961–970 of 1001 posts
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Hilarious, but he never actually said he'd stop writing, just that he'd continue writing until proven wrong. And provably, he did. He wrote until then, and continued after. Since he never stopped writing, he met the challenge. He's now free to stop writing whenever he wants and still not fail that statement. ;)
Are you a software tester?
> February 2025: "I will keep writing this stuff until I’m proven wrong." Wrong (Zitron continues to write despite repeatedly being proven wrong) This was a good one.
The doctor said I was sick...but I did not die on Tuesday, so checkmate! You are confusing an imprecise prognosis with a false diagnosis. And The funniest part is that "he keeps writing, therefore he was proven wrong" contains no actual proof that he is wrong.
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Here's two possible set of predictions: - a list of predictions that are entirely wrong, from A-to-Z, and are not even resembling what ends up happening - a list of predictions that are wrong, but where the underlying points are in fact interesting and have some predictive value, and it's just the "last step" that is wrong For example, one person might say "oh it's raining in Dallas therefore I should buy some TI sto…
> The prediction was early, overestimated how long of a tail RIM would experience, but how wrong was it? Was the prediction of some utility? Wrong enough that the utility is seriously diminished. Predicting a specific quantity dropping to a specific level at a specific date is a lot more valuable than saying “those guys are cooked”. And even if some minuscule utility existed: why should predictors be so coddled by th…
> why should predictors be so coddled by their observers?
I suppose that in the RIM example the predictor correctly identified causes and concerns. The timelines are off. But highlighting the causes are interesting to me, as a datapoint.
If someone says "hey there's a problem here", you can somewhat independently look at the problem and validate its seriousness on your end.
Some people in this thread are like "well the value is in the prediction", but from my perspective I'm thinking "the value is in the causal analysis". Because if you merely think the timelines are wrong you can easily just change numbers around.
Obviously Zitron is not "always right", and isn't getting all causal analysis right IMO. I do think he's bringing up things though.
Every transaction in the financial market is a bet with two sides with opposite beliefs. I don't get why people make such a big deal off bears and bulls. Everyone is on one of these sides at every investment they make or liquidate.
Zitron does not seem to put his own skin in the game by going short though - He sells bearishness via his substack, podcasts and media appearances.
My point is: all analysis is contingent, there is no point in saying bulls or bears are chronically wrong or that they should beat the market to merit being listened to.
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> 1. Zitron claims model capability has peaked … Zitron is probably right in this regard … Is there any objective measure that shows this? Would we use examples such as his Feb 2024 claim "I believe we're reaching the upper limits about what generative AI can do"? > 2. Zitron claims AI lab growth (user and revenue) has stalled.… I'm giving Zitron the benefit of the doubt … Is there some date by which you'd say it'd b…
I'll paste my response to your pre-edited questions: I think atomic weapons peaked during the trinity test. The subsequent creation of bigger explosions by packing more fissile material does not meaningfully improve the technology. Since LLMs are a generative technology, let's use a generative skill - painting. There are tons of brilliant painters, all with their own styles. What I think is consistent among master pa…
That's not a great summary of what happened with the invention of the H-bomb.
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> We have people telling us the next recession being imminent all the time. Yeah uhm so I'm not sure if you've like seen the world recently, but uh. Yea
S&P 500 - All time high DJIA - All time high Unemployment rate - Near all time low (for last 20 years) Number of US small businesses - All time high US GDP - All time high [Sources] https://www.bls.gov/charts/employment-situation/civilian-une... https://www.sellerscommerce.com/blog/small-business-statisti... https://fred.stlouisfed.org/series/GDP
the s&p doesnt tend to go down until a recession is either imminent or happening, and modern economic policy may even prevent that due to the vastly expanded wealth disparity
the unemployment rate isn't really the tool it once was--if you include two groups that count as "employed" by the US unemployment rate--people seeking full time jobs but working only 1-34 hours a week, and people earning below the poverty line (under 26k pre-tax anually), the functional unemployment rate climbs to 24.9%--higher even than any month in the post-covid period of 2022-2024 (inclusive).
yes, more small businesses than ever, but growth last year was almost non-existent. and it generally proxies vs able-bodied adults, which would have seen an increase larger than the businesses.
gdp is high but much of that is ai company shuffle and debt-to-gdp ratio is rising once again--now the highest it's been since the 2020 massive covid bump
birth rates are broadly down as well, likely stemming from cost of living, and birth rates do tend to predict recessions.
it's fine to point at numbers but they don't really mean anything in isolation
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The added value other than the stock market would be in making major life decisions. In the case of the 2008 crisis, specific knowledge of the timing could matter for buying or selling a house. In the case of technological predictions, specific knowledge of the timing could affect whether you want to take a university program in a given field or join a certain company. If a predictor can’t help with picking stocks or…
> If a predictor can’t help with picking stocks or making big decisions, then what are these predictions for, entertainment? Not sure how you constructed that specific sentence from my message. My point was that most big decisions aren't that sensitive to small timing changes, like stock market can be. Your examples highlight that point: few would change their university choices depending on the knowledge that a futu…
Fair enough, I didn’t.
> most big decisions aren't that sensitive to small timing changes
That makes sense for a single year at least.
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> The prediction was early, overestimated how long of a tail RIM would experience, but how wrong was it? Was the prediction of some utility? Wrong enough that the utility is seriously diminished. Predicting a specific quantity dropping to a specific level at a specific date is a lot more valuable than saying “those guys are cooked”. And even if some minuscule utility existed: why should predictors be so coddled by th…
I think this is a legit read about the utility. > why should predictors be so coddled by their observers? I suppose that in the RIM example the predictor correctly identified causes and concerns. The timelines are off. But highlighting the causes are interesting to me, as a datapoint. If someone says "hey there's a problem here", you can somewhat independently look at the problem and validate its seriousness on your…
In 2024, if Ed Zitron presented all his analysis of AI companies without the specific “model capabilities have peaked this year” style statements that Dan Luu scrutinized, that would be more honest and provide the value you are looking for.
Similarly for the RIM example nobody would have to claim that RIM would fail in a particular year, or that “RIM is cooked”, they could present their data about the present without any projection.