suriya-ganesh

this is not what they're claiming.

the reason why clinical trial exists, is to prevent reward hacking. either by organizations or LLMs. the reasoning about why a drug works is usually post facto discovery (if that happens at all). the R&D environment around drug discovery is hilariously lacking (my wife works in this space. sometimes my mind just blows hearing some stories.)

if the model comes with a ridiculously shaped drug that no human could understand. you could basically put through the clinical trial process (mouse -> apes -> RCT with humans.) and decide whether we want to continue or not.

I've been working in the privacy space for ~4 years now and have worked across, homomorphic encryption, Federated Learning and finetuning.

I've also run multiple user studies on privacy during my time doing a master's in privacy at CMU. almost 10/10 times users will choose, easy to use and accessible over complex and more control over their data.

In fact, for one of the Mag7 we proved that, users only want to have the feeling of safety and don't really care what gets done with the data.

very unfortunate, but this is the world we live in.

I see this too often. But, realistically users do not care about the harvesting as it is unseen and behind the scenes. Most people just want get stuff done in a competent, fast and easy-to-use operating system.

>It also locks you into the cloud services of an advertising company

this is pretty much any company these days. microsoft is guilty of the same.

incredibly impressive demos. I wonder how the training data for these models look like?

is it separate batches of special "skills" that are added post training? how can they guarantee the models won't eventually lose a skill?

it's been a things since 2002. but it's a news aggregator not directly competing with newyork times

there has been a product called Google News since 2002. It was only aggregating information from news channels

Will the big labs leave anything for external competition?

This probably killed a thousand startups in this space.

in the early internet you wouldn't see google creating their own news site or facebook building their own animal farm. what happened to platformication of everything?

i suppose a quick test would be getting the model to write down Micken's essay end to end.

if the original essay was stuffed within the prompt window. the result will be word accurate.

unless this is a model trained specifically on Micken's essay (which claude is not).

This is unlikely. The way model distribution works is that the model retains a lossy representation of James Micken's writing. Very likely, it cannot repeat Micken's writing verbatim. Neither can it reason about the training cutoff in this manner.

It's a lossy representation

this is definitely not true.

with AI agents, you're obtaining a mildly lossy perspective of the code itself. whereas if you wrote it by hand, you'd have a more concrete understanding.

This is not too different from an engineering manager directing junior developers.

The stereotype of the engineering manager who forgot to write a line of code is not wrong.

since tbpn is known for their quite oblique satire. i wonder if this is some long April 1st thing.

also it should be noted that LinkedIn had a 5 year plan of migrating everything to azure but abandoned it after a year.