Étiquette : prediction (Page 1 of 2)

“Asking people to choose between privacy and health is, in fact, the very root of the problem. Because this is a false choice. We can and should enjoy both privacy and health. We can choose to protect our health and stop the coronavirus epidemic not by instituting totalitarian surveillance regimes, but rather by empowering citizens. In recent weeks, some of the most successful efforts to contain the coronavirus epidemic were orchestrated by South Korea, Taiwan and Singapore. While these countries have made some use of tracking applications, they have relied far more on extensive testing, on honest reporting, and on the willing co-operation of a well-informed public.”

Source : Yuval Noah Harari: the world after coronavirus | Financial Times

Your Smartphone’s Location Data Is Worth Big Money to Wall Street

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“When Tesla Chief Executive Elon Musk said the car maker would work around the clock to boost production of its Model 3 sedan, the number crunchers at Thasos Group decided to watch. They circled Tesla’s 370 acres in Fremont, Calif., on an online map, creating a digital corral to isolate smartphone location signals that emanated from within it. Thasos, which leases databases of trillions of geographic coordinates collected by smartphone apps, set its computers to find the pings created at Tesla’s factory, then shared the data with its hedge-fund clients, showing the overnight shift swelled 30% from June to October. Last week, many on Wall Street were surprised when Tesla disclosed a rare quarterly profit, the result of Model 3 production that had nearly doubled in three months. Shares shot up 9.1% the next day.”

Source : Your Smartphone’s Location Data Is Worth Big Money to Wall Street – WSJ

Tom Insel and Paul Dagum

“A startup founded in Palo Alto, California, by a trio of doctors, including the former director of the US National Institute of Mental Health, is trying to prove that our obsession with the technology in our pockets can help treat some of today’s most intractable medical problems: depression, schizophrenia, bipolar disorder, post-traumatic stress disorder, and substance abuse. Mindstrong Health is using a smartphone app to collect measures of people’s cognition and emotional health as indicated by how they use their phones. Once a patient installs Mindstrong’s app, it monitors things like the way the person types, taps, and scrolls while using other apps. This data is encrypted and analyzed remotely using machine learning, and the results are shared with the patient and the patient’s medical provider.”

Source : The smartphone app that can tell you’re depressed before you know it yourself – MIT Technology Review

“The team at Oak Ridge says Summit is the first supercomputer designed from the ground up to run AI applications, such as machine learning and neural networks. It has over 27,000 GPU chips from Nvidia, whose products have supercharged plenty of AI applications, and also includes some of IBM’s Power9 chips, which the company launched last year specifically for AI workloads. There’s also an ultrafast communications link for shipping data between these silicon workhorses.
Bob Picciano of IBM says all this allows Summit to run some applications up to 10 times faster than Titan while using only 50 percent more electrical power. Among the AI-related projects slated to run on the new supercomputer is one that will crunch through huge volumes of written reports and medical images to try to identify possible relationships between genes and cancer. Another will try to identify genetic traits that could predispose people to opioid addiction and other afflictions”.

Source : The world’s most powerful supercomputer is tailor made for the AI era – MIT Technology Review

“YouTube Music is Google’s most direct competitor to Spotify yet, coming with “a reimagined mobile app” and a new desktop player, both of them designed specifically for music. The YouTube advantage, argues Google, is that it will combine all the official versions of songs with access to “thousands” of related playlists, remixes, covers, live versions, and of course, music videos. Google’s AI mastery is also being integrated into YouTube Music, with the promise that the app will discover songs either by lyric or just a general description”.

Source : YouTube Music and YouTube Premium announced as YouTube Red replacements – The Verge

“The Selfish Ledger positions Google as the solver of the world’s most intractable problems, fueled by a distressingly intimate degree of personal information from every user and an ease with guiding the behavior of entire populations. There’s nothing to suggest that this is anything more than a thought exercise inside Google, initiated by an influential executive. But it does provide an illuminating insight into the types of conversations going on within the company that is already the world’s most prolific personal data collector.”

Source : Google’s Selfish Ledger is an unsettling vision of Silicon Valley social engineering – The Verge

«Derrière la modélisation, s’impose également une vision politique. La modélisation du monde est elle-même un modèle politique : elle suppose souvent que la dynamique de changement doit venir de l’extérieur de la situation plutôt que de la créativité des acteurs impliqués. Au final, la mise en équation de la société repose sur une conception de la société qui ne peut pas faire société».

Source : Peut-on modéliser la société ? | InternetActu.net

«Neural nets are just thoughtless fuzzy pattern recognizers, and as useful as fuzzy pattern recognizers can be—hence the rush to integrate them into just about every kind of software—they represent, at best, a limited brand of intelligence, one that is easily fooled. A deep neural net that recognizes images can be totally stymied when you change a single pixel, or add visual noise that’s imperceptible to a human. Indeed, almost as often as we’re finding new ways to apply deep learning, we’re finding more of its limits. Self-driving cars can fail to navigate conditions they’ve never seen before. Machines have trouble parsing sentences that demand common-sense understanding of how the world works.Deep learning in some ways mimics what goes on in the human brain, but only in a shallow way—which perhaps explains why its intelligence can sometimes seem so shallow».

Source : Is AI Riding a One-Trick Pony? – MIT Technology Review

«L’analyse des attributs géographiques des cellules a permis de pointer 21 facteurs de risque, allant de la présence d’arrêts de bus, de magasins de restauration rapide, de café et de bar, de pharmacie, de guichet de banque, de magasin d’alimentation… mais aussi bien sûr des lieux où sévissent trafic de drogue et prostitution. Et ces différents facteurs s’agencent dans un autre ordre de jour et de nuit. Peut-on pour autant prédire ou prévoir ?»

Source : Police prédictive (1/2) : dépasser la prédiction des banalités ? | InternetActu

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