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"Il faut aujourd'hui seulement 3,7 secondes d'audio afin de cloner votre voix. Cette annonce impressionnante mais aussi quelque peu inquiétante a été émise par le géant chinois de la tech Baidu. Il y a un an, l'outil de cette entreprise appelé Deep Voice nécessitait 30 minutes d'audio afin de pouvoir cloner une voix humaine. Les prouesses de l'intelligence artificielle permettent désormais une évolution technologique de plus en plus réaliste."

récap du CES Asia 12'08 Baidu smart speaker avec voix + caméra + écran + paiement via reconnaissance faciale + détection émotions + télé-médecine

Révélations des conditions de travail et des pratiques des micros travailleurs pour Apple et Siri. Ces témoignages révèlent qu'Apple écoute ses usagers à leur insu et des conditions de travail précaires et de traumatismes.

"La société de Jeff Bezos pense avoir la solution pour améliorer les compétences de son assistant vocal. Les utilisateurs d'Alexa vont être être mis à contribution et peuvent désormais aider les équipes d'Amazon à faire progresser l'intelligence artificielle. Ce nouveau programme s'appelle Alexa Answers et donne la possibilité aux utilisateurs de répondre eux-mêmes aux questions d'autres utilisateurs." [...] "Pour encourager les réponses, Amazon récompensera les contributeurs avec des points et leur permettra de concourir pour obtenir le statut de « premier contributeur ». Génial…" > digital labor https://www.fastcompany.com/90402924/exclusive-amazon-will-let-anyone-answer-your-alexa-questions-now

un panorama sur le travail des invisibles, nouveau prolétariat des plateformes.Et en particulier le travail derrière l'IA. Faut il adapter le droit du travail à ces nouvelles pratiques, comme créer un nouveau statut pour ce type d'emploi et/ou introduire de la négociation collective, du dialogue social dans ces plateformes (Facebook Google Amazon)

"Some companies and scientists present Affective Computing, the algorithmic analysis of personality traits also known as "artificial emotional intelligence", as an important new development. But the methods that are used are often dubious and present serious risks for discrimination. It was announced with some fanfare that Alexa and others would soon demonstrate breakthroughs in the field of emotion analysis. Much is written about affective computing, but products are far from market ready. For example, Amazon's emotion assistant Dylan is said to be able to read human emotions just by listening to their voices. However, Dylan currently only exists in form of a patent. So far, Amazon, Google et al. have not launched such products. Identifying unique signals that indicate that someone is sad seems to be a bit more complicated than they initially thought. Maybe someone's voice sounds depressed because they are depressed, but maybe they are just tired or exhausted. However, these difficulties do not prevent other companies from launching products that claim to have solved these complex problems by using voice and speech for character and personality analysis." > One is the company Precire, based in Aachen, a city on border with Belgium. Their idea: you record a voice sample, and based on the person's choice of words, sentence structure and many other indicators, the software then produces an analysis of their character traits. The software can be used in staff recruitment or to identify candidates for promotion. > critique de la méthode : biais, discrimination...

Réflexion sur la mélancolie des machines, le fantasme de l'IA, installation artistique. (présenté à la Biennale Numérique Paris 19-20)

"In a recent paper that made waves in the ML community, a team at the University of Massachusetts, Amherst, found that training a model for natural-language processing - the field that helps "virtual assistants" like Alexa understand what you're saying - can emit as much as 626,155lb of carbon dioxide. That's about the same amount produced by flying roundtrip between New York and Beijing 125 times." "When it comes to ML, a group of researchers are calling for a more energy-conscious approach, which they call "Green AI". "

"In the past year, natural language models have become dramatically better at the expense of getting dramatically bigger. [...] In response, many researchers are focused on shrinking the size of existing models without losing their capabilities. [...] In addition to improving access to state-of-the-art AI, tiny models will help bring the latest AI advancements to consumer devices. They avoid the need to send consumer data to the cloud, which improves both speed and privacy. For natural-language models specifically, more powerful text prediction and language generation could improve myriad applications like autocomplete on your phone and voice assistants like Alexa and Google Assistant."

"Julie est micro travailleuse et elle a entraîné Cortana, l'assistant vocal de Microsoft. Nassim lui, était livreur pour Deliveroo et son temps de travail était décidé par un algorithme. Deux histoires de micro travailleurs précaires qui posent d'importants problèmes éthiques."

"The creator of the famous voice assistant dreams of a world where Alexa is everywhere, anticipating your every need." "The crux of the plan is for the voice assistant to move from passive to proactive interactions. Rather than wait for and respond to requests, Alexa will anticipate what the user might want. The idea is to turn Alexa into an omnipresent companion that actively shapes and orchestrates your life. This will require Alexa to get to know you better than ever before." "From a technical perspective, all this would be an incredible achievement. " "From a consumer's perspective, however, these changes also have critical privacy implications. " "Prasad's vision effectively assumes Alexa will follow you everywhere, know a fair bit about what you're up to at any given moment, and be the primary interface for how you coordinate your life. At a baseline, this requires hoovering up enormous amounts of intimate details about your life. Some worry that Amazon will ultimately go far beyond that baseline by using your data to advertise and market to you. "This is ultimately about monetizing the daily lives of individuals and groups of people," says Jeffrey Chester, the executive director of the Center for Digital Democracy, a consumer privacy advocacy organization based in Washington, DC."

"Emotion-classifying AI isn't anything new, but traditional approaches are supervised, meaning that they ingest training data labeled according to speakers' emotional states. Scientists at Amazon took a different approach recently, which they describe in a paper scheduled to be presented at the International Conference on Acoustics, Speech, and Signal Processing. Rather than sourcing an exhaustively annotated "emotion" corpus to teach a system, they fed an adversarial autoencoder a publicly available data set containing 10,000 utterances from 10 different speakers. The result? The neural network was up to 4% more accurate at judging valence, or emotional value, in peoples' voices." https://developer.amazon.com/fr/blogs/alexa/post/2d8c2128-eec9-44cc-9274-444940eb0a4d/using-adversarial-training-to-recognize-speakers-emotions

"In a free service, bots call restaurants and make reservations. The technology is impressive, except for when the caller is actually a person." "In other words, Duplex, which Google first showed off last year as a technological marvel using A.I., is still largely operated by humans. While A.I. services like Google's are meant to help us, their part-machine, part-human approach could contribute to a mounting problem: the struggle to decipher the real from the fake, from bogus reviews and online disinformation to bots posing as people." "Google's A.I. is eerily human, when it works" "Duplex needs lots of data to improve" "Duplex is proficient at making a restaurant reservation over the phone, but much like Facebook, Google still leans on human intelligence. At any given moment, it is lifelike. But it struggles to deal with the unexpected. "There are three things that are important when it comes to A.I.'s interactions with humans: context, context and context," said Jerry Kaplan, author of "Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence" and a Stanford University lecturer on artificial intelligence. "Machines are very good with detail but terrible at context," he said."

Les chercheurs de la start-up d'intelligence artificielle Dessa ont créé une réplique de la voix de Joe Rogan, célèbre podcasteur américain. "La start-up précise que son modèle pourrait potentiellement reproduire la voix de n'importe qui, à condition que suffisamment de données soient disponibles. " "Bien que cette technologie présente des avantages, la start-up a décidé de ne pas la rendre accessible au public. Il en est de même pour ses recherches. En effet, pour l'entreprise, une simulation de voix aussi perfectionnée est susceptible d'être exploitée à des fins malveillantes." "Du côté des avantages, Dessa indique tout de même que sa technologie pourrait permettre de créer des assistants vocaux plus réalistes. Il serait également possible de concevoir des voix synthétiques réalistes et personnalisées pour les personnes atteintes de troubles de la parole. "