Sam Greengard on Muck Rack

Sam Greengard

Verified
West Linn
As seen in: Communications of the ACM, Datamation, InformationWeek, Encyclopaedia Britannica, WIRED (UK), Healthline, ACM - Association for Computing Machinery, Flipboard, CSO, Dark Reading, Data Center Knowledge, eWEEK, RFID Journal and
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Articles

Teaching LLMs to Give Better Answers

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By Sam Greengard Verified
| Communications of the ACM Verified
Ask an LLM a question and you’re likely to receive a response that sounds like it came from a Ph.D; whether the information is accurate—or even based in reality—is another issue. Somewhere between training, inference, and the real world of spitting out words and code lies a persistent problem: these models are unable at times to recognize basic errors.
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Can AI Detectors Be Trusted?

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By Sam Greengard Verified
| Communications of the ACM Verified
Society has always trusted editors, teachers, peer reviewers, and readers to set acceptable standards for writing. In the past, the biggest challenge was detecting plagiarism and cracking down on other forms of cheating. Now, AI detectors are rewriting the script: they assign a score based on the likelihood that the text was created by a human or a large language model (LLM). The verdict can determine whether a publication accepts an article or a student passes a class.
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Peering into Dark Places

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By Sam Greengard Verified
| Communications of the ACM Verified
Human vision has its limitations. Descend into a cave or venture into the woods at night, and the world begins to dim. Add smoke, fog, rain, haze, snow, or dust to the mix, and it becomes next to impossible to see anything, even with the aid of a lantern or headlights. These conditions don’t just challenge people; they blind machines. As autonomous vehicles, robots, drones, and other devices attempt to navigate an array of places and spaces, they can become disoriented.
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