You’ve no doubt heard quite a bit about Artificial Intelligence (AI) and Machine Learning (AL) over the past few years. The promise of AI / ML and the impacts they will have on our Software Testing industry are enticing. What’s particularly exciting is how AI technology will enhance, not replace, the roles of QA professionals. AI technology can lessen the burden on QA organizations by automating many tedious test tasks and allow QA professionals to focus on what is most important – ensuring the quality and usability of their companies’ products. Join tapQA, a national thought leader in Quality, and our guest Kevin Surace, CTO of and renowned AI expert, for a look at Building The AI-Enabled QA Strategy. We discuss how a balanced approach utilizing the speed and coverage of AI technology and the domain expertise and empathetic approach of human testers will lead to the ultimate success of a QA organization. Our focus is on: • Overview of AI + ML, and their impacts on QA / Testing • How AI won’t replace Human Testers – keep Humans focus on “human-centric things” • Creating the perfect blend of AI speed and human creativity to maximize the value of a QA organization • A demonstration of’s AIQ platform and how it can lessen the burden on QA organizations
A masterclass to discuss data science career development options and how to develop a personal capacity building roadmap. It speaks to the hype, myths and facts on data science career while providing versed yet converged research-based evidence on the opportunities, growth drivers and emerging applications of AI for personal and societal value creation. It showcases how you can play in the four domains of impact -Business problem-solver, Expert Practitioner, Researcher and Community builder.
China is pursuing an ambitious plan to make an omnipresent video surveillance network to track where people are and what they’re up to. The Post’s Simon Denyer looks at the technology that will make this possible. Subscribe to The Washington Post on YouTube: Follow us: Twitter: Instagram: Facebook:
Learn more about AWS at – —AWS Public Sector Summit Singapore 2017— Artificial Intelligence (AI) and Machine Learning (ML) are no longer the stuff of science fiction. Organizations are increasingly using A.I. and Machine Learning to drive innovation — namely,’s retail experience. Join us for an inside look at how Amazon thinks about this technology, and gain insight into a range of new AI/ML services offered by AWS for use in your own business. – Management Track – Speaker: Olivier Klein, Emerging Technologies Solutions Architect, Amazon Web Services
What is this? We want this to be a coming-of-age “vodcast” where we attempt to showcase perspectives from people still “figuring it out”, it being their academics, careers, relationships, and lives. Who are we? Our degrees classify us as engineers. After graduating from the same college, we’re now in different timezones, different careers and at different stages of life. Why are we doing this? Everyone’s struggling with their identities, nobody has it all worked out. The sooner we realise this, the sooner we’ll start enjoying the short amount of time we have being alive. We plan this to be a common place to collect experiences and thoughts that may help people facing similar struggles in their lives. It would also be something tangible (or should we say, audible) for us to look back on (or hear) years down the line. Enjoy! Available on Spotify :… Follow us on Instagram ➡️: Goutham B : Goutham K : Yadu K : Song: JJD – Adventure [NCS Release] Music provided by NoCopyrightSounds Free Download/Stream: Watch: #artificialintelligence #samharris #tedtalk #buildingai #future
Embodied Artificial Intelligence: Building brain and body together in bio-inspired robots Theme: Brains and Machines Abstract: Our brains grow together with our mechanical bodies, and the developmental process of embodiment plays significant roles in shaping the structures of neuronal circuits and information processing. In this talk, I will be introducing some of our attempts to apply an engineering approach to the development of artificial brains for bio-inspired robots of various kinds (e.g. walking, hopping, crawling, swimming, and dancing robots), and discuss how this synthetic methodology could lead to our further understanding of embodied intelligence. Short biography: Fumiya Iida is a Professor of Robotics at Department of Engineering, University of Cambridge, the director of Bio-Inspired Robotics, and the director of Cambridge Observatory for Human Machine Collaboration. He received his bachelor and master degrees in mechanical engineering at Tokyo University of Science (Japan, 1999), and Dr. sc. nat. in Informatics at University of Zurich (2006). In 2004 and 2005, he was also engaged in biomechanics research of human locomotion at Locomotion Laboratory, University of Jena (Germany). From 2006 to 2009, he worked as a postdoctoral associate at the Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology in USA . In 2006, he awarded the Fellowship for Prospective Researchers from the Swiss National Science Foundation, and in 2009, the Swiss National Science Foundation Professorship for an assistant professorship at ETH Zurich from 2009 to 2015. He was a recipient of the IROS2016 Fukuda Young Professional Award, Royal Society Translation Award in [More]
Get the slides: ABOUT THE TALK With recent developments in open source tools and cloud infrastructure, it has become easier to build Data Engineering applications. Lean Startup methodologies and MVPs have taken over product development. But can you apply them to building an AI product? How do you solve the Catch-22 of finding the data you need to get started? How do you iterate quickly (and cheaply) to a model that creates value for customers? What is an MVP in AI? How do you keep experimenting fast while ensuring the reliability of your data pipelines? With a team size that’s a rounding error at Uber or AirBnb? In this talk, we’ll share some of the issues we encountered trying to apply “lean startup” techniques to the development of a pure-play ML product and the techniques and tools we used to circumvent these difficulties. ABOUT THE SPEAKER Paul is the co-founder and CTO of MadKudu, a company using Machine Learning to optimize customer journeys at scale. Prior to MadKudu, he was a Product Manager in charge of the data platform at AgilOne. For reasons that made sense at the time, Paul holds MS Degrees in Nuclear Engineering from UC Berkeley and Ecole Polytechnique. ABOUT DATA COUNCIL: Data Council ( is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers. Make sure to subscribe to our channel for more videos, including DC_THURS, our series of live online interviews with [More]
Max Tegmark speaking at the 2019 6th International FQXi Conference, “Mind Matters: Intelligence and Agency in the Physical World.” The Foundational Questions Institute (FQXi) catalyzes, supports, and disseminates research on questions at the foundations of physics and cosmology, particularly new frontiers and innovative ideas integral to a deep understanding of reality but unlikely to be supported by conventional funding sources. Please join us at!
Meet Jan Jongboom (CTO) and Jenny Plunkett (Engineer) at Edge Impulse (, a company that makes it easy for developers to work with TinyML using TensorFlow. Edge Impulse has an active developer community (with 50,000 projects and growing!) See two quick demos, with links you can use to learn more. Resources: Edge Impulse → Getting started with any device → Coursera: Introduction to Embedded Machine Learning → Coursera: Computer Vision with Embedded Machine Learning → Speakers: Josh Gordon, Jenny Plunkett, Jan Jongboom Watch all Google’s Machine Learning Virtual Community Day sessions → Subscribe to the TensorFlow channel → #MLCommunityDay product: TensorFlow – General; event: ML Community Day 2021; fullname: Josh Gordon, Jenny Plunkett, Jan Jongboom; re_ty: Publish;
Clarifai Community brings together the world’s best AI resources, including state-of-the-art models from organizations like Google, Facebook, and HuggingFace. These models can then become the building blocks for your own AI using Clarifai Mesh, which lets you create workflows by chaining together models to solve complex problems. And, of course – you can also share your favorite workflows with the public. Read our blog: Learn more at:
Barcelona CITY.AI third event for applied Artificial Intelligence. – Slides: – Timestamps: 00:00 – Intro 00:46 – Summary of the projects 09:48 – How to approach any ML problem (as a startup) 23:27 – Bullsh*t in AI startups 28:20 – Potential innovations in the industry 35:04 – Tips and take-aways
Elon Musk discusses his new project digging tunnels under LA, the latest from Tesla and SpaceX and his motivation for building a future on Mars in conversation with TED’s Head Curator, Chris Anderson. Visit to get our entire library of TED Talks, transcripts, translations, personalized talk recommendations and more. The TED Talks channel features the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and more. You’re welcome to link to or embed these videos, forward them to others and share these ideas with people you know. Become a TED Member: Follow TED on Twitter: Like TED on Facebook: Subscribe to our channel: TED’s videos may be used for non-commercial purposes under a Creative Commons License, Attribution–Non Commercial–No Derivatives (or the CC BY – NC – ND 4.0 International) and in accordance with our TED Talks Usage Policy ( For more information on using TED for commercial purposes (e.g. employee learning, in a film or online course), please submit a Media Request at
Day 1 Session 3: Building Morality into Machines :00 – Matthew Liao Opening Remarks 1:52 – Stephen Wolfram “How to Tell AIs What to Do (and What to Tell Them)” 38:20 – Francesca Rossi “Ethical Embodied Decision Making” 1:13:30 – Peter Railton “Machine Morality: Building or Learning?” 1:47:00 – Speaker panel More info: On October 14-15, 2016, the NYU Center for Mind, Brain and Consciousness in conjunction with the NYU Center for Bioethics hosted a conference on “The Ethics of Artificial Intelligence”. Recent progress in artificial intelligence (AI) makes questions about the ethics of AI more pressing than ever. Existing AI systems already raise numerous ethical issues: for example, machine classification systems raise questions about privacy and bias. AI systems in the near-term future raise many more issues: for example, autonomous vehicles and autonomous weapons raise questions about safety and moral responsibility. AI systems in the long-term future raise more issues in turn: for example, human-level artificial general intelligence systems raise questions about the moral status of the systems themselves. This conference will explore these questions about the ethics of artificial intelligence and a number of other questions, including: What ethical principles should AI researchers follow? Are there restrictions on the ethical use of AI? What is the best way to design AI that aligns with human values? Is it possible or desirable to build moral principles into AI systems? When AI systems cause benefits or harm, who is morally responsible? Are AI systems themselves potential objects of moral [More]
This tutorial was recorded at KDD 2020 as a live, hands-on tutorial. The content is available at
Why do people collaborate? Because we achieve more together than we can alone. The same is true of man and machine. Leaders need to add machine learning to their data and analytics strategies to unlock actionable insights that help employees make better business decisions. This is augmented intelligence. In the sixth installment of his “Journeys in Transformation” webchat series, Genpact’s Chief Digital Officer, Sanjay Srivastava, shares a framework for augmented intelligence. Joining him are: • JoAnn Stonier, Chief Data Officer at MasterCard • Henna Karna, Chief Data Officer at AXA XL • Vikram Mahidhar, Leader, AI Growth Strategy at Genpact
Peter Albert Railton is an American philosopher who is Gregory S. Kavka Distinguished University Professor and John Stephenson Perrin Professor of Philosophy at the University of Michigan, Ann Arbor, where he has taught since 1979.
It’s been 7 years since my first interview with Gary Marcus and I felt it’s time to catch up with him. Gary is the youngest Professor Emeritus at NYU and I wanted to get his contrarian views on the major things that have happened in AI as well as those that haven’t happened. Prof. Marcus is an interesting interviewee not only because he is an expert in the field but also because he is a skeptic on the current approaches and progress towards Artificial General Intelligence but an optimist that we will eventually figure it all out. During this 90 min interview with Gary Marcus we cover a variety of interesting topics such as: Gary’s interest in the human mind, natural and artificial intelligence; Deep Mind’s victory in Go and what it does and doesn’t mean for AGI; the need for Rebooting AI; trusting AI and the AI chasms; Asimov’s Laws and Bostrom’s paper-clip-maximizing AI; the Turing Test and Ray Kurzweil’s singularity timeline; Mastering Go Without Human Knowledge; closed vs open systems; Chomsky, Minsky and Ferrucci on AGI; the limits of deep learning and the myth of the master algorithm; the problem of defining (artificial) intelligence; human and machine consciousness; the team behind and the mission of Robust AI. As always you can listen to or download the audio file above or scroll down and watch the video interview in full. To show your support you can write a review on iTunes, make a direct donation or become a patron [More]
Title: Break Into AI: A Q&A with Andrew Ng on Building a Career in Machine Learning Speaker: Andrew Ng Date: 12/4/2018 Abstract Andrew Ng will share tips and tricks on how to break into AI. He will discuss some of the most valuable skills for today’s machine learning engineers, how to gain the experience to successfully switch careers, and how to build a habit of lifelong learning. He will also take questions from aspiring engineers and business professionals who want to work on AI-powered products. SPEAKER Andrew Ng, General Partner, AI Fund; CEO, Landing AI; Adjunct Professor, Stanford University Dr. Andrew Ng, a globally recognized leader in AI, is a General Partner at AI Fund and CEO of Landing AI. As the former Chief Scientist at Baidu and the founding lead of Google Brain, he led the AI transformation of two of the world’s leading technology companies. A longtime advocate of accessible education, Dr. Ng is the Co-founder of Coursera, an online learning platform, and founder of, an AI education platform. Dr. Ng is also an Adjunct Professor at Stanford University’s Computer Science Department. MODERATOR Juan Miguel de Joya, UN ITU; ACM Practitioners Board Juan Miguel de Joya is the in-house consultant for Artificial Intelligence and Emerging Technologies at the United Nations International Telecommunications Union. Prior to this role, he served as a contractor at Facebook/Oculus and Google, worked at Pixar Animation Studios and Walt Disney Animation Studios, and was an undergraduate researcher in graphics at the Visual Computing [More]
Geordie Rose, Founder and CTO of D-Wave Systems describes some of the challenges the team had to overcome in building the first commercial quantum computer. Learn more about D-Wave and the first commercial quantum computers at
Recorded at the GAIA conference on April 10th 2018 in collaboration with Ericsson. Artificial Intelligence and Machine Learning have made enormous progress during the last decade, and AI techniques are already widely used in industry and society. Expectations on these technologies are high, often so high that the technology we have today cannot come close to fulfil them. We will discuss what modern AI is, what is possible and what problems remain to be solved. We will present what RISE AI does within the area, how to create more interpretable machine learning models, approaches to bridge the gap between learning and reasoning, and what we believe is a way forward towards more general, large-scale AI-systems.
Our opinions of AI have been formed by mainstream media, but that stops now. We’re joined by New York Times best-selling author, Martin Ford to talk about what’s exciting, what’s scary, and what’s to come from machine learning. In his new book, Ford records the conversations he has had with the very people developing artificial intelligence. Get Your Copy of “Architects of Intelligence” at is an NYC based artificial intelligence company that’s raised over $30 million. I sat down with the founder Dennis Mortensen to learn more about how they’re positioning and selling the product to the enterprise. Talking to him got me super curious about the rise of artificial intelligence, and I hope this interview does similar for you. SUBSCRIBE for more videos like this: START OR GROW YOUR BUSINESS: ONE ON ONE MENTORSHIP: FREE DOWNLOADS: /// R E S O U R C E S Get the sales and service agreement we use to close business (free client contract template) [$1,000 value]: Get the actual questions we use to qualify clients on the first call: Get the proposal template you can use to sell 5 and 6 figure deals: — __ /// MORE FROM ALEX Subscribe for more content like this: __ /// BUSINESS INQUIRIES: For sponsorships you can reach us at:
In this Keynote Session, some of Google’s leading minds on artificial intelligence and machine learning discuss their vision for a future where artificial intelligence can improve the lives of everyone. Rate this session by signing-in on the I/O website here → Watch more machine learning sessions from I/O ’18 here → See all the sessions from Google I/O ’18 here → Subscribe to the Google Developers channel → #io18