If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
BRUSSELS – The EU's proposal for a temporary ban on facial-recognition technology won backing from Alphabet Chief Executive Sundar Pichai on Monday but got a cool response from Microsoft President Brad Smith. While Pichai cited the possibility that the technology could be used for nefarious purposes as a reason for a moratorium, Smith said a ban was akin to using a meat cleaver instead of a scalpel to solve potential problems. "I think it is important that governments and regulations tackle it sooner rather than later and give a framework for it," Pichai told a conference in Brussels organized by think-tank Bruegel. "It can be immediate but maybe there's a waiting period before we really think about how it's being used," he said. "It's up to governments to chart the course" for the use of such technology.
ActionAI is a python library for training machine learning models to classify human action. It is a generalization of our yoga smart personal trainer, which is included in this repo as an example. These instructions will show how to prepare your image data, train a model, and deploy the model to classify human action from image samples. See deployment for notes on how to deploy the project on a live stream. We recommend using a virtual environment to avoid any conflicts with your system's global configuration.
We are embarking on a project that will empower our global community with machine learning ready training and validation datasets for air quality applications around the world. We are sending this very short questionnaire that we believe should take about 2 to 3 minutes to complete to get some feedback from various stakeholders including scientists, machine learning experts, data scientists and providers, end-users, educators, and students. We thank you in advance for participating in this survey.
Using one of your examples, for me the symbolic constraints for OCR of printed source code seem conceptually similar to how standard OCR systems implement the split between the character OCR model (which provides the probabilities of individual characters) and the language model (which provides the probabilities of long combined sequences of possible alternative characters) - any symbolic rules and constraints could be integrated straight into the language model, by adding an extra penalty to the likelihood of sequences that don't match some rule. The algorithms to effectively explore the solution space in this manner (often some form of beam search) already exist and would be already implemented and tested in an OCR system, so the symbolic rules would just change how the cost function is calculated.
Some tech CEOs run the show but don't really understand the nuts and bolts of the company's product. Riveiro is the CEO of Vilynx (pronounced "VEE-links"), a firm which uses artificial intelligence (AI) and machine learning to help media companies make video "smarter." To date, the Spanish company has received about $15 million in funding from European and North American venture capital and angel investors. Vilynx has offices in Barcelona, Palo Alto and New York City. This interview has been edited for brevity and clarity.
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This year marks the 30th anniversary of the adoption of the Convention on the Rights of the Child (CRC). As the global community reflects on progress made to date, one change from the world of 1989 will significantly impact the next 30 years for children's rights: artificial intelligence (AI). Recent progress in the development of AI systems are expected to profoundly influence life and work in the 21st century, raising both hopes and concerns for human development. As UNICEF explores the many compelling reasons to use AI for children's development (such as education, health and social welfare), it is also concerned about a world in which AI remains unchecked. AI systems, often working as "black boxes", raise issues of privacy, accountability, recourse and exclusion, particularly for those who are least aware of their rights in the digital age: children.
Smart is a word in transition. Once almost exclusively applied to human (and some animal) intelligence, today everything and anything is called "smart." With the growing field of AI (artificial or augmented intelligence) predicting self-learning inanimate objects, smart might be a minimum term with genius close behind. In construction, the application of computer technology to every facet of the trade is achieving inroads at companies large and small. But the focus is now turning to the implementation and installation of smart technology in the actual buildings.
To accelerate the Agrifood industry transformation using A.I., Danone and Microsoft are launching together the AI Factory for Agrifood - a 3 months accelerator program for innovative AI based solutions. Created by Microsoft in partnership with the Inria laboratory, the AI Factory program unites a community of startups dedicated to the development of innovative solutions based on Artificial Intelligence. At Danone, our vision is that the health of people and the health of the planet are interconnected. This program is a call for entrepreneurs and innovators to join the food revolution and build together a more sustainable food system. If you want to join this community and benefit from Microsoft and Danone expertise, please fill out this application form and make sure to complete the requested information accurately.
Studying how people move to music is a powerful tool for researchers looking to understand how and why music affects us the way it does. Over the last few years, researchers at the Centre for Interdisciplinary Music Research at the University of Jyväskylä in Finland have used motion capture technology -- the same kind used in Hollywood -- to learn that your dance moves say a lot about you, such as how extroverted or neurotic you are, what mood you happen to be in, and even how much you empathize with other people. Recently, however, they discovered something that surprised them. "We actually weren't looking for this result, as we set out to study something completely different," explains Dr. Emily Carlson, the first author of the study. "Our original idea was to see if we could use machine learning to identify which genre of music our participants were dancing to, based on their movements."