Reg Myers

New Quanta article looks at one of the coolest tiny machines in biology - the bacterial flagellar motor. It’s basically a microscopic spinning engine that bacteria use to move. After decades of trying to fully understand it, scientists are finally figuring out how it actually works. The motor is powered by a flow of charged particles (kind of like a tiny battery), which creates force and makes it rotate. So what looks like something alive and mysterious is really just an incredibly advanced microscopic machine running on the same basic rules as everything else. More broadly, the article addresses the idea of a "life force." It argues that no special force is needed to explain life. Instead, biological activity arises from physical processes that operate far from equilibrium, where constant energy flow keeps the system active and organized. The flagellar motor shows that living systems can be understood as energy driven, self organizing systems. What appears to be uniquely "alive" can be explained by standard physical laws, such as thermodynamics and molecular interactions. Physics pushed to an extreme level of complexity.

@drakefjustin Just add an extra ‘!’ at the end and it’ll be fine… 🤣😂

Today is a monumentous day for quantum computing and cryptography. Two breakthrough papers just landed (links in next tweet). Both papers improve Shor's algorithm, infamous for cracking RSA and elliptic curve cryptography. The two results compound, optimising separate layers of the quantum stack. The results are shocking. I expect a narrative shift and a further R&D boost toward post-quantum cryptography. The first paper is by Google Quantum AI. They tackle the (logical) Shor algorithm, tailoring it to crack Bitcoin and Ethereum signatures. The algorithm runs on ~1K logical qubits for the 256-bit elliptic curve secp256k1. Due to the low circuit depth, a fast superconducting computer would recover private keys in minutes. I'm grateful to have joined as a late paper co-author, in large part for the chance to interact with experts and the alpha gleaned from internal discussions. The second paper is by a stealthy startup called Oratomic, with ex-Google and prominent Caltech faculty. Their starting point is Google's improvements to the logical quantum circuit. They then apply improvements at the physical layer, with tricks specific to neutral atom quantum computers. The result estimates that 26,000 atomic qubits are sufficient to break 256-bit elliptic curve signatures. This would be roughly a 40x improvement in physical qubit count over previous state-of-the-art. On the flip side, a single Shor run would take ~10 days due to the relatively slow speed of neutral atoms. Below are my key takeaways. As a disclaimer, I am not a quantum expert. Time is needed for the results to be properly vetted. Based on my interactions with the team, I have faith the Google Quantum AI results are conservative. The Oratomic paper is much harder for me to assess, especially because of the use of more exotic qLDPC codes. I will take it with a grain of salt until the dust settles. → q-day: My confidence in q-day by 2032 has shot up significantly. IMO there's at least a 10% chance that by 2032 a quantum computer recovers a secp256k1 ECDSA private key from an exposed public key. While a cryptographically-relevant quantum computer (CRQC) before 2030 still feels unlikely, now is undoubtedly the time to start preparing. → censorship: The Google paper uses a zero-knowledge (ZK) proof to demonstrate the algorithm's existence without leaking actual optimisations. From now on, assume state-of-the-art algorithms will be censored. There may be self-censorship for moral or commercial reasons, or because of government pressure. A blackout in academic publications would be a tell-tale sign. → cracking time: A superconducting quantum computer, the type Google is building, could crack keys in minutes. This is because the optimised quantum circuit is just 100M Toffoli gates, which is surprisingly shallow. (Toffoli gates are hard because they require production of so-called "magic states".) Toffoli gates would consume ~10 microseconds on a superconducting platform, totalling ~1,000 sec of Shor runtime. → latency optimisations: Two latency optimisations bring key cracking time to single-digit minutes. The first parallelises computation across quantum devices. The second involves feeding the pubkey to the quantum computer mid-flight, after a generic setup phase. → fast- and slow-clock: At first approximation there are two families of quantum computers. The fast-clock flavour, which includes superconducting and photonic architectures, runs at roughly 100 kHz. The slow-clock flavour, which includes trapped ion and neutral atom architectures, runs roughly 1,000x slower (~100 Hz, or ~1 week to crack a single key). → qubit count: The size-optimised variant of the algorithm runs on 1,200 logical qubits. On a superconducting computer with surface code error correction that's roughly 500K physical qubits, a 400:1 physical-to-logical ratio. The surface code is conservative, assuming only four-way nearest-neighbour grid connectivity. It was demonstrated last year by Google on a real quantum computer. → future gains: Low-hanging fruit is still being picked, with at least one of the Google optimisations resulting from a surprisingly simple observation. Interestingly, AI was not (yet!) tasked to find optimisations. This was also the first time authors such as Craig Gidney attacked elliptic curves (as opposed to RSA). Shor logical qubit count could plausibly go under 1K soonish. → error correction: The physical-to-logical ratio for superconducting computers could go under 100:1. For superconducting computers that would be mean ~100K physical qubits for a CRQC, two orders of magnitude away from state of the art. Neutral atoms quantum computers are amenable to error correcting codes other than the surface code. While much slower to run, they can bring down the physical to logical qubit ratio closer to 10:1. → Bitcoin PoW: Commercially-viable Bitcoin PoW via Grover's algorithm is not happening any time soon. We're talking decades, possibly centuries away. This observation should help focus the discussion on ECDSA and Schnorr. (Side note: as unofficial Bitcoin security researcher, I still believe Bitcoin PoW is cooked due to the dwindling security budget.) → team quality: The folks at Google Quantum AI are the real deal. Craig Gidney (@CraigGidney) is arguably the world's top quantum circuit optimisooor. Just last year he squeezed 10x out of Shor for RSA, bringing the physical qubit count down from 10M to 1M. Special thanks to the Google team for patiently answering all my newb questions with detailed, fact-based answers. I was expecting some hype, but found none.

@AppleHelix If you start looking at it from a tumor-cell access (immune cell infiltration) perspective, it may change the way you interpret some of the data. Genentech never did explain bev efficacy. VEGF-a isoform was once investigated as a biomarker in equivocal tumor types.

@pharma_reg I was under the impression the at preclinical data of PD1xVEGF looks good but clinical was iffy. Now, it seems like preclinical is iffy as well

I have been looking for murine cancer models for PD-1xVEGF bispecifics. Surprisingly, I have not found clear preclinical data of synergy that compares - aPD-1xVEGF - aPD-1 alone - aPD-1 + aVEGF Am I not looking at the right places? The early work of ivonescimab was comparing to aVEGF. Would appreciate it if you can point me to more compelling preclinical data.

@AppleHelix From memory - going back 15+ years (think Avastin adjuvant) - the vasculature normalization hypothesis appeared more credible than anti-angiogenic/anti-tumor wrt to chemo (bolus/infusion) partner and sq (deeper, bulkier tumors but more prone to bleeds) vs non-sq clinical data.

@Feargal_Sharkey petition.parliament.uk/petitions/7574…

@JaneSymons1 @British_Airways Have you tried logging-in twice, confirming you’re a human 3 times, and at least 4 ‘hail Mary’s’ ?

Hey @British_Airways is there an issue with your website? It won't allow us to check in?

@virginmedia @E811914461530 @Ofcom My mate Dave says it’s fine as long as whoever wrote the advert had their fingers crossed behind their back at the time…

@E811914461530 @Ofcom Hi there, thanks for contacting us. As with many companies we have ever changing offers. The deal you got one month may not be available the next. At the time you would've got it at the lowest price we can offer it, whereas now it is at the current lowest price we can offer.

@the_blind_thing Looks like @CambsCC are having a go too… just a little less successfully… not sure what genre of music they were going for… #potholes

Japan is building roads that literally play music when cars drive over them, like something straight out of a sci-fi movie. Meanwhile in India, our roads play a different kind of music -the nonstop thud thud of potholes testing your suspension and patience every single day.

Skynet probing for weakness…

@henryfraser0 Absolute LEGEND! Nice one.

Before my accident I always enjoyed pushing myself physically, and this is exactly the same challenge, just on a fundamentally different level. It’s tough and exhausting both physically and mentally but when you put in the effort all that pain turns into something positive.

@bankertobuilder Silicone smoothing tools….? no mate… I just used my big toe 😂

A lot of people will see our recent counter install and think — “OMG you ruined the kitchen?!” On the contrary, this stone costs $100/sf and this home is right on the San Andreas fault. So we charged the client an additional $200/sf to install silicone shock absorbers for those 8.0+ magnitude earthquakes. May even add LED lighting to take it to the next level.

The POIESIS Trial is seeking participants aged 18+ for a large global Phase 3 study in patients with myelofibrosis who have never been treated with a JAK inhibitor. Want to know more? Visit us today!

Brandolini’s Law (also known as the bullshit asymmetry principle): The amount of energy needed to refute bullshit is an order of magnitude bigger than that needed to produce it.

🚨 The older the sperm, the more likely it is to cause autism Sequencing sperm using nearly error-free sequencing → measure % sperm carrying disease-causing mutations: 2% at age 30 → 4.5% at 70 Most were autism genes New paper in @Nature today 🧵

"Hi, is that 'We Buy Any Yacht'?"

The problem isn’t that people don’t know. It’s that they trust people who don’t know - as long as they sound confident. Listen to me on this one, please: 🧵👇1/

Love this simple summary… 🤣

Excellent!

I've worked in industry for 20 years. Many studies are funded by industry. Some people say: "Don't trust them. They're biased." But here's the uncomfortable truth: Without industry studies, most of the safety data you rely on wouldn't exist. Let me explain. Want to approve a new pesticide or drug? You need data: → Toxicology. → Residue data. → Carcinogenicity. → Environmental fate. → Endocrine disruption. → Reproductive studies. → Chronic exposure tests. These studies are required by regulators. Guess who pays for them? Industry doesn’t do these studies for fun. They do them because they’re legally mandated. EFSA, EPA, ECHA, FDA, ANSES - all require massive data packages. Some submissions are 100,000+ pages. They take years and cost millions. No university is going to do that. Industry studies don’t stay behind closed doors. They’re: → Audited. → Publicly available. → Reviewed by independent experts. → Summarized in regulatory assessments. They’re not hiding in some secret vault. They’re sitting on EFSA’s website. "But they’re biased!" Yes - every study has potential for bias. That’s why the methods matter. Industry studies follow guidelines, GLP protocols, and strict regulatory checklists. Not blog-science. Not cherry-picked stats. Structured. Transparent. Reproducible. Academics often publish hypothesis-driven research. Industry? They test everything: → What happens at low dose? → What happens over 2 years? → What if the animal is pregnant? → What about bees? Soil? Water? This isn’t just science. It’s exhaustive documentation. EFSA doesn’t rubber-stamp anything. Neither does the EPA. They dissect every study line by line. Then they ask for more. If the study was junk - they’d reject it. If you throw out industry studies, here's what happens: → No new medicines. → No safer chemicals. → No food innovations. → No climate-friendly fertilizers. → No modern toxicology databases. You don’t get precaution. You get paralysis. So what should we do? → Push for open science. → Demand transparency. → Allow independent reanalysis. But don’t discard industry studies just because of who funded them. Evaluate the evidence - not the logo on the lab coat. Industry studies are not perfect. But without them, we’d still be guessing. Science isn’t about who you trust. It’s about what you can prove - under scrutiny. And these studies face more scrutiny than most. Understand the process. Read the methods. Follow the data. Not the headlines. Seen a story that dismissed a study just because it was industry-funded? Share it. ♻️ Repost to push back against bias in the name of science.