Clarence Hu

Gemma 4 looks at a parking lot. Decides what to ask. Calls SAM 3.1. "Segment all vehicles." 64 found. "Now just the white ones." 23 found. One model reasoning and orchestrating. One model executing. Both running locally on a MacBook. MLX. No cloud. No API.

a lot of folks point to dmd as a case study to support an fda that was too lax. the argument is these products increase dystrophin by only ~1%, and no trials have shown an improvement in function. instead of arguing about this, let's consider the consequences of such a 'mistake'. the system paid for drugs that don't work, patients didn't benefit. but... the revenues proved there was an opportunity and this incentive unleashed an innovation flywheel that is now producing drugs that increase dystrophin to near carrier/normal levels. these products are going to be transformative, possibly a cure for many patients. if the first gen products had never been approved, this flywheel is very unlikely to have ever started. we are living thru a similar process in Alzheimer's with abeta drugs (and those glp1s we all love, was a similar journey that started with byetta's approval in '05). when debating where to set the line, it is important to understand this nature of innovation, what seems too incremental a step is often the key to laying a foundation for transformative innovation.

Something I've been thinking about - I am bullish on people (empowered by AI) increasing the visibility, legibility and accountability of their governments. Historically, it is the governments that act to make society legible (e.g. "Seeing like a state" is the common reference), but with AI, society can dramatically improve its ability to do this in reverse. Government accountability has not been constrained by access (the various branches of government publish an enormous amount of data), it has been constrained by intelligence - the ability to process a lot of raw data, combine it with domain expertise and derive insights. As an example, the 4000-page omnibus bill is "transparent" in principle and in a legal sense, but certainly not in a practical sense for most people. There's a lot more like it: laws, spending bills, federal budgets, freedom of information act responses, lobbying disclosures... Only a few highly trained professionals (investigative journalists) could historically process this information. This bottleneck might dissolve - not only are the professionals further empowered, but a lot more people can participate. Some examples to be precise: Detailed accounting of spending and budgets, diff tracking of legislation, individual voting trends w.r.t. stated positions or speeches, lobbying and influence (e.g. graph of lobbyist -> firm -> client -> legislator -> committee -> vote -> regulation), procurement and contracting, regulatory capture warning lights, judicial and legal patterns, campaign finance... Local governments might be even more interesting because the governed population is smaller so there is less national coverage: city council meetings, decisions around zoning, policing, schools, utilities... Certainly, the same tools can easily cut the other way and it's worth being very mindful of that, but I lean optimistic overall that added participation, transparency and accountability will improve democratic, free societies. (the quoted tweet is half-ish related, but inspired me to post some recent thoughts)

A remarkable result supported by remarkably clean data. A recent study published in Cell tackles a difficult and important question: Can a routine vaccine influence dementia risk? Instead of relying on correlations, they use a quasi-experimental design built around age-based eligibility for the shingles vaccine. Individuals just above and below the cutoff are nearly identical, except for vaccination status. This creates a rare opportunity in human populations: something close to randomization at scale. The result: vaccinated individuals show a lower incidence of dementia over time. The separation is gradual, internally consistent across analyses, and robust to multiple checks. Even among people already diagnosed with dementia, vaccination is associated with slower progression and lower mortality. No mechanism is claimed. No overreach. Just a clear signal from a well-constructed natural experiment. The implication is hard to dismiss: a single, widely used vaccine — given for an unrelated reason — may meaningfully alter the trajectory of one of the most complex diseases in medicine.

Offhand — * Vacillation on masks, with abundant motivated reasoning in every case. * Promulgation of made-up thresholds with no evidentiary basis (e.g. 6 feet). * Authoritarian delight in nanny state intrusiveness (policing the beach and such). * 180 on many issues around BLM. * Lack of effective response from science funding bodies. * Denial of aerosolized transmission. * Changing of trial readouts so that they’d occur after the election. (Confirmed to me by senior OWS officials.) * Crazy criteria for vaccine distribution. * Adamant insistence on vaccine efficacy beyond what was supported by data. * Almost complete lack of follow-through on OWS (on pan-variant vaccines). I’m sure there are more, but those are the ones that stick out.

We used AI to predict the failure of a Phase 3 trial before the results were announced. Today, we're publishing 10 more predictions for the future. Thread 🧵

If your scientists are not making at least making a million constructs // sequencing thousands of colonies via Plasmidsaurus // generating petabytes of imaging data…