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sentinelle : ai   20

If My AI Wrote this Post, Could I Own the Copyright? - The Scholarly Kitchen
In the most novel of cases, machine learning algorithms do not simply regurgitate the best compilation of the input, but instead generate a new outcome based on the training. Some have argued that by exposing the AI to the world of content to derive new approaches is most like how humans are exposed to art, reading, and cultural styles in developing their own voices. Some are concerned that machine reading is simply a way to ingest and utilize authors’ works without due compensation, particularly as the machine is generating new works based on original works.

In the Copyright Office’s Compendium of U.S. Copyright Office Practices, released on 22 December, 2014, the Office stated that, “only works created by a human can be copyrighted under United States law, which excludes photographs and artwork created by animals or by machines without human intervention” and furthermore, “Because copyright law is limited to ‘original intellectual conceptions of the author,’ the [copyright] office will refuse to register a claim if it determines that a human being did not create the work. The Office will not register works produced by nature, animals, or plants.”  What is left open to wide interpretation is the role of human intervention. In the case of AI, so the argument goes, there is human intervention in the design of the algorithms, in their training, and in their post-algorithm curation.
IA  AI  copyright  propriété  intellectuelle  IP  droit  d'auteur  Todd  A  Carpenter 
6 weeks ago by sentinelle
The State of AI Adoption - High Performers Show the Way
Overall, 63% report revenue increases in the business unit where the AI use case is deployed.  Revenue growth is highest in marketing and sales, - pricing, prediction of likelihood to buy, and customer-service analytics; in product and service development, - creating new AI-based products and enhancements; and in supply-chain management, - sales and demand forecasting, and spend analytics.  At the same time, 44% report cost savings in the business units where the AI use case is deployed.  Cost decreases are highest in manufacturing, - yield, energy and throughput optimization; and in supply-chain management, - spend analytics, and logistics-network optimization.

AI high performers had significantly higher revenue increases and cost reductions, - being nearly three times likelier than other companies to report revenue gains of more than 10%, and more than four times likelier to report cost reductions of at least 10%.
AI  IA  intelligence-artificielle 
7 weeks ago by sentinelle
Five ways book publishers can take advantage of artificial intelligence — BookNet Canada
Artificial intelligence (AI) is quickly becoming an essential part of modern business and can assist publishers on many levels from enhancing discoverability through precise keywords to helping optimize marketing and sales plans. AI can also automate complicated processes, such as finding comps, simplifying the task to take just a matter of minutes.

Here are five easy ways book publishers can integrate (and are already integrating) AI into their everyday decision-making.
AI  IA  édition  Monica  Landers 
8 weeks ago by sentinelle
How Are Artificial Intelligence, Big Data and Machine Learning Used in Publishing as of Today ?
Is artificial intelligence coming? That’s the wrong question. Because there are already countless – often unnoticed – examples for the use of AI. On 9 and 10 May in Berlin, the Publishers’ Forum will present two approaches to this mega-trend – Early Bird rates available until Feb 2019.

Discussion points include:

Which questions and problem areas can the use of AI already provide solutions for that are suitable for everyday use?
Which practical examples in the publishing industry demonstrate how we can already benefit from the use of AI here and now?
IA  AI  BigData  MachineLearning  Berlin  PublishersForum  conférence 
february 2019 by sentinelle
The Internet Of Things (IOT) Will Be Massive In 2018: Here Are The 4 Predictions From IBM
As more and more devices become connected and capable of speaking to each other, AI – deep learning, natural language processing, image recognition and neural-network driven decision-making – will help them to understand each other, and us.

“In the early days you could do IoT in your home in a lot of different ways and there were a lot of wires and a lot of hard-code – mobile apps came later, but it was still an isolated experience that doesn’t really feel connected”, Greenstein tells me.

“AI is helping to bridge that gap – now we are seeing automakers and hotels and other companies trying to create more integrated experiences and using AI to better understand and interact with people.”
IoT  AI 
january 2018 by sentinelle
Can 10,000 Humans Clean Up YouTube? - MIT Technology Review
Clearly, AI is not yet enough. That message appears to be being reiterated by YouTube’s CEO, Susan Wojcicki. In a new blog post, she explains that the video site is swelling its moderation team to include 10,000 staff across Google to help battle objectionable content.

What will they do? To a large extent, more of the same. “Since June, our trust and safety teams have manually reviewed nearly 2 million videos for violent extremist content,” she writes. “We are also taking aggressive action on comments, launching new comment moderation tools and in some cases shutting down comments altogether.”

But Wojcicki also points out that all the work has another use: training AIs. “Human judgment is critical to making contextualized decisions on content,” she writes, adding that by collecting data about how its moderators work, YouTube will be able to “train ... machine-learning technology to identify similar videos in the future.”

If this all sounds familiar, well, that’s because Facebook added 3,000 extra content policers itself earlier this year. At the time, we argued that extra people alone, without robust and reliable AI, would be unlikely to make much of a dent in offensive content—because there’s so damn much of it to sift through.

In YouTube’s case, with 300 hours of footage uploaded every minute, it seems equally unlikely to succeed—at least until its algorithms have learned all they need from the meatspace moderators.
AI  YouTube  modération 
december 2017 by sentinelle
How Are Retailers Using Artificial Intelligence? | eMarketer Retail
Artificial intelligence (AI) adoption is still limited, but among retail marketers who do employ the technology, many use it in their search or recommendation engines.

A January 2017 survey from Sailthru, which aggregates and analyzes user data sets for companies to create personalized customer experiences, polled retail marketers in Canada, the UK and the US about how they use AI to accomplish their goals. Respondents were primarily from ecommerce retailers, but included retailers with ecommerce and physical retail locations.

The largest share of retail marketers using AI—over a third—said they use it in search efforts. Nearly as many said they do so in recommendation engines for their products or content.

Meanwhile, more than a quarter reported using AI in their programmatic advertising efforts, and another 13% in chatbot efforts.
AI  survey  sondage  usage  revendeurs  eMarketing  intelligence-artificielle 
september 2017 by sentinelle
6 practical guidelines for implementing conversational AI - O'Reilly Media
“Many people still have a misperception of bots just as speaking or typing,” says Chris Mullins of Microsoft. In fact, there are various ways (or modalities) that bots can use to interact with and convey information:

Speech (Alexa, Siri, Google Home)
Typing (bots in messaging apps)
Keyboard support that provides cues that narrow the range of input options
Cards that display the information visually
“In most successful scenarios,” says Mullins, “we see a mix of modalities win. At the right time, spoken language is perfect. At another time, typing may be perfect. Sometimes you want cards or keyboard support. Conversational modeling is a phenomenally hard problem, and no one has gotten it quite right yet.”
IA  AI  chatbots  interaction  conversationnel  assistants  personnels  Alexa  Siri  Cortana  GoogleHome 
august 2017 by sentinelle
AI versus machine learning: what's the difference? | WIRED UK
“AI is basically the intelligence – how we make machines intelligent, while machine learning is the implementation of the compute methods that support it. The way I think of it is: AI is the science and machine learning is the algorithms that make the machines smarter.

“So the enabler for AI is machine learning,” she added.

Chappell went on to explain that machine learning is the fastest growing part of AI, so that’s why we are seeing a lot of conversations around this lately. Even though it’s a small percentage of the workloads in computing today, it’s the fastest growing area, so that’s why everyone is honing in on that.
AI  MachineLearning 
july 2017 by sentinelle
Apple announces new machine learning API to make mobile AI faster - The Verge
Like the rest of the tech world, Apple wants to make AI on your mobile device as fast and powerful as possible. That’s why the company unveiled a new machine learning framework API for developers today named Core ML.

The key benefit of Core ML will be speeding up how quickly AI tasks execute on the iPhone, iPad, and Apple Watch. This could cover everything from text analysis to face recognition, and should have an effect on a broad category of apps. It means, says Apple, that image recognition on the iPhone will be six times faster than on Google’s Pixel.

Core ML will support a number of essential machine learning tools, including all sorts of neural networks (deep, recurrent, and convolutional), as well as linear models and tree ensembles. And because this is Apple, there’s also a privacy focus, too — Core ML is for on-device processing, meaning the data that developers use to improve user experience won’t leave customers’ phones and tablets.
IA  AI  Intelligence-artificielle  CoreML  API 
june 2017 by sentinelle
[I/O 2017] Lens, Assistant, Home, Android O... Ce qu’il faut retenir de la keynote d’ouverture de Google
De "mobile first", Google est définitivement passé à l’ère de l’ "AI first". Sur la scène du Shoreline Amphitheatre, Sundar Pichai, le PDG d’Alphabet (société-mère de Google) a commencé par montrer les muscles en dévoilant une ribambelle de (gros) chiffres : 2 milliards de devices sous Android, un milliard de vidéos visionnées chaque heure sur Youtube, 800 millions d’utilisateurs sur Google Drive et 1,2 milliard de photos ajoutées au quotidien à Google Photos.
"Nous avons repensé tous nos produits en incluant l’intelligence artificielle", a déclaré Sundar Pichai. Dernier exemple en date : les smart reply (suggestion de réponses intelligentes) intégrées à Gmail, la messagerie Google au milliard d’utilisateurs. Le patron du géant de la tech a ensuite annoncé le lancement de, une plateforme dédiée aux développeurs afin que ces derniers intègrent l’IA de Google à leurs applications.
fr  google  AI  I/O  Home  IA  keynote  Lens  Assistant  Androïd 
may 2017 by sentinelle
Amazon envahit le monde avec son intelligence artificielle Alexa
Alexa, l'assistant personnel d'Amazon, est devenu une pieuvre tentaculaire capable comme dans les contes de changer de forme comme bon lui semble. Cette solution basée sur la reconnaissance vocale est intégrée dans plus d'une centaine d'objets connectés fabriqués par des constructeurs tiers. Le Consumer Electronics Show de Las Vegas, qui s'est déroulé en janvier dernier, a permis à de multiples entreprises d'annoncer des partenariats avec le géant du e-commerce : Whirlpool, Lenovo et LG utilisent par exemple le système pour commander respectivement leurs lave-linge, enceintes et réfrigérateurs communicants. L'ensemble des véhicules de Ford équipés du système d'information Sync 3 seront équipés d'Alexa cet été. L'assistant pourra lire des livres aux occupants de la voiture ou encore ouvrir les portes de leur garage à la demande
fr  amazon  IA  AI  Alexa  IoT 
april 2017 by sentinelle
AI Literacy: The basics of machine learning – World Writable
“What are the differences between artificial intelligence, machine learning, neural networks, and deep learning?”
These are all real terms with distinct meanings but are often used interchangeably. I actually think that’s fine in most contexts, but the distinctions can help you understand where the industry has been and where it’s going.
AI  intelligence-artificielle  Liza-Daily  MachineLearning 
april 2017 by sentinelle
DeepMind Finds Way to Overcome AI’s Forgetfulness Problem - Bloomberg
DeepMind, the London-based artificial intelligence company owned by Alphabet Inc., claims it overcame a key limitation affecting one of the most promising machine learning technologies: the software’s inability to remember.

The breakthrough, described in a paper published Tuesday in the academic journal Proceedings of the National Academy of Sciences, may open the way for artificial intelligence systems to be more easily applied to multiple tasks, instead of being narrowly trained for one purpose. It should also improve the ability of AI systems to transfer knowledge between tasks and to master a sequence of linked steps.
DeepMind  AI 
march 2017 by sentinelle
AI is the Future of IoT - Disruption
This is where artificial intelligence (AI) has an important role to play. Organizations are beginning to employ these technologies as a means of unlocking the value from large volumes of digital data. AI systems can rapidly consume vast quantities of structured and unstructured data, and give it meaning by creating models of entities and concepts, and the relationships among them. They generate hypotheses, formulate possible answers to questions, and provide predictions and recommendations, which can be used to augment human intelligence and decision making. The new IBM “Cognitive Advantage” study reveals that nearly six in ten early adopters regard AI as a “must have” to remain competitive within the next few years.
AI  IA  data  intelligence-artificielle 
january 2017 by sentinelle
AI is the new UI ? Non, je ne pense pas ! |
En ce moment, il ne se passe pas un jour sans que j’entende parler d’intelligence artificielle, de machine learning, d’algorithmes auto-apprenant… Si les avancées technologiques dans ces domaines sont indéniables, j’ai l’impression que nous atteignons un point de saturation. Je suis tombé récemment sur une citation qui me fait grincer des dents : « AI is the new UI« . Martelé comme des punchlines, ce genre d’assertion est non seulement erroné, mais en plus très néfaste pour l’industrie. J’aurais pu réagir sur Twitter, mais le sujet est complexe et mérite des explications précises. De plus, nous touchons ici du doigt LE gros enjeu de 2017 : la compréhension de toutes ces nouvelles technologies.
AI  UI  machine-learning 
december 2016 by sentinelle
Artificial Intelligence Integration Allows Publishers a First Look at Meta Bibliometric Intelligence - Aries Systems Corporation
Bibliometric Intelligence uses sophisticated machine learning algorithms that were trained using Meta’s corpus of millions of full-text articles – a collection that now comprises the largest scholarly text-mining collection on Earth. As newly-submitted manuscripts are processed, hundreds of unique features are pulled from the papers and fed through the algorithms. Based on this analysis, Meta estimates the future citation count and impact of a manuscript, with a speed, accuracy, and consistency that far exceed human ability.

Large-scale trials conducted by Meta in partnership with industry demonstrated that Bibliometric Intelligence out-performed tens of thousands of human editors by a factor 2.5x at predicting article-level impact for new manuscripts, prior to publication. It also performed 2.2x better than the same group of editors at identifying “superstar articles” – those that represent the top 1% of high-impact papers, prior to publication.
IA  AI  Meta  AriesSystems  bibliométrique  intelligence  manuscript  machine  learning 
october 2016 by sentinelle
Pearson in 'virtual tutor' partnership | The Bookseller
Pearson has announced a global education partnership with computing platform IBM Watson Education to give college students "a more immersive learning experience."

The collaboration will see Pearson's online courses embedding adaptive learning technology to offer a "virtual tutor" that has the ability to engage in "natural" conversation with students to help them with coursework.

The virtual tutor can ask questions, guide students with hints, and give feedback and explanations about key concepts. It also provides instructors insights about when and where their students are struggling the most, allowing them to better manage the course and flag students who need help. 

The feature is being piloted in 2017 with the potential to be rolled out thereafter.
bots  watson  ibm  Pearson  AI  tuteur  virtuel  bot 
october 2016 by sentinelle
Getting Next-Gen Messaging based experiences — to work — Medium
Without these two fundamental Human-Machine inter-connections (memory and multi-sentences) AIs will never understand Context and give us what we really WANT.
I don’t want to have to say (explicitly):
Let’s contact Ted and see if he wants to have lunch today
Lets decide where to eat lunch today
Lets see if there’s a table at Ivy’s for lunch — today
Lets book that table — for 12:30 — today
Now lets let Ted know that we got a table at Ivy’s and confirm that booking with him
I just wanna say:
“Hey Ted — wanna do lunch today?”
“Ivy’s is coolio, see you there……”
Combining more than one sentence in a ChatBot query and having some sort of memory is the Holy Grail of AI and Viv is the only platform out there that can do that!
Viv is the new Next-Gen AI “Virtual Assistant” platform — coming from the same folks who created Siri. They know exactly what Siri can and can’t do ‘cause Steve Jobs had them take OUT a whole bunch of stuff so they could ship Siri!
Viv  Siri  AI  intelligence  artificelle  bots  interaction 
may 2016 by sentinelle
“Georgia Tech Uses Artificial Intelligence to Crowdsource Interactive Fiction” | LJ INFOdocket
Georgia Institute of Technology researchers have developed a new artificially intelligent system that crowdsources plots for interactive stories, which are popular in video games and let players choose different branching story options. “Our open interactive narrative system learns genre models from crowdsourced example stories so that the player can perform different actions and still receive a coherent story experience,” says Mark Riedl, lead investigator and associate professor of interactive computing at Georgia Tech. A test of the AI system, called Scheherazade IF (Interactive Fiction) — a reference to the fabled Arabic queen and storyteller – showed that it can achieve near human-level authoring. (...) The creators say that they are seeking to inject more creative scenarios into the system. Right now, the AI plays it safe with the crowdsourced content, producing what one might expect in different genres.
GeorgiaTech  AI  fiction  interactivité  innovation  narration  crowdsourcing 
september 2015 by sentinelle

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