ARTIFICIAL INTELLIGENCE

Just what do we know about Artificial Intelligence or AI?  Portions of this post were taken from Forbes Magazine.

John McCarthy first coined the term artificial intelligence in 1956 when he invited a group of researchers from a variety of disciplines including language simulation, neuron nets, complexity theory and more to a summer workshop called the Dartmouth Summer Research Project on Artificial Intelligence to discuss what would ultimately become the field of AI. At that time, the researchers came together to clarify and develop the concepts around “thinking machines” which up to this point had been quite divergent. McCarthy is said to have picked the name artificial intelligence for its neutrality; to avoid highlighting one of the tracks being pursued at the time for the field of “thinking machines” that included cybernetics, automation theory and complex information processing. The proposal for the conference said, “The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”

Today, modern dictionary definitions focus on AI being a sub-field of computer science and how machines can imitate human intelligence (being human-like rather than becoming human). The English Oxford Living Dictionary gives this definition: “The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”

Merriam-Webster defines artificial intelligence this way:

1. A branch of computer science dealing with the simulation of intelligent behavior in computers.
2. The capability of a machine to imitate intelligent human behavior.

About thirty (30) year ago, a professor at the Harvard Business School (Dr. Shoshana Zuboff) articulated three laws based on research into the consequences that widespread computing would have on society. Dr. Zuboff had degrees in philosophy and social psychology so she was definitely ahead of her time relative to the unknown field of AI.  Her document “In the Age of the Smart Machine: The Future of Work and Power”, she postulated the following three laws:

• Everything that can be automated will be automated
• Everything that can be informated will be informated. (NOTE: Informated was coined by Zuboff to describe the process of turning descriptions and measurements of activities, events and objects into information.)
• In the absence of countervailing restrictions and sanctions, every digital application that can be sued for surveillance and control will be used for surveillance and control, irrespective of its originating intention.

At that time there was definitely a significant lack of computing power.  That ship has sailed and is no longer a great hinderance to AI advancement that it certainly once was.

 

WHERE ARE WE?

In recent speech, Russian president Vladimir Putin made an incredibly prescient statement: “Artificial intelligence is the future, not only for Russia, but for all of humankind.” He went on to highlight both the risks and rewards of AI and concluded by declaring that whatever country comes to dominate this technology will be the “ruler of the world.”

As someone who closely monitors global events and studies emerging technologies, I think Putin’s lofty rhetoric is entirely appropriate. Funding for global AI startups has grown at a sixty percent (60%) compound annual growth rate since 2010. More significantly, the international community is actively discussing the influence AI will exert over both global cooperation and national strength. In fact, the United Arab Emirates just recently appointed its first state minister responsible for AI.

Automation and digitalization have already had a radical effect on international systems and structures. And considering that this technology is still in its infancy, every new development will only deepen the effects. The question is: Which countries will lead the way, and which ones will follow behind?

If we look at criteria necessary for advancement, there are the seven countries in the best position to rule the world with the help of AI.  These countries are as follows:

• Russia
• The United States of America
• China
• Japan
• Estonia
• Israel
• Canada

The United States and China are currently in the best position to reap the rewards of AI. These countries have the infrastructure, innovations and initiative necessary to evolve AI into something with broadly shared benefits. In fact, China expects to dominate AI globally by 2030. The United States could still maintain its lead if it makes AI a top priority and charges necessary investments while also pulling together all required government and private sector resources.

Ultimately, however, winning and losing will not be determined by which country gains the most growth through AI. It will be determined by how the entire global community chooses to leverage AI — as a tool of war or as a tool of progress.

Ideally, the country that uses AI to rule the world will do it through leadership and cooperation rather than automated domination.

CONCLUSIONS:  We dare not neglect this disruptive technology.  We cannot afford to lose this battle.

ARTIFICIAL INTELLIGENCE & ELON MUSK

Elon Musk has warned again about the dangers of artificial intelligence, saying that it poses “vastly more risk” than the apparent nuclear capabilities of North Korea does. I feel sure Mr. Musk is talking about the long-term dangers and not short-term realities.   Mr. Musk is shown in the digital picture below.

This is not the first time Musk has stated that AI could potentially be one of the most dangerous international developments. He said in October 2014 that he considered it humanity’s “biggest existential threat”, a view he has repeated several times while making investments in AI startups and organizations, including Open AI, to “keep an eye on what’s going on”.  “Got to regulate AI/robotics like we do food, drugs, aircraft & cars. Public risks require public oversight. Getting rid of the FAA would not make flying safer. They’re there for good reason.”

Musk again called for regulation, previously doing so directly to US governors at their annual national meeting in Providence, Rhode Island.  Musk’s tweets coincide with the testing of an AI designed by OpenAI to play the multiplayer online battle arena (Moba) game Dota 2, which successfully managed to win all its 1-v-1 games at the International Dota 2 championships against many of the world’s best players competing for a $24.8m (£19m) prize fund.

The AI displayed the ability to predict where human players would deploy forces and improvise on the spot, in a game where sheer speed of operation does not correlate with victory, meaning the AI was simply better, not just faster than the best human players.

Musk backed the non-profit AI research company OpenAI in December 2015, taking up a co-chair position. OpenAI’s goal is to develop AI “in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return”. But it is not the first group to take on human players in a gaming scenario. Google’s Deepmind AI outfit, in which Musk was an early investor, beat the world’s best players in the board game Go and has its sights set on conquering the real-time strategy game StarCraft II.

Musk envisions a situation found in the movie “i-ROBOT with humanoid robotic systems shown below.  Robots that can think for themselves. Great movie—but the time-frame was set in a future Earth (2035 A.D.) where robots are common assistants and workers for their human owners, this is the story of “robotophobic” Chicago Police Detective Del Spooner’s investigation into the murder of Dr. Alfred Lanning, who works at U.S. Robotics.  Let me clue you in—the robot did it.

I am sure this audience is familiar with Isaac Asimov’s Three Laws of Robotics.

• First Law: A robot may not injure a human being, or, through inaction, allow a human being to come to harm.
• Second Law: A robot must obey orders given it by human beings, except where such orders would conflict with the First Law.
• Third Law: A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

Asimov’s three laws indicate there will be no “Rise of the Machines” like the very popular movie indicates.   For the three laws to be null and void, we would have to enter a world of “singularity”.  The term singularity describes the moment when a civilization changes so much that its rules and technologies are incomprehensible to previous generations. Think of it as a point-of-no-return in history. Most thinkers believe the singularity will be jump-started by extremely rapid technological and scientific changes. These changes will be so fast, and so profound, that every aspect of our society will be transformed, from our bodies and families to our governments and economies.

A good way to understand the singularity is to imagine explaining the internet to somebody living in the year 1200. Your frames of reference would be so different that it would be almost impossible to convey how the internet works, let alone what it means to our society. You are on the other side of what seems like a singularity to our person from the Middle Ages. But from the perspective of a future singularity, we are the medieval ones. Advances in science and technology mean that singularities might happen over periods much shorter than 800 years. And nobody knows for sure what the hell they’ll bring.

Author Ken MacLeod has a character describe the singularity as “the Rapture for nerds” in his novel The Cassini Division, and the turn of phrase stuck, becoming a popular way to describe the singularity. (Note: MacLeod didn’t actually coin this phrase – he says he got the phrase from a satirical essay in an early-1990s issue of Extropy.) Catherynne Valente argued recently for an expansion of the term to include what she calls “personal singularities,” moments where a person is altered so much that she becomes unrecognizable to her former self. This definition could include post-human experiences. Post-human (my words) would describe robotic future.

Could this happen?  Elon Musk has an estimated net worth of $13.2 billion, making him the 87th richest person in the world, according to Forbes. His fortune owes much to his stake in Tesla Motors Inc. (TSLA), of which he remains CEO and chief product architect. Musk made his first fortune as a cofounder of PayPal, the online payments system that was sold to eBay for $1.5 billion in 2002.  In other words, he is no dummy.

I think it is very wise to listen to people like Musk and heed any and all warnings they may give. The Executive, Legislative and Judicial branches of our country are too busy trying to get reelected to bother with such warnings and when “catch-up” is needed, they always go overboard with rules and regulations.  Now is the time to develop proper and binding laws and regulations—when the technology is new.

ARTIFICIAL INTELLIGENCE (AI)

Portions of the following post were taken from an article by Rob Spiegel publishing through Design News Daily.

Two former Apple design engineers – Anna Katrina Shedletsky and Samuel Weiss have leveraged machine learning to help brand owners improve their manufacturing lines. The company, Instrumental , uses artificial intelligence (AI) to identify and fix problems with the goal of helping clients ship on time. The AI system consists of camera-equipped inspection stations that allow brand owners to remotely manage product lines at their contact manufacturing facilities with the purpose of maximizing up-time, quality and speed. Their digital photo is shown as follows:

Shedletsky and Weiss took what they learned from years of working with Apple contract manufacturers and put it into AI software.

“The experience with Apple opened our eyes to what was possible. We wanted to build artificial intelligence for manufacturing. The technology had been proven in other industries and could be applied to the manufacturing industry,   it’s part of the evolution of what is happening in manufacturing. The product we offer today solves a very specific need, but it also works toward overall intelligence in manufacturing.”

Shedletsky spent six (6) years working at Apple prior to founding Instrumental with fellow Apple alum, Weiss, who serves Instrumental’s CTO (Chief Technical Officer).  The two took their experience in solving manufacturing problems and created the AI fix. “After spending hundreds of days at manufacturers responsible for millions of Apple products, we gained a deep understanding of the inefficiencies in the new-product development process,” said Shedletsky. “There’s no going back, robotics and automation have already changed manufacturing. Intelligence like the kind we are building will change it again. We can radically improve how companies make products.”

There are number examples of big and small companies with problems that prevent them from shipping products on time. Delays are expensive and can cause the loss of a sale. One day of delay at a start-up could cost $10,000 in sales. For a large company, the cost could be millions. “There are hundreds of issues that need to be found and solved. They are difficult and they have to be solved one at a time,” said Shedletsky. “You can get on a plane, go to a factory and look at failure analysis so you can see why you have problems. Or, you can reduce the amount of time needed to identify and fix the problems by analyzing them remotely, using a combo of hardware and software.”

Instrumental combines hardware and software that takes images of each unit at key states of assembly on the line. The system then makes those images remotely searchable and comparable in order for the brand owner to learn and react to assembly line data. Engineers can then take action on issues. “The station goes onto the assembly line in China,” said Shedletsky. “We get the data into the cloud to discover issues the contract manufacturer doesn’t know they have. With the data, you can do failure analysis and reduced the time it takes to find an issue and correct it.”

WHAT IS AI:

Artificial intelligence (AI) is intelligence exhibited by machines.  In computer science, the field of AI research defines itself as the study of “intelligent agents“: any device that perceives its environment and takes actions that maximize its chance of success at some goal.   Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

As machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition. For instance, optical character recognition is no longer perceived as an example of “artificial intelligence”, having become a routine technology.  Capabilities currently classified as AI include successfully understanding human speech,  competing at a high level in strategic game systems (such as chess and Go), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data.

FUTURE:

Some would have you believe that AI IS the future and we will succumb to the “Rise of the Machines”.  I’m not so melodramatic.  I feel AI has progressed and will progress to the point where great time saving and reduction in labor may be realized.   Anna Katrina Shedletsky and Samuel Weiss realize the potential and feel there will be no going back from this disruptive technology.   Moving AI to the factory floor will produce great benefits to manufacturing and other commercial enterprises.   There is also a significant possibility that job creation will occur as a result.  All is not doom and gloom.