Todd White

@leecronin Not Turing complete, or not Turing equivalent?

Today I’m trying to write the framework that explains why biology is not Turing complete.

@BoWang87 Not to mention anyone who wrote a thesis in the late 80s/90s in STEM probably owe him a debt of gratitude for TeX!

For those who don’t know Prof. Donald Knuth — --1974 Turing Award laureate. --Often called the father of algorithm analysis. --Author of The Art of Computer Programming — the book that shaped generations of computer scientists. He just turned 89 this year! Absolute legend. Respect!

@BoWang87 It's the topic that needs to be discussed and hammered home if we are to make progress.

I have a curiosity: why is it the case that it is easier to get MAID in Canada than it is to access experimental treatments which carry a higher risk? In the past, I used to think ppl do not like "deaths caused by the medical system", but for MAID the prob of death is 100%...

True trend.

Finally got time to read this interesting preprint : Virtual Cells Need Context, Not Just Scale! 📄 biorxiv.org/content/10.648… Interesting preprint, I agree with the need for context, but I'd push back on the conclusion a bit. "Scaling doesn't work for Virtual Cells" — that's true right now, but the diagnosis is wrong. Scaling hasn't failed. The data hasn't scaled yet. We have a handful of public genome-scale perturbation datasets covering a tiny slice of cell biology. Of course models plateau. And that's before we even address the bigger issue: a Virtual Cell is not a genetic perturbation predictor. It needs to model transcription, translation, signaling, metabolism, cell state — the full complexity of cellular behavior across disease contexts. Framing this as a "causal transport problem" in a perturbation benchmark undersells the actual scope of the problem. The field doesn't need to abandon scaling. It needs to earn the right to scale — by generating causally-rich, contextually-diverse experimental data at a scale that doesn't yet exist in public databases. That's exactly what we're building at @Xaira_Thera ! When the data is there, the models will catch up. They always do. Stay tuned!

Bytedance just dropped a paper that might change how AI thinks. Literally. They figured out why LLMs fail at long reasoning — and framed it as chemistry. The discovery: Chain-of-thought isn't just words. It's molecular structure. Three bond types: • Deep reasoning = covalent bonds (strong, unbreakable) • Self-reflection = hydrogen bonds (flexible, context-aware) • Exploration = van der Waals (weak, ever-present) Why most AI "thinking" sucks: Everyone's been imitating keywords — "wait," "let me check" — without building the actual bonds. It's like copying the shape of a protein without the atomic forces holding it together. Bytedance proved: structure emerges from training, not prompting. The fix: Mole-Syn Their method doesn't just generate text. It synthesizes stable thought molecules. Results: better reasoning, more stable RL training. Bytedance is treating AI reasoning like organic chemistry — and it works. Paper: arxiv.org/abs/2601.06002

This is a critical distinction, and one which I never fully appreciated until we started working on the BAFAR project at @TTIScience. Worst still, we are ill-equipped to even produce good biology LLM "parrots" because we haven't developed the data to train LLMs on the correct first principles. Sadly, this lack of investment continues to fall on mostly deaf ears who feel the technology itself is sufficient and slows progress.

A side effect of more weakly trained biologists entering techbio is we’re just scaling the same irrelevant experiments that are a root cause of drug failures. Pharma companies have already run more automated screens in these models than you can imagine.

@elonmusk Money only ever provided agency. Happiness has been, and will always be an internal struggle, and it is extremely cost effective to achieve.

Whoever said “money can’t buy happiness” really knew what they were talking about 😔

Turns out Shetland ponies can live up to 50 years, but the average is closer to 35. Normal horses live closer to 25 years. This shows again that the smaller species within a family live longer, similar observations in other mammals. This is what we study at @TTIScience.

Looking forward to seeing this year's Vitalist Bay lineup - great speakers and discussions to be had!

How could tiny breakthroughs in aging science change U.S. GDP and population growth? What’s the economic value of making 41 the new 40, or 65 the new 60? How many lives could we create or save if we could slow reproductive or brain aging by just 1 year? What would billions of healthier hours be worth to the economy, if we assume no change in the age of retirement? I spent the last two years obsessing over the design, research, and execution of this project. The result is a book upcoming with Harvard University Press, a preprint, and—maybe your favorite part—an interactive simulation tool that lets you input your own timelines and assumptions for specific breakthroughs in aging bio, then see the ROI in terms of US population & GDP growth. From @RickEcon and Jason DeBacker—the economists who co-developed the open-source, macro model that made this project possible—to extensive comments by @tylercowen, @sapinker, Richard Freeman, @NDHendrix, @ebudish, @elidourado, @geochurch, @jasoncrawford as well as interviews with 102 scientists (!) and countless iterations with award-winning designer Giorgia Lupi and the @pentagram team, we built something we hope will be a benchmark for how scientists, economists, designers, philosophers, entrepreneurs and storytellers can come together to paint, fund, and build different flourishing futures for our species. I couldn’t be more excited to share this. It’s the start of an open and evolving project—the labor and product of love, obsession, and unrelenting care. I hope you have fun playing with our simulation tool — and if you do, please share!

@parmita @m__marinova @MaxUnfried

I have added some of the coolest people to this bio/acc group and we actually chat here about cool stuff! I am deleting this and re-making the gc with the new encrypted DMs. PLEASE tag awesome people who should join People who are BIOLOGISTS or IN BIOTECH !

Greateful to our ~30 collaborators inc. @AlekseyVBelikov @UriAlonWeizmann @HaggSara @prof_horvath @DocLarus @ScheibyeKnudsen @TSchmauck @MaxUnfried @DToddWhite @EmmaTeeling1 @robwilliamsiii plus @impetusgrants @hevolution_f and @TTIScience for supporting this project. 3/3

People should indeed be really excited about this talk. Probably one of the best I heard on why longevity matters!

Some impressions from my @TEDx talk on our approach at @TTIScience & biological mega-projects for life extension at the @MITMuseum. Thank you to @RaianyRomanni and @johnkwerner for including me. Other great talk by @mkaeberlein, @AlexJColville, @davidasinclair, & @MartinBJensen happened at @WHOOP HQ.

@MarcosArrut Surprising this has not been understood as clearly as it should. Makes you wonder what happened to first principles thinking in biology?

Correcting the epigenome will correct the transcriptome. Correcting the transcriptome will correct the proteome. Correcting the proteome will correct aging. And when we correct aging, we will extend life; and by extending life, we will be free. That's all.