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AI6/10

Bryan Johnson Praises Midjourney's Whole-Body Scanner

Bryan Johnson calls the Midjourney scanner revolutionary after using it at the unveiling, arguing its fast, low-cost whole-body imaging could create routine health baselines. He says he plans to add weekly scans to his data and AI-driven health analysis.

Original post · 6 min read
The Midjourney scanner is revolutionary. There’s a bullish case that exceeds the most optimistic takes.

I was at the unveiling and used the scanner myself. I personally want to experiment with a weekly whole body Midjourney scan to add to my 1.5 billion data points and let my AI and doctors start connecting the dots.

Most of the early commentary has focused on the wrong questions: “is it as good as MRI?” and “what about false positives?” These are legitimate concerns, but they miss the bigger shift.

The more important question is: what does fast, low cost, safe whole body imaging unlock?

Let’s start with measurement.

A speedometer tells you how fast you are going. A fuel/battery gauge tells you when to stop. A thermostat tells you what to wear. The stock price tells you how much money you’ve made or lost. We measure what we care about.

Except, oddly, for our bodies, which are among the least measured things in our lives. Most people have more data on their favorite sports team, bank account, and social media performance than their body. The future will think we were crazy for this.

The first law of medicine is to do no harm. Our current system has harm baked into it.

+ an undiagnosed condition progressing silently is harm
+ a doctor who can’t easily get a patient screened preventively is harm
+ having no baseline to compare against when something shows up is harm

Our preventive net is narrow and inconsistent. Late stage diagnoses that could have been caught earlier remain common. Midjourney’s technology won’t eliminate that overnight, but it points toward a future where routine wholebody baselines become normal rather than exceptional.

Midjourney can help flip harm-by-default into a new expectation for our health infrastructure: almost no one will ever again be blindsided by a late-stage, life-threatening diagnosis that could have been caught earlier reasonably and cost-effectively.

Some examples of what earlier structural visibility enables:

+ breast cancer caught while localized has a ~99% five year survival rate. Once it has spread distantly, that drops to around 32%.

+ an abdominal aortic aneurysm kills more than 8 in 10 people when it ruptures. A single ultrasound finds the aorta in 99 percent of people, and screening cuts aneurysm deaths by a third to a half.

Midjourney’s technology will not do it all on its own. Its full angle, water immersion approach works around bone rather than seeing through it, and routes bowel gas to image the full abdominal cross section. Yet two real limits remain: air filled lungs stay a blind spot even here, and the brain is out of reach behind the skull, beyond the torso and legs this scanner covers.

That is fine, and they may improve these areas over time. Midjourney doesn’t need to do it all in order for it to be one of the biggest things to hit medicine in a long time.

Let’s look at where specifically Midjourney may be useful to each of us. We’ll start with where we get data today:

1) Blood draws tell us what is happening chemically.
2) Wearables tell us how the body is functioning.
3) Imaging tells us what is happening structurally.

The third layer, soft tissue, is the one we have never been able to access easily. MRI is great, but it is expensive, intimidating, and slow.

Midjourney's technology excels with soft tissue. Here are three places it could be game changing. There are many more.

1. Metabolic health - fatty liver is one of the earliest structural signs of metabolic dysfunction. It’s strongly linked to insulin resistance, type 2 diabetes, and cardiovascular risk. Being able to track visceral fat, muscle fat infiltration, and liver fat over time could give a much clearer picture than blood markers alone. Over 88% of Americans are metabolically unhealthy.

2. Endocrine tissue - the same metabolic patterns often cluster with thyroid issues, PCOS, and hypogonadism. Ultrasound can directly image the thyroid and ovarian structures. Fat tissue itself is an endocrine organ, so tracking it structurally adds another useful data layer.

3. Soft tissue + multiomics - new proteomic aging clocks can already predict risk for many chronic diseases from blood proteins. These molecular models could become significantly more powerful when combined with actual structural imaging data. The two are complementary, not competitive.

The real advantage: baseline + longitudinal tracking

The biggest unlock isn’t a single scan. It’s having a baseline followed by regular follow-ups. A one off scan in a moment of concern turns every finding into a potential crisis. Without context, you have no idea whether something is new, stable, or changing. With baseline + repeated measurement, the question changes from “what is this?” to “is this changing?” Most incidental findings stay stable. The dangerous ones tend to grow or evolve. Trajectory is often more informative than any single image or timepoint.This is why false positives become more manageable with frequent, low-friction imaging.

Midjourney has a difficult road ahead. Building robust, clinically validated medical hardware and software is extremely hard. Regulatory, technical, and adoption challenges shouldn’t be understated. Also, David is doing this for the right reasons and he’s well positioned financially to push through the difficulty.

On the horizon

We are moving quickly into a future where we will have continuous biological measurement. It will be all around us, a lot of it invisible and autonomous. Measurement will be in our gyms, beds, homes, clothing, offices, cars, glasses, and wearables. It will also be inside of us, in tissue and circulating in our blood vessels. This moves us from managing crises to preventing them. But this future will not just show up. We need bold builders like David and his team, willing to do the hard work.
Midjourney @midjourney
A technical dive inside our new "Midjourney Scanner"
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More in AI

AI9/10

OpenAI Releases Broad Set of Mathematical Results From Internal Model

OpenAI announced it is releasing a range of new mathematical results produced by an internal frontier model, consulting the Institute for Advanced Study's Advisory Group on Mathematics and Artificial Intelligence on how to release them, with materials published on GitHub.

Original post · 1 min read
We’re releasing a broad range of new mathematical results produced by an internal frontier model.

We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.

github.com/openai/math
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AI9/10

OpenAI Publishes 722 AI-Generated Math Manuscripts From Internal Model

OpenAI Publishes 722 AI-Generated Math Manuscripts From Internal Model

OpenAI released 722 mathematical manuscripts produced by an unreleased internal model, grouped into 372 families of results from about 4,000 research problems, averaging three hours of ChatGPT Pro compute per result. The author highlights claimed results including a zero-free half-plane for the zeta function and a quasi-Riemann hypothesis advance, which remain to be independently assessed.

Original post · 1 min read
Ok so I took a closer look at the results, and OpenAIs AI-generated mathematics manuscripts are *even more* significant than I initially thought.

I spent the morning going through it. Some thoughts.

The list is absurd. A zero-free half-plane for the zeta function (Re s > 7/8), which is the first result of its kind in over a century. Hilbert's tenth problem over the rationals. The Hodge conjecture for CM abelian varieties. Irrationality of Catalan's constant. Dozens more.

Any one of these would normally be a career.

But the number that many arent seeing is the following: It's 3. That's the average hours of ChatGPT Pro compute per result. A month ago, Navier–Stokes took them around 10,000 agents and 88 hours. That efficency gain within just a few weeks.

Also OpenAI claims to have solved the quasi-Riemann hypothesis. That alone would be a historic breakthrough in mathematics.

This is a weaker version of the famous Riemann hypothesis, which concerns how prime numbers are distributed. The full hypothesis remains unsolved, but the claimed advance would be enormous in its own right.

Math twitter obviously is shocked. Again: this is literally the intelligence explosion happening right now. 2027 will be the year of Superintelligence. Im now convinced by that.
Chubby♨️ @kimmonismus
HOLY, the rumors were true: OpenAI has published 722 mathematical manuscripts produced by an *unreleased* internal model.

The collection groups them into 372 families of related results, drawn from an evaluation involving approximately 4,000 research problems.

OpenAI says the standard procedure used an average of three hours of ChatGPT Pro thinking compute per result.

The release includes papers, proof artifacts and selected reasoning summaries. The model itself remains unreleased.
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AI8/10

Derek Thompson Calls OpenAI's Big Maths Day Potentially Historic for Science

Derek Thompson shares a quoted passage calling October 6, 2026 probably the biggest day of scientific advancement in history for AI in mathematics. The quoted Josh Gans post discusses OpenAI's Big Maths Day announcement.

Original post · 1 min read
Jesus.

"It isn’t an overstatement to say that this is probably the biggest day of scientific advancement in history. I suspect October 6th, 2026, will go down as some form of Judgment Day for AI in mathematics, but it portends so much more."
Joshua Gans @joshgans
My thoughts on OpenAI's Big Maths Day. joshuagans.substack.com/p/openai-drops-a-bomb-…
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AI8/10

Meta and Sierra Announce Open Personal Agent Protocol Standard

Meta and Sierra Announce Open Personal Agent Protocol Standard

Bret Taylor announces the Personal Agent Protocol, an open standard being developed by Meta and Sierra with partners including Genesys, Shopify, Stripe and Walmart. It defines how personal agents interact with businesses and is open for anyone to implement.

Original post · 1 min read
Today we’re announcing Personal Agent Protocol — an open standard @Meta and @SierraPlatform are developing along with industry partners at @Genesys, @instinct, @RocketOTD, @Shopify, @stripe, and @Walmart. It will help define how personal agents interact with businesses and is open for anyone to implement. You can read more here - and if anyone is interested in joining let me know! sierra.ai/blog/introducing-personal-agent-prot…
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AI8/10

Suleyman Cites Acemoglu Estimate That AI Will Replace Only 5% of Tasks

AI won't take your job anytime soon. In 10 yrs, only 5% of what humans do will be replaced by AI

Mustafa Suleyman shares an essay from The Humanist Review in which economist Daron Acemoglu argues AI will replace about 5% of human work tasks over ten years and adds roughly 1.5% to GDP. Acemoglu calls for pro-worker AI and changes to labor taxes, antitrust and data payments.

Original post · 2 min read
X ArticleAI won't take your job anytime soon. In 10 yrs, only 5% of what humans do will be replaced by AI
AI won't take your job anytime soon. Over the next 10 years, it will replace only about 5% of what humans do.
This is the prediction Nobel laureate Daron Acemoglu makes in the first issue of The Humanist Review, our new magazine exploring the future of AI, published by MAI. He argues we need to stop building AI to replace people, and start building it to make them better at their jobs.
52% of Americans are worried about AI's impact on their jobs. The fear is overblown, and it's steering how we build AI.
AI isn't in the productivity statistics yet. Most firms using it aren't seeing real gains. Expect roughly 1.5% added to GDP over 10 years, not a revolution.
Electricity took decades to spread. New York and London had power stations by 1881, yet only about half of factories and homes used it by the 1920s. AI's adoption will likely be even slower, because companies have to reorganize around it.
Dragon's voice recognition was nearly 95% accurate in 1997, yet PC dictation today is barely better than in 2000. A great technology goes nowhere without the right products.
Even 99% accuracy isn't enough for full automation. The last 1% is the hard part.
We're making a mistake by forcing AI to mimic human intelligence. The two are fundamentally different, so the goal should be to pair them, not to have one take over everything.
The better path is pro-worker AI: tools that make people better at their jobs, and they're buildable today.
The US taxes labor at over 25% and capital at close to zero, which effectively subsidizes automation.
The seven largest tech companies make up 60% of the NASDAQ. That concentration crowds out new ideas.
The fix: tax labor and capital equally, enforce antitrust, tax digital ads, and pay experts for their data.
Read the full essay: humanistreview.ai/issue-1/acemoglu-ai-replace-…
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AI8/10

a16z Top 100 Consumer AI Apps Report Shows Expansion Beyond Chatbots

a16z Top 100 Consumer AI Apps Report Shows Expansion Beyond Chatbots

a16z's seventh Top 100 Consumer AI Apps report adds a revenue leaderboard alongside traffic rankings. It notes ChatGPT's 1B+ monthly mobile actives, Claude reaching nearly 1B monthly web visits, and growth into vibe coding, music, design and video, while nine of 15 consumer categories have no AI product in the top 100.

Original post · 1 min read
"Most people aren't looking to save time, they're looking for ways to spend their time."

9 of 15 consumer internet categories have zero AI products in the Top 100. These built some of the biggest companies of the last two eras:

- Streaming
- Social
- Dating
- Gaming
- Travel
- Retail
- Finance
- Real estate
- Jobs

More charts in our Top 100 Consumer AI Apps breakdown: a16z.news/p/top-100-consumer-ai-apps-seventh
a16z @a16z
The seventh edition of our Top 100 Consumer AI Apps is here.

New this time: a revenue leaderboard, alongside the usual web and mobile traffic rankings.

Three years ago we published the first edition. ChatGPT was #1, Claude was unranked, and the entire category was chatbots, image generators, and not much else.

In today's edition:

- ChatGPT still holds the throne, now with 1B+ monthly actives on mobile

- Claude has climbed to #3 on web with nearly 1B monthly visits

- The category has expanded to vibe coding (Lovable, Cursor, Replit), music (Suno), design (Figma), voice (ElevenLabs), video…
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