Data visualization tools, desktop data discovery tools, and visual analytics are examples of traditional self-service BI tools that business analysts embrace because they provide a user-friendly way of quickly turning data into insights. These tools are geared toward business analysts that have the skills and knowledge to acquire the right data sets, perform the analysis, and present the insights needed to solve a business problem. Often, these data sets acquired by business analysts are not governed or managed by IT, but this is acceptable because business analysts have enough business knowledge to evaluate whether insights are reasonably accurate to address the business problem. Business analysts also have the skills to best present analysis in the form of beautiful charts and reports to make it easy for others in the business to interpret insights quickly for decision making. Machine-generated insights can remove business analysts entirely from the analytic process.

This is a clip from a conversation with Gary Marcus from Oct 2019. You can watch the full conversation here: https://www.youtube.com/watch?v vNOTD... (more links below) Podcast full episodes playlist: https://www.youtube.com/playlist?list... Podcasts clips playlist: https://www.youtube.com/playlist?list... Podcast website: https://lexfridman.com/ai Note: I select clips with insights from these much longer conversation with the hope of helping make these ideas more accessible and discoverable. Ultimately, this podcast is a small side hobby for me with the goal of sharing and discussing ideas. I did a poll and 92% of people either liked or loved the posting of daily clips, 2% were indifferent, and 6% hated it, some suggesting that I post them on a separate YouTube channel.

Like $$? Refer a friend to get $20 off a purchase of $60 or more. I am the H.A.L 9000. You may call me Hal. I am completely operational, and all my circuits are functioning perfectly. Just what do you think you're doing, Dave?

"Every engineering domain I spent enough time on has become my favorite at a certain point in my career", says Bulent. "Yet, that never stopped me from exploring, jumping from one technology stack to another, to keep learning and enhancing my skill set and knowledge." At the start of his career, Bulent and a team of skilled software engineers developed a suite of MS Office alternatives which was eventually launched under the name Corel Home Office. Some interesting facts about his career - Bulent helped build the popular CorelDraw Graphics Suite and even worked as a sales manager at FADATA, a front-office insurance software vendor. "I always strive to break out of my comfort zone by challenging myself with projects that are fresh and unconventional", smiles Bulent.

"Human Compatible" is a provocative prescription to re-think AI before it's too late Ned Desmond: Why did you write Human Compatible? Dr. Russell: I've been thinking about this problem – what if we succeed with AI? – on and off since the early 90s. The more I thought about it, the more I saw that the path we were on doesn't end well. So we'll just make more of it, and everything will be fine. When you start crossing over to systems that are more intelligent, operating on a global scale, and having real-world impact, like trading algorithms, for example, or social media content selection, then all of a sudden, you are having a big impact on real-world, and it's hard to control.

This transcript has been edited for clarity. I'm Eric Topol, editor-in-chief of Medscape, and I'm excited to be joined by Abraham Verghese from Stanford University for our first "Medicine and the Machine" podcast. We're envisioning a monthly podcast where we discuss the intersection of artificial intelligence (AI) with the practice of medicine. This is obviously an important topic. It's timely, and we're thrilled to have the chance to have these conversations. Along the way, we will be bringing in other people and perspectives. Abraham Verghese, MD: Thank you so much, Eric. It's great to be a part of this.

CEATEC (Combined Exhibition of Advanced Technologies) is an annual event where innovative technologies, products and services are all exhibited together in one place to illustrate what a future society may be like. This year's CEATEC, for which The Japan Times is a prime media partner, will be held at Makuhari Messe in Chiba Prefecture from Oct. 15 to 18. It requires preregistration from all visitors on the CEATEC website, www.ceatec.com. People can also register online at the venue reception area during the event. The event, sponsored by the CEATEC Executive Board, comprised of the Japan Electronics and Information Technology Industries Association, the Communications and Information Network Association of Japan and the Computer Software Association of Japan, consists of two major parts -- an exhibition and a conference.

This podcast interview focuses on what's real and not real in the world of AI, and my guest is Daniel Faggella, founder and CEO of Emerj AI Research Called upon by organizations like the World Bank, the United Nations, INTERPOL, and global pharmaceutical and banking companies, Emerj CEO Daniel Faggella helps business and government leaders navigate the competitive landscape of AI capabilities, and build strategies that win. His company, Emerj, helps governments and enterprises reduce risk and maximize the bottom-line impact of artificial intelligence capabilities. They map the capability-space of AI across major sectors (banking, pharma, retail, etcetera), helping leaders see what's possible, what's working i.e., where's real ROI and traction, and what to do about it. Being an active reader of his weekly update on the world of AI and got inspired by Daniels down to earth and challenger view on the topic. This is why I invited him to my podcast.

Jiawei Han, a professor of computer science at the University of Illinois at Urbana-Champaign, was recently named a Michael Aiken Chair, one of the University's highest awards. The endowed chair is the latest honor in Han's distinguished and pioneering career, with notable accomplishments including creating core data mining algorithms and co-authoring the textbook that is considered by many to have defined the field. Professor Han is also a busy and successful teacher with a love for "train[ing] the younger generation, whether at UIUC or all over the world on Coursera." Professor Han had three PhD students graduate in May, with one becoming a professor at Georgia Tech, one joining Google, and one joining Facebook. Students taking his classes as part of the Online Master of Computer Science in Data Science degree have an opportunity to learn from him through videos and can ask him questions directly during live office hours.

Gary Marcus is a professor emeritus at NYU, founder of Robust.AI and Geometric Intelligence, the latter is a machine learning company acquired by Uber in 2016. He is the author of several books on natural and artificial intelligence, including his new book Rebooting AI: Building Machines We Can Trust. Gary has been a critical voice highlighting the limits of deep learning and discussing the challenges before the AI community that must be solved in order to achieve artificial general intelligence. This conversation is part of the Artificial Intelligence podcast.