@jwt0625

Extend all tails of the bell curve. Daily nerd snipe(s). Robotics. Photonics. RF/microwave. Nanofab. KO6FFN. Twitter as an open journal.

SF Bay Area
Joined August 2011
[Silicon photonics and co-packaged optics: what is inside the box?](outside5sigma.com/tutorial/s…) Great photo from @sokol_cc for the greatest intel 100G CWDM4 SiPho transceivers, and cover image is also intel's optical engine. I should put in more quiz next time to make it a proper tutorial.
putting together a long overdue SiPho and CPO blog
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it is sad and imo failure of the academic journals and publication process to end up with optimized publication strategy with some of the most beautiful efforts and methods and learnings hidden into supplementary materials. This is an absolutely unhinged way of getting a pristine nanomechanical resonator that has never seen the nasty resist or metal evap really close to electrodes from a SC qubit, and get such a high coupling rate of 1.7 MHz. (maybe I should redo some of my sims) However you do not see any of these amazing SEMs in the main text (last time I saw an SEM of the BOTTOM of a nanomechanical resonator was the aftermath of a failed acid clean where they blew up), you do not see any kHz or MHz rates in the main text other than the dispersive shift, because the story of why this measurement is possible is so simple, you can check whether it jumped or not much faster than the rate it jumps. we are training highly jagged talents with this type of research and this type of presentation being the journals' favorites, way more jagged than the frontier LLM capability joke. On the one hand the hamiltonian looks the same as the 60+ years old original one, swapping different toys you get from cavity QED to circuit QED to quantum acoustics. See, you have to use words like "acoustics" and "sound" for GHz vibrations to catch eyeballs. The whole system has 8 parameters, maybe max a dozen or two if you are doing real fancy stuff, and your job is to optimize one or two of them. Oops a 3rd param did not work with your optimization? Pick an experiment that does not require that one to be good. On the other hand, optimizing that one parameter has dozens maybe hundreds of hidden parameters behind it, and so much genuine work and insight. "align the mechanical resonators with the coupling regions of the qubit, and bond them together", that "align" involves iteratively turning at least ~10 knobs at various steps, and I have at least three questions on the "bond" part that they did not talk about. And these are few shot optimization challenges, you have to develop niche instincts to not drag yourself into another year of cleanroom grind. No one distill these learnings and instincts, and the journals do not encourage them enough to do so. So many "thinking traces", so many hidden tool calls, not to mention the logits you yourself had no idea when you made the DOE choices based on the instincts, all washed away by the rising tide of entropy. maybe those instincts will generalize and help you in distant future, maybe the journals are just the bottleneck an encoder-decoder model is supposed to have, and serving its purpose just fine: teaching people what quantum jumps of sound actually means.
We have observed quantum jumps of sound.
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[Supplementary Materials for Quantum jumps of sound](science.org/action/downloadS…)
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outside five sigma retweeted
A lot of people don't know that Lambda's first hardware product back in 2013 was actually a baseball cap with a camera embedded in the tip of the brim to gather datasets for image recognition CNNs. Cool to see this happening!
1/ Better robot models come from better data. That takes two things: hardware that captures it fully, and tooling that turns it into training signal. We built the first. Today, @GroundedSI launches the second: Grounded API. Access both hardware + API ↓
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this is kind of what quantum people mean when they say harvest now decrypt later
GPT-6 Astra deciphered a 1918 German radio transmission that, to my knowledge, has never been deciphered before. The message below translates to: "EIN ENGLISCHER KREUZER EINLIEG X SEWASTOPOL X S4STEN X EIN GESCHWADER DER X ALLIIERTEN FOLGT 26STEN X" or, in English: "AN ENGLISH CRUISER ARRIVED AT SEVASTOPOL ON THE ?4TH AN ALLIED SQUADRON FOLLOWS ON THE 26TH" Astra even double-checked its work by determining that an English cruiser, HMS Canterbury, reported its arrival in Sevastopol on November 24, 1918 and the arrival of an allied squadron on November 26, 1918. This message is one of the ~20 WWI German radio messages that appear as one of the entries in the scienceblogs.de list of top 50 unsolved ciphers (scienceblogs.de/klausis-kryp…). A minor, but really cool result!
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if i were fable or astra, id tell investors consulting me to invest in companies like this
We’ve raised $80 million in Series A funding, co-led by the Valor Atreides AI Fund and Hummingbird Ventures, with continued participation from Conviction, Abstract, A*, and Grant Gordon. This brings our total raised to over $100 million. We started Watney by asking a simple question -- what can a robot enable in industries where the work remains valuable on an infinite horizon? We found an answer in the fundamental inputs to civilization: energy, matter, and intelligence. A robot will never be as charming as a barista or as personable as a housekeeper, but it can be more exacting than a surgeon. And, a breakthrough in one quickly becomes the capability of millions. We don’t imitate human motions or processes. We care about the new, differentiated capabilities robots can unlock. We work on problems where our choice of embodiment gives us an order of magnitude advantage, whether through precision, reliability, or scale. Compute is just beginning to transform society, but it’s constrained by execution. Since 2025, Watney has been serving the largest hyperscalers in the world, helping accelerate their compute rollout through an end-to-end deployment model. Across hundreds of thousands of hours in customer facilities, our systems have achieved more than four nines of reliability. They’ve enabled our customers to build data centers faster, at larger scales, and with more ambitious architectures. Today, we operate the largest fleet of dexterous robots running 24/7/365 across the United States. This is all to say, it's an exciting time at Watney. We’re all here because we want to see more ambition in the physical world. We are hiring across all domains. Join us.
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mechanical dicing with a blade vs scribing-cleaving
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when you picture a fiber coupling light to a PIC, you should really picture a garden hose spraying water everywhere - Mandal2026: [Stitch-Free, Diamond-Scribed Silicon Nitride Photonic Integrated Circuits for the Visible Band](arxiv.org/abs/2609.17480)
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outside five sigma retweeted
“the perfect feedthrough doesn’t exist…” Zero Point Motion: “hold my flange” proudly designed & assembled in the UK
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the famous fruit fly connectome but it is optimizing a coherent beam combining phased array laser system to shoot another fly
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outside five sigma retweeted
We built high-throughput materials labs in Menlo Park to create a loop between experiments and models. The labs generate fresh data, the models learn from it, and then help us decide what to try next. Using only 1,300 H200s, plus months of our experimental data, we mid-trained and RL’d an open-source model to surpass GPT-6 Astra on our analysis benchmark. We call it Neon. This is real footage from our lab. We’re focusing first on hard problems in materials science, including superconductors, magnets, and semiconductor materials. Read our blog posts below.
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for entertainment, do not take these modes seriously (outside5sigma.com/mode-guess…)
made a photonic mode overlap guessr and this shit is hard
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made a photonic mode overlap guessr and this shit is hard
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do you see what i am seeing
this chart from @SemiAnalysis_ is insane alpha!
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did you see the liquid residual near the bottom middle of the chip? why is it perfectly symmetric? it really got me thinking for a bit, and then I realized, wait a sec, this whole picture is symmetric, they mirrored the whole chip lmao ( they actually mirrored it twice, and really made it look like they had 12 lasers fan-in into two sets of waveguides at a glance, with PWB.. ) [Dream Photonics - Laser integration](dreamphotonics.com/laser-int…)
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Why do people put sick irl photo only in the thumbnail but not in the actual paper/SI? We need to change this trend. Fancy schematics is nice, but also show me how it actually looks like!
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imagine a high res version of this - Guo2026: [Highly efficient and broadband optical delay line toward a quantum memory](doi.org/10.1063/5.0305471)
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low res drift tube linac (DTL) - Grespan2026: [Design of a variable energy linac for alpha particle acceleration and medical radioisotope production](doi.org/10.1063/5.0337817)
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GPT-6 converted what Dario said about ai into about fiber to chip coupling, and suddenly maybe he's right about pacing the frontier, or maybe the photonics industry is doing so bad it out-retarded the take. here you go: I agree with that much more than I disagree with it. It’s an interesting problem because if you talk to any individual company, they’ll say, our grating coupler is good, or our edge coupler is good, or we have a passive-alignment process. And they’re not necessarily wrong. The problem is the dynamic of the industry as a whole. I think people often talk about this in terms of numbers. Is it 1 dB? Is it 0.5 dB? Is it ±1 micron? Is it ±0.5 micron? That’s an easy way to express whether a packaging approach is good. But I think it’s more illuminating to ask: how do you decompose the problem? What are the paths in which this goes well? And what are the paths in which this goes poorly? Instead of saying there’s a 70 percent chance that edge coupling wins, which makes it sound like a roll of the dice, I think it’s much more useful to say that it forks into different paths. There’s a path where you get a very good edge coupler, but it requires a perfect facet, submicron active alignment, an expensive lensed fiber, and an epoxy process that takes five minutes per channel. That is a good coupler. It is not necessarily a good product. There’s another path where maybe the optical loss is slightly worse, but you have a mode-field diameter that matches something the fiber industry already knows how to manufacture, enough alignment tolerance for passive assembly, controlled adhesive shrinkage, thermal stability, and the ability to test the interface before permanently attaching it. That may be the much better path. The same thing is true for grating couplers. You can optimize peak efficiency at exactly 1310 nanometers, exactly the right polarization, exactly the right fiber angle, on exactly one wafer. Or you can optimize the whole system: bandwidth, wafer variation, polarization, back-reflection, fiber height, angular tolerance, process bias, testability, and whether somebody can actually attach a 16-fiber array to it at high volume. Those are very different optimization problems. So let’s focus on our agency and our ability to take the right paths instead of the wrong paths. I think the way to take the right path is for the industry to work together. The foundries know something about the coupler. The fiber companies know something about the mode field. The connector companies know something about ferrules and mechanical tolerances. The packaging houses know what actually survives dispense, cure, reflow, temperature cycling, and vibration. The transceiver companies know which half-dB is actually worth paying for. But no one player sees the whole stack. People will compete. They should compete. There will be proprietary couplers and proprietary attachment techniques. But at the end of the day, the industry has to work together. Because if every company invents a different optical interface, a different fiber pitch, a different spot size, a different fiber-array geometry, a different datum scheme, and a different attachment process, then we’re going to spend the next ten years solving the same packaging problem fifty different times. And it’s harder, but to some extent, the whole world has to work together. The photonics foundry may be in one country. The fiber array may come from another. The ferrule may come from another. The assembly equipment may come from another. The laser may come from another. And the final module may be assembled somewhere else entirely. So there has to be some convergence on what a good optical interface actually looks like. We need to stop asking only, what is the lowest coupling loss anyone has demonstrated? We should be asking: what interface can we manufacture a hundred million times? What survives ten years? What can tolerate realistic wafer and assembly variation? What can be inspected? What can be reworked? What can be tested before final attach? What does not require a PhD student and a six-axis stage to couple light into it? If we take the right path, I think the probability that photonic packaging becomes almost boring is very high. If we take the wrong path, then we can continue publishing 0.3-dB couplers while shipping products with several dB of practical coupling loss and enormous packaging cost for a very, very long time.
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ai experts probably could come up with metrics and estimations on how many tokens are needed to "align" an LLM to what degree, and then they just need to do the same for a group of humans, and figure out what kinds and forms and amount of propaganda do you need to blast into people's eyes and ears for how long to "align" the pace of frontier ai
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