Why We Need to Fine-Tune Our Definition of Artificial Intelligence

AI, Artificial Intelligence, Robotics, Technology
Image source: Singularity Hub
By  – Singularity Hub

 

Sophia’s uncanny-valley face, made of Hanson Robotics’ patented Frubber, is rapidly becoming an iconic image in the field of artificial intelligence. She has been interviewed on shows like 60 Minutes, made a Saudi citizen, and even appeared before the United Nations. Every media appearance sparks comments about how artificial intelligence is going to completely transform the world. This is pretty good PR for a chatbot in a robot suit.

But it’s also riding the hype around artificial intelligence, and more importantly, people’s uncertainty around what constitutes artificial intelligence, what can feasibly be done with it, and how close various milestones may be.

There are various definitions of artificial intelligence.

For example, there’s the cultural idea (from films like Ex Machina, for example) of a machine that has human-level artificial general intelligence. But human-level intelligence or performance is also seen as an important benchmark for those that develop software that aims to mimic narrow aspects of human intelligence, for example, medical diagnostics.

The latter software might be referred to as narrow AI, or weak AI. Weak it may be, but it can still disrupt society and the world of work substantially.

Then there’s the philosophical idea, championed by Ray Kurzweil, Nick Bostrom, and others, of a recursively-improving superintelligent AI that eventually compares to human intelligence in the same way as we outrank bacteria. Such a scenario would clearly change the world in ways that are difficult to imagine and harder to quantify; weighty tomes are devoted to studying how to navigate the perils, pitfalls, and possibilities of this future. The ones by Bostrom and Max Tegmark epitomize this type of thinking.

This, more often than not, is the scenario that Stephen Hawking and various Silicon Valley luminaries have warned about when they view AI as an existential risk.

Those working on superintelligence as a hypothetical future may lament for humanity when people take Sophia seriously. Yet without hype surrounding the achievements of narrow AI in industry, and the immense advances in computational power and algorithmic complexity driven by these achievements, they may not get funding to research AI safety.

Some of those who work on algorithms at the front line find the whole superintelligence debate premature, casting fear and uncertainty over work that has the potential to benefit humanity. Others even call it a dangerous distraction from the very real problems that narrow AI and automation will pose, although few actually work in the field. But even as they attempt to draw this distinction, surely some of their VC funding and share price relies on the idea that if superintelligent AI is possible, and as world-changing as everyone believes it will be, Google might get there first. These dreams may drive people to join them.

Yet the ambiguity is stark. Someone working on, say, MIT Intelligence Quest or Google Brain might be attempting to reach AGI by studying human psychology and learning or animal neuroscience, perhaps attempting to simulate the simple brain of a nematode worm. Another researcher, who we might consider to be “narrow” in focus, trains a neural network to diagnose cancer with higher accuracy than any human.

Where should something like Sophia, a chatbot that flatters to deceive as a general intelligence, sit? Its creator says: “As a hard-core transhumanist I see these as somewhat peripheral transitional questions, which will seem interesting only during a relatively short period of time before AGIs become massively superhuman in intelligence and capability. I am more interested in the use of Sophia as a platform for general intelligence R&D.” This illustrates a further source of confusion: people working in the field disagree about the end goal of their work, how close an AGI might be, and even what artificial intelligence is.

Stanford’s Jerry Kaplan is one of those who lays some of the blame at the feet of…Continue reading

 

Article source: https://singularityhub.com/2018/06/20/why-we-need-to-fine-tune-our-definition-of-artificial-intelligence/ 

Advertisements

10 ways AI will impact the enterprise in 2018

Technology, Artificial Intelligence
Image: iStockphoto/chombosan

By  | January 4, 2018

Artificial intelligence (AI) and machine learning are buzzwords that have entered the vernacular at many enterprises, but few have managed to realize the full benefits of the technologies. But 2018 may be the year that companies begin more strategic implementations and start realizing some of AI’s benefits.

“The percolation of AI and machine learning technologies into businesses still seems to be in its early stages, ranging over awareness that they need to collect data, to awareness that they already have a lot of data but are not making productive use of it, to rudimentary analyses of these data,” said Pradeep Ravikumar, Associate Professor, Machine Learning Department, School of Computer Science, Carnegie Mellon University.

AI will continue to be a fast-moving field in the coming year, and it’s critical for companies to have close contact and collaborations with those in the AI research community to stay on the cutting edge, Ravikumar said.

“From autonomous drones to AI-powered medical diagnostics, 2018 will see the needs of AI expand beyond research as companies bring these solutions to market,” said Julie Choi, head of marketing in the Artificial Intelligence Products Group at Intel. AI hardware will also need to adapt to new form factors, including low-power chips to support small smart home devices or drones, and more purpose-built hardware to speed the training process in data centers, Choi said.

Here are 10 predictions for how AI will grow and the challenges it will face in the enterprise this year.

1. More AI professionals will be hired

In efforts to realize the benefits of AI, companies will hire a variety of professionals to contribute, according to Alex Jaimes, head of R&D at DigitalOcean. Larger organizations may look to add a Chief AI Officer or other senior-level position who will guide how AI and machine learning can be integrated into the company’s existing products and strategy. Others may look at hire…Continue Reading

 

Article source: https://www.techrepublic.com/article/10-ways-ai-will-impact-the-entierprise-in-2018/

Artificial Intelligence Is Killing the Uncanny Valley and Our Grasp on Reality

Artificial Intelligence, Technology
Image Credit: LAURENT HRYBYK

By , Backchannel Executive Editor

There’s a revolution afoot, and you will know it by the stripes.

Earlier this year, a group of Berkeley researchers released a pair of videos. In one, a horse trots behind a chain link fence. In the second video, the horse is suddenly sporting a zebra’s black-and-white pattern. The execution isn’t flawless, but the stripes fit the horse so neatly that it throws the equine family tree into chaos.

Turning a horse into a zebra is a nice stunt, but that’s not all it is. It is also a sign of the growing power of machine learning algorithms to rewrite reality. Other tinkerers, for example, have used the zebrafication tool to turn shots of black bears into believable photos of pandas, apples into oranges, and cats into dogs. A Redditor used a different machine learning algorithm to edit porn videos to feature the faces of celebrities. At a new startup called Lyrebird, machine learning experts are synthesizing convincing audio from one-minute samples of a person’s voice. And the engineers developing Adobe’s artificial intelligence platform, called Sensei, are infusing machine learning into a variety of groundbreaking video, photo, and audio editing tools. These projects are wildly different in origin and intent, yet they have one thing in common: They are producing artificial scenes and sounds that look stunningly close to actual footage of the physical world. Unlike earlier experiments with AI-generated media, these look and sound real.

The technologies underlying this shift will soon push us into new creative realms, amplifying the capabilities of today’s artists and elevating amateurs to the level of seasoned pros. We will search for new definitions of creativity that extend the umbrella to the output of machines. But this boom will have a dark side, too. Some AI-generated content will be used to deceive, kicking off fears of an avalanche of algorithmic fake news. Old debates about whether an image was doctored will give way to new ones about the pedigree of all kinds of content, including text. You’ll find yourself wondering, if you haven’t yet: What role did humans play, if any, in the creation of that album/TV series/clickbait article?

A world awash in AI-generated content is a classic case of a utopia that is also a dystopia. It’s messy, it’s beautiful, and it’s already here. Continue reading

 

Article source: https://www.wired.com/story/future-of-artificial-intelligence-2018/

How AI Is Being Used To Prove Authenticity In The Art World

Art, Paintings, Forgeries, Artificial Intelligence, AI
Image source: psfk.com

By MATT VITONE |Originally published 30 NOVEMBER 2017

Artificial intelligence is already able to imitate the work of great artists, so why shouldn’t it also be able to spot genuine works from forgeries? In a new paper, researchers at Rutgers University in New Jersey and the Atelier for Restoration & Research of Paintings in the Netherlands examined how machine learning can be harnessed to more effectively spot fakes.

The researchers tested the AI using a data set of 300 digitized drawings consisting of over 80,000 strokes from artists including Pablo Picasso, Henry Matisse and Egon Schiele, among others. Using a deep recurrent neural network (RNN), the AI was able to learn which strokes were typical of each artist, and then used that information to make educated guesses.

The results showed that the AI was able to identify the individual strokes with an accuracy of between 70 to 90%. The researchers also commissioned artists to create fake drawings similar to the originals in the AI’s data set, and in most test settings it was able to detect forgeries with 100% accuracy, simply by looking at a single brushstroke.

The use of artificial intelligence in art has…Continue reading

Article source: https://www.psfk.com/2017/11/ai-prove-authenticity-art-world.html

AI and machine learning in sales: Everything you need to know for the future

AI, Artificial Intelligence, Sales, Business
Image source: the-future-of-commerce.com
Originally posted November 29, 2017
Swati Sinha

“Innovation distinguishes between a leader and a follower.” -Steve Jobs

Organizations are transforming their sales functions with artificial intelligence to stay ahead of the game. If you have not yet embraced the trend, you are missing a crucial competitive edge.

The emergence of vast amounts of data from multiple sources and platforms, generating new information every minute, has gifted companies with more consumer information than they’ve ever had before. Technology is getting smarter as it continues learning and optimizing recommendations. A study published in MIT Sloan Management Review reveals that “76% of early adopters are targeting higher sales growth with machine learning.”

AI and machine learning in sales: An explainer

Artificial intelligence is the broader concept of machines making decisions or performing process as a human would. Machine learning is an application of artificial intelligence that enables computer models to recognize shapes, designs, and patterns in existing data, allowing the machines to then learn for themselves how to take next action or make business predictions.

Each new piece of data received allows the machine to learn even more, update information, look for new patterns and continuously optimize recommendations. For example, every time Alexa doesn’t get the right command, or Netflix misses the movie recommendation, the model learns from this new data and alters its recognition process to adapt and respond better, or provide better suggestions the next time around.

Intelligent sales: From prospect to client, AI will be sales best friend

We are seeing a paradigm shift in sales from being reactive to proactive, and from instinct-driven to insight and data-driven. AI can guide the sales journey from identification to customer retention. Sales applications can pick up each…Continue reading

Article source” http://www.the-future-of-commerce.com/2017/11/29/ai-and-machine-learning-in-sales/

How artificial intelligence is revolutionizing healthcare

artificial intelligence, healthcare, technology
Image source: thenextweb.com

by — 5 weeks ago in ARTIFICIAL INTELLIGENCE

There’s currently a shortage of over seven million physicians, nurses and other health workers worldwide, and the gap is widening. Doctors are stretched thin — especially in underserved areas — to respond to the growing needs of the population.

Meanwhile, training physicians and health workers is historically an arduous process that requires years of education and experience.

Fortunately, artificial intelligence can help the healthcare sector to overcome present and future challenges. Here’s how AI algorithms and software are improving the quality and availability of healthcare services.

AI health assistants

One of the most basic yet efficient use cases of artificial intelligence is to optimize the clinical process. Traditionally, when patients feel ill, they go to the doctor, who checks their vital signs, asks questions, and gives a prescription. Now, AI assistants can cover a large part of clinical and outpatient services, freeing up doctors’ time to attend to more critical cases.

Your.MD is an AI-powered mobile app that provides basic healthcare. The chatbot asks users about…Continue reading

Article source: https://thenextweb.com/artificial-intelligence/2017/04/13/artificial-intelligence-revolutionizing-healthcare/#.tnw_6h2qZTV0

In the Age of AI, Our Human Workforce Must Remain Relevant

AI, Artificial Intelligence, TechnologyIn the Age of AI, Our Human Workforce Must Remain Relevant
By Kym Gordon Moore

As artificial intelligence (AI) technologies are developing how can we ensure that the well-being of human value and the human experience remain significant? AI is becoming faster and more human-like, but questions are being raised whether or not this technology is a prerequisite to the alienation and extinction of solid human workforces. Can such know-how as the rise of quantum computing go awry? By all accounts, artificial intelligence whether we like it or not is here for the long run.

With the proliferation of AI technology comes the trepidation of what will become of the human workforce as we know it. We must find common ground to merge the two together without severing our human labor force. Aside from businesses expecting their revenues to increase and costs to decrease significantly, there are also ethical concerns involved in the application of artificial intelligence. Here are a few considerations organizations should keep in mind:

Article source: http://ezinearticles.com/?In-the-Age-of-AI,-Our-Human-Workforce-Must-Remain-Relevant&id=9631131