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| How Badly Did ChatGPT and Copilot Fail to Predict the Winners of the Kentucky Derby? |
jemboet |
54 minutes ago |
In 2016, an online "swarm intelligence" platform stunned horse-racing fans by making a correct prediction for the Kentucky Derby — naming all four top finishers in order. (But the next year its predictions weren't even close, with TechRepublic suggesting 2016's race just had an unusual cluster of obvious picks.) Since then it's become almost a tradition — asking AI to predict the winning horses each year, then see how close it came. So before today's race, a horse named "Journalism" was given the best odds of winning by professional bookmakers — but could AI make a better prediction? USA Today reports: The USA TODAY Network asked Microsoft Copilot AI to simulate the order of finish for the 2025 Kentucky Derby field based on the latest, odds, predictions and race factors on Thursday, May 1. Journalism came out on top in its projection. The AI-generated response cited Journalism's favorable post position (No. 8), which has produced the second-most Kentucky Derby winners and a four-race winning streak that includes last month's Santa Anita Derby. ChatGPT also picked the exact same horse, according to FanDuel. But in fact, the winning horse turned out to be "Sovereignty" (a horse Copilot predicted would finish second). Meanwhile Copilot's pick for first place ("Journalism") finished in second. But after that Copilot's picks were way off... Copilot's pick for third place was a horse named Rodriguez — which hours later was scratched from the race altogether. (And the next day Copilot's pick for 10th place was also scratched.) Copilot's pick for fourth place was "Sandman" — who finished in 18th place. Copilot's pick for fifth place was "Burnham Square" — who finished in 11th place. Copilot's pick for sixth place was "Luxor Cafe" — who finished in 10th place Copilot's pick for seventh place was "Render Judgment" — who finished in 16th place... An online racing publication also asked "a trained AI LLM tool" for their predictions, and received a wildly uneven prediction: Burnham Square (finished 11th) Journalism (finished 2nd) Sandman (finished 18th) Tiztastic (finished 15th) Baeza (finished 3rd)
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| AI Compute Costs Drive Shift To Usage-Based Software Pricing |
jemboet |
1 week, 3 days ago |
The software-as-a-service industry is undergoing a fundamental transformation, abandoning the decades-old "per seat" licensing model in favor of usage-based pricing structures. This shift, Business Insider reports, is primarily driven by the astronomical compute costs associated with new "reasoning" AI models that power modern enterprise software. Unlike traditional generative AI, these reasoning models execute multiple computational loops to check their work -- a process called inference-time compute -- dramatically increasing token usage and operational expenses. OpenAI's o3-high model reportedly consumes 1,000 times more tokens than its predecessor, with a single benchmark response costing approximately $3,500, according to Barclays. Companies including Bolt.new, Vercel, and Monday.com have already implemented usage-based or hybrid pricing models that tie costs directly to AI resource consumption. ServiceNow maintains primarily seat-based pricing but has added usage meters for extreme cases. "When it goes beyond what we can credibly afford, we have to have some kind of meter," ServiceNow CEO Bill McDermott said, while emphasizing that customers "still want seat-based predictability."
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