pay premium prices for the best minds in AI. It also seems like AI researchers are now in the same arena as professional athletes, especially at $10M+/year.
Source: Yuchen Jin on X
Question to Ponder
“Will we see the first one-person billion-dollar company within the next 5 years?”
As Archimedes famously said, “Give me a lever long enough and a place to stand, and I will move the earth.”
I’m a big believer that technology ultimately boils down to two things. Scale and leverage. Yet Silicon Valley has been historically accelerating in the opposite direction.
Throwing people at a problem instead of leveraging technology and outsourcing to scale.
Auren Hoffman highlights this perfectly:
“If you start stripping out everything that is not unique to your company, you’re left with just a few people who make the unique parts of the company. And then add a few people who need to explain its unique benefits to the market. Imagine your 100 person company going to 6 people. Imagine your 1000 person company going to 20. How much faster could you move?”
I see a very real possibility of a 3-person team reaching this billion-dollar valuation.
A CEO who distributes the thing (whilst also being proficient at building the thing).
A CTO who builds the thing.
A COO who manages the thing.
This triumvirate effectively covers product development, marketing, support, operations, finance and legal functions by leveraging automation, agents and APIs.
In the past, we’ve seen this trend start to take shape:
2008: Plenty of Fish (1 employee) generating $10M in revenue
2012: Instagram (13 employees) selling to Facebook for $1B
2014: WhatsApp (32 employees) selling to Facebook for $19B
Whilst the idea of a one-person billion-dollar company might seem like a stretch today—you’d likely need a hyper-viral self-serve platform—the constraints of yesterday are very different from the constraints of tomorrow.
Build once. Let it work for you. Iterate over time. That’s the ultimate form of leverage.
We’re now coming closer and closer to making this a reality.
Got a question about AI?
Reply to this email and I’ll pick one to answer next week 👍
💡 If you enjoyed this issue, share it with a friend.
See you next week,
Alex Banks
P.S. Drunk robot.
Fascinating — what a great collection of news, future insights, immediate tools. The AI fertility breakthrough story was incredible.