Government Falsehoods and AI Malinvestments.
We Have Been Here Before.
Today's Skye's Links continues our discussion of energy and the terrible malinvestments made to save the planet. The technology cannot work as promised because of undeniable physical science, material resource, and financial constraints.
Various smooth-talkers are demanding the United States nationalize and then triple the capacity of the electrical power grid to fit intermittent solar and wind's 24-hour needs. It won't work because it cannot work, while the balance of the grid becomes less reliable by the day.
Remember the efforts to ban natural gas appliances? At the root, the plan is to deny the escape hatch created by home emergency generators fueled by natural gas, creating a Cloward-Piven energy crisis.
Immigration is now entirely out of control, and Texas Governor Abbot has his own Cloward-Piven strategy to move migrants to blue cities. While New York and Chicago have received a tiny fraction of the immigrants flooding Texas, the blue city systems are so brittle that they fail from a feather. Politics in New York and Chicago cannot withstand substituting the new preferred minority for the old minority, and things are getting hot.
It was not just the CDC and NIH that lied outright about Covid, but the FBI, DOJ, and the rest of the government knowingly pushed the false Trump Collusion narrative. They did this to expand institutional power at the Constitution's and the nation's expense. The Durham report is 300 pages of shame and dishonor. It names the names, including Obama and John Brennan, as masterminds working to elect Hillary and Xiden. And, of course, their massive supporting casts.
AI technology is very good with language but less with math, science, and idea generation. The core technology predicts words likely to follow a query using trained databases. ChatGBT can use, in theory, up to 32,000 keywords at once to refine its work product. Google taps out after eight keywords. But whatever is asked, it relies on the user having a correct premise to define a problem. So far, it is excellent with standardized tests such as the LSAT, but it must search for existing information to generate solutions. This characteristic makes errors self-reinforcing and a potential investment advice disaster.
Money flows into AI ventures faster than any investments in history, yet armies of poorly educated minimum-wage workers are training the programs. Their worldview and politics are being baked into the cake.
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