Yes, you're correct. To add - companies don't fundamentally care about all the things that we like to think of as "nice things", like good design, lack of dark patterns, robust security architecture, minimizing technical debt, etc.

If customers cared about reputational damage from cybersecurity incidents (sure.. some do) , then you would see that reflected in their priorities. Also, non-technical customers don't really know who to blame for security anyway. They'll just blame the OS vendor or other random parties even if its the Application that is not secure.

reputational damage

Ah but the thing is that every company sucks so there is nowhere for customers to flee to.

Does sitting and closing eyes not do the same thing? That's what I do when I'm overwhelmed.

Screen and battery replacements are by far the number one repair service that people avail. The data is clear. I'm afraid you're completely wrong.

There are various types of triggers for gene activation, some genes turn on/off all the time (housekeeping), some follow the circadian rythm, some are immediate response, some are specific to specific phases of cell division, some are persistently on all the time, etc ,etc. Not sure what type of chart you're looking for.

Thanks. Those modal categories of activations are a great start for organizing a visualization. I wonder what sort of patterns would show up. For example, what role does placement in a specific chromosome have (if at all!) in determining whether the gene is periodic, reactive, systemic, or developmental , etc.

> Not sure what type of chart you're looking for. Just geek curiosity.

> some follow the circadian rythm

Oh no…

As someone who has an highly irregular sleeping pattern, do you know of any or where I can find more info on this?

This is true when fresh college grads are building stuff. Experienced engineers know how to build things much more efficiently.

Also people like to fantasize that their project, their API, their little corner of the codebase is special and requires special treatment. And that you simply cant copy the design of someone much more experienced who has already solved the problem 10 years ago. In fact many devs boast about how they solved (resolved) that complex problem.

In other domains - Professional engineers (non-swe) know that there is no shame in simply copying the design for a bridge that is still standing after all those years.

BTW - UAC is not a security boundary, so UAC-bypass is not the same as privilege escalation, and there is no bounty for it, etc, etc. It's a common misunderstanding, probably in no small part due to Microsoft's own lack of communication around it.

The amount of private data that is locked up inside private internal databases is huge. This is especially true of regulated industries. There is a wealth of data - financial data showing how to budget for things, pricing data on various products that are B2B, standard operating procedures at mature companies that have gone through various revisions, designs for manufacturing plants so people don't keep reinventing and making the same mistakes again, and on and on.

I think it's implied that they're not talking about private data when they say they've run out.

fair. I want to +1 the fact that there is a large amount of data unseen by LLMs.

I think there are post training tweaks that can be done with corporate data to help fit an AI to a specific corporation. But I don’t think that private data will deliver us AGI. The knowledge for AGI is out in the world, not hidden inside corporations. Private data brings us knowledge of the XYZ project status and the division ABC budget and whether Bob wants a chocolate cake for his going away dinner or not.

I'm not seeing it the same way. Businesses in various industries have several types of moats - money, knowledge, experience, skills, etc. There is ton of competitive intelligence hidden in private data.

Its one of the reasons you can't use chatGPT and start manufacturing chips or vaccines, or anti-cancer medication. The gap between publicly available data that informs academic "core science" research versus specific product-based knowledge that shows you how to make a successful drug candidate that can withstand regulatory scrutiny or be a safe and effective drug for the worlds population.

We could iterate so quickly if this private data set was democratized.

Dystopian future where AI pumps out slop and uses human feedback and comments to correct the output.

  > uses human feedback and comments to correct the output

tbf, lots of saas have a similar attitude with things like "give us feedback" on their pages; like i'm paying you money to figure this stuff out so why are you asking me if its good or not? with more and more "vibing" i feel this kind of attitude is going to infect everything at some point...

Isn’t this a bit like spell-checking a Nigerian Prince email? The valuable eyeballs are the ones that don’t notice or don’t care.

Sure, If ranking is done purely based on clicks and not quality. I'm just thinking of it as a meta "loss" function in the AI context. So I'd say its the passionate enthusiasts who care enough to provide feedback on such topics.

Dystopian present

>The thing is, LLM's produce better quality one-shots than any of the products that get returned from overseas ultra-budget contractors in India or SEA.

Source?

lived experience

They use data from the poor student tier, but arguably, large corporates and businesses hiring talented devs are going to create higher quality training data. Just looking at it logically, not that I like any of this...