Henry Garner

I'm just going outside and may be some time.

[Henry Garner @henrygarner]

The darkest timeline

[Henry Garner @henrygarner]

I'm just going outside and may be some time https://t.co/eVbMD1kx29

[Henry Garner @henrygarner]

@MichaelDrogalis Agreed! This became really clear to me when I epic, 8k, hyper detailed, ultra detailed, photorealistic, unreal engine, octane render, Depth of Field, Cinematic, sharp detail, --v 6

[Henry Garner @henrygarner]

@petergyang HONDᴬ

[Kevin Fischer @kevinafischer]

I don't talk much about this - I obtained one of the first FDA approvals in ML + radiology and it informs much of how I think about AI systems and their impact on the world. If you're a pure technologist, you should read the following:

There's so much to unpack for both why Geoff was wrong, and why his future predictions should not be taken seriously either.

Geoff made a classic error that technologists often make, which is to observe a particular behavior (identifying some subset of radiology scans correctly) against some task (identifying hemorrhage on CT head scans correctly), and then to extrapolate based on that task alone.

The reality is that reducing any job, especially a wildly complex job that requires a decade of training, to a handful of tasks is quite absurd.

Here's a bunch of stuff you wouldn't know about radiologists unless you built an AI company WITH them instead of opining about their job disappearing from an ivory tower.

(1) Radiologists are NOT performing 2d pattern recognition - they have a 3d world model of the brain and its physical dynamics in their head. The motion and behavior of their brain to various traumas informs their prediction of hemorrhage determination.

(2) Radiologists have a whole host of grounded models to make determinations, and actually, one of the most important first order determination they make is whether there is anything notably wrong with a brain structure that "feels" off. As a result, classifiers aren’t actually performing the same task even as radiologists.

(3) Radiologists, because they have a grounded brain model, only need to see a single example of a rare and obscure condition to both remember it and identify it in the future. This long tail of rare conditions to avoid missing is a large part of their training, and no one has any clue how to make a model that acts similar in this way.

(4) There’s so many ways to make Radiologist lives easier instead of just replacing them, it doesn’t even make sense to try. I interviewed and hired 25 radiologists, whose primary and chief complaint was that they had to reboot their computers several times a day.

(5) A large part of the radiologist job is communicating their findings with physicians, so if you are thinking about automating them away you also need to understand the complex interactions between them and different clinics, which often are unique.

(6) Every hospital is a snowflake, data is held under lock and key, so your algorithm might not work in a bunch of hospitals. Worse, the imagenet datasets have such wildly different feature sets they don’t do much for pretraining for you.

(7) Have you ever tried to make anything in healthcare? The entire system is optimized to avoid introducing any harm to patients - explaining the ramifications of that would take an entire book, but suffice to say even if you had an algorithm that could automate away radiologists I don’t even know if you could create a viable adoption strategy in the US regulatory environment.

(8) The reality is that for every application, the amount of specific and UNKNOWABLE domain knowledge is immense.

LONG STORY SHORT: thinkers have a pattern where they are so divorced from implementation details that applications seem trivial, when in reality, the small details are exactly where value accrues.

Should you be worried about GPT5 being used to automate vulnerability detection on websites before they’re patched? Maybe.

Should you be worried GPT5 is going to interact with SOCIAL systems and destroy our society single-handedly? No absolutely not.

[Simon Willison @simonw]

I've tried to debunk all of these here, but I'm beginning to feel like a prompt injection Cassandra: doomed to spend my life trying to convince people this is an unsolved problem and facing the exact same arguments, repeated forever https://t.co/t2Y7PoSpTZ

[potential difference @potentialdiffer]

Here's a micro-documentary about the making of our new show.

It's inspired by the physical scraps of script of a famous play from Ancient Greece - otherwise completely lost to time.

What was the story?

https://t.co/wgMAkINFdC

[Max 🇺🇦🇪🇦🇪🇺 new faces same old shit... @MaxMigliorato]

The level of wrong of this is staggering, but maybe, just maybe it is down to the fact that unlike Italians and Germans, the Brits have not been taught this part of history properly.
I will try and explain in the shortest possible number of Tweets.
🧵/1

[Yann LeCun @ylecun]

Hotter take: ML would have advanced faster if another front-end language had been available and widely adopted instead of Python.
One that is interactive yet fast & compilable, multithreaded (no GIL), isn't bloated, doesn't care about white spaces,...
E.g. Julia or some Lisp.

[Henry Garner @henrygarner]

@ncntxt3bnsalad Henry Paker-Werewolves

[Shreya Shankar @sh_reya]

Our understanding of MLOps is limited to a fragmented landscape of thought pieces, startup landing pages, & press releases. So we did interview study of ML engineers to understand common practices & challenges across organizations & applications: https://t.co/RLkNqz8XtG

[Laurie Voss @seldo]

This was both bad and avoidable but I think there's a broader point to be made here, which is that calling machine learning "AI" is not just a marketing decision, it's dangerously inaccurate and misleading: https://t.co/ufi8NNtli9

[Henry Garner @henrygarner]

@Justsharesonaim I've got the Carney Harmonic Trading vols 1 & 2. Would you suggest anything else for the library?

[Henry Garner @henrygarner]

@Justsharesonaim Seriously impressive call. Nailed it!

[Henry Garner @henrygarner]

@iquilezles An off by 1.618 error

[Moxie Marlinspike @moxie]

Wrote some notes summarizing my first impressions of web3: https://t.co/16MoPROOGc

[fhr @fhr]

I'm hiring data/AI/eng people of many types to build up my data team at @healx ! Let me know if you're interested - remote-first, mission-driven, super interesting fast growing company. Pro/con, you get to work with me 😉 eg role https://t.co/GCXPSfuTrf

[Henry Garner @henrygarner]

@thattommyhall Congratulations! ��

[Jeffrey Ely @Jeffely]

The base-rate fallacy is about to become a daily nuisance when it comes to processing outbreak data in highly vaccinated societies. Here's a cautionary tale.

[Henry Garner @henrygarner]

@JulianBirch @agile_geek @madar1a The nighttime superpower to make lights dance by tilting your head from side to side never goes away #blessed