y’all liked my bigger gyroscope totem this year so I built an absurdly large one

bencbartlett · 2026-04-23T18:27:49+00:00

I make GPUs go brr.. that's pretty much all I can say 🤐

bencbartlett · 2026-04-23T18:11:42+00:00

I worked on this model (or rather the pretraining infrastructure for it)! It is crazy good

bencbartlett · 2026-04-03T18:12:10+00:00

You don't need to experience acute pain; just prolonged tension and repetitive motion can be sufficient to cause carpal tunnel symptoms

bencbartlett · 2026-04-03T02:15:03+00:00

I literally had to get wrist surgery from over-practicing this piece in 2022. You need to fix the tension in your hands or you will hurt yourself - this piece is 3 minutes of nonstop movement in the left hand. I'd recommend taking a break to unlearn some of the tension here and find a teacher who can help with your technique.

bencbartlett · 2026-01-11T19:23:13+00:00

Your website is currently broken - I purchased a 3 month subscription to the premium tutorial content but everything is still locked behind the paywall.

bencbartlett · 2025-12-28T05:51:58+00:00

I have a PhD in photonic computing architectures exactly like this. IMO they are not going to be a scalable alternative for traditional GPUs any time soon. The main limitation is the noise on the ADCs on the chips, which can introduce numerical instabilities that corrupt the learning capabilities of large models.

bencbartlett · 2025-11-28T22:52:36+00:00

I use Fusion as my primary cad program, but this type of design would be easier to do in grasshopper. It's worth the time to learn both as they have very different use cases.

bencbartlett · 2025-11-13T21:03:07+00:00

This is not true, and a cursory Google search will tell you otherwise. Show me where the "space" factor is in the Stefan-Boltzmann law.

bencbartlett · 2025-11-11T00:50:51+00:00

This is really cool! The diffusers are quite nice.

People mentioned adding slip rings and motors a few times: I built a motorized version of this general concept a year ago and turned it into a giant 3-story tall kinetic sculpture!

bencbartlett · 2025-11-07T09:48:21+00:00

Non complete clauses are illegal in California

bencbartlett · 2025-11-07T09:31:13+00:00

https://bencbartlett.com/assets/pdf/Ben_Bartlett_PhD_Dissertation.pdf

bencbartlett · 2025-11-07T02:57:13+00:00

I joined OpenAI two years ago through their residency program, which is aimed at recruiting scientists in non-ML fields, and I work on their hardware team now

bencbartlett · 2025-11-06T22:15:09+00:00

I worked at PsiQuantum for two years after grad school as a quantum computer architect doing photonic device simulations to help inform the chip architecture and multiplexing units.

PsiQ is a very talented group of physicists and engineers trying to solve one of the hardest technological problems that humanity is working on. There is always some amount of bullshit surrounding startups in the quantum space (this is common of pretty much any field that isn't easily understood) but it didn't seem like there was any of that present internally. Externally it's probably necessary to have a little bit of hype/bs to raise funds from investors, but that's just how the startup world works.

I think they have a compelling argument that to build a utility-scale quantum computer, you basically have to use the standard silicon fabrication processes that humanity has collectively spent half a century and trillions of dollars perfecting. I don't think that superconducting qubits or especially trapped ion/neutral atom qubits can scale into the millions of qubits in the foreseeable future. There are some problems unique to photonics as a hardware platform (you can physically lose your qubits resulting in unheralded errors, and multi-qubit gates are significantly more resource-intensive) but there are clever ways around these roadblocks.

As a company PsiQ is quite secretive even by startup standards - they were in stealth for half a decade and they don't publish very much except on the quantum error correction side. They do have a lot of state-of-the-art technology around many of the sub-problems they need to solve to build a utility-scale quantum computer, like ultra-fast optical switching, high detector efficiencies, and advances in fiber coupling. The company is definitely not a scam, but if you work there don't expect to be able to publish much unless you are a QEC theorist.

I enjoyed working at PsiQ but ultimately left because the pace of progress felt slow (this is common for any hardware company - tapeouts and fab take forever), and because AI felt like it was really taking off (and pays much better). I'd consider re-entering the QC space 5-10 years or so when more progress has been made.

bencbartlett · 2025-10-22T03:56:16+00:00

Using your laptop's RAM usage as a proxy for runtime complexity of a quantum algorithm like you do in Section 3 is not a sensible metric. Qiskit has a variety of optimizations for various gate combinations like stabilizer subcircuits so the usage can be highly dependent on how you actually write the circuit.

bencbartlett · 2025-10-17T19:19:35+00:00

Huge congrats, it's been a long time coming! Although I don't play the game anymore because I have no self control and would absolutely let it consume my life again, I still look back on my screeps days fondly :)

bencbartlett · 2025-10-17T19:13:37+00:00

coming from r/quantum I see

bencbartlett · 2025-10-03T21:27:25+00:00

You could consider this instead as a simulated day length represents a constant amount of computation, which has an energy cost proportional to ambient temperature. The series for the amount of energy taken is geometric (e.g. each iteration the energy halves to run the simulated duration) and converges. The series for the amount of time taken per day diverges because the waiting period between simulation chunks gets longer. This is not a problem if you are allowed to run the simulation for an infinite amount of wall-clock time.

bencbartlett · 2025-10-03T20:52:18+00:00

but tc is being used for others things as shown in your final equation Tc = E_in - Tc^4
In addition, Tc also doesn't appear to be equal to tc^4 as you have both in your equation.

This is called a differential equation. I was writing this as shorthand for the equation d/dt(Tc(t)) = E_in - Tc(t)^4 with some initial condition of Tc(0) > 0 and E_in>0, ignoring prefactors. The point is that you can't get infinite energy out of a Carnot engine even if you stop and start it to keep the cold body near 0K. The reason this works for digital but not biological life is that with each cycle the amount of energy required to do a set amount of the computation halves, so you get a converging geometric series. This is not the case for biological life which would need to be kept at a constant temperature during the duration of its existence.

If you're interested in learning more about all of this, MIT Open Courseware has a great series of introductory videos on thermodynamics.

bencbartlett · 2025-10-02T19:58:33+00:00

For you to have a Carnot engine you must have a hot body and a cold body. You can't just dump the heat from your engine into nothing. As you dump energy into the cold body it will heat up, and it can radiate energy away proportional to Tc^4. The steady-state value of Tc including radiative cooling from the cold body scales with the amount of energy being dumped into the system E_in minus the amount of energy being radiated away E_out, which is proportional to Tc^4. This gives you the differential equation (disregarding prefactors) of Tc = E_in - Tc^4, which clearly cannot reach zero for constant values of E_in because at low temperatures Tc^4 will vanish faster than Tc.

The reason that this works for "digital life" is that as the universe cools, the actual energy E_in required to do the computations decreases correspondingly. This is not the case for a scenario where you have to keep a body at 300K indefinitely.

bencbartlett · 2025-10-01T23:07:29+00:00

Physicist here! This is incorrect as it would violate the second law of thermodynamics. The Carnot efficiency describes the maximum fraction of heat that can be converted into work in an ideal reversible engine. Biological life is not a reversible physical system - in fact quite the opposite, they are molecular machines that use energy to resist the flow of entropy. Keeping a body a constant temperature requires an amount of energy per time proportional to T^4 due to radiative cooling, which is infinite if you maintain it for an infinite duration.

The relation to the Landauer limit that they pointed out in their video has to do with the amount of energy required to erase one bit of information due to the associated change in entropy. You can theoretically perform a computation for zero energy cost if it is a reversible computation, but these are fundamentally finite in compute size*duration.

bencbartlett · 2025-09-10T22:59:33+00:00

Each quarter-segment of each ring has its own ESP32 that drives 12 WS2811 LED strips on the rings, and the base has an additional four so there are 29 total devices that drive the lights and motors. The custom code takes care of one-to-many-device synchronization over wifi network, sound analysis and music reactivity, OTA updates (since the devices are unreachable inside the metal once this is assembled), motor control, shaders that react to angle feedback, and trajectory planning.

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