… working through the night is a fundamental challenge to the human body. It unsettles our finely tuned biology, forcing us to be active when powerful impulses are telling us to lie down and dream. A growing body of research links a lack of sleep to increased morbidity — an average of less than six hours sleep per night in the long term puts you at a 13 per cent higher mortality risk than someone getting seven to nine hours, according to the research organisation Rand Europe.
Ignore the hype over big tech. Its products are mostly useless | John Harris | Opinion | The Guardian
… À regular ritual of hype and hysteria is now built into the news cycle. Every now and again, at some huge auditorium, a senior staff member at one of the big firms based in northern California – ordinarily a man – will take the stage dressed in box-fresh casualwear, and inform the gathered multitudes of some hitherto unimagined leap forward, supposedly destined to transform millions of lives. (There will be whoops and gasps in response, and a splurge of media coverage – before, in the wider world, a palpable feeling of anticlimax sets in.)
It happened again a fortnight ago, when the Google chief executive, Sundar Pichai, addressed his company’s annual developers’ conference. Among his other tasks, he was there to rhapsodise about developments in artificial intelligence, and the ever-evolving application known as Google Assistant (created, he said, to “help you get things done”), and a new innovation called Duplex. “It turns out that a big part of getting things done is making a phone call,” he said.
Companies of all kinds are adopting artificial intelligence (AI) and machine-learning systems at an accelerated pace. International Data Corp. (IDC) projects that shipments of AI software will grow by 50% per year and will reach $57.6 billion in 2021 — up from $12 billion in 2017 and just $8 billion in 2016. AI is being applied to a range of tasks, including rating mortgage applications, spotting signs of trouble on power lines, and helping drivers navigate using location data from smartphones.
But companies are learning the hard way that developing and deploying AI and machine-learning systems is not like implementing a standard software program. What makes these programs so powerful — their ability to “learn” on their own — also makes them unpredictable and imminently capable of errors that can harm the business.