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Do you have specific examples?

This study published in Nature [0] says that rural populations in particular are typically UNDERCOUNTED (exactly like the Papa New Guinea in the OP's article), and that this happens at similar rates across poorer and wealthier countries: "no clear effect of country income on the accuracies of the five datasets can be observed."

[0]: https://www.nature.com/articles/s41467-025-56906-7



He doesn't need to configure it because he made his preferences the default.


>It seems we crossed into the realm of intentionally doing damage.

"The Trump administration’s decision to shut down the U.S. Agency for International Development (USAID) has resulted in hundreds of thousands of deaths from infectious diseases and malnutrition, according to Harvard T.H. Chan School of Public Health’s Atul Gawande ... The dismantling of USAID, according to models from Boston University epidemiologist Brooke Nichols, “has already caused the deaths of six hundred thousand people, two-thirds of them children,” Gawande wrote. He noted that the toll will continue to grow and may go unseen because it can take months or years for people to die from lack of treatments or vaccine-preventable illnesses—and because deaths are scattered." [https://hsph.harvard.edu/news/usaid-shutdown-has-led-to-hund...]


Post your work so we can see what you made.


You run a company that does AI code review, and you've never devised any metrics to assess the quality of code?


We have ways to approximate our impact on code quality, because we track:

- Change in number of revisions made between open and merge before vs. after greptile

- Percentage of greptile's PR comments that cause the developer to change the flagged lines

Assuming the author is will only change their PR for the better, this tells us if we're impacting quality.

We haven't yet found a way to measure absolute quality, beyond that.


Might be harder to track but what about CFR or some other metric to measure how many bugs are getting through review before versus after the introduction of your product?

You might respond that ultimately, developers need to stay in charge of the review process, but tracking that kind of thing reflects how the product is actually getting used. If you can prove it helps to ship features faster as opposed to just allowing more LOC to get past review (these are not the same thing!) then your product has a much stronger demonstrable value.


I don't know what studies Blinken's State Department considered, but here are 2 studies on the matter.

https://www.academia.edu/72263493/Effect_of_Typeface_Design_...: "For Latin, it was observed that individual letters with serif cause misclassification on (b,h), (u,n), (o,n), (o,u)."

https://par.nsf.gov/servlets/purl/10220037: [Figure 5 shows higher accuracy for the two sans-serif fonts, Arial and DejaVu compared to Times New Roman, across all OCR engines]


This video is a great overview of spaceships\gliders: https://www.youtube.com/watch?v=5yLcsaewxJQ

The level of engineering necessary to do this in 1 dimension is still beyond me, as is the "simple" explanation posted on the Conway forums. But I feel like I appreciate the achievement a little bit more now.


https://www.businessinsider.com/anthropic-ceo-ai-90-percent-... (March 2025):

>"I think we will be there in three to six months, where AI is writing 90% of the code. And then, in 12 months, we may be in a world where AI is writing essentially all of the code," Amodei said at a Council of Foreign Relations event on Monday.

>Amodei said software developers would still have a role to play in the near term. This is because humans will have to feed the AI models with design features and conditions, he said.

>"But on the other hand, I think that eventually all those little islands will get picked off by AI systems. And then, we will eventually reach the point where the AIs can do everything that humans can. And I think that will happen in every industry," Amodei said.

I think it's a silly and poorly defined claim.


you’re once again cutting the quote short — after “all of the code” he has more to say that’s very important for understanding the context and avoiding this rage-bait BS we all love to engage in

edit: sorry you mostly included it paraphrased; it does a disservice (I understand it’s largely the media’s fault) to cut that full quote short though. I’m trying to specifically address someone claiming this person said 90% of developers would be replaced in a year over a year ago, which is beyond misleading

edit to put the full quote higher:

> "and in 12 months, we might be in a world where the ai is writing essentially all of the code. But the programmer still needs to specify what are the conditions of what you're doing. What is the overall design decision. How we collaborate with other code that has been written. How do we have some common sense with whether this is a secure design or an insecure design. So as long as there are these small pieces that a programmer has to do, then I think human productivity will actually be enhanced"


can you post the full quote then? He has posted what the rest of us read


I believe:

> "and in 12 months, we might be in a world where the ai is writing essentially all of the code. But the programmer still needs to specify what are the conditions of what you're doing. What is the overall design decision. How we collaborate with other code that has been written. How do we have some common sense with whether this is a secure design or an insecure design. So as long as there are these small pieces that a programmer has to do, then I think human productivity will actually be enhanced"

from https://www.youtube.com/live/esCSpbDPJik?si=kYt9oSD5bZxNE-Mn

(sorry have been responding quickly on my phone between things; misquotes like this annoy the fuck out of me)


[dead]


uh it proves the original comment I responded to is extremely misleading (which is my only point here); CEO did not say 90% of developers would be replaced, at all


Generative text to speech models can hallucinate and produce words that are not in the original text. It's not always consequential, but a court setting is absolutely the sort of place where those subtle differences could be impactful.

Lawyers dealing with gen-AI TTS rulings should compare what was spoken compared to what was in the written order to make sure there aren't any meaningful discrepancies.


People can also make mistakes while reading, and I suspect we do so at just as much if not more frequency as gen AI text-to-speech algos.

It's the AI thinking that makes me wary, not AI text-to-speech.


Perhaps other groups are. But Anthropic wouldn't be able to publish a blog article about those.


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