🩺 Microsoft's AI beats doctors

Welcome back, Superhuman. Can you buy your way to AGI — or does long-term vision matter more? Meta is apparently betting on the former, as it brings on at least 11 new hires to jumpstart its “superintelligence” efforts. But skeptics argue that AI talent alone won’t get you to AGI.

Today: Learn how to optimize your prompts with AI, and get the latest headlines and social media posts.

TODAY IN AI

1. Meta sheds light on long-rumored superintelligence team: Mark Zuckerberg revealed that the former CEOs of Scale AI and GitHub will helm a new group called Meta Superintelligence Labs. Meta also announced 11 new AI-focused hires scooped from the likes of Google, Anthropic, and OpenAI, but the jury’s still out on whether that will be enough to recover from its lackluster Llama 4 release. Meanwhile, OpenAI is “largely shutting down” this week to give employees (many of whom work 80 hours/week) a break as it tries to recover from Meta’s relentless poaching streak.

2. Apple weighs turning to OpenAI or Anthropic for Siri help: Apple reportedly has a new plan to get back into the virtual assistant game. Instead of building its own custom model as planned, it’s now talking with OpenAI and Anthropic about potentially plugging one of their models into Siri. It’s a tough call: On the one hand, Apple doesn’t want to be completely reliant on one of its rivals. But without a solid AI product, it risks permanently falling behind.

3. Vibe coding just got easier with Cursor’s new web app: Anysphere, the $9.9B-valued company behind Cursor, just announced a new web and mobile app that lets you control a team of agents from anywhere. They can “launch bug fixes, build new features, or answer complex codebase questions,” even when you’re not there. Previously, you could only access Cursor via its IDE (a specialized app that hosts your codebase).

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FROM THE FRONTIER

Microsoft unveils AI that’s 4x more accurate than doctors

Microsoft claims we’re one step closer to “medical superintelligence,” and it brought receipts. The company’s new AI system can allegedly boost the accuracy of complex medical diagnoses by 300% over human doctors — at least when paired with OpenAI’s advanced reasoning model, o3.

The experiment: Microsoft used 304 extremely challenging cases from the New England Journal of Medicine to put its new framework to the test. After asking an initial batch of questions, the system came up with some educated guesses about what might be going on. Next, a separate agent searched for additional information, like blood tests or X-rays, to narrow down the possibilities.

Promising Results: Using this method, the AI system was able to land on the correct diagnosis about 80% of the time, compared to just 20% for a panel of human doctors. Unlike previous multiple-choice tests, this one is more significant since the model couldn’t rely on memorization to find the answer. (Here’s a short video with more details.)

What’s next? While the system isn’t ready for clinical use just yet, Microsoft AI CEO Mustafa Suleyman told The Guardian, “it’s pretty clear that we are on a path to these systems getting almost error-free in the next 5-10 years.”

Beyond diagnoses, it’s already been a big week for AI-related scientific breakthroughs, from Chai Discovery’s new “zero-shot antibody discovery” model to Arc Institute’s ongoing biological simulations.

THE AI ACADEMY

How to optimize your prompts with AI

• Open the OpenAI Playground and go to the “Prompts” section.

• Click on ‘Configure’, and write a system message — clearly describing what you want the AI to do.

• Click on the ‘Optimize’ button to automatically improve your prompts.

• Review the optimized prompt, make any final adjustments, and click ‘Save’.

• Give it a suitable name so you can easily reuse it in future projects or API calls.

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IN THE KNOW

What’s trending on socials and headlines today

💡 AI Epiphany: A viral article from AI researcher Jack Morris recently resurfaced, and it could completely reshape how you think about AI progress. Or, here’s a TLDR version.

✍️ Stroke of Genius: A Redditor might have just stumbled upon a genius prompting technique that gets ChatGPT to do exactly what you want.

💼 Inside Scoop: A new study reveals how 300 top software execs use AI at work. Investor Deedy Das shares his biggest takeaways from the report.

✨ Also Worth Checking Out: An AI-generated band goes viral, Olympic diving takes a multi-species turn, and a prompt turns ChatGPT into a personal stock research assistant.

Chinese tech giant Baidu announced it’s open-sourcing its Ernie chatbot this week, a surprise move that could threaten OpenAI, Anthropic, and even domestic rival DeepSeek.

Runway is gearing up to release a video game generation platform that lets you create interactive experiences with text and image prompts. A stripped-down version is reportedly only days away, with the full release expected later this year.

Google announced it’s making a major investment in fusion power company Commonwealth Fusion Systems, which is harnessing “the same process that powers the sun and stars” to develop more sustainable energy sources.

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PROMPT STATION

Learn Anything Faster

Prompt: [SUBJECT]=Topic or skill to learn
[CURRENT_LEVEL]=Starting knowledge level (beginner/intermediate/advanced)
[TIME_AVAILABLE]=Weekly hours available for learning
[LEARNING_STYLE]=Preferred learning method (visual/auditory/hands-on/reading)
[GOAL]=Specific learning objective or target skill level

Step 1: Knowledge Assessment
1. Break down [SUBJECT] into core components
2. Evaluate complexity levels of each component
3. Map prerequisites and dependencies
4. Identify foundational concepts
Output detailed skill tree and learning hierarchy

~ Step 2: Learning Path Design
1. Create progression milestones based on [CURRENT_LEVEL]
2. Structure topics in optimal learning sequence
3. Estimate time requirements per topic
4. Align with [TIME_AVAILABLE] constraints
Output structured learning roadmap with timeframes

~ Step 3: Resource Curation
1. Identify learning materials matching [LEARNING_STYLE]:
   - Video courses
   - Books/articles
   - Interactive exercises
   - Practice projects
2. Rank resources by effectiveness
3. Create resource playlist
Output comprehensive resource list with priority order

~ Step 4: Practice Framework
1. Design exercises for each topic
2. Create real-world application scenarios
3. Develop progress checkpoints
4. Structure review intervals
Output practice plan with spaced repetition schedule

~ Step 5: Progress Tracking System
1. Define measurable progress indicators
2. Create assessment criteria
3. Design feedback loops
4. Establish milestone completion metrics
Output progress tracking template and benchmarks

~ Step 6: Study Schedule Generation
1. Break down learning into daily/weekly tasks
2. Incorporate rest and review periods
3. Add checkpoint assessments
4. Balance theory and practice
Output detailed study schedule aligned with [TIME_AVAILABLE]

Source: r/ChatGPTPromptGenius

The Eye Cleaner

ChatGPT Prompt: A hyper-realistic scene of a tiny man dressed as a high-rise window cleaner, complete with a safety harness, helmet, and ropes. He is standing on the surface of a giant human eye, carefully cleaning the eyeball with a squeegee. The eye is highly detailed with reflections, veins, and moisture, and the tiny man is leaving a clean streak across the cornea. The background is softly blurred, drawing focus to the surreal contrast between the massive human eye and the miniature cleaner. The lighting is natural and slightly dramatic, emphasizing the glossiness of the eye and the texture of the cleaning gear.

Whenever you’re ready to take the next step

• Check out our Top 125 AI Tools

• Get better at prompting with our Top 1,000 Prompts

• Learn how to use AI at work and get certified with our free course

Grow customers & revenue: Join companies like Amazon, Hubspot, and Salesforce. Showcase your product to our 1M+ readers and 2M+ followers on socials. Get in touch.

Until next time — Zain & the Superhuman AI team