Physicist & CEO of DÆDÆLUS; Join the conversation on our evolving knowledge of the nature of time & causality. And how we make the world safe for transactions.
Palo Alto, CA
Joined October 2015
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Paul Borrill retweeted
I’m a physics teacher, and quite a few stories have stayed with me throughout my career.
In my class, there’s an unwritten rule: For every final research project, students must submit a lab notebook recording all raw measurement data. Missing data or fabricated results mean an automatic F, in science there’s simply no room for dishonesty.
At the end of the term that year, a girl came to turn in her reversible pendulum project which was meant to measure the acceleration due to gravity. The data in her notebook was all over the place, and her graph was wildly off from the theoretical value of 9.8 m/s².
"My results are... completely ruined," she said. "Everyone else got nice numbers close to 9.8. I guess I'm getting an F".
I looked at her densely packed notebook, filled with meticulous notes: measurements taken at 2:00 AM, the humidity in her bedroom, even the exact times the string snapped and had to be retied. Having taught for over a decade, I can easily tell who fakes their numbers to match the textbook and who stays up all night putting in the real work.
"Why didn't you just tweak the numbers a bit to get closer to 9.8, like the others?" I asked.
She looked up, her eyes rimmed with red, but her voice was steady: "Because the data is what it is. You taught us that a scientist never lies about their data."
I silently flipped to the next page and marked a big red A.
She was stunned. "Wait... but my experiment completely failed?"
"Your experiment didn't fail. It just proved that your pendulum had air drag and a wobbly pivot" I said. "Science isn't about manufactured perfection, it's about the pursuit of truth. You stood up for the truth, and that's the true mark of a researcher."
Starting that semester, I created a small award in the corner of the lab: "The Best Failed Lab Report", given to the experiment with the most skewed results, but the most honest logs and thorough error analysis.
I want these kids to understand that having the courage to acknowledge mistakes and confront reality matters far more than faking a perfect score just to please someone else.
Paul Borrill retweeted
Nice, cc @plborrill
A single metasurface uses quantum interference to generate, transform, and distribute four Bell states across 21 channel pairs, providing an ultracompact and scalable platform for multiuser quantum networking.
Letter: go.aps.org/4sFc5MC
PhysMag: go.aps.org/4qPUz6D
Paul Borrill retweeted
Classical billiards can compute.
With @Isaacramr__ , we show that 2D billiard systems are Turing complete, implying the existence of undecidable trajectories in physically natural models from hard-sphere gases to celestial mechanics.
Determinism ≠ predictability. 🎱🧠@ETH_en
Paul Borrill retweeted
Microservices is the software industry’s most successful confidence scam. It convinces small teams that they are “thinking big” while systematically destroying their ability to move at all. It flatters ambition by weaponizing insecurity: if you’re not running a constellation of services, are you even a real company? Never mind that this architecture was invented to cope with organizational dysfunction at planetary scale. Now it’s being prescribed to teams that still share a Slack channel and a lunch table.
Small teams run on shared context. That is their superpower. Everyone can reason end-to-end. Everyone can change anything. Microservices vaporize that advantage on contact. They replace shared understanding with distributed ignorance. No one owns the whole anymore. Everyone owns a shard. The system becomes something that merely happens to the team, rather than something the team actively understands. This isn’t sophistication. It’s abdication.
Then comes the operational farce. Each service demands its own pipeline, secrets, alerts, metrics, dashboards, permissions, backups, and rituals of appeasement. You don’t “deploy” anymore—you synchronize a fleet. One bug now requires a multi-service autopsy. A feature release becomes a coordination exercise across artificial borders you invented for no reason. You didn’t simplify your system. You shattered it and called the debris “architecture.”
Microservices also lock incompetence in amber. You are forced to define APIs before you understand your own business. Guesses become contracts. Bad ideas become permanent dependencies. Every early mistake metastasizes through the network. In a monolith, wrong thinking is corrected with a refactor. In microservices, wrong thinking becomes infrastructure. You don’t just regret it—you host it, version it, and monitor it.
The claim that monoliths don’t scale is one of the dumbest lies in modern engineering folklore. What doesn’t scale is chaos. What doesn’t scale is process cosplay. What doesn’t scale is pretending you’re Netflix while shipping a glorified CRUD app. Monoliths scale just fine when teams have discipline, tests, and restraint. But restraint isn’t fashionable, and boring doesn’t make conference talks.
Microservices for small teams is not a technical mistake—it is a philosophical failure. It announces, loudly, that the team does not trust itself to understand its own system. It replaces accountability with protocol and momentum with middleware. You don’t get “future proofing.” You get permanent drag. And by the time you finally earn the scale that might justify this circus, your speed, your clarity, and your product instincts will already be gone.
Paul Borrill retweeted
For the first time, physicists have formulated quantum theory without imaginary numbers, overturning a 2021 claim that these unreal numbers are essential for describing the quantum world. @dangaristo reports: quantamagazine.org/physicist…
Paul Borrill retweeted
An efficient probabilistic hardware architecture for diffusion-like models
arxiv.org/abs/2510.23972
✍️ @andyJelincic @GillVerd @trevormccrt1 et al. via @arxiv @extropic @beffjezos
👉 This work proposes "an all-transistor probabilistic computer that implements powerful denoising models at the hardware level"
👉 "A system-level analysis indicates that devices based on our architecture could achieve performance parity with GPUs on a simple image benchmark using approximately 10,000 times less energy"
@Corix_JC @jeanyvesgonin @sonu_monika @JagersbergKnut @ahier @sim010101 @maponi @EstelaMandela @Shi4Tech @CEO_Aisoma @SpirosMargaris @IngridVasiliu @dinisguarda @mvollmer1 @RamonaEid @ChuckDBrooks @FernandaKellner @PVynckier @JoannMoretti @NeiraOsci @tlloydjones @SusanHayes_ @theomitsa @TarakRindani @FrRonconi @Nicochan33 @mikeflache @Khulood_Almani @TysonLester @CurieuxExplorer @KanezaDiane @Ym78200 @amalmerzouk @sulefati7 @pchamard @Analytics_699 @MaryRich78 @TheAIObserverX @NathaliaLeHen @sminaev2015 @jeancayeux @WillyRayNick @DanielleLargier @RLDI_Lamy
ALT An efficient probabilistic hardware architecture for diffusion-like models https://arxiv.org/abs/2510.23972 📸Source Fig 5 / arxiv.org/abs/2510.23972
Paul Borrill retweeted
Some early HC employees will probably remember me joking that it was my divine mission to eliminate YAML from the world. I joked I started HC only to kill YAML. Like, back in 2013. And we (as an industry) were so close! Then Kubernetes came out and fucked it all up.
Paul Borrill retweeted
Every now and then, the database world dips into a mania where really dumb ideas flourish. The separation of storage and compute at scale for OLTP is the latest. Making all your queries slower so you can shut your DB off quickly is an insane trade-off that nobody serious would make
Paul Borrill retweeted
DDR5 is unstable garbage.
Max out your memory channels? Flaky.
Temperature a bit too hot? Silent Throttle with no logs.
Too “Dense” of a stick? Good luck training.
Last gen was rock solid by comparison. Here's what happened.
Paul Borrill retweeted
.@mjgoldwater: Why do you have a positive vision for humanity?
@DavidDeutschOxf: Well, I think I'd rather use the word aspiration. So, I think that human beings are what I call universal explainers, which means that they're capable of arriving at any conclusion, but that's true or false. So, and we arrive at true ones via a history of false ones.
So, I think there is nothing beyond human capacity to create, to understand, to control, with the only limitation being the laws of physics. But equally, there's no limit to the size of error we can make. And we depend for both things on error correction.
So, error correction is the most important attitude of the mind, and it's also the most important institute, the most important characteristic of institutions in society.
@mjgoldwater: Sort of the most important mechanism. Yes.
So, just to drill down on that, why is error correction so important?
@DavidDeutschOxf: Because errors are inevitable. So, I'm a fallibilist, like Karl Popper. So, I believe that there's nothing infallible in the world.
There's no touchstone of truth that we can find somewhere in the garden and pick up and say, you know, is this true or not? And it'd be infallible.
@mjgoldwater: Sorry, whenever you say that, when I'm listening to you on your podcasts, I always think of the Pope.
@DavidDeutschOxf: Yes.
@mjgoldwater: Surely you must say, except for the Pope.
@DavidDeutschOxf: No. As I have often explained, even if the Pope is infallible, your theory that the Pope has said a particular thing is fallible.
Your theory that that is the Pope, you heard saying it, is fallible. Even if you break into the Vatican and hide somewhere, and by the way, he has to be sitting in the throne for it to be infallible.
@mjgoldwater: I didn't know that.
@DavidDeutschOxf: If he's not sitting in the throne, it doesn't count... So, he's sitting in the throne, you're hiding in the room, you see him sitting in the throne, and he says a thing.
You still can't be sure. You're not infallibly sure because you don't know that this is the day on which he's going to... Maybe he's doing a dress rehearsal.
@mjgoldwater: Or it could be a fake Pope. It could be a stand-in for the Pope.
@DavidDeutschOxf: So, these are all examples of the fact that in order to conclude that something is true on the grounds of papal infallibility, you have to assume fallibly a lot of other conditions, and you can't get past that.
There's no way of getting past that completely.
@mjgoldwater: So, we come to knowledge through fallibility. Is that what you're saying?
@DavidDeutschOxf: Yes.
Paul Borrill retweeted
IMO database per micro service is about extreme failure isolation few orgs need.
You can achieve many 9’s by having a solid data arch & still retain read your own writes semantics & without eventual consistency between modules.
Extreme isolation prematurely has many drawbacks
Paul Borrill retweeted
When I was younger I believed all of the social media about don’t use the DB as a scheduler. Don’t use the DB as a queue.
But when I look at things like DBOS there’s a huge advantage of having atomicity and rollbacks of operations between the scheduler and app operations.
Paul Borrill retweeted
Everyone knows that the x86 ISA is big.
Modern CPUs have ~1000+ mnemonics. Guess how many make up 90% of compiled C/C++ code?
TWELVE. I'm not kidding.
The question is…what if we shrank it?
Paul Borrill retweeted
"Reductionism and holism are both mistakes. In reality, explanations do not form a hierarchy with the lowest level being the most fundamental. Rather, explanations at any level of emergence can be fundamental. Abstract entities are real, and can play a role in causing physical phenomena. Causation is itself such an abstraction."
@DavidDeutschOxf
Paul Borrill retweeted
If you do functional programming (like in Wolfram Language) you've probably used lots of pure functions, or lambdas. But what are lambdas like in the wild? Things I'm doing in CS, bio and ML converged to make me curious to find out... And as seems to happen whenever I go exploring in the computational universe ... they surprised me ...
writings.stephenwolfram.com/…
Paul Borrill retweeted
Summer of OLTP continues...
- databricks acquires @neondatabase for $1B
- snowflake acquires @crunchydata for $250M
- mariaDB (re)acquires @skysql
- temporal acquires @auto_dba
- vector (PE firm) buys @SingleStoreDB
- @supabase raising at $5B
turns out everyone needs txns 🙂
Paul Borrill retweeted
If you store data forever, you don’t use any power.
Sound’s ridiculous, but computation doesn’t *actually* require energy.
The field of Reversible Computing experiments with “reverse” programming languages, compilers, and yes, even CPUs:
Paul Borrill retweeted
The main source of heat in processors is *erasing* bits.
Known as Landauer’s principle, irreversibly destroyed information has a thermodynamic cost.
The trick, is to perform "uncomputing" instead:
Compute -> Copy Result -> Uncompute
Paul Borrill retweeted
A crazy open problem in algebra:
Conjecture (Poonen): 100% (asymptotic density) of finite commutative rings have characteristic EXACTLY 8, i.e. 4 ≠ 0 and 8 = 0 both hold.
From this amazing paper: arxiv.org/abs/math/0608491
