I believe that AI holds a lot of promise and many great things; however, we have to correct some very critical issues 1st before compound a huge issue that we have today. And, that is Cyber Security and re-establish trust with our consumers and customers. Without these 2 being fully addressed; you will compound these two challenges with AI plus run the risk of having an IoT that most people will not wish to use due to hackers, bad data, etc. Not to mention lawsuits for Wi-Fi connected robotics that were hacked and injured or worse some innocent person.
I believe need to ensure priorities are in order before we make things worse.
Unexpected convergent consequences…this is what happens when eight different exponential technologies all explode onto the scene at once.
This post (the second of seven) is a look at artificial intelligence. Future posts will look at other tech areas.
This is one that truly depends on the targeted audience. I still believe that the 1st solely owned & operated female robotics company will make billions.
Beyond correct pronunciation, there is the even larger challenge of correctly placing human qualities like inflection and emotion into speech. Linguists call this “prosody,” the ability to add correct stress, intonation or sentiment to spoken language.
Today, even with all the progress, it is not possible to completely represent rich emotions in human speech via artificial intelligence. The first experimental-research results — gained from employing machinelearning algorithms and huge databases of human emotions embedded in speech — are just becoming available to speech scientists.
Synthesised speech is created in a variety of ways. The highest-quality techniques for natural-sounding speech begin with a human voice that is used to generate a database of parts and even subparts of speech spoken in many different ways. A human voice actor may spend from 10 hours to hundreds of hours, if not more, recording for each database.
Radiation works as a ‘tuning fork’ to control the spin of electrons.
Scientists have found a new way of moving information between quantum bits in a computer. They used a highly purified sample of silicon doped with bismuth atoms (left) before fitting a superconducting aluminium resonator to it (middle and right).
“We need to start thinking very seriously—what will humans do when machines can do almost everything?” Vardi said. “We have to redefine the meaning of good life without work.”
And increase inequality.
Robots and artificial intelligence have long posed a threat to humans’ jobs, but a group of scientists on Sunday issued an especially dire warning about the impact of such machines.
The article entitled “Yes Robots Will Steal Our Jobs, But Don’t Worry We’ll Get New Ones” published by Rawstory is a very Interesting Article; however, again, I see too many gaps that will need to be address before AI can eliminate 70% of today’s jobs. Below, are the top 5 gaps that I have seen so far with AI in taking over many government, business, and corporate positions.
1) Emotion/ Empathy Gap — AI has not been designed with the sophistication to provide personable care such as you see with caregivers, medical specialists, etc.
2) Demographic Gap — until we have a more broader mix of the population engaged in AI’s design & development; AI will not meet the needs for critical mass adoption; only a subset of the population will find will connection in serving most of their needs.
Elite X-Plane General Aviation Dream Package flight simulator system (credit: Xforce PC)
You can learn how to improve your novice pilot skills by having your brain zapped with recorded brain patterns of experienced pilots via transcranial direct current stimulation (tDCS), according to researchers at HRL Laboratories.
“We measured the brain activity patterns of six commercial and military pilots, and then transmitted these patterns into novice subjects as they learned to pilot an airplane in a realistic flight simulator,” says Matthew Phillips, PhD.
The study, published in an open-access paper in the February 2016 issue of the journal Frontiers in Human Neuroscience, found that novice pilots who received brain stimulation via electrode-embedded head caps improved their piloting abilities, with a 33 percent increase in skill consistency, compared to those who received sham stimulation. “We measured the average g-force of the plane during the simulated landing and compared it to control subjects who received a mock brain stimulation,” says Phillips.
Theoretical physicists at MIT recently reported a quantum computer design featuring an array of superconducting islands on the surface of a topological insulator. They propose basing both quantum computation and error correction on the peculiar behavior of electrons at neighboring corners of these islands and their ability to interact across islands at a distance. “The lowest energy state of this system is a very highly entangled quantum state, and it is this state that can be used to encode and manipulate qubits,” says graduate student Sagar Vijay, lead co-author of the paper on the proposed system, with senior author Liang Fu, associate professor of physics at MIT, and Timothy H. Hsieh PhD ’15. As Vijay explains it, the proposed system can encode logical qubits that can be read by shining light on them. At the simplest level of explanation, the system can characterize the state of a quantum bit as a zero or a one based on whether there is an odd or even number of electrons associated with a superconducting quantum bit, but the underlying physical interactions that allow this are highly complex.
Lack of good Cyber Security across the net, will continue to be a key reason why AI in general will not deliver the return on new AI tech products and robots / devices. $3+ million in ranson may not be that large to mid size and large tech companies; however, it is everything to small businesses and small businesses and consumers is what keeps tech in business.
Hospital staff severely impeded in their day-to-day work.
In professional cycling, it’s well known that a pack of 40 or 50 riders can ride faster and more efficiently than a single rider or small group. As such, you’ll often see cycling teams with different goals in a race work together to chase down a breakaway before the finish line.
This analogy is one way to think about collaborative multi-agent intelligent systems, which are poised to change the technology landscape for individuals, businesses, and governments, says Dr. Mehdi Dastani, a computer scientist at Utrecht University. The proliferation of these multi-agent systems could lead to significant systemic changes across society in the next decade.
Image credit: ResearchGate
“Multi-agent systems are basically a kind of distributed system with sets of software. A set can be very large. They are autonomous, they make their own decisions, they can perceive their environment, “Dastani said. “They can perceive other agents and they can communicate, collaborate or compete to get certain resources. A multi-agent system can be conceived as a set of individual softwares that interact.”
As a simple example of multi-agent systems, Dastani cited Internet mail servers, which connect with each other and exchange messages and packets of information. On a larger scale, he noted eBay’s online auctions, which use multi-agent systems to allow one to find an item they want to buy, enter their maximum price and then, if needed, up the bid on the buyer’s behalf as the auction closes. Driverless cars are another great example of a multi-agent system, where many softwares must communicate to make complicated decisions.
Dastani noted that multi-agent systems dovetail nicely with today’s artificial intelligence. In the early days of AI, intelligence was a property of one single entity of software that could, for example, understand human language or perceive visual inputs to make its decisions, interact, or perform an action. As multi-agent systems have been developed, those single agents interact and receive information from other agents that they may lack, which allows them to collectively create greater functionality and more intelligent behavior.
“When we consider (global) trade, we basically define a kind of interaction in terms of action. This way of interacting among individuals might make their market more efficient. Their products might get to market for a better price, as the amount of time (to produce them) might be reduced,” Dastani said. “When we get into multi-agent systems, we consider intelligence as sort of an emergent phenomena that can be very functional and have properties like optimal global decision or situations of state.”
Other potential applications of multi-agent systems include designs for energy-efficient appliances, such as a washing machine that can contact an energy provider so that it operates during off-peak hours or a factory that wants to flatten out its peak energy use, he said. Municipal entities can also use multi-agent systems for planning, such as simulating traffic patterns to improve traffic efficiency.
Looking to the future, Dastani notes the parallels between multi-agent systems and Software as a Service (SaaS) computing, which could shed light on how multi-agent systems might evolve. Just as SaaS combines various applications for on-demand use, multi-agent systems can combine functionalities of various software to provide more complex solutions. The key to those more complex interactions, he added, is to develop a system that will govern the interactions of multi-agent systems and overcome the inefficiencies that can be created on the path toward functionality.
“The idea is the optimal interaction that we can design or we can have. Nevertheless, that doesn’t mean that multi-agent systems are by definition, efficient,” Dastani said. “We can have many processes that communicate, make an enormous number of messages and use a huge amount of resources and they still can not have a sort of interesting functionality. The whole idea is, how can we understand and analyze the interactions? How can we decide which interaction is better than the other interactions or more efficient or more productive?”
Researchers say they’ve developed a 3-D bioprinter that can create artificial body parts with ready-made channels for getting nutrients and oxygen to the implanted cells. If the technology can be perfected, the device could solve one of the biggest obstacles to creating 3D-printed organs: how to nourish masses of manufactured tissue.
“It can fabricate stable, human-scale tissue of any shape,” Anthony Atala, director of the Wake Forest Institute for Regenerative Medicine in North Carolina, said in a news release. “With further development, this technology could potentially be used to print living tissue and organ structures for surgical implantation.”
Atala and his colleagues describe their experiments with the bioprinter, known as the Integrated Tissue-Organ Printing System or ITOP, in a study published today by Nature Biotechnology.
