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Joined 3 years ago
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Cake day: June 14th, 2023

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  • I think the issue is most people don’t understand what an LLM is doing.

    It’s engineered to respond conversationally, not diagetically. You’re not supposed to know how it is processing your inputs. A black box by design.

    And I get the knee-jerk impulse to see this as a search engine “stealing” click-throughs to strangle a site. But I think people often forget why click-throughs are so vital for a site’s existence to begin with. Why do you need to send your browser through the front door for the data? What does the site get out of that interaction that it doesn’t get out of an LLM fetching the data for you?

    If it’s about something you’re not going to find on the internet then the LLM will just make up something that sounds convincing. And that’s the problem. It may sound convincing but it’s a con man.

    You can see this with known hiccups in the model. “How many 'r’s are in strawberry?” is a classic (that was eventually fixed) that hinges on a question you’re not going to find pre-answered in the publicly scrapped data.

    But if you’re fetching data from an existing website then this isn’t the problem you’re going to run into. It’s going to fetch the data accurately (baring some other glitch) and return a summary of contents modeled into whatever output template the LLM prefers.

    The con-man aspect really kicks in as part of the templating of the answer. You could engineer an LLM to respond in the negative when it failed to find useful data. Or you could engineer it to return data as spreadsheets with “Description” and “Source” (not unlike how Google normally returns links and short blurbs) that allow you to interrogate the source info easily. Instead, we get a definitive pronouncement made with links buried at the bottom of the extended blurb.







  • The biggest liar I know is still in jail for raping children

    I will happily spot you “Don’t hire child rapists” as a rule of thumb. I think “fudging your resume is a slippery slope to sexually assaulting a minor” is a stretch of logic.

    My industry and group are weird when it comes to credentials. We don’t have a strict, you need this degree situation.

    I know employers who use “college degree” as a proxy for “capable of following instructions” and won’t hire anyone without a bachelors.

    I know employers who are much more fast and loose, bringing in anyone with “potential” as they broadly define it.

    Idk exactly what the right answer is. But “powers through a MOOC in a few weeks to get a certificate that says I can competently execute a job” doesn’t strike me as a moral failing.



  • It was explained to me that this was because the government requested for them to take it, because it would help legitimize the program if all the banks took it.

    Sure. I’ve heard this line - “If everyone takes the loan, then nobody has a stigma for taking the loan”. But it was also an incredibly generous line of credit extended against assets that were trading at decade lows. That was part of the enticement to get more banks onboard.

    As much as I hate and disagree with the concept of “too big to fail”, the US government made a huge profit on the TARP program.

    They made a tiny gross profit off flipping equity off the post-'08 dip, booking $15.3 billion in surplus, as it earned $441.7 billion on the $426.4 billion invested.

    Although the Government arguably did not profit from the transaction considering that the program was funded by deficit spending, with an interest rate of between 2% to nearly 4% during 2008 to 2009. The cost to service the debt the Government incurred to fund the program would be at least $8 to $16+ billion a year.

    The Treasury could have made significantly more, if they’d traded the equity they held as collateral back at market rates. Finance stocks saw a 50-100% jump between the '08 lows and '10 recovery. Dividends on the preferred shares would have, similarly, produced a much bigger ROI. These loans were structured to be favorable to the businesses if they recovered and costly to the government if they followed the Lehman Bros crash out.

    But it wasn’t free money. It was a loan that was paid back with interest.

    It was a below-prime-rate loan with a number of debts written off as a loss, where the Treasury basically broke even.

    It also did nothing to provide relief for the home owners paying through the nose on double-digit sub-prime mortgage rates with property that was underwater. The end result was the 2010 Foreclosure Crisis during which banks lobbied state courts and legislatures to allow aggressive and often fraudulent repo of delinquent mortgages (many of which weren’t even delinquent, just bundled with other delinquent debts).

    So, plenty of scandal to go around for both the “bad” banks and the “good” ones.


  • If a hire is open about their credentials I would not care.

    Typically, any job that gets filled at my company has to have a competitive candidate to consider. I’ve seen them fudge this a few times (bringing in someone they know isn’t qualified just to balance against), but it’s a hiring standard that you have to consider at least two (preferably three or four) candidates for any position.

    If you show up and you don’t have the credentials for the position, you’re simply not getting the job.

    I’ve witnessed what happens when people are ok with liars.

    Sure. The Enron offices are spitting distance from where I work.

    But I also see a lot of people fudging resumes to get feet in the door. And I don’t see people who were honest, but got screened out by a filter. So I’m the victim of selection bias, in many regards.



  • Ctrl + v

    There’s a multitude of different paste options in Excel, based on whether you want to copy the whole cell, just the value, the formula that produced the value, just the format, a link to the original cell, or an assortment of more specialized options.

    So Ctrl+V does work, but it doesn’t always paste what you thought you copied.


  • I believe the explanation for this is the first cell is formatted as text. And summing text concatenates rather than adds. Then the new value is saved as a number, adding the 3, to get 15.

    This is an error that can already happen in Excel and one any experienced Excel user has to look out for when moving between alphanumeric and numeric cell types.




  • If an employer asks for a copy of your transcript, what are you going to give them?

    That’s half the joke, though. The employers are using automated tools to sift for staff. Why would prospective staff not use automated tools to bump themselves up in the queue for a job?

    Or maybe you’ll falsify a transcript, but if you were going to do that then why did you pay $4,000 for your college diploma anyway?

    Because then it’s not a “false” transcript. It’s real and true, fully accredited and identical to a transcript issued by a four year school.

    Of course it’s partly the student’s fault

    This is a structural failure. It isn’t the fault of any single (non-billionaire) individual. As we pull more and more humans out of the bureaucratic chain and dump more and more automation onto lowest-bidder third parties, we accumulate technical debt. That technical debt exposes vulnerabilities in our bureaucratic systems. And then people naturally move in to exploit those vulnerabilities when they can’t get what they need out of a normally functional bureaucracy.





  • I saw someone being interviewed who didn’t know who hilter was. Apparently genuine.

    There was a bit that Conan O’Brian used to do back when he had a late-night show. He’d go out and do Man-On-The-Street interviews in… Times Square, I think? Can’t remember if he was LA or NY. But he’d ask some absurdly complex question and get this excellently reasoned and well-thought out answer from randos. And then he’d ask what they did for a living. It was inevitably some NASA engineer or finance professional or other well-educated individual. And they were all just… in the crowd. Because in a city as big as that, of course you’re going to get this extremely mixed bag.

    On the flip side, there’s Sailor Socialism, a podcaster and aspiring actress who baited an interview with an InfoWars reporter, in which she was dressed in a sailor fuku, then went viral talking about how she wanted universal health care and liked Bernie Sanders.

    Interview twenty people and edit the content down to the one or two who make for good entertainment. It’s a tried-and-true strategy.