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Artificial Intelligence and Robotics

arXiv.org Artificial Intelligence

The recent successes of AI have captured the wildest imagination of both the scientific communities and the general public. Robotics and AI amplify human potentials, increase productivity and are moving from simple reasoning towards human-like cognitive abilities. Current AI technologies are used in a set area of applications, ranging from healthcare, manufacturing, transport, energy, to financial services, banking, advertising, management consulting and government agencies. The global AI market is around 260 billion USD in 2016 and it is estimated to exceed 3 trillion by 2024. To understand the impact of AI, it is important to draw lessons from it's past successes and failures and this white paper provides a comprehensive explanation of the evolution of AI, its current status and future directions.


Frontier AI: How far are we from artificial "general" intelligence, really?

#artificialintelligence

Some call it "strong" AI, others "real" AI, "true" AI or artificial "general" intelligence (AGI)… whatever the term (and important nuances), there are few questions of greater importance than whether we are collectively in the process of developing generalized AI that can truly think like a human -- possibly even at a superhuman intelligence level, with unpredictable, uncontrollable consequences. This has been a recurring theme of science fiction for many decades, but given the dramatic progress of AI over the last few years, the debate has been flaring anew with particular intensity, with an increasingly vocal stream of media and conversations warning us that AGI (of the nefarious kind) is coming, and much sooner than we'd think. Latest example: the new documentary Do you trust this computer?, which streamed last weekend for free courtesy of Elon Musk, and features a number of respected AI experts from both academia and industry. The documentary paints an alarming picture of artificial intelligence, a "new life form" on planet earth that is about to "wrap its tentacles" around us. There is also an accelerating flow of stories pointing to an ever scarier aspects of AI, with reports of alternate reality creation (fake celebrity face generator and deepfakes, with full video generation and speech synthesis being likely in the near future), the ever-so-spooky Boston Dynamics videos (latest one: robots cooperating to open a door) and reports about Google's AI getting "highly aggressive" However, as an investor who spends a lot of time in the "trenches" of AI, I have been experiencing a fair amount of cognitive dissonance on this topic.


Frontier AI: How far are we from artificial "general" intelligence, really?

#artificialintelligence

Some call it "strong" AI, others "real" AI, "true" AI or artificial "general" intelligence (AGI)... whatever the term (and important nuances), there are few questions of greater importance than whether we are collectively in the process of developing generalized AI that can truly think like a human -- possibly even at a superhuman intelligence level, with unpredictable, uncontrollable consequences. This has been a recurring theme of science fiction for many decades, but given the dramatic progress of AI over the last few years, the debate has been flaring anew with particular intensity, with an increasingly vocal stream of media and conversations warning us that AGI (of the nefarious kind) is coming, and much sooner than we'd think. Latest example: the new documentary Do you trust this computer?, which streamed last weekend for free courtesy of Elon Musk, and features a number of respected AI experts from both academia and industry. The documentary paints an alarming picture of artificial intelligence, a "new life form" on planet earth that is about to "wrap its tentacles" around us. There is also an accelerating flow of stories pointing to an ever scarier aspects of AI, with reports of alternate reality creation (fake celebrity face generator and deepfakes, with full video generation and speech synthesis being likely in the near future), the ever-so-spooky Boston Dynamics videos (latest one: robots cooperating to open a door) and reports about Google's AI getting "highly aggressive" However, as an investor who spends a lot of time in the "trenches" of AI, I have been experiencing a fair amount of cognitive dissonance on this topic.


To Root Artificial Intelligence Deeply in Basic Science for a New Generation of AI

arXiv.org Artificial Intelligence

One of the ambitions of artificial intelligence is to root artificial intelligence deeply in basic science while developing brain-inspired artificial intelligence platforms that will promote new scientific discoveries. The challenges are essential to push artificial intelligence theory and applied technologies research forward. This paper presents the grand challenges of artificial intelligence research for the next 20 years which include:~(i) to explore the working mechanism of the human brain on the basis of understanding brain science, neuroscience, cognitive science, psychology and data science; (ii) how is the electrical signal transmitted by the human brain? What is the coordination mechanism between brain neural electrical signals and human activities? (iii)~to root brain-computer interface~(BCI) and brain-muscle interface~(BMI) technologies deeply in science on human behaviour; (iv)~making research on knowledge-driven visual commonsense reasoning~(VCR), develop a new inference engine for cognitive network recognition~(CNR); (v)~to develop high-precision, multi-modal intelligent perceptrons; (vi)~investigating intelligent reasoning and fast decision-making systems based on knowledge graph~(KG). We believe that the frontier theory innovation of AI, knowledge-driven modeling methodologies for commonsense reasoning, revolutionary innovation and breakthroughs of the novel algorithms and new technologies in AI, and developing responsible AI should be the main research strategies of AI scientists in the future.


What is AI? Everything you need to know about Artificial Intelligence ZDNet

#artificialintelligence

This ebook, based on the latest ZDNet / TechRepublic special feature, advises CXOs on how to approach AI and ML initiatives, figure out where the data science team fits in, and what algorithms to buy versus build. It depends who you ask. Back in the 1950s, the fathers of the field Minsky and McCarthy, described artificial intelligence as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task. That obviously is a fairly broad definition, which is why you will sometimes see arguments over whether something is truly AI or not. AI systems will typically demonstrate at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, problem solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity. AI is ubiquitous today, used to recommend what you should buy next online, to understand what you say to virtual assistants such as Amazon's Alexa and Apple's Siri, to recognise who and what is in a photo, to spot spam, or detect credit card fraud. AI might be a hot topic but you'll still need to justify those projects.