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) …
Microsoft announced a $1 billion investment in OpenAI, a lab co-founded by Elon Musk to develop "artificial general intelligence." The investment is the start of a long-term partnership between the two organizations. OpenAI will ensure its services work on Microsoft's Azure cloud platform, and the companies will collaborate on new supercomputers. OpenAI's stated mission is to develop "artificial general intelligence," or AGI. In layman's terms, AGI is AI that can think like a human (possibly even better) while carrying out complex tasks autonomously.
Expect an enhanced workforce dedicated to AI safety, big steps in reaching what's known as "general" intelligence, and more of the same (i.e. Unlike other emerging technologies, AI never seems to go away. It's perpetually talked about, studied, revered, and feared. It's going to give robots sentience! And they're going to take over the human race!
Artificial intelligence (AI) has come a long way in recent years. For example, AI has defeated the human world champion of Go, recreated the periodic table of elements, enabled self-driving vehicles, identifed crop diseases, and predicted depression from speech. Imagine what could happen as AI improves capabilities in areas that are squarely in the domain of the human brain. Today, technology is far from achieving parity with human-level intelligence, also known as "strong AI" or artificial general intelligence (AGI). Recent AI advances in one capability--pattern recognition--has spawned an investment gold rush for AI startups and machine learning talent from venture capital, corporations, and governments who have recognized the potential competitive advantage.
Microsoft's 2019 data and AI tech immersion workshop demonstrated the vendor's strategy to democratize AI by providing a small group of about 30 journalists, industry analysts and other tech industry experts with hands-on experience in programming AI bots using the cognitive services in the Microsoft Azure public cloud platform. It provided meaningful glimpses of the future of AI in enterprise applications, from prebuilt AI models in Azure and machine teaching efforts of today to a future quantum coprocessor that will one day function as Azure's sidekick in a hybrid computing model. The immersion approach of the workshop, which I attended, mimics the real-world experience of AI users who aren't data scientists. Most attendees did not own or have access to the massive data sets needed to complete the exercises on a variety of real-life AI use cases. The software giant overcame that obstacle by providing an open remote desktop connection app on our individual workstations, giving us access to the immersion environment and preloaded data sets in Azure.
So, a few months ago, I was walking down the street in Shenzhen, in the Guangdong Province of southeastern China. I was hungry and looking for lunch. Armed with my credit card and plenty of the local currency, I strode out of my hotel to check out the many street vendors selling delicious-smelling food. Using Google Translate, I was able to order a fried fish dish, but when I went to pay, the vendor refused my credit card. Undaunted I pulled out cash, but that too was refused. The guy pointed me to a large QR code and asked me to pay using the WeChat app. As this was my first day in China, I hadn't yet set the app to pay for things, so I walked away, a little embarrassed. Still hungry, I came to a large junction and saw a promising looking restaurant across a busy street.
The general premise of this article is different from most of my previous AI Power articles. While most of the articles in this series have related to the near-term struggles for power between organizations and governments with regards to regulation, data, and international policy, this article will focus on the long-term trajectory that AI and technology are headed towards and what that means for the most powerful nations and organizations. In the long term (15-40 years ahead), the power struggles around AI will not end with economic and military competition. Ultimately, AI power will involve determining the trajectory of intelligence itself. This might involve the creation of astronomically powerful artificial general intelligence (AGI) and/or the creation of vastly more capable and powerful cognitively enhanced humans (transhuman transition).
The evolution of artificial intelligence (AI) For the Evolution of Artificial Intelligence, there are three types of AI:- Artificial Narrow Intelligence (ANI) Artificial General Intelligence (AGI) Artificial Super Intelligence (ASI) Time by time they are evaluated by us and from Artificial Narrow Intelligence (ANI), through Artificial General Intelligence (AGI), then Artificial Super Intelligence (ASI) -- is on its thanks to dynamic everything. It's expected that shortly, computing can mix the complexness and pattern recognition strength of human intelligence with the speed, memory and information sharing of machine intelligence. If These are getting stuck in your head!! follow my Artificial Intelligence series then read this... read more for Better understand. If digital workplaces are being noncontinuous by the continued development of artificial intelligence (AI) driven apps, by 2021 those disruptors might find yourself in their flip being noncontinuous. The emergence of a brand new kind of AI, or a second wave of AI, referred to as increased AI is therefore vital that Gartner is predicting that by 2021 it'll be making up to $2.9 trillion of business worth and half-dozen.2 billion hours of employee productivity globally.
This is a guest talk part of MIT course 6.S099: Artificial General Intelligence. This class is free and open to everyone. Our goal is to take an engineering approach to exploring possible paths toward building human-level intelligence for a better world. CONNECT: - If you enjoyed this video, please subscribe to this channel.
If digital workplaces are being disrupted by the ongoing development of artificial intelligence (AI) driven apps, by 2021 those disruptors could end up in their turn being disrupted. The emergence of a new form of AI, or a second wave of AI, known as augmented AI is so significant that Gartner is predicting that by 2021 it will be creating up to $2.9 trillion of business value and 6.2 billion hours of worker productivity globally. Gartner defines augmented intelligence as a human-centered partnership model of people and AI working together to enhance cognitive performance. This includes learning, decision making and new experiences. "As AI technology evolves, the combined human and AI capabilities that augmented intelligence allows will deliver the greatest benefits to enterprises," Svetlana Sicular, research vice president at Gartner, said in a statement..
In coming years, the most intelligent organizations will need to blend technology-enabled insights with a sophisticated understanding of human judgment, reasoning, and choice. Those that do this successfully will have an advantage over their rivals. To succeed in the long run, businesses need to create and leverage some kind of sustainable competitive edge. This advantage can still derive from such traditional sources as scale-driven lower cost, proprietary intellectual property, highly motivated employees, or farsighted strategic leaders. But in the knowledge economy, strategic advantages will increasingly depend on a shared capacity to make superior judgments and choices. Intelligent enterprises today are being shaped by two distinct forces. The first is the growing power of computers and big data, which provide the foundation for operations research, forecasting models, and artificial intelligence (AI). The second is our growing understanding of human judgment, reasoning, and choice.