Virginia Commonwealth University School of the Arts in Qatar (VCUarts Qatar) is hosting a lecture by Dr James She from Hong Kong University of Science and Technology (HKUST), titled, 'AI and Smartphone Technologies for New Artwork Creation, Interaction and Definition'. The lecture will take place this Tuesday, 18 February, 12:30 pm, at the VCUarts Qatar Atrium. The event is open to everyone. Emerging Artificial Intelligence (AI) and smartphone technologies are making disruptive changes and new possibilities for people in business, manufacturing, travel, education and even art. In this talk, examples of AI and smartphone technologies will be selected to show how recent developments in those technologies could facilitate the creation of, and interaction with, artworks.
Artificial intelligence--code that learns--is likely to be humankind's most important invention. It's a 60-year-old idea that took off five years ago when fast chips enabled massive computing and sensors, cameras, and robots fed data-hungry algorithms. We're a couple of years into a new age where machine learning (a functional subset of AI), big data and enabling technologies are transforming every sector. In every sector, there is a big data set behind every question. Every field is computational: healthcare, manufacturing, law, finance and accounting, retail, and real estate.
AI has been one of the biggest buzzwords in the technology industry over the past few years, given its immense potential to transform our world. With more tasks being performed with AI, the enterprise adoption of this nascent technology is rapidly evolving. From business planning and forecasting to predictive maintenance and customer service, AI is now an intrinsic part of an enterprise ecosystem. The potential of AI is limitless, but certain barriers are holding traditional large enterprises back from embracing AI in a big way. These include factors such as the absence of a clear strategy, lack of data, skills shortage, and functional silos within the organization.
In Washington, DC, where big decisions are made daily, an assembly of executives, data scientists and analytics professionals will gather for the world's premier analytics conference, SAS Global Forum. During the event, March 29 through April 1, these analytics enthusiasts will share insights and learn how analytics and artificial intelligence (AI) help businesses make better, faster decisions that improve lives around the globe. This year's conference will transform the Walter E. Washington Convention Center into an interactive analytics showcase. Featuring more than 600 sessions from leading organizations across industries, SAS Global Forum also includes hands-on workshops, e-learning, training, demos and networking opportunities, all designed to empower users and executives to "Do Great Things," this year's theme. Now in its 44th year, SAS Global Forum showcases the technologies and industry topics that analytics professionals most want on the agenda.
We're experiencing a profound shift in how educational content is created and delivered. Online education platforms are flourishing, and a recent Pew Research poll shows the world's leading video platform YouTube has finally become more than a repository of cat videos -- about half of YouTube users say it's very important for helping them figure out how to do things they've never done before. The year 2019 saw unprecedented growth in YouTube educational content on artificial intelligence. Synced has selected 10 AI-oriented YouTube channels we hope might provide our readers a cozy little holiday binge-watching session. Preserve Knowledge focuses on advances in mathematics, computer science, and artificial intelligence.
Here on Codementor I usually see lots of students and developers trying to get into Machine Learning confused with complicated topics they are facing at the very beginning of their journey. I want to make a deep yet understandable introduction to the algorithm which is so simple and elegant that you would like it. If you are a Machine Learning engineer but have a limited understanding of this one, it could be also useful to read it. I was working as a software developer for years and everyone around me was talking about this brand new data science and machine learning thing (I understood that there is nothing new on this planet later), so I've decided to take masters studies in the University to get known to it. Our first module was a general introductory course to Data Science and I remember myself sitting and trying to understand what's going on.
I recently asked the Twitter community about their biggest machine learning pain points and what work their teams plan to focus on in 2020. One of the most frequently mentioned pain points was deploying machine learning models. More specifically, "How do you deploy machine learning models in an automated, reproducible, and auditable manner?" The topic of ML deployment is rarely discussed when machine learning is taught. Boot camps, data science graduate programs, and online courses tend to focus on training algorithms and neural network architectures because these are "core" machine learning ideas.
So we don't have to construct the actual algorithms used to process data and train models. However, there's still a level of math that you have to grapple with when dabbling in Machine Learning. You need to first be able to process data to pass into ML algorithms and models. You also need to have some knowledge of ML framework settings and configuration. Most of the work done by data scientists is involved in preparing the data.
It seems that every year Google plans to shock the artificial intelligence(AI) world with new astonishing progress in natural language understanding(NLU) systems. Last year, the BERT model definitely stole the headlines of the NLU research space. Just a few weeks into 2020, Google Research published a new paper introducing Meena, a new deep learning model that can power chatbots that can engage in conversations about any domain. NLU has been one of the most active areas of research of the last few years and have produced some of the most widely adopted AI systems to date. However, despite all the progress, most conversational systems remain highly constrained to a specific domain which contrasts with our ability as humans to naturally converse about different topics.
The Open University is the UK's largest university, a world leader in flexible part-time education combining a mission to widen access to higher education with research excellence, transforming lives through education. We are seeking to appoint a Lecturer or Senior Lecturer in Artificial Intelligence to join the School of Languages and Applied Linguistics. The candidate will work in one or more of the topics of central importance to the School of Languages and Applied Linguistics, with special attention to workplace communication and/or the interface between social media and AI. The successful candidate will have a master's degree or equivalent in linguistics or a related field, at Senior Lecturer level you will also have a PHD or equivalent in interactional linguistics, preferably ethnomethodological conversation analysis and/or interactional linguistics. Evidence of an emerging research profile in AI and human communication is also essential for this post.