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"It forecast 14 earthquakes within a 200-mile area of the estimated epicenter and also made a very accurate forecast regarding their intensity, a report on the university's website said. It failed to warn of just one earthquake and gave eight false predictions. The research team trained the AI to detect statistical bumps in real-time seismic data that the research team had paired with previous earthquakes, the report explained. Once trained, the AI monitored for signs of approaching earthquakes. "Predicting earthquakes is the holy grail," said Sergey Fomel, a professor at UT's Bureau of Economic Geology and a member of the research team, adding: "What we achieved tells us that what we thought was an impossible problem is solvable in principle.""

"Shadbolt also forecasts that future changes to the web will mean people will be "connected all the time" to medical diagnostic systems - but also that search companies including Google and China's Baidu may face challenges as web use shifts from the desktop to handheld and mobile devices."

"But you might not end up reassured. Though it promises robot carers for an ageing population, it also forecasts huge numbers of jobs being wiped out: up to 35% of all workers in the UK and 47% of those in the US, including white-collar jobs, seeing their livelihoods taken away by machines."

Much of current science deals with even more complicated systems, and similarly lacks exact solutions. Such models have to be "computational" - describing how a system changes from one instant to the next. But there is no way to determine the exact state at some time in the future other than by "simulating" its evolution in this way. Weather forecasting is a familiar example; until the advent of computers in the 1950s, it was impossible to predict future weather faster than it actually happened.

"About two years ago the retail team lost another key task: negotiating with major brands and manufacturers the terms of popular sales on the site called "Lightning Deals." Common during the holidays as well as Mother's Day and Father's Day, they help move lots of inventory in a short period. Now, instead of calling their vendor manager at Amazon, the makers of handbags, smartphone accessories and other products simply logged into an Amazon portal that would determine if Amazon liked the deal being offered and the quantity it was willing to buy. No small talk. No give and take. Thousands of Amazon man hours spent forecasting demand, planning marketing strategies and negotiating deals was now handled by software, a major leap in efficiency."

"The system used historical data, including arrest records and electronic police reports, to forecast crime and help shape public safety strategies, according to company and city government materials. At no point did those materials suggest any effort to clean or amend the data to address the violations revealed by the DOJ. In all likelihood, the corrupted data was fed directly into the system, reinforcing the department's discriminatory practices."

"But, as he and other modellers warn, much information about how SARS-CoV-2 spreads is still unknown and must be estimated or assumed - and that limits the precision of forecasts. An earlier version of the Imperial model, for instance, estimated that SARS-CoV-2 would be about as severe as influenza in necessitating the hospitalization of those infected. That turned out to be incorrect."

"Half a century ago, before the first Apple computer was even sold, climate scientists started making computer-generated forecasts of how Earth would warm as carbon emissions saturated the atmosphere (the atmosphere is now brimming with carbon). It turns out these decades-old climate models - which used math equations to predict how much greenhouse gases would heat the planet - were pretty darn accurate. Climate scientists gauged how well early models predicted Earth's relentless warming trend and published their research Wednesday in the journal Geophysical Research Letters."

"Analyst Brian Nowak estimates that the AI technology will have a $4.1 trillion economic effect on the labor force - or affect about 44% of labor - over the next few years by changing input costs, automating tasks and shifting the ways companies obtain, process and analyze information. Today, Morgan Stanley pegs the AI effect at $2.1 trillion, affecting 25% of labor. "We see generative AI expanding the scope of business processes that can be automated," he wrote in a Sunday note. "At the same time, the input costs supporting GenAI functionality are rapidly falling, enabling a strongly expansionary impact to software production. As a result, Generative AI is set to impact the labor markets, expand the enterprise software TAM, and drive incremental spend for Public Cloud services.""