MobiHealthNews about a digital twins company: “Unlearn uses machine learning to create digital twins of clinical trial participants before being randomized in a controlled trial. The digital twin can provide researchers insight into the participants’ health outcomes. The startup pitches its technology as a way to run smaller clinical trials more quickly, since researchers can find fewer participants for the control group…”Pharmaceutical companies are spending over $100 billion dollars a year on clinical research, yet the industry remains skeptical about new technology that has the power to truly transform research,” said Charles Fisher, founder and CEO of Unlearn. “Breaking down these barriers and proving the value of digital twin technology continues to be a main driver for us at Unlearn. And, this round of financing will allow us to not only grow our team but also expand our capabilities into more therapeutic areas to build awareness and prove the value.”
FT: “The starting point is to recognise that bots are essentially “counterfeit” humans, as the philosopher Daniel Dennett has noted. This suggests, as historian and author Yuval Harari recently told me, that we should explore how governments have battled “counterfeits” elsewhere — most notably, through history, in the sphere of money…The key takeaway from financial history is that it is possible to create a cultural frame that criminalises counterfeiting. Now that would certainly not address all the deepfake problems online.”
WaPo: ““Why We Read: On Bookworms, Libraries and Just One More Page Before Lights Out,” a warm and funny memoir in essays from the appropriately named Shannon Reed. Covering topics ranging from the deliciousness of that twist in “Gone Girl” and the joy of Amish romance novels to the semester she spent decoding George Saunders’s “Lincoln in the Bardo,” Reed — who teaches writing and contemporary fiction at the University of Pittsburgh — chronicles her lifelong relationships with books and reading. Underlying each essay, though, is a conviction that people should read what they want to read. The latest Emily Henry book, “Moby-Dick” and tomes on U.S. history, she explains, all offer value to the reader. “There are simply too many rules about reading,” she writes. “Worse, the higher up the ladder of being a Good Reader … people go, the more rules they seem to have internalized.””
Arnold Kling: “Economist Thomas Sowell is known for saying “There are no solutions, only trade-offs.” That should be known as Sowell’s Law. When we are faced with a set of binary decisions of a given sort, Sowell’s Law can be described as the trade-off between making two types of mistakes. In classical statistics, a Type I error means claiming that the evidence for a hypothesis is strong when it isn’t. And a Type II error means failing to recognize that the evidence for a hypothesis actually is strong. But Type I and Type II errors can be used to describe many more situations. For instance, in a court case, the jury must find the defendant guilty or not. One mistake would be to convict an innocent defendant. Call that a Type I error. The opposite mistake would be to fail to convict a guilty defendant. That is a Type II error. By setting a standard of “innocent unless guilty beyond a reasonable doubt,” our legal tradition is saying that we should try to minimize Type I errors, at the risk of committing Type II errors.”
