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) …
Artificial intelligence has become such a big part of our lives, you'd be forgiven for losing count of the algorithms you interact with. But the AI powering your weather forecast, Instagram filter, or favorite Spotify playlist is a far cry from the hyper-intelligent thinking machines industry pioneers have been musing about for decades. Deep learning, the technology driving the current AI boom, can train machines to become masters at all sorts of tasks. But it can only learn only one at a time. And because most AI models train their skillset on thousands or millions of existing examples, they end up replicating patterns within historical data--including the many bad decisions people have made, like marginalizing people of color and women. Still, systems like the board-game champion AlphaZero and the increasingly convincing fake-text generator GPT-3 have stoked the flames of debate regarding when humans will create an artificial general intelligence--machines that can multitask, think, and reason for themselves. Beyond the answer to how we might develop technologies capable of common sense or self-improvement lies yet another question: who really benefits from the replication of human intelligence in an artificial mind? "Most of the value that's being generated by AI today is returning back to the billion dollar companies that already have a fantastical amount of resources at their disposal," says Karen Hao, MIT Technology Review's senior AI reporter and the writer of The Algorithm. "And we haven't really figured out how to convert that value or distribute that value to other people."
To put it simply, the moral circle is the people we care about. Our understanding of it is usually based on William Lecky's History of European Morals from Augustus to Charlemagne. William observes that "at one time the benevolent affections embrace merely the family, soon the circle expanding includes first a class, then a nation, then a coalition of nations, then all humanity, and finally […] the dealings of man with the animal world." In other words, each individual's circle grows as that individual grows older. Just as humanity's moral circle expands from age to age.
It is not every day that humans are exposed to questions like what will happen if technology exceeds the human thought process. Or what will happen if machines became conscious or start having conscience so that they can take decisions, equivalent to that of humans? However, scientists and researchers are looking out for an alternative solution that can perform tasks which the traditional artificial intelligence and its subsidiaries cannot. Termed as Artificial General Intelligence, this cutting edge technology has been acknowledged by scientists and researchers, since the inception of artificial intelligence. Artificial general intelligence will be the technology that pairs its general intelligence with deep reinforcement learning.
C3.ai CEO Tom Siebel is rarely short of opinion and his next big bet is that artificial intelligence is going to drive CRM software in a new direction. The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, and figuring out where the data science team fits in and what algorithms to buy versus build. Fresh off a partnership with Microsoft and Adobe to meld data, CRM and AI, we caught up with Siebel to talk about C3.ai's Digital Transformation Institute, COVID-19 data lakes, education's next innovation and why social media firms need to be regulated. The full interview is in the video. Here are some of the takeaways from my interview with Siebel.
Here, most often the objective is to detect basic elements directly available in the input file, e.g., lines, circles etc. in a drawing, or words used to mention an entity in a sentence. Sometimes, we use supervised models (artificial intelligence for pattern recognition) to directly recognize complex shapes such as dining table. In the context of a document, in the detection step, we identify phrases that indicate an entity. As a result of parsing, we get a structured representation of the input, which can be referred to as Parsed-KG, if stored in KG.
We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.
Recent advances in AI and ML, while not actually close to real AGI, have made a feeling that AGI is close, as surprisingly fast for many years. Artificial Intelligence is something that's been around quite a while. Since its development into the public consciousness through sci-fi, many have expected that one day machines will have "general intelligence", and considered diverse practical, ethical and philosophical implications. In all actuality, AI has been the discussion of standard pop-culture and sci-fi since the first Terminator film turned out in 1984. These motion pictures present an example of something many refer to as "Artificial General Intelligence".
Artificial Intelligence is something that's been around quite a while. Since its development into the public consciousness through sci-fi, many have expected that one day machines will have "general intelligence", and considered diverse practical, ethical and philosophical implications. In all actuality, AI has been the discussion of standard pop-culture and sci-fi since the first Terminator film turned out in 1984. These motion pictures present an example of something many refer to as "Artificial General Intelligence". No compelling reason to state that superhuman AI is not even close to happening.
What does the AI enterprise of the future look like? That's a tough question that I've been asked to consider, along with a distinguished panel at Valley ML AI Expo 2020. The title of the panel is, "Life, the Universe and the AI Enterprise of the Future." Based on an initial chat with panel chair Gautam Khera, I've written up some possible topics we'll be covering on the panel. Consider this a preview of the talk.
You know how some people are called having "book smarts" while others refer to one's knowledge as "street smarts"? It refers to where people get their specific knowledge from and for what purpose they use it. People having street smarts generally learned from practice and doing the work in the field, while the book smart people got theirs from gathering theoretical information. There are different types of "smart" in people, it just depends on how you learn best and what you wish to use it for. Personally I find the term "weak AI" a little condescending.