@johanjessen
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Applied Philosopher. Invests in elite founders who make sci-fi real. Past founder of ionlace and rebel at Google X, Lyft L5, Apple, and Stanford.
Joined February 2009
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Always light touch. Avoid gripping too tight. Sense the pull. Your intuition is correct.
this is insane. i genuinely don't understand why ambitious people aren't shown this lecture before their careers start consuming their entire lives.
clayton christensen spent his career studying why successful companies collapse. in his final class, he asked students to apply the theory to themselves: if you keep allocating your time the same way, what life are you actually building?
he had already seen the answer in his own harvard mba class. everyone looked successful at the fifth reunion; by the 10th, 15th, 20th, and 25th, many were unhappy, divorced, and living far from their children.
work shows you the score immediately. close a sale, ship a product, finish a presentation, earn a promotion, get paid.
an hour with your child may produce nothing you can measure today; it may take 20 years to understand what that hour built. so the next free hour goes back to work, one rational decision at a time.
this is how people build lives they never planned: through hundreds of right decisions that lead in the wrong direction, day after day.
money, titles, and headcount are easy to count. christensen believed a life should be measured by the people who became better because you were there.
he died in 2020.
one question remains: if someone saw only where your time, energy, and attention went this year, what would they think actually mattered to you?
the full 19-minute lecture is in the video below.
Johan Jessen retweeted
there is a vanishingly small number of humans alive at any given point that have the skills to do complex, high personality, high convexity dealmaking. this has replaced “general management” as the most sparse asset in the world and will pay you trillions if you actually have it
the modern deal guy has no permanent capital, no permanent loyalty, and no permanent location.
the modern deal guy is playing a repeated game, he doesn't care who he pisses off, there's going to be another hand.
the modern deal guy is much more a broker than a principal. he has an ecosystem around him that identify as "his guys"
the modern deal guy has 99% of his chips on the table at any given moment, the next hand will always be bigger.
the modern deal guy is reticent to monetize any given opportunity early, but when he decides its time to sell, he does so savagely and without concern for fallout.
the modern deal guy is only concerned about where he spends his time. he runs a schedule like a CAA agent
the modern deal guy is only constrained by sourcing talent to put behind ideas at scale, capital and opportunity sets are infinite
the modern deal guy either has an exhaustively curated public persona, or none at all, anything in the middle is a mess.
the modern deal guy has very little concern for whats "on the paper", he's playing a very different game of pressure and repetition
the modern deal guy is unusually concerned about studying history and learning from adjacencies.
the modern deal guy has a personal burn that would make your nose bleed. all in service of maximum optionality
the modern deal guy can be better thought of as a "franchise" rather than a firm. the modern deal guy will generate dozens of lesser deal guys that will repeat the playbook in his stead.
Johan Jessen retweeted
there remains unbelievable alpha in paying attention to data broker procurement postings as well as frontier lab postings.
literally a public roadmap for where the frontier is at a given moment
We’ll pay you up to $100K for every company you refer that licenses its data to @Mercor.
We’ve partnered with > 500 companies so far.
If you know a company with 100+ employees and data in code, gaming, manufacturing, healthcare or professional services, refer them at data.mercor.com/refer.
Good insight. Same issue with sensor fusion.
It is unfortunate that so much of the robotics world uses 50 hz joint targets, while the video data collection is at 60 hz. That skew isn't in the top ten problems for most robotics efforts today, but eventually it should be. Easier to adjust the robot fine control rates than all the video data! Add a gen-lock like trigger signal to lock the phases while you are at it.
Johan Jessen retweeted
To their great shame, the Danes managed to bully Sweden into closing the Barsebäck reactor in 1997. After spending two decades on the cause. Now data centers have to wait 10+ years to be connected in Denmark because wind has wrecked the grid. Tragic self-own.
Denmark spent decades building nearly 5,000 wind turbines
Together, they produced 21.6 TWh in the last 12 months
One nuclear plant in Sweden made 23.3 TWh
Oh, and nuclear runs 24/7 — wind doesn’t
There's one big reason Denmark has some of the most expensive electricity in the world
transparency.entsoe.eu/gener…
api.energidataservice.dk/dat…
eia.gov/electricity/monthly/…
iaea.org/publications/16059
Johan Jessen retweeted
lol can you imagine how goated the Danish economy would have been is they hadn’t gone anti-nuclear in the 80s.
Johan Jessen retweeted
JUST IN: Two former SpaceX engineers raised another $115M to turn existing airplanes into self-flying aircraft.
Reliable Robotics is building an autonomy system that can be retrofitted onto planes already in service.
-Automates engine startup, taxiing, takeoff, flight, and landing
-First target is the widely used Cessna 208B Caravan
-Already demonstrated a Caravan flying with nobody onboard
-First version keeps a pilot onboard using a touchscreen
-Next step moves the pilot to a ground-control station
-System is being designed for FAA certification
Reliable is now valued at more than $1B, with its first certification targeted within 18–24 months.
Johan Jessen retweeted
We found a way to scale humanoid control that reduces GPU-hours by more than 1000Ă—.
Across 129,514 motions, SuperMimic surpasses the state of the art (128 GPUs, 7 days) with 1 GPU in 3 hours.
Project: supermimic.github.io
Demo: supermimic.github.io/demo/
Johan Jessen retweeted
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from scratch in under 4 months
Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
Johan Jessen retweeted
People who cured / are curing their own cancer on X:
1/ @sytses - bone cancer, billionaire founder of Gitlab, developed 10+ personalized therapies for himself.
2/ @paul_conyngham - shrank his dog Rosie's mast cell cancer tumors after chemo and surgery weren't enough. Now backed by YC and Founders Fund
3/ @miriamgonp - stage 4 breast cancer, tumor sequenced, searching for vaccine manufacturer now
4/ @kevinace - stage 4 lung cancer, angel investor in 300+ companies, first drug stopped working after 18 months. Vaccine designed, now paying $300k out of pocket for the vaccine
5/ @masonbgrant: going founder mode on his his 32-year-old wife's rare liver cancer, sequencing her tumor with AI agents
6/ @ArunRLverma: former product leader at Atoms and Shopify, brain tumor, built a vaccine from his tumor. Now building an AI health agent startup based on what he went through
We're going to make it
Johan Jessen retweeted
Last month, we demonstrated high-rate alchemy: turning mercury into real, stable gold, beating CERN’s record by a factor of 10.
Last week, we enriched isotopes in the world’s most powerful plasma centrifuge, beating the Soviet record that stood for 40 years.
Now, we’re building a fusion reactor in San Francisco to achieve record power density.
Johan Jessen retweeted
“One of the worst things that slows down progress is the concept of 'emergence.'”
This week on 632nm, @drmichaellevin (@TuftsUniversity) argues that the concept of emergence can hold science back by treating unexpected biological behavior as an explanation rather than something to investigate.
“Emergence just means surprise... You didn’t see it coming.”
If we call something “emergent,” we still need to explain why this behavior emerged instead of another. The goal should be to understand the underlying patterns well enough to predict and control them.
We discuss how this perspective could reshape biology, our understanding of intelligence, and AI.
Full episode on X and YouTube (see comment).
Timestamps:
00:00 - Intro
01:16 - Platonic Space
03:55 - Biology in the Absence of Evolution
21:11 - Extracting Knowledge from Platonic Space
37:04 - Development and Loss Functions
50:09 - Investigating Layers of Control
55:35 - Is Computer Science Misleading Our Understanding of Minds?
58:14 - Bioelectric Patterns and Drug Discovery
1:04:07 - How to Build a Predictive Developmental Model
1:13:20 - Levin’s Top Books, Thoughts on Collective Existence
1:18:00 - Questions that Keep Michael Up at Night
1:22:32 - How Does Levin Interact with AI?
Johan Jessen retweeted
GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration?
DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in making cholesterol. GPT-Rosalind suggested a possible explanation: cholesterol may not be reaching where neurons need it.
That gives scientists a specific mechanism to test and, if confirmed, a direction for developing new treatments for neurodegenerative disorders.
With @perturbai_tx and @scrippsresearch, a team of thousands of GPT-Rosalind agents worked in parallel, connecting gene-expression results from millions of mouse brain cells with scientific literature in just 32 minutes. We’re now expanding this collaboration to identify new drug targets.
openai.com/index/scaling-ai-…
Johan Jessen retweeted
Over the summer, we achieved more drug development milestones than in the rest of @newlimit history. We scaled our manufacturing processes, ran our first large animal model studies, and engaged productively with regulators. Our pipeline of reprogramming payloads continued to grow, hitting new all time highs for both the quality of our best payloads and the quantity of payloads we explored.
>2X stronger regenerative rescue in old hepatocytes
+2 payloads rescue multiple functions in old hepatocytes
+8 payloads restore function in old endothelial cells, +5 in hepatocytes
314X scale up of therapeutic manufacturing, 13X quality improvement
2.5X improvement in endothelial cell age prediction accuracy
>5000 payloads tested (during just the summer) for effects on cell age (all time high!)
5X improvement in data efficiency from transfer learning
Johan Jessen retweeted
We’ve raised a $45m Series A, co-led by
@foundersfund and The @OpenAI Startup Fund, to build cancer therapy that learns. Technology is rapidly changing medicine, but data loops and rapid adjustments are still largely missing. When you start cancer treatment, knowing whether what you’re doing is working is too slow. Clearly there is a better way. Build systems to watch cancer in real time, then feed that data into a system that itself can treat the disease. This seeds a future where, unlike drugs, we develop medicine that continuously learns to improve itself. We've been building neurotechnology and BCI platforms to do just that.
@coherenceneuro
Image classifiers strike again. thelancet.com/journals/landi…
In 2016 I was toying with an idea at Google X called Project Elion named after Gertrude Elion. It was simple. A bathroom mirror with embedded sensors that would sensor vitals via high-res images of your eyes, skin, expressions, heart rate. And track it over time. Predict disease, strokes, common colds, pregnancies... before symptoms showed up.
It was too early. Still reeling from Glasshole mania, Google execs weren't too keen on funding a bathroom mirror with cameras. Understandably. But controlling light, time of day, and frequency is super important for diagnostics. The pieces are all there.
Eventually someone stumbles over this idea again and makes it real. And I'll be eager to buy one.
Johan Jessen retweeted
1) Today we're announcing Atomwell, our state-of-the-art foundation model for predicting experimental outcomes, alongside scaling laws for molecular discovery.
We trained models from 800M to 9B parameters on ~80M experimental measurements, and found clean scaling laws in both model size and data.
Johan Jessen retweeted
Today we introduce Plato: the ring for near-silent speech.
We speak faster than we write. But we can’t always say out loud what we’re thinking.
Plato turns thought into action.
Dictate. Transform. Delegate.
Order now: plato.it.com. Limited supply.