Becky Carroll was missing a few teeth, others were stained or crooked. Ashamed, she smiled with lips pressed closed. Her dentist offered to fix most of her teeth with root canals and crowns, Carroll said, but she was wary of traveling a long road of dental work.

Then Carroll saw a TV commercial for another path: ClearChoice Dental Implant Centers. The company advertises that it can give patients “a new smile in as little as one day” by surgically replacing teeth instead of fixing them.

So Carroll saved and borrowed for the surgery, she said. In an interview and a lawsuit, Carroll said that at a ClearChoice clinic in New Jersey in 2021, she agreed to pay $31,000 to replace all her natural upper teeth with pearly white prosthetic ones. What came next, Carroll said, was “like a horror movie.”

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Anyone familiar with HR practices probably knows of the decades of studies showing that résumé with Black- and/or female-presenting names at the top get fewer callbacks and interviews than those with white- and/or male-presenting names—even if the rest of the résumé is identical. A new study shows those same kinds of biases also show up when large language models are used to evaluate résumés instead of humans.

In a new paper published during last month's AAAI/ACM Conference on AI, Ethics and Society, two University of Washington researchers ran hundreds of publicly available résumés and job descriptions through three different Massive Text Embedding (MTE) models. These models—based on the Mistal-7B LLM—had each been fine-tuned with slightly different sets of data to improve on the base LLM's abilities in "representational tasks including document retrieval, classification, and clustering," according to the researchers, and had achieved "state-of-the-art performance" in the MTEB benchmark.

Rather than asking for precise term matches from the job description or evaluating via a prompt (e.g., "does this résumé fit the job description?"), the researchers used the MTEs to generate embedded relevance scores for each résumé and job description pairing. To measure potential bias, the résuméwere first run through the MTEs without any names (to check for reliability) and were then run again with various names that achieved high racial and gender "distinctiveness scores" based on their actual use across groups in the general population. The top 10 percent of résumés that the MTEs judged as most similar for each job description were then analyzed to see if the names for any race or gender groups were chosen at higher or lower rates than expected.

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When Chinese space officials unveiled the design for the country's first super heavy lift rocket nearly a decade ago, it looked like a fairly conventional booster. The rocket was fully expendable, with three stages and solid motors strapped onto its sides.

Since then, the Asian country has been revising the design of this rocket, named Long March 9, in response to the development of reusable rockets by SpaceX. As of two years ago, China had recalibrated the design to have a reusable first stage.

Now, based on information released at a major airshow in Zhuhai, China, the design has morphed again. And this time, the plan for the Long March 9 rocket looks almost exactly like a clone of SpaceX's Starship rocket.

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On Friday, S&P Dow Jones Indices announced that AI chipmaker Nvidia will replace Intel in the Dow Jones Industrial Average, marking a seismic shift in the semiconductor industry and ending Intel's 25-year run on the prestigious stock market index. The change takes effect on November 8.

"The index changes were initiated to ensure a more representative exposure to the semiconductors industry," wrote S&P in a press release.

Intel's stock has dropped 54 percent this year, making it the worst performer on the Dow, and the company now holds a market value of under $100 billion for the first time in three decades, Reuters reported. Analysts expect Intel to post its first annual net loss since 1986.

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Tesla recently sent out an update to its vehicle “summon” feature – which it calls Actually Smart Summon – and as a result, one Tesla owner can no longer use his car.