MACHINE-LEARNING is beginning to shake up finance. A subset of artificial intelligence (AI) that excels at finding patterns and making predictions, it used to be the preserve of technology firms. The financial industry has jumped on the bandwagon. To cite just a few examples, “heads of machine-learning” can be found at PwC, a consultancy and auditing firm, at JP Morgan Chase, a large bank, and at Man GLG, a hedge-fund manager. From 2019, anyone seeking to become a “chartered financial analyst”, a sought-after distinction in the industry, will need AI expertise to pass his exams.
Founded in 2004 by Peter Thiel and some fellow PayPal alumni, Palantir cut its teeth working for the Pentagon and the CIA in Afghanistan and Iraq. The company’s engineers and products don’t do any spying themselves; they’re more like a spy’s brain, collecting and analyzing information that’s fed in from the hands, eyes, nose, and ears. The software combs through disparate data sources—financial documents, airline reservations, cellphone records, social media postings—and searches for connections that human analysts might miss. It then presents the linkages in colorful, easy-to-interpret graphics that look like spider webs. U.S. spies and special forces loved it immediately; they deployed Palantir to synthesize and sort the blizzard of battlefield intelligence. It helped planners avoid roadside bombs, track insurgents for assassination, even hunt down Osama bin Laden. The military success led to federal contracts on the civilian side. The U.S. Department of Health and Human Services uses Palantir to detect Medicare fraud. The FBI uses it in criminal probes. The Department of Homeland Security deploys it to screen air travelers and keep tabs on immigrants.
Finland has found the answer to homelessness. It couldn’t be simpler | Harry Quilter-Pinner | Opinion | The Guardian
The number of homeless people dying on the streets or in temporary accommodation in the UK has more than doubled over the past five years to more than one per week. The average age of a rough sleeper when they die is 43, about half the UK life expectancy.
The tragedy is that it’s entirely within our power to do something about it: homelessness is not a choice made by the individual, it is a reality forced by government policy. As homelessness has rocketed in the UK – up 134% since 2010 – it has fallen by 35% in Finland over a similar period of time. The Finnish government is now aiming to abolish it altogether in the coming years.
I recently travelled to Finland to understand how it had done this. It turns out its solution is painfully simple and blindingly obvious:give homes to homeless people.
Probabilities may be expressed in two ways. Statistical probabilities are based on empirical evidence concerning relative frequencies. Most intelligence judgments deal with one-of-a-kind situations for which it is impossible to assign a statistical probability. Another approach commonly used in intelligence analysis is to make a “subjective probability” or “personal probability” judgment. Such a judgment is an expression of the analyst’s personal belief that a certain explanation or estimate is correct. It is comparable to a judgment that a horse has a three-to-one chance of winning a race.
Verbal expressions of uncertainty–such as “possible,” “probable,” “unlikely,” “may,” and “could”–are a form of subjective probability judgment, but they have long been recognized as sources of ambiguity and misunderstanding. To say that something could happen or is possible may refer to anything from a 1-percent to a 99-percent probability. To express themselves clearly, analysts must learn to routinely communicate uncertainty using the language of numerical probability or odds ratios.
Laundry can be frustrating, even for a laundry enthusiast. It’s time-consuming, unceasing and there is so very much that can go wrong. For many of us, it’s one of those chores we learned to do from our parents, a dormmate, a significant other or whoever else, and then we stop asking questions. But questions are great! Because knowledge is power and can make doing laundry easier and more effective. This guide aims to help you understand your machines, how fabric types behave and the methods for treating common problems like stains, dinginess and odor