exploring new frontiers / crypto optimist / host @interintellect_ / ☧ / rewilding maximalist
London
Joined March 2008
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David McDougall retweeted
a serious company would move its headquarters onto a reservation, enroll every employee in the tribe, and enforce its non-competes in its own tribal court while avoiding any federal oversight but they simply won't do it
David McDougall retweeted
Any aspiring sound designers in our midst? I'm after for someone who can do sound design for a narrative short film (3.5 minutes): inventive, technically capable, pref. with your own sound recorder (in case you need to record something custom on your end).
@reckoner165
David McDougall retweeted
here’s what I think might be the essential challenge of parenting:
your children are born not as your peers, but as your dependents. if you treat them like your peers when they’re too young, it’s unfair to them. but if you treat them like dependents for too long, that’s unfair to them too. you can try to be scrupulous about being fair, but you can’t make the cost of that scrupulosity their problem.
your task is to raise them to *become* your peers. meaning you have to repeatedly update how you relate to them. this is hard!! 99% of human interactions aren’t like this! Most interactions happen in comparatively stable configurations. It’s rare that your boss today is your employee tomorrow. But in parenting this dynamism is inevitable. The child ages into the adult, the adult ages into the child.
every parent probably has a phase that they’re uniquely In The Zone for. Alice might be great with toddlers. Bob might be great with 7yos. Claire might be great with preteens. Whatever your strength is, you likely have a corresponding weakness. And your kids, if you’re lucky, will grow through all of the ages. So you’ll inevitably find yourself in a context you’re uniquely unsuited for. And it’s your duty to show up and try your best anyway.
it’s a very elaborate, nested series of balancing acts, which requires a level of attunement you likely didn’t have before. every day you encounter the need to balance humility and confidence, or some other bullshit like that, and the next challenge hits you before you have time to process the last one.
It’s great. Knowing what I know now, I wish we had our kids sooner. I have a lot more to say on the topic (particularly why it’s great, both *despite* the challenge, and *because* but I gotta end this here because we’re in the middle of shopping for Deepavali clothes so ttyl)
David McDougall retweeted
the proudest moments of my life have always been when I knew I needed something different from my status quo even when I had severe doubts it was possible, and acted on it. sometimes you have to move towards things you can't even see, and it feels like utter insanity
David McDougall retweeted
God loves movement — my favorite excerpt from a recent edition of Bookbear Express, one of my favorite Substacks: open.substack.com/pub/ava/p/… I’ve had to learn this lesson again and again, and imagine I will again in the future.
David McDougall retweeted
The benefits of abundant intelligence will accrue far outside of San Fransisco.
Spent the last year writing about capital, sovereignty, and the coming reordering of economic power.
THE COMMANDING HEIGHTS
Commanding-Heights.com
David McDougall retweeted
imagine telling a kid who finished 3rd grade math in a single day that he's "not developmentally ready" for 4th grade math
maybe the age-based grade level is already over, just most people haven't heard about it yet ...
David McDougall retweeted
500+ have installed decks
would love to have more people try it out. if you are trying to build a deck and want it to not be filled with slop or pretty slides that dont say anything, try it out
happy to help you with your pitch too, dm me
github.com/paulmil11/decks
David McDougall retweeted
The TSO, or Technology Support Office, was established in April to 'covertly disrupt and sabotage foreign technology programs considered threats to American military superiority.'
In September the Washington Sun reported that the NSA told lawmakers in classified intelligence briefings that it estimates it has spent billions of dollars 'evaluating and testing' models this year already.
In the draft S-1 leaked by the WSJ yesterday, Anthropic said that one-fifth of its $16.3 billion in revenue in the first half of 2026 came from just two customers.
Motive, means, and opportunity. I think a lot of money is being spent by agencies through Project Glasswing or channels related to it, and they have probably covertly penetrated every nation on earth to look at anything even potentially considered a threat. There is no defense against the current internal version of Mythos unless you have access to it. No foreign intelligence agency on earth has anything even close. It's actions would also almost certainly be undetectable. Assume US agencies know much more about any technological progress in China than they are letting on; given Dario's openly stated position on China, this would almost certainly be done with his approval.
David McDougall retweeted
8 simple changes to make your "about us" page more visible in AI search
1. start with a clear value prop
2. add a "what [company] Does"
3. add a "what makes [company] different"
4. add a "who uses [company]
5. add a "the team behind [company]
6. add a "how [company] works" section
7. add a "key facts"
8. finish with a "frequently asked questions"
David McDougall retweeted
Writing is not just output to be consumed, it is also reputation-building for the author.
If AI wrote the piece, not you, then I'm less interested in hiring you, inviting you to my conference/podcast, etc.
@tylercowen made a great point here.
some of the best social experiences I’ve had are:
1. meeting writers I like in real life
2. meeting people in real life and then discovering I like their writings
David McDougall retweeted
Steven Sinofsky on why it's so hard to diffuse AI into companies: most work runs on know-how that's hard to turn into step-by-step instructions for an agent.
"Algorithmic thinking is really, really, really hard for the vast majority of people who have jobs."
"If you were to go to any person and ask them to create a flow chart for a particular thing that they have to go do, they would probably fail at producing that flow chart."
"Say doing a marketing plan and there's 50 marketing people working on a giant product line. One person probably understands and could document the flow chart."
"So if you put one of these agents in front of people to create these things, their ability to explain to it what to do is really, really limited."
"You're basically just developing the next abstraction layer for how people interact. And developing an abstraction layer has historically, at each level of the abstraction layer, been a highly skilled, very specific individual within an organization."
@stevesi
Jean-Denis Greze, founder of @TownAI, argues AI isn't diffusing because most people aren't tinkerers: a text box isn't enough, so the product must both identify the value prop and perform the work for them.
"There's this business that rents surfboards on an island to people and then uses Town to inspect surfboards and little beach buggies, whether they've been damaged, to decide whether afterwards the person should get their deposit back."
"What makes it work there is the tinkerer... The unlock is, is there someone over there that gets AI enough to wanna tinker a solution to their problem?"
"And the problem with that is that there aren't enough tinkerers in the world, or there aren't enough people that have the time to be tinkerers to help their business. And I think that's why AI is not diffusing."
"Instead what you're doing is you're using [AI tools] as a replacement, as like a better Google search."
"If you can make a non-tinkerer into getting the same value as a tinkerer... you could be a ginormous business today because AI can solve so many business problems. You don't need more intelligence. The intelligence is there."
@jgreze @arampell
David McDougall retweeted
I've been thinking a lot about data bottlenecks, and I'm not sure who else is screaming this from the hilltops. I feel like I'm taking crazy pills looking at the jagged frontier thinking it's smooth if you order by data volume.
the spikes in the jagged frontier are tasks with tons of data (either static or simulated; think math, programming, games), and the valleys are tasks with little or no data (cooking a lasagna, olfaction, manufacturing a passenger train). I don't know of any exceptions.
if you order the jagged frontier by data it looks like a spiral frontier. models are superintelligent where we have enormous data, and progressively less so as we have less data. some tasks may draw data from static lakes of data, some may be from limitless waterfalls from simulators that convert compute into data. but ultimately, intelligence on a task is proportional to the data absorbed by the model for that task.
scaling laws are real. if you are not bound by compute or algorithms (increasingly we are not), then intelligence is proportional to data. since we don't have a very good notion of task similarity, it's often difficult to know if data for one task will help you with another, without training a model and seeing. but, it doesn't seem like chess data helps much with math performance and vice versa. so when I refer to data, I refer to data that is task-relevant.
maybe we call this the 'no shortcuts hypothesis'. all the rules-of-thumb about learning are at the root, the same -- Malcom Gladwell's 10,000 hours, Moravec's Paradox, Scaling Laws, the Bitter Lesson, Age of experience. If your learning system (model, brain, whatever) is unconstrained by compute, intelligence is proportional to accumulated experience. no shortcuts. want to be superhuman at chess? play all the chess, more than the whole species combined (good thing a model can do that in 24 hours). want to be superhuman at math? build a math simulator and lock the model in it and run it faster than reality. superhuman at coding? first, collect all public examples of humans writing and responding to code ever, make the model learn from that first, and then lock the model in a simulator where it fixes bug after bug, faster than realtime.
superhuman at image generation? no shortcuts. but here, we don't have a simulator. so now we're moving around the spiral frontier away from closed-loop into large static lakes. still big enough to be superhuman though, which also applies to video, text, and audio. oh! and once you have a superhuman model, you can use it to bootstrap other tasks by making a superhuman model a judge on other tasks.
let's keep marching along the spiral frontier, out of the realm of data abundance, simulators and large static lakes.
biology? no shortcuts. go get a ton of data. and be freaking careful! you can get bad data in biology pretty easily. tilting a well plate 5 degrees the wrong way can ruin an experiment. so make sure you understand the domain, otherwise you're going to have to filter a lot out.
robotics? no shortcuts. get the data. if you can build a simulator, do it, but be mindful our simulators don't have perfect correspondence with reality. so, build an arm farm. fold 1M shirts, put 1B balls in cups. play ping pong forever.
olfaction? no shortcuts. smell the world. build a laboratory of chemical sensors, an international network of trained sensory panelists, a scent production factory, and link them all together. make millions of samples. smell millions of samples. take billions of chemical sensor readings.
I totally buy super intelligence as a concept because I feel it, I use it for coding, the breakthrough math results speak for themselves. I see RSI coming, because how could an all-digital task like ML research and model building not fall to the current paradigm? But the notion that AI will come for everything, all at once, irrespective of domain, feels silly, because there are no shortcuts. if you want a specific form of intelligence, you have to get the data.
looking at you @willdepue, I feel like we're both seeing the same thing
🤖 Made with AI
David McDougall retweeted
this is incredible
the guys at Citrini used Claude to design completely new proteins for a potential scorpion antivenom
Claude launched more than 300 agents, ran the research, designed 211 proteins in 64 hours, and sent the designs to a lab for testing.
17 of the 211 designs actually worked in the lab, binding to their targets
we are now at the point where just a few people with AI can do in days computational design work that used to require entire teams of specialized scientists
and this is just the beginning
What is AI really capable of in bio?
To separate hype from reality, we spent 3 months working firsthand with @AnthropicAI's internal research model to see if it could create an experimental scorpion antivenom.
Introducing Citrini Therapeutics.
citriniresearch.com/p/citrin…
David McDougall retweeted
The best seed-stage stories don’t start with “I’m building,”
They start with “I noticed…”
David McDougall retweeted
imagine paying accenture $32M for a website and them never shipping anything
could probably build it in a day on a $200 plan now
David McDougall retweeted
One of my favourite writers, @CharlesCMann, joins Works in Progress as a regular contributor. I am thrilled.
1491 and 1493, two of Charles's books, are among the best works of history I have ever read. 1491, which is about the Americas before Columbus, was one of those books that made me wonder if it could possibly be true, it was so surprising and shocking about that lost world. I read while I was travelling through Guatemala's countryside, and it made me understand the tragedy of the collapse and destruction of the pre-Columbian civilizations much better.
1493 is a rather different book, being about how the Americas changed the rest of the world. It is often tragic too, given the subject matter, but also completely captivating on how everyday things like rubber and potatoes changed the world.
What I think Charles's writing consistently has is a "fascination with the ordinary" – the conviction that even mundane-seeming everyday things often have a fascinating backstory. His articles for Works in Progress will continue this fascination. I strongly recommend his debut piece, out today, on the invention and reinvention of porcelain, written in the same spirit that has made his other writing so brilliant and eye-opening.
What do a cutting-edge bone implant and Mrs Potts from Beauty and the Beast have in common? Both are made from porcelain, a material humans first made over 3,000 years ago and are still reinventing today.
worksinprogress.co/issue/eve…
We focus on advances in computing, but the world around us has been transformed just as much by materials science. And within this already underrated field sits an even more underrated material. Plenty of people have heard of semiconductors, but almost no one thinks about porcelain. For @WorksInProgressMag, @CharlesCMann wrote about its remarkable journey:
- Porcelain is basically an ancient nanotechnology. 3000 years ago, Chinese potters found that firing a white clay called kaolin to around 1,200°C transformed it completely: its crystals get rebuilt, producing a material that is hard, dense, and sometimes translucent. Nobody knew why it worked at the time: they discovered it by trial and error.
- Europeans prized porcelain immensely – but had no clue had to make it. When porcelain arrived in Europe in the 12th century, it was so superior to European ceramics that aristocrats called it "white gold." But despite attempting to reverse-engineer it, Europeans failed to create porcelain for centuries.
- Fake it until you make porcelain. Böttger, an alchemist imprisoned in the early 1700s for falsely claiming to make gold, was set to work with a legitimate scientist on making porcelain. Remarkably, the scientist succeeded where others had failed for centuries, creating the first European porcelain cup. But he did not live to profit: ever the liar, Böttger claimed his discovery for himself.
- Less slippery when wet. Innovation in materials science picked up again in the 20th century and continues to this day, producing Porcelain 3.0. Today, porcelain can be found across a surprising number of household objects: from kitchen countertops to tiles that become less slippery when wet, which also makes them safer.
- The most futuristic use of all: researchers can now 3D-print porous porcelain scaffolds to repair damaged bone. The advantage is that blood vessels and bone cells grow into the scaffold’s tiny openings, while the scaffold slowly dissolves as new bone replaces it, allowing a bone-like natural structure to persist.
Porcelain has already gone from fragile imperial teacups to artificial joints and scaffolds that help bone regrow. But its 3000 year long story is far from over: expect this underrated material to play new roles in everything from medicine to architecture in the coming decades!
