Étiquette : machine learning (Page 9 of 10)

4 novembre 2016 / noflux

Researchers from Carnegie Mellon University have shown that specially designed spectacle frames can fool even state-of-the-art facial recognition software. Not only can the glasses make the wearer essentially disappear to such automated systems, it can even trick them into thinking you’re someone else. By tweaking the patterns printed on the glasses, scientists were able to assume one another’s identities or make the software think they were looking at celebrities.

Source : These glasses trick facial recognition software into thinking you’re someone else – The Verge

17 octobre 2016 / noflux

On pourrait certainement construire depuis Facebook un modèle prédictif permettant de prédire quand un utilisateur risque de prendre de la drogue selon l’évolution de ses centres d’intérêt et les relations qu’il développe. Mais comment délivrer et utiliser cette information ?

Source : Big Data, de la prédiction à l’intervention | InternetActu

7 octobre 2016 / noflux

Big law firms are pouring money into AI as a way of automating tasks traditionally undertaken by junior lawyers. Many believe AI will allow lawyers to focus on complex, higher-value work. An example is Pinsent Masons, whose TermFrame system emulates the decision-making process of a human. It was developed by Orlando Conetta, the firm’s head of R&D, who has degrees in law and computer science and did an LLM in legal reasoning and AI. TermFrame guides lawyers through different types of work while connecting t

Source : Artificial intelligence disrupting the business of law

6 octobre 2016 / noflux

Il faudrait toutefois être fortement naïf pour y voir autre chose qu’une tentative plus ou moins subtile de prendre le contrôle du débat public sur l’intelligence artificielle, pour fixer eux-mêmes les limites éthiques à ne pas franchir, et celles qui ne poseraient pas de problèmes.

Source : IA : Pourquoi Apple ne se joint pas au lobby de Facebook, Microsoft et Google – Business – Numerama

2 octobre 2016 / noflux

At SONY CSL Research Laboratory, we have created two entire pop songs composed with Artificial Intelligence, thanks to Flow Machines. How is it possible? That’s because our Flow Machines software learns music styles from a huge database of songs. Then, exploiting unique combinations of style transfer, optimization and interaction techniques, it can compose in any style.French composer Benoît Carré arranged and produced the songs, and wrote the lyrics.

Source : AI makes pop music in different music styles

25 septembre 2016 / noflux

Excitingly, our model does indeed develop the ability to generate accurate new captions when presented with completely new scenes, indicating a deeper understanding of the objects and context in the images. Moreover, it learns how to express that knowledge in natural-sounding English phrases despite receiving no additional language training other than reading the human captions.

Source : Research Blog: Show and Tell: image captioning open sourced in TensorFlow

2 septembre 2016 / noflux

For English, speech recognition was three times faster than typing, and the error rate was 20.4 percent lower. In Mandarin Chinese, speech was 2.8 times faster, with an error rate 63.4 percent lower than typing.

Source : Speech recognition faster at texting | Stanford News

28 août 2016 / noflux

If AI learns language sufficiently well, it will also learn cultural associations that are offensive, objectionable, or harmful. At a high level, bias is meaning. “Debiasing” these machine models, while intriguing and technically interesting, necessarily harms meaning.

Source : Language necessarily contains human biases, and so will machines trained on language corpora

28 août 2016 / noflux

According to sources, the Trending team’s editorial staff were alerted at 4pm that they were being fired—as the news of Facebook’s switch to algorithms first broke—and were asked to leave the building by 5pm.

However, removing human writers from Trending doesn’t necessarily eliminate bias. Human bias can be embedded into algorithms, and extremely difficult to strip out.

Source : Facebook (FB) fired its Trending editors, apparently trying to get rid of bias by getting rid of humans — Quartz

25 juillet 2016 / noflux

Our machine learning system was able to consistently achieve a 40 percent reduction in the amount of energy used for cooling, which equates to a 15 percent reduction in overall PUE overhead after accounting for electrical losses and other non-cooling inefficiencies. It also produced the lowest PUE the site had ever seen.

Source : Google DeepMind

Étiquette : machine learning (Page 9 of 10)

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