#data-accuracy

#data-accuracy

In early August, data from the Los Angeles Homeless Services Authority showed only two out of 88 beds at an East Hollywood homeless shelter were occupied, a shockingly low rate in a county where some 47,000 sleep on the streets. There's just one big problem, according to the nonprofit PATH, which operates the shelter. The data were dead wrong. Path's internal data showed 84 beds were filled.

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Economists and decision-makers face a dilemma between needing swift information and the necessity of accuracy, often relying on preliminary estimates that are later revised.

The property listing data and information were provided to MLS Property Information Network, Inc. from third-party sources including sellers and public records.

Anshul Kundaje sums up his frustration with the use of artificial intelligence in science in three words: "bad benchmarks propagate". He expresses concern about questionable claims made by researchers about AI models, which take months to verify and often turn out to be false due to poorly defined benchmarks. This problem creates misinformation and wrong predictions, as flawed benchmarks are misused by enthusiastic users. The lack of reliable benchmarks threatens to undermine AI's potential to accelerate scientific progress rather than enhance it.