Technology

That was sundar pichai? Or someone else? Do you know what terms I'd need to look up to find sources for that? Thats information I'd absolutely like to include when talking about this with people, thank you for filling me in, I had no idea about that and it adds a lot of substance to that point

Edit: from the provided link the person who killed google search was Prabhakar Raghavan, who was apparently responsible for yahoo search over the period in which it fell precipitously off a cliff. He was put in that role by sundar pichai, replacing someone who explicitly cared about search and was deeply important to search development and had been there since the beginning

Do you want to know what Prabhakar Raghavan’s old job was? What Prabhakar Raghavan, the new head of Google Search, the guy that has run Google Search into the ground, the guy who is currently destroying search, did before his job at Google?

He was the head of search for Yahoo from 2005 through 2012 — a tumultuous period that cemented its terminal decline, and effectively saw the company bow out of the search market altogether. His responsibilities? Research and development for Yahoo's search and ads products

So not Sundar pichai, but the article does explain that he was specifically picked to become the new head of search by sundar pichai, and that Sundar used to work for McKinsey Consulting, who were responsible for the business strategy that fueled the opioid crisis, among lots of other things. Super dense, but well worth the read!

Absolutely agree, the data collection feels like even a step beyond the already horrifying amount of people's personal information we've normalized scraping directly into the pockets of corporations

It is like the prisoner dilemma. If you think you'll do the right thing enough people will cheat that you are then obligated to cheat also to keep up.

There's a difference.

When Daren goes 80 in a 30, they actually might be punished as that abuse is recognized and penalized.

With LLMs, there's no such thing as consequences for the bad uses, only rewards.

Internet video feeds are chock full of slop now because that is rewarded. Video platforms are even making "AI remix" buttons to accelerate taking an actual video with thought and effort behind it into uninspired slop. People are making knockoffs left and right but the courts are largely ruling that AI is 'transformative' so those knockoffs that a human would get sued over are getting passes. Managers are micromanaging worker use of AI in hopes that maybe they can prove they can fire most of them.

LLMs enable the worst users more than they enable good users. In software development, the responsible operation of an LLM might speed up a developer 20-50%, depending on the context. An irresponsible one that just assumes the output is good will post a whole lot of crap. Same for all fronts, prose, video production, music. People who care about the medium can get some speedups, but people who are just lazy, uninspired, but see an opportunity can drown out the quality content.

The automobile has been a net benefit to society

Automobiles are also in practice quite harmful to public health because their addictive and user-lock-in effects and the resulting total lack of exercise. US Americans are mostly not aware of that because the notion to walk half an hour to get somewhere is already completely alien to them. Like somebody who first drinks two bottles of beer in the morning, in order to barely function, can possibly not understand that somebody can just drink whater when they are thirsty.

AI as it is forced on people today will probably be worse for both critical thinking, and social cognitive abilities.

[ checks own name ]

Phewph, came real close to being a Daren, there.

The problem for me personally, is that AI has worked exactly 0% of the time when I try to use it.

Your mistake is knowing that you're doing, so you catch AI's mistakes.

Try using it for stuff you're not remotely qualified to do in the first place, then it can look useful!

I've been experimenting with agentic coding the past couple of weeks. The task is to write a data scraper for a report file I get out of a commercial tool I have to use for work.

It's a pain of a format because it's not written with computer parsing in mind. It's verbose, contains loads of redundant parts, and doesn't have good delimiters around data. It's big too. 500MB uncompressed, so we keep them gzip'd.

All reasons why I don't want to write the code to do it.

The model identifies the file format without me saying where it came from, but it sits in this loop:

• "Let me analyse the input file" - Does various greps, seds, and awks to pull out sections and find patterns in their formatting.
• "I understand the format enough for now" - and then proceeds to write out a list of rules it's discovered. This bit is actually quite impressive.
• "Now I need to draft the data structures the data will go into" - ...and it will write some over-decomposed objects. Not out to disk though.
• "The user says they want a parser, so let me start writing the actual code" ... Finally!... But hang on...
• "Actually, I need to understand the file format more" - loop to the top.

It does this for hours.

The tiny bits of code I've actually managed to get out of it are really bad. It's like the code you'd get back from some race-to-the-bottom offshore software "team" you were forced to work with 10-15 years ago because your boss had found an "amazing opportunity". In actuality it was somebody's teenage nepo-hire. Similar adherence to rules and standards too.

I already have a rough data scraper for this file. It's a couple of hundred lines of python. I wrote it in an afternoon. It's not great. It doesn't get everything I want out. However it exists and is usable. This isn't an intractable task.