There absolutely is such a thing as epigenetic inheritance. E.g. https://en.wikipedia.org/wiki/Genomic_imprinting Epigenetics is a pretty broad term. Transgenerational epigenetic inheritance of environmentally-induced expressions, however, has never been firmly demonstrated in mammals, let alone humans. There's a bunch of needles that need to be threaded to achieve it, for example modifying gametes, then sneaking past the epigenetic resetting that occurs during meiosis, etc. Repeat the feat to cross more than one generation.
There's a ton of extravagant claims and overly credulous reception driven in part by powerful cultural narratives. AFAIU, epigenetics in the popular discourse has different connotations then for most scientists. And when a scientist says epigentic processes are beyond dispute--because many of them are clearly established as key to some basic developmental processes--the lay person takes this as validation of, e.g., epigenetically inherited intergenerational trauma. But there's tremendous distance between those two extremes, both semantically and physically.
As a thought experiment, there's a big difference between "3 companies share 70% of a market, while 30 companies sharing the remaining 30%", and "30 companies share the whole market, none being larger than 8%".
In the former example, there's far more pressure on the smaller companies, which is why in such a regime people expect more consistent quality from the big guys, and the smaller guys are often boutique in some way (=offering something unique in their service/product in order to be able to compete). Small guys have a hard time standing up to big guys.
On the other hand, in a regime where no one becomes that huge, like the latter example, there's still pressure, but the competition is fair, just like if all the companies were similarly big (except that you can't have that many big companies in a single industry, by proportion definitions).
Realizing this drove home why inconsistent antitrust enforcement appears to produce bad results. Because it leaves us in the state of the former example. It's also unfortunately the intermediate state of getting serious with antitrust enforcement.
You're talking about different measures / types of quality.
> Anyone who thinks AI is good with writing code that is hard to write for the operator, not due to lack of basic software engineering know how but complexity of the domain, either has access to models beyond what is available to the public or is completely lost.
You could read it as quality in the operational correctness sense, but just as well in the software architectural design sense. My comment indeed applies to only one of those.
However, why judge correctness as a "cringe on quality", rather than just objectively saying its producing errors. This is why my response is in the software direction.
Agreed. The recent privacy kerfuffle with Grok CLI (plus the untrue "it's your fault" response, although they then changed the behavior) is a really bad sign for how your code and data will be the treated.
> It’s hard to collect enough data using invasive methods. Few people want a chip in their brain! But non-invasive methods are getting much better. The hardware is improving and getting cheaper, though I apologize for being vague about the particularities of our hardware.
Their data acquisition routine was driven by Claude and they were recruiting random people off Craigslist pretty aggressively a few months back. I know a couple of folks who responded out of curiosity and described a very janky setup in the rented basements of a couple of residential houses in SF. From what I heard about the setup the data they got must have been incredibly noisy.
To the people who are sceptical here, I wouldn't count them out yet. They almost certainly can get funding with what they captured, which would get them better hardware. And given the state of brain scanning - people have captured images from scanned brain activity some years ago as I recall - I'd say they have a good shot. But yeah, it's not telepathy.
Claude seems to do this all the time. That, the empty words and the increased self initiative of claude were all reasons I decided to just use codex (now merged into GPT).
Codex does this too, I've noticed. LLMs seem to love documenting irrelevant implementation details in what should be user-facing text. I guess because the context is overwhelmingly the technical side of things, so without a later directive to steer it, that's what's most likely to come out.
The user-facing string stuff is definitely the thing that drives me the most nuts. I guess it's nice that it defaults to gag-inducingly transparent, but I don't think the backend structure should be written out in the title element of the app.
What' especially annoying is when you as a code reviewer have to go through tons of such comments that keep distracting you because the author could not bother reading those comments and assessing that they contain references to prompts / instructions that are completely irrelevant to he target audience
Absolutely, makes my blood boil. Claude proposes an obviously wrong/overengineered solution to a problem. I come up with a better approach and we agree to do that instead. Every step of the way, Claude leaves code comments with long-winded explanations of how we're doing X instead of doing $insane_thing.
Literally # This method rejects splines that can't be reticulated. This helps us avoid murdering puppies and punching a baby in the face.
Claude using documentation and comments as its personal diary is one of the most infuriating behaviors it exhibits.
Half the time it’ll record some temporary implementation quirk, which later sessions interpret as infallible product design requirements. Absolutely unsustainable.
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