Étiquette : artificial intelligence (Page 25 of 33)

Deep Learning

«DL will not disagree with any data, will not figure out the injustices in the society, it’s just all “data to learn”. You should hire a dedicated human staff to create fake fair data of an ideal society where white people are arrested as often as blacks, where 50% of directors are women, and so on. But the cost of creating vast amounts of de-biased data edited by human experts, just to train a DL model, makes not worth to replace humans with AI in first place! Further, even if you had trained a DL model that really is fair, you have no evidence to convince a judge or a user about the fairness of any decision, since the DL will give no explanations».

Source : Deep Learning is not the AI future

AlphaGo Zero: Learning from scratch

«The paper introduces AlphaGo Zero, the latest evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is arguably the strongest Go player in history. Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play».

Source : AlphaGo Zero: Learning from scratch | DeepMind

«Convoquer des spéculations sur des formes d’IA qui n’existent pas encore et n’existeront probablement jamais, pour terrifier et mobiliser les foules relève plus de la religion que de la science. Ces invitations à embrasser une forme de futur inévitable qu’on martèle pour se persuader qu’il va advenir me cassent les pieds» – Hubert Guillaud.

Source : L’avenir de l’intelligence artificielle est-il… inévitable ? (2/2) : du réductionnisme à l’éthique de l’intelligence | InternetActu.net

«Cette coopération résulte d’une vision sur le long terme. En laissant les universitaires continuer à former la future main-d’œuvre, on s’assure qu’il n’y aura jamais de pénurie en IA» – Jean-François Gagné (Element AI).

Source : Element AI, la start-up qui affole le Canada

«Comment le défenseur ou le garde s’oriente-t-il par rapport à vous ? Dans un jeu, on court après un ballon, dans l’autre, on manie l’épée, le contenu est évidemment très différent, mais du point de vue de l’intelligence artificielle, il y a beaucoup de similitudes. Idem pour la coordination d’un groupe : que ce soit une équipe ou une garnison, les problématiques pour nous sont les mêmes» – Ashraf Ismail.

Source : « “FIFA” et “Assassin’s Creed”, beaucoup de similitudes dans l’intelligence artificielle »

«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

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