"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.

I'm going to lead with the punchline on this one. I believe that LPI should invest in providing a certification path for some kind of machine learning, specifically geared to open source development in artificial intelligence. Whatever you may think about automation and artificial intelligence from the perspective of what it will eventually mean for humanity, there's no question that some form of artificial intelligence is present in every aspect of our lives. Those of us who own one or more Google Home or Alexa speakers know full well how much AI touches our lives. Smart systems like Google's Assistant are built using TensorFlow ( https://tensorflow.org), an open source programming library that has become a kind of goto set of tools for anyone building machine learning, deep learning, natural language processing (as in your smart speaker), or neural network based applications.

Yoshua Bengio is recognised as one of the world's leading experts in artificial intelligence and a pioneer in deep learning. Following his studies in Montreal, culminating in a PhD in computer science from McGill University in 1991, Professor Bengio did postdoctoral studies at the Massachusetts Institute of Technology (MIT) in Boston. In 2019, he was awarded the Killam Prize as well as the 2018 Turing Award, considered to be the Nobel prize for computing. These honours reflect the profound influence of his work on the evolution of our society. Yoshua Bengio is also known for collecting the largest number of new citations in the world in the year 2018.

In this episode I have a conversation with Filip Piękniewski, researcher working on computer vision and AI at Koh Young Research America. His adventure with AI started in the 90s and since then a long list of experiences at the intersection of computer science and physics, led him to the conclusion that deep learning might not be sufficient nor appropriate to solve the problem of intelligence, specifically artificial intelligence. I read some of his publications and got familiar with some of his ideas. Honestly, I have been attracted by the fact that Filip does not buy the hype around AI and deep learning in particular. He doesn't seem to share the vision of folks like Elon Musk who claimed that we are going to see an exponential improvement in self driving cars among other things (he actually said that before a Tesla drove over a pedestrian). I have a somewhat complex love and hate relationship with deep learning.

Thomas Bayes (/beɪz/; c. 1701 – 7 April 1761)[2][3][note 1] was an English statistician, philosopher and Presbyterian minister who is known for formulating a specific case of the theorem that bears his name: Bayes' theorem. Bayes never published what would become his most famous accomplishment; his notes were edited and published after his death by Richard Price.[4] Thomas Bayes was the son of London Presbyterian minister Joshua Bayes,[5] and was possibly born in Hertfordshire.[6] He came from a prominent nonconformist family from Sheffield. In 1719, he enrolled at the University of Edinburgh to study logic and theology. On his return around 1722, he assisted his father at the latter's chapel in London before moving to Tunbridge Wells, Kent, around 1734.

Kevin Warwick is Emeritus Professor at Reading and Coventry Universities. Prior to that he was Deputy Vice Chancellor (Research) at Coventry University, England. His main research areas are artificial intelligence, biomedical systems, robotics and cyborgs. Due to his research as a self-experimenter he is frequently referred to as the world's first Cyborg. Kevin was born in Coventry, UK and left school to join British Telecom.

TechRepublic's Karen Roby talks with an AI expert who believes we need to rethink our approach and focus more on cost benefit tradeoffs and resourcing. The following is an edited transcript of the interview. We're talking with Arijit Sengupta, he's an AI expert with over 20 years of education and experience working in artificial intelligence and even wrote a book called AI is a Waste Of Money. So Arijit, you obviously think we need to re-evaluate our approach to AI… explain! Arijit Sengupta: The answer is to go back to the fundamentals.

Weld is an open-source Rust project for improving the performance of data-intensive applications. It is an interface and runtime that can be integrated into existing frameworks including Spark, TensorFlow, Pandas, and NumPy without changing their user-facing APIs. Data analytics applications today often require developers to combine various functions from different libraries and frameworks to accomplish a particular task. For instance, a typical Python ecosystem application selects some data using Spark SQL, transforms it using NumPy and Pandas, and trains a model with TensorFlow. This improves developers' productivity as they are taking advantage of functions from high-quality libraries.

It wasn't that long ago that Sophia Withers was travelling around Australia and Asia after her undergraduate degree. After a stint working on farms and in brunch cafes, she moved to Melbourne and joined KPMG Australia. While working as a coordinator for their audit division, she began studying the University of Birmingham's part-time Online MSc International Business, in 2018. It was during the program that she deep dived into her passion for blockchain and emerging technology. Her degree research project--How will Blockchain 3.0 facilitate social and economic impact?

Founded in 1990, the Martin Luther King Jr. (MLK) Visiting Professors and Scholars Program honors the life and legacy of Martin Luther King by increasing the presence of, and recognizing the contributions of, underrepresented minority scholars at MIT. MLK Visiting Professors and Scholars enhance their scholarship through intellectual engagement with the MIT community and enrich the cultural, academic, and professional experience of students. Six scholars are visiting MIT this academic year as part of the program. Kasso Okoudjou is returning for a second year as an MLK Visiting Professor in the Department of Mathematics. Originally from Benin, he moved to the United States in 1998 and earned a PhD in mathematics from Georgia Tech. Okoudjou joins MIT from the University of Maryland College Park, where he is a professor.