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also, human capacity rendered as a subscription service
more or less
precogs in the story basically do the similar predictive as AI, I thought it was apt
also, human capacity rendered as a subscription service
more or less
"we can remember it for you wholesale"
But not a car company
Correct
What is it?
(it) is owned by the richest man in the world.
Already told you
Robotaxi could be a hint
Nope.
What's the use in being coy?
Just say things. It's not going to kill you.
"vegetative electron microscopy"
https://www.sciencealert.com/a-stran...papers-but-whyFinding errors of this sort is not easy. Fixing them may be almost impossible.
One reason is scale. The CommonCrawl dataset, for example, is millions of gigabytes in size. For most researchers outside large tech companies, the computing resources required to work at this scale are inaccessible.
Another reason is a lack of transparency in commercial AI models. OpenAI and many other developers refuse to provide precise details about the training data for their models. Research efforts to reverse engineer some of these datasets have also been stymied by copyright takedowns.
When errors are found, there is no easy fix. Simple keyword filtering could deal with specific terms such as vegetative electron microscopy. However, it would also eliminate legitimate references (such as this article).
More fundamentally, the case raises an unsettling question. How many other nonsensical terms exist in AI systems, waiting to be discovered?
OpenAI announces that it will start showing product recommendations in ChatGPT, even for logged-out users, with buy buttons that link to merchants' sites (Reece Rogers/Wired)
this is the path to profitability?
Don't knock it, Dumper. He used the same path to Presidency.
hands off!
the proof isn't in the pudding, but in the eating
https://fortune.com/2025/05/09/klarn...rticle-content
- After years of depicting Klarna as an AI-first company, the fintech’s CEO reversed himself, telling Bloomberg the company was once again recruiting humans after the AI approach led to “lower quality.” An IBM survey reveals this is a common occurrence for AI use in business, where just 1 in 4 projects delivers the return it promised and even fewer are scaled up.
the future is going all in on tech with no proven value that you don't understand
because of FOMO
Wunderkid Aidan Toney-Rodgers apparently faked the data set for his study on worker productivity
(Toney-Rodgers used AI to generate the data set and the analysis, and nearly got published in a top economics journal)
not very disruptive or revolutionary so far
https://fortune.com/2025/05/18/ai-ch...ny-occupation/“AI chatbots have had no significant impact on earnings or recorded hours in any occupation,” economists Anders Humlum and Emilie Vestergaard wrote in a National Bureau of Economic Research working paper released this week.
Humlum, an assistant professor of economics at the University of Chicago’s Booth School of Business, and Emilie Vestergaard, an economics PhD student at the University of Copenhagen, looked at 25,000 workers across 7,000 workspaces, focusing on occupations believed to be susceptible to disruption by AI: accountants, customer support specialists, financial advisors, HR professionals, IT support specialists, journalists, legal professionals, marketing professionals, office clerks, software developers, and teachers.
They pulled records from Denmark, a country whose rates of AI adoption as well as hiring and firing practices are similar to those in the U.S. but where record-keeping is far more detailed, allowing the study to anonymously match survey responses to records of actual hours and pay.
On average, users of AI at work had a time savings of 3%, the researchers found. Some saved more time, but didn’t see better pay, with just 3%-7% of productivity gains being passed on to paychecks.
In other words, while they found no mass displacement of human workers, neither did they see transformed productivity or hefty raises for AI-wielding superworkers.
https://www.notus.org/health-science...itation-errors
Our national health science is now reduced to elementary school quality AI hallucination driven research papers.
GIGO
But simple prompts "not to use bias" undid the problem
https://news.lehigh.edu/ai-exhibits-...ting-decisionsThe study used real mortgage application data, drawn from a sample of 1,000 loan applications included in the 2022 Home Mortgage Disclosure Act (HMDA) dataset, to create 6,000 experimental loan applications. In the experiment, researchers manipulated race and credit score variables to determine their effects.
The results were stark: Black applicants consistently faced higher barriers to homeownership, even when their financial profiles were identical to white applicants.
Based on the experimental results using OpenAI’s GPT-4 Turbo LLM, Black applicants would, on average, need credit scores approximately 120 points higher than white applicants to receive the same approval rate, and about 30 points higher to receive the same interest rate.
Echo chamber of nonsense by crazy copypasta leftist WH.
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