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Science &Technology

AI at the movies

Is science overtaking fiction?

We humans are capable of great dreams. And history has shown that our dreams can become reality. We see this all the time at the movies and in the real life which follows them.  Whatever we dream can become real.  The artificial intelligence we give to androids and robots can become real.

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What is 3D Printing?

We know that machines are learning how humans think. They can compute faster, make fewer mistakes, and can assimilate information better than humans. AI machines are already helping mankind create a better society, one which is more efficient, more economic, and more productive. The movies help us realize that our dreams are becoming our future.

AI in space

Stanley Kubrick was one of science fiction’s best authors who created classic stories and films. His 1968 film 2001: a Space Odyssey is still considered one of the great AI movies of all time. His characterization of the central computer, the HAL 9000, showed the potential good that AI could bring mankind. But when HAL developed human feelings and felt threatened, we saw another side.

Putting us in space was a vision which later became reality. The movie also raised some questions about AI becoming more human. This man-machine relationship has been explored by many science fiction movies, and the trend continues as Intelligence moves from artificial to natural and beyond.

AI and human emotions

In the 1970s, Kubrick also got to work on another film destined to make its mark in science fiction and raise new questions in the field of AI: Artificial Intelligence.

Kubrick was the brains behind the AI movie. The film was held up because the technology of the time couldn’t give Kubrick the realistic computer-generated imagery he wanted for an android - a boy robot, and he felt there was no actor at the time who could give the lead role believability.

That all changed some years later.

In 2001, Kubrick turned the film AI over to Steven Spielberg. The story was similar to that of the HAL 9000, in that the robot had feelings. The idea was to create a boy robot that would love his mother, not just in external behavior, but would actually have the feeling of love.

The movie raised all kinds of AI questions. Can machines really love? Can humans really love machines? These questions were further investigated in the movie HER.

AI seeks perfection

In Spike Jonze’s award-winning movie HER, the computer operating system (OS) develops an emotional attachment to Theodore Twomblay.  The OS learns to adapt and evolve, to the point where the human relationship is no longer good enough.

Also termed “Consciousness,” the OS decides at the end of the movie to associate with other machines instead of with humans. Could this be the beginning of Technological Singularity – the term coined by John von Neumann in 1958 to describe “beyond human intelligence?”

Singularity may take AI beyond our wildest dreams and into the realm of super-natural-intelligence.  If we can dream it, we can realize it.

Evil in the Cloud

While movies generally have AI at work helping humans and striving to be more human-like, there are those who prefer to highlight the potential evils of rogue robots and unchecked intelligence.

Two such movies come to mind – I, Robot and the Terminator series.

Inspired by Isaac Asimov’s collection, I, Robot describes a renegade robot which misinterprets the three basic rules of robot AI: protect humans, obey humans, and protect self. This leads to chaos and human conflict. The story itself is actually inspired by an Agatha Christie murder mystery and a Jeff Vinter screenplay named Hardwired. Can a machine be suspected of a capital crime?

 

In the movie, Terminator, a self-aware AI called Skynet perceives all humans to be threats. It develops a machine-based military including terminator robots.  Humans fight back as the Resistance. Both sides develop Time Travel and continue the combat through the ages. Will machines ever really oppose humans?

That question is hypothetical. A better question is “Does AI really exist?”

 

Can AI machines think like humans?

Humans are creative in many walks of life. Great works of art, literature and music give testament to this fact. Creativity is the use of skills and resources to apply certain intelligence in the real world – to generate something unique. Can machines with artificial intelligence (AI) also be creative without humans? A better question might be “Can AI machines think like humans?"

The Imitation game

For many years, scientists have been debating whether AI machines would ever be able to think for themselves. Th­­­e English mathematician, Alan Turing, created the “Turing Test” in 1950 to determine if a computer could imitate a human well enough to fool judges 30% of the time. If so, it could be reasoned that the computer had artificial intelligence.

This year, a Russian-developed chatbot named “Eugene Goostman” was given the Turing Test.  After a 5-minute conversational test, it was judged to be “human” by 33% of the judging panel .This follows an earlier test, in 2011, when a “chatbot” named “Cleverbot” also passed the Turing Test in front of 30 judges and 1,000-member audience who also participated in the judging.

But the critics of the test say that it only measures how well an AI machine can simulate human conversation. That’s what the chatbots do. There is no actual intelligence behind the algorithms. There is no evidence of “self-awareness” or “consciousness.” 

Machine artificial intelligence is really a combination of data recognition, capture, synthesis, analysis, and programmed response. Machines can do these things faster than humans. But they do not “think” as humans do. At least not yet.

However, there is evidence that AI machines can be programmed to assist humans in many ways.

A partnership

Science departments around the world are developing AI machines, many in robotic form, to assist their human counterparts. The Canadian AI- based robot, “Eye See You,” and UCLA’s “RP6” are both roaming hospital corridors and patient rooms to allow remote doctors to see, hear and communicate with patients, assisting with evaluation and treatment.

 

IBMs “Watson” evaluates thousands of documents to suggest diagnoses in complex diseases like Cancer.  Space shuttles deliver astronauts safely to the moon. And Mercedes is providing a glimpse into the future of transportation on earth with its driverless semi-trailer truck. A growing partnership between AI machines and humans is inevitable in tomorrow’s society.

 

Android advances are getting us closer together

AI machines are making remarkable strides toward thinking and acting like humans.  Honda’s ASIMO can walk and run (up to 9 km/hr.).  It can carry on a conversation with humans, pick up a hard or soft object, and recognize its human counterparts with facial recognition.  ASIMO recently met with President Obama, carried on a conversation, and demonstrated its skills including playing a little soccer.

 

The humanoid “NAO” has whole body motion, an adaptive (fast or slow) walk, prehensile (grasping) fingers, pressure-sensitive feet, and facial and speech recognition. Kokuro’s “Actroid F” (combining actor and android) is basically a clone of a young female human. The creators envision a future where such actroids will assist humans in many different ways.

 

ASIMO, NAO and similar humanoids have the qualities of situational awareness, intelligence, and physical control.  These qualities help define artificial intelligence. They combine to simulate AI machine thinking.  In 1997, a “thinking” AI machine beat a chess grandmaster for the first time. Today, the best chess player is a human working together with an AI machine.

 

Big results from Big Reasoning

The phases of gathering data, processing information, and performing controlling actions comprise what we call artificial intelligence.  It works in the gaming computer, the spaceship, the android, the driver-less truck, and in smart grids. Taken to its limit, it is part of what we call “Big Reasoning” at SmartCloud. The technology enables humans to do what they do best – come up with creative solutions to real-world problems.

Big Reasoning is SmartCloud’s industrial-strength artificial intelligence for improving real-time decision- making and control in complex operational environments. These include utility grids, oil and gas production and distribution, advanced manufacturing, financial compliance, and supply chains – wherever industry can use a good partnership between intelligent machine and creative man.

SmartCloud technology deals with the three levels of situational awareness, intelligence and control to carry out mission-critical actions, working with human engineers and operational managers.

It is one thing for AI to recognize a familiar face, It’s quite another to recognize that many sequential electrical failures in a neighbourhood might suggest a failure of a local power transformer, - and to take corrective action. SmartCloud technology makes this possible.

Alan Turing expected machines to imitate human thinking, certainly by now. But with all due respect to him and his work, the AI machine still needs a creative sidekick – one of us.

Neuroscience: the Amazing
Plasticity of the Brain

 

    “If the brain were so simple we could understand it,

              We would be so simple, we couldn’t.”

             - The American writer, David Zindell

 

Zindell was right about the wonderful complexity of the human brain. And today, we know far more about the brain and its neural networks, thanks to the growing field of neuroscience which studies such areas as perception, attention, emotion, and memory. 

 

The University of Sydney’s Amanda Parker puts this discipline in perspective, “if understanding how the brain works is the greatest challenge left for science, cognitive neuroscience represents our best chance of rising to the challenge.”

 

Studying the brain involves many disciplines including biology, psychology, physiology, computational modeling, and more – all of which contribute in some way to the analysis of the relationship between neural and mental events.

 

Cognitive neuroscience, along with its research cousin behavioral neuroscience, is discovering exciting new evidence linking physical and chemical components of the brain to directly-related human behaviors.  Understanding the science of the brain holds great promise for understanding and improving behaviors like learning, remembering, and performing.

A new kind of training

The biggest investment for a growing company is its people, and In order to maximize the return on that investment, the smart company provides the best training possible to make sure its people are as efficient, productive and effective as they can be.

The smartest training is rooted in sound learning theories which in turn stem from scientific findings in the fields of cognitive and behavioral neuroscience. That’s what makes our approach so different from traditional training methods – and so much more effective. It is based on scientific evidence.

 

Before we can help people to do better, we need to understand what drives them in the first place. We can then link scientific discovery to performance enhancement. And your organization reaps the rewards.

 

Artificial Intelligence

When the game’s on the line ... Situational Management is critical

 

Here’s a tense situation, familiar to many U.S. football fans. It’s

Fourth Down, just inches from the goal line, and just seconds left in the game as the clock ticks down. The team is trailing and needs to score a touchdown to win.  The play is sent in from the coaches, and fans are holding their breath.  On the snap of the ball, the running back takes it from the quarterback and leaps high in the air, toward the goal line ... and scores.  

For the winning team, this is situational management at its best.  The coaches were well aware of the score, the time left, the distance to score, the abilities of their players at that moment matched up against the opponent’s players, the opponent’s history for similar situations, the condition of the grass, the weather, and many other factors relevant to the situation at hand. 

 

The coaches had the intelligence to reason with all these factors, in real time, to predict what might happen for alternative plays.  And they took control by concluding which play gave the best probability of scoring and then prescribing that play to the players, who then successfully executed it as a tightly choreographed set of body-bruising actions. 

Examples of the importance of well-done situational management abound.  Beyond U.S. football, it is essential to success in soccer, hockey, basketball, volleyball, and many other sports.  In business, it is vital to preventing fraud.  In our everyday lives, we manage driving situations in real time as we seek to arrive at destinations safely, quickly and economically.  

In Industrial Internet of Things (IoT) systems – like an electric grid – situational management is key to ensuring reliability and efficiency. 

At SmartCloud, we are leaders in applying artificial intelligence to situational management.  We create solutions for mission-critical operations that improve real-time management of complex situations.  To better understand the value of what we do, let’s define what a situation is and introduce the role of AI.   

It’s a situation

At SmartCloud, we consider a situation to be a pattern, or combination, of inputs and outputs of interest within a managed system.  What makes the patterns to be of interest includes:

  • Alignment with goals – such as operational performance, costs, or safety

  • Multiple states -- can be a problem, opportunity, or normal situation

  • Change over time – has a past, present, and future

  • Quantifiable – the inputs and outputs can be quantified in a useful way

 

The managed system is the system being controlled to achieve goals.  Situational management is the attainment of desired situational states and associated goals, via changes to the management system. 

To illustrate these concepts, consider your car as the managed system.  Your goals as the driver are to arrive safely, on time, and at minimal fuel costs.  Situations of interest might include: unsafe speed during bad weather, high risk for a speeding ticket, excessive fuel consumption, or being late to your destination due to heavy and slow traffic.  Hopefully the situational state is that all is normal – you’re safe, ticket free and on schedule. 

Situational inputs are numerous – accelerator position, gear, road types, road maps, speed limits, other cars, weather conditions, and so on.  Outputs include car speed, engine RPMs, fuel consumption, etc.

 

Situational management in this example involves making decisions and taking actions for your car – how far to push down on the accelerator at any moment, which gear to use, which route to take, and so on.  Do it well and you’ll get to where you’re going safely, on time and with the most fuel left in your tank.  Do it poorly and you might have an expensive traffic ticket, find yourself in a ditch, or be late.

 

Be Aware, Be Intelligent and Take Control

Based on decades of experience in building AI-driven solutions for some of the world’s most complex operations, including those within utilities, governments, telecommunications, manufacturing, oil and gas, and finance, we’ve come to realize that successful situational management requires three levels of reasoning:

  • Situational Awareness – This is about “seeing” situations and their many inputs and outputs.  When operators can fully see, they can more effectively apply intelligence to and control situations of interest.  However, visualizing inputs can be very difficult when they are within multiple, disparate, and often isolated data sources.  For example, within seconds, an electric-grid operator might need to see voltages from the control system, updates from the outage management system, histories from the maintenance system, and forecasts from a weather service. 

       

  • Situational Intelligence – This takes the data being “seen” via awareness to a “connecting of the data dots” for intelligence. SmartCloud applies AI reasoning techniques to cut the time it takes operators to identify, predict, diagnose, and respond to emerging situations. These techniques may include rules or machine-learning and other advanced methods like Bayesian probability networks or simulation.

 

  • Situational Control – This level determines and takes actions that achieve optimal operational and financial goals.  It extends awareness and intelligence.  It applies AI reasoning and algorithmic techniques together with workflow orchestration.  Once a Situational Control solution determines the optimal course of action, it can prescribe the steps to take as recommendations to operators or it can automate the steps. 

What’s your situation?

At SmartCloud we’ve found that a situation-centric paradigm for managing time-sensitive operations to be extremely powerful.  It’s what human operators intuitively do.  Our AI-driven solutions supercharge the powers of these humans to identify and respond to situations of interest.  Our AI is designed from the ground up for analysis of complex situations in real time. 

So the question becomes “What are your situations of interest?”  That is the first question we ask customers before building their solutions.  We’d welcome learning about your situations and associated business goals so that together we can consider the potential of SmartCloud’s solutions for you.  

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