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) …
Through the Azure AI Camp, the ML practitioner will learn how to use Azure ML, Databricks, ML on the Edge and other Microsoft AI technologies to unlock insights on big datasets and deploy AI services to the cloud and edge. It is designed as a hands-on workshop experience, recommended in instructor-led format or on-demand learning by using the documentation and resources provided for guidance. In this workshop, the following resources will get provisioned. In practice, most are shared amongst an organization or group. For this workshop it will depend upon the Azure Subscription setup.
The technology behind Autonomous vehicles can surprise you. These vehicles are characterized by not having to deal with human limitations, such as tiredness and inattention. To the delight of many, these machines can park alone, and they do not drive drunk or speak on the phone while driving, like many humans that we know. It is known that human failures cause 94% of traffic accidents, and this innovation is mainly developed to save lives, reducing consistently the fatalities. According to a study from 2015 by the National Highway Traffic Safety Administration (NHTSA), traffic accidents are the most significant cause of death of young people between 15 and 29 years globally, overcoming the victims of AIDS, flu, and dengue together, according to the World Health Organization (WHO).
The 2020 Breakthrough Days event aims to generate and fuel meaningful projects in each of this year's three AI for Good Global Summit domains – Gender, Food, and Pandemics – that will advance progress on the UN Sustainable Development Goals (SDGs). Hear from keynote speakers and participate in interactive workshops designed to launch solutions to some of the world's greatest challenges. "Beneficial AI to advance SDGs" Keynote Speaker: Stuart Russell, Professor of Computer Science at UC Berkeley Moderator: Amir Banifatemi, Chief Innovation Officer, XPRIZE; Chair of the AI for Good Programme Committee In an effort to allow teams to prepare for main stage presentations on Monday and Tuesday, we have designated Friday 25 September as a time for teams and attendees to converse individually. Please use the AI for Good workspace on Slack to continue the conversation. Join us on Monday 28 September as we hear from teams in each of this year's AI for Good Breakthrough Track "What is AI for Good Anyway?" Keynote Speaker: Sasha Luccioni, Postdoctoral Researcher – AI for Humanity, Université de Montréal, Mila – Quebec AI Institute Moderator: Amir Banifatemi, Chief Innovation Officer, XPRIZE; Chair of the AI for Good Programme Committee Keynote Address Keynote Speaker: Peter H. Diamandis, entrepreneur, founder and executive chairman of the XPRIZE Foundation, Bestselling author of "Abundance – The Future Is Better Than You Think" Moderator: Amir Banifatemi, Chief Innovation Officer, XPRIZE; Chair of the AI for Good Programme Committee Interested individuals and teams from around the world have submitted project ideas to the Gender, Food and Pandemics Breakthrough Tracks. After being mentored by world-renowned experts and Brain Trusts, the top three finalists in each domain have been selected to present their project proposals in a series of interactive workshops during the Breakthrough Days event.
On Tuesday the 7th of July we virtually welcomed 10 professionals from across different industries involved with human resources, innovation, and management strategy for our first Risk Classification Framework Workshop. Organisations are searching for the right approach to evaluating AI systems for the potential harms they could cause. At the Institute for Ethical AI (IEAI), we have been exploring the potential of using a risk-based governance approach to provide appropriate oversight for systems that use probabilistic reasoning. An essential part of risk-based governance is understanding what causes higher risk and how changes in technology or governance can mitigate those risks. We have been running a series of workshops to gather the views of professionals on how to approach classifying risk.
This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park. The collection marks two decades since the first ILP workshop in 1991. During this period the area has developed into the main forum for work on logic-based machine learning. The chapters cover a wide variety of topics, ranging from theory and ILP implementations to state-of-the-art applications in real-world domains. The international contributors represent leaders in the field from prestigious institutions in Europe, North America and Asia.
IEEE Intelligent Systems 24, 2 (2009) In the decade since then, the research community have done a lot with quantity, but quality has been left behind 16. http://lora-aroyo.org Data Quality is not only human error 20. Data Quality should consider context of use it is not easy to give Y/N answer for most of our AI tasks the answer typically depends on the context, on the task, on the usage, etc 21. http://lora-aroyo.org Data Quality should include real world diversity it is not easy to give Y/N answer for most of our AI tasks the answer typically depends on the context, on the task, on the usage, etc disagreement is signal for diversity and should be included in AI training 22. http://lora-aroyo.org Data Quality is difficult even with experts For prevention of malaria, use only in individuals traveling to malarious areas where CHLOROQUINE resistant P. falciparum MALARIA has not been reported.
The Association of Data Scientists (ADaSci) recently announced Deep Learning DEVCON or DLDC 2020, a two-day virtual conference that aims to bring machine learning and deep learning practitioners and experts from the industry on a single platform to share and discuss recent developments in the field. Scheduled for 29th and 30th October, the conference comes at a time when deep learning, a subset of machine learning, has become one of the most advancing technologies in the world. From being used in the fields of natural language processing to making self-driving cars, it has come a long way. As a matter of fact, reports suggest that by 2024, the deep learning market is expected to grow at a CAGR of 25%. Thus, it can easily be established that the advancements in the field of deep learning have just initiated and got a long road ahead.
One cannot, in all their seriousness, comprehend what went into writing the "Requiem for a dream" or painting the frescoes on the ceiling of the Sistine Chapel. But, what happens when this intelligence is augmented with an external entity, an algorithm? Artificial intelligence has intruded into the space of creativity, the final frontier of the human intellect, through algorithms such as Generative Adversarial Networks (GANs). GANs have become fertile tools for artistic exploration. Artists such as Refik Anadol, Robbie Barrat, Sofia Crespo, Mario Klingemann, Jason Salavon, Helena Sarin, and Mike Tyka generate fascinating imagery with models learned from natural imagery.
A lot happened this week in the AI space. The Guardian wrote an article with GPT-3 and again demonstrated that no matter what OpenAI paid to train and create the language model, the free marketing might be worth more. After losing the JEDI cloud contract appeal with the Pentagon, Amazon appointed to its board Keith Alexander, who oversaw the National Security Agency mass surveillance revealed by Edward Snowden leaks in 2013. And Portland passed the strictest facial recognition bans in U.S. history, outlawing government and business use of the technology. However, AI Weekly attempts to reach into the zeitgeist and highlight the issues on people's minds. This week without question it's the smoke that has hung over the western United States and the underlying problem of climate change.
A lot happened this week deserving of attention in the AI space. The Guardian wrote an article with GPT-3 and again demonstrated that no matter what OpenAI paid to train and create the language model, the free marketing might be worth more. After losing the JEDI cloud contract appeal with the Pentagon, Amazon appointed Keith Alexander to its board -- the man who oversaw the National Security Agency mass surveillance revealed by Edward Snowden leaks in 2013. And Portland passed the strictest facial recognition bans in U.S. history, outlawing government and business use of the technology. However, AI Weekly attempts to reach into the zeitgeist and highlight important events on people's minds. This week without question it's the smoke that's hung over the western United States and the underlying issue of climate change.