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) …
At H2O.ai, it is our goal to democratize AI by bridging the gap between the State-of-the-Art (SOTA) in machine learning and a user-friendly, enterprise-ready platform. We have been working tirelessly to bring the SOTA from Kaggle competitions to our enterprise platform Driverless AI since its very first release. The growing list of Driverless AI features and our growing team of Kaggle Grandmasters and industry expert data scientists can be seen as our effort and commitment to achieve that goal. Today, we are excited to announce the availability of our latest Driverless AI release 1.9 which comes with tons of new features. This article is the first of the 1.9 release blog series.
Join Xilinx and TigerGraph to learn about the next-generation machine learning solutions on connected data. We will explore different practical use cases that rely on product or service recommendation and fraud detection solutions ranging from patient similarity in the health sector to anti-money laundering in the financial services industry. We will hear directly from the area and product experts so be sure to sign up now.
Last February, President Trump signed an Executive Order on Maintaining American Leadership in Artificial Intelligence (AI). It prompted federal agencies and offices to build out their AI capabilities by employing new tools and methods of adoption. This hour long video webinar will will bring together thought leaders from federal civilian agencies -- and their counterparts in the private sector -- to discuss how AI is being used to reduce cybersecurity risks, adopt modern identity strategies, and enable security models based on zero trust. CART Captioner Professional Certifications Our CART services are provided by Home Team Captions. All of our CART captioners hold, at minimum, the CCP (Certified CART Provider) certification, or higher, from NCRA (National Court Reporters Association.) To view the CART feed for this webinar: Register for this webinar, login from the link provided, and click on the CART Tab and click the link to begin using CART.
It's no secret now that esports are taking over both real and virtual worlds with a global audience nearing half a billion spectators. And esports industry statistics are earth-shattering, with annual growth rates as high as 20 per cent and revenues exceeding 1 billion USD per year. But what about the technology that makes the esports multiverse so compelling? This was the question explored by a recent AI for Good webinar as part of the Global Dialogue on Esports. Featuring expert panellists hailing from Singapore, Toronto, Manchester and more, the diversity of speakers and attendees demonstrated how esports is truly a global phenomenon.
Automation Anywhere is one of the most popular vendors which offers user-friendly and powerful RPA capabilities. Edureka is partnering with Automation Anywhere for this webinar on Decoding futuristic career roles in RPA with Automation Anywhere. The guest speaker for this session would be Arjun Meda who is an RPA evangelist and part of the Bot Store developer relations team. The average salary for an Automation Anywhere Engineer is around $113k per annum – Payscale.com The Robotic Process Automation market is estimated to reach USD 2,467.0 million by 2022, at a CAGR of 30.14% between 2017 and 2022 – MarketsandMarkets.com
Tomorrow, Friday July 17, 2020 at 5:00 PM WAT (9:00 AM PDT), join me for a Q&A session with Laurence Moroney, a Developer Advocate at Google working on Artificial Intelligence with TensorFlow. In my humble opinion, if there were 3 people on the planet that could "explain Machine Learning to you like you were 5 years old", Laurence would appear twice on that list! Check out these 2 playlists on YouTube: - Machine Learning Zero to Hero (I urge you to watch the entire 4-part mini-series) - Machine Learning Foundations (Freshly minted episodes still being created and released) Laurence's instructor bio on Coursera, states that he is the "author of more programming books than he can count". I can't wait to ask him about this! If you'd like to ask him anything, please send in your questions ahead of tomorrow's webinar via this link.
For today's warfighters, it's imperative to have access to the latest technology at the blink of an eye to ensure mission success and warfighter safety. To meet the challenge of equipping today's warfighters with mission-critical information, milCloud 2.0 is stepping up to provide the technology that is vital to that effort. On Wednesday July 22, General Dynamics Information Technology (GDIT), Intel, Oracle, and MeriTalk will be hosting a webinar, "milCloud 2.0: Leveraging the Latest Tech for the Mission" to educate mission partners about the latest milCloud 2.0 capabilities and technologies, as well as how the platform helps support rapid innovation in mission-critical areas including artificial intelligence (AI), machine learning (ML), cyber sensing, and other emerging technology solutions. The July 22 webinar – the second in a series of four – will help organizations maximize milCloud 2.0 capabilities, and will dive into: The digital conversation will be led by three preeminent subject matter experts: Senior Director for Oracle Public Sector Lauren Farese; Cloud Services Portfolio Lead for milCloud 2.0 at GDIT Jeffrey Phelan; and Chief Enterprise Solution Architect at Intel Darren Pulsipher. Managed by the Defense Information Systems Agency and operated by GDIT, milCloud 2.0 connects commercial cloud service offerings to Defense Department (DoD) networks.
Artificial intelligence has made significant strides in recent years, but modern AI techniques remain limited, a panel of MIT professors and the director of the MIT-IBM Watson AI Lab said during a webinar this week. Neural networks can perform specific, well-defined tasks but they struggle in real-world situations that go beyond pattern recognition and present obstacles like limited data, reliance on self-training, and answering questions like "why" and "how" versus "what," the panel said. The future of AI depends on enabling AI systems to do something once considered impossible: Learn by demonstrating flexibility, some semblance of reasoning, and/or by transferring knowledge from one set of tasks to another, the group said. The panel discussion was moderated by David Schubmehl, a research director at IDC, and it began with a question he posed asking about the current limitations of AI and machine learning. "The striking success right now in particular, in machine learning, is in problems that require interpretation of signals--images, speech and language," said panelist Leslie Kaelbling, a computer science and engineering professor at MIT.
Bots are now a key starting point for conversations with customers, so it's vital that companies think through how they use them. Artificial intelligence is a technology that has already transformed how consumers interact with their home devices, with brands, even with their cars. It has shown benefits both for companies and customers, but what's next for virtual agents and their kin? In this webinar, P.V. Kannan, coauthor of "The Future of Customer Service Is AI-Human Collaboration," discusses how virtual agents are proving themselves as a technology and the ways AI-driven customer service will empower contact center agents to provide great customer experiences. Get periodic email updates on upcoming webinars, panel discussions, and other special events.
Experts from MIT and IBM held a webinar this week to discuss where AI technologies are today and advances that will help make their usage more practical and widespread. Artificial intelligence has made significant strides in recent years, but modern AI techniques remain limited, a panel of MIT professors and IBM's director of the Watson AI Lab said during a webinar this week. Neural networks can perform specific, well-defined tasks but they struggle in real-world situations that go beyond pattern recognition and present obstacles like limited data, reliance on self-training, and answering questions like "why" and "how" versus "what," the panel said. The future of AI depends on enabling AI systems to do something once considered impossible: Learn by demonstrating flexibility, some semblance of reasoning, and/or by transferring knowledge from one set of tasks to another, the group said. The panel discussion was moderated by David Schubmehl, a research director at IDC, and it began with a question he posed asking about the current limitations of AI and machine learning.