Digital Twin: the 2018 agile wind tunnel with quantum future

Digital Twins enable testing of real world testing of complex systems. The concept of living test lab has been dream for testers. Digital Twins are not static, but allow for constant new input based on the real world from IoT sensors. Digital Twins make use of AI, Machine Learning, and IoT to simulate complex system behaviors. IBM is working in our labs and with our clients to find exciting new ways to use and create digital twins.

When flight first started, a man had to risk his life to test each innovation. An innovation had a high threshold since the bet was a human life. Eventually, engineers built wind tunnels where they could simulate the effect of the air flow over the plane. While it no longer was risking a life, it had limitations on size (can’t fit an entire 747 in wind tunnel), was artificial, and was costly.  Also how do you simulate more complex events like sudden down drafts, lightening strikes, rough landings, wear and tear over years (metal fatigue, corrosion)? Now with digital twin, you can test the effect of changes to the digital twin of the airplane. We can run 100’s or 1,000’s of changes and combinations of changes to identify the impacts. Only the best of these changes will be put into use.

The while the changes put into use could be small, similar to agile built software application, they would add up to significant impacts. The feedback from the IoT devices in the real world will then update the digital twin allowing new sets of changes to be developed, deployed, and tested before the best combinations are rolled out in rapid succession. As most planes are now fly by wire and highly digital, incremental changes are possible to many of the systems. Today it might not be possible to reshape physical parts like wings, fuselage and rudders, but maybe in the future technologies could reshape the surface to change physical parts of the plane. Clearly there would need to be progression from test bed, to unmanned, to test flights before it went into passenger aircraft, but the rate of innovation in safety related industry goes up by orders magnitude and the risk and costs come down proportionally, too.

The ability to try millions and even billions of combinations in each digital twin is not yet possible as it would overwhelm the compute power of traditional binary computers. The rapidly evolving Quantum Computer may provide the power required to make machine learning nearly unlimited in capacity enabling deep learning and unlimited numbers of combinations of factors in our digital twins. You can even try out quantum for yourself in IBM’s DevOp environment – bluemix.

Benefits of digital twins can apply to almost any machine, group of machines, or ecosystem of lots of groups of machines. I wonder if in the future, a quantum digital twin could be more complex and subtle in its simulation than the real world. As of today, our models of reality pale in complexity to the real world. Below is simply mind map machine systems with a focus on transportation machines. It shows how digital twins can use data from other digital twins. It is model composed of multiple models.

A network of machine ecosystems that can become digital twins

How could a digital twin help your industry? How can you take advantage of a digital twin to improve the quality of life and leverage the vast amount of data pouring out from mushrooming number of IoT sensors? It is an exciting problem to explore with real business implications.

If IBM Watson (AI) is so smart, why isn’t Watson able tell IBM how to make billions dollars?

“If IBM Watson (AI) is so smart, why isn’t Watson able to tell IBM how to make billions dollars? Can’t you just ask Watson how to make more money?” It was an earnest question from a skeptical client. We all want an oracle we can ask.

I answered “IBM Watson can’t just know how to make money. It has to be taught first by humans. A person must teach Watson the knowledge and then Watson can expand on it.” The simple answer is IBM Watson is similar to all Artificial Intelligence (AI) tools. It is just a tool and not an all-seeing, all-knowing oracle. Buying a chef’s knife does not make me a chef. The old saying is “a fool with a tool is still a fool.” Watson, or any AI, can’t just imagine ideas, create new solutions, or create new solutions. While it isn’t an oracle, it is highly useful tool.

The real purpose of this tool labeled as Artificial Intelligence, Cognitive Intelligence, or Assistive Intelligence is to provide computers with more human like interactions and understanding. Reading, writing, speaking, listening, seeing, and feeling are very human experiences. We define our world this way via our senses and sense of self being. At IBM, we have Watson focus more on the cognitive (thinking and feeling like a human) and being more supportive via assistive intelligence. The cognitive capability provides the computer a better and more natural way to move, communicate, interact, and learn in our human focused world.

A good example is Watson Cancer Diagnostics. It first was taught how to diagnose and treat cancer. The cognitive capabilities allowed it to speak, listen, write, and read both questions and answers. I even learned to read radiographs (visual). That gave the solution a baseline capability. Now it is moving onward by reading printed journals. We as humans think of it as nothing to extract information out of reading a book, but this is unstructured data which only a few years ago, computers couldn’t understand. Now with Watson, they can. Today Watson Cancer Diagnostics can work with doctors and suggest treatments, but ultimately, we still rely on the doctor to make the final diagnosis and treatment.

Water is the universal solvent. Humans are the universal problem solver. Computers are wonderful tools to enable humans. By adding cognitive capabilities, computers become even better and easier to use tools to assist us in shaping our world and hopefully for better.

 

Terrific Practical 10 step path for success with Analytics from Jerry Kurz.

Thirty years of experience talking. Worthy of 15 minutes of your time.

Folks, I am very proud and happy to have my dear friend Jerry Kurtz do a guest blog on my site. Jerry runs the Cognitive and Analytics businesses in my portfolio, and is a long time IBMer. He has been in this field for 30 years across SAP, Managed Business Process Services and Analytics and […]

via And Jerry Says : A Path to SUCCESS with Advanced Analytics — Vijay’s thoughts on all things big and small

Now technology bubbles up to the Business Enterprise level from Consumers

The technology at the Consumer Electronics Show (CES) will bubble up into business and into enterprises quickly – far quicker than IBM, HPE, Cisco, or any of the enterprise strength IT companies would like. Initially technology came from business to consumers – think PCs. The sheer size of consumer market and its willingness to put up with beta releases makes the consumer world the ideal proving ground for the less fault tolerant enterprise world.

Drones are bubbling up. While they started in the military, they now are big segment of the consumer market. Drones or autonomous flying vehicles have been improving including automated stabilization, 4K cameras, enhanced flying times, etc. Many of them have dozens of computers on board and some rather impressive programming to make them simple to use.

Due to the wide-spread usage of drones in the consumer market, they are vastly improved and far less expensive. One of the leader’s in the industry, DJI’s basic drone, Phantom 3 Standard, is just under $500 flying for ~25 mins, includes GPS tracking, tracks subjects based photo recognition using a 1080 camera for photos and stills. Refurb is $329 and knock offs are even cheaper.  Just 5 years ago, this would have been a top of the line $5K drone, if even available.

Part of the attractiveness of the consumer world is scale. The other factor is that the consumer world is filled with willing beta testers. Recent releases of drones from reputable companies come with lots of complaints on the internal boards of not flying well, not following waypoints, and simply flying away. A drone that loses its signal is supposed to fly back to the point of origin and land. In the business world, this would be a breach of contract and might result in loss of property or life. In the consumer world, the drone manufacturer can just send a firmware update, a coupon, or at worst replaces the device.

While scale makes the money, it is the willing beta tester that enables advancement. Haven’t you signed up to be a beta or an alpha tester. I know I am for many of IBM’s early release programs. We have marvelous internal site called “Technology Adoption Program” where individuals submit their software inventions. Many have become key enablers of IBM’s business.

What else might bubble up? Virtual Reality has real possibilities for training. Consumer IoT devices will make it into manufacturing. Fitness IoT devices will make it into Medical IoT devices. Home IoT devices by Amazon, Google, and Apple will rapidly make both IoT device and cognitive (AI) advances as we all beta test their devices for more hardened uses. I know send in correction reports regularly and in general they do a good job following up. The list is endless as people gobble up consumer technologies.

We used to make fun of 3rd world countries using the computers out of toys to steer their weapons. Maybe they were just ahead of their time.

Consumer Technology enables SCALE and RAPID INNOVATION

Consumers enable SCALE and RAPID INNOVATION in Technology. As I walked around the Consumer Electronics Show (CES), I could see how the technology will “bubble up” into business and into enterprises quickly. Initially, technology came from business to consumers – think PCs. The sheer size of consumer market, hunger for new functionality, and its willingness to put up with beta releases makes the consumer world the ideal proving ground for the less fault tolerant enterprise world. Companies that span both world can leverage the consumer world for its SCALE and RAPID INNOVATION and bubble those innovations into the enterprise world for higher profits.

Drones are an example of bubbling up. While they started in the military, they are now a big segment of the consumer market. Drones or autonomous flying vehicles have been improving including automated stabilization, 4K cameras, enhanced flying times, etc. Many of them have dozens of computers on board and some rather impressive programming to make them simple to use. First it was movies, then multi-million dollar homes and now you see mid-market homes with drone footage. It has become a toy for teenagers, too.

Due to the wide-spread usage of drones in the consumer market, they are vastly improved and far less expensive. One of the leader’s in the industry (Drone Market Map)( https://www.droneii.com/top20-drone-company-ranking-q3-2016)), DJI’s basic drone is just under $500, flys for ~25 mins, includes GPS tracking, tracks subjects based photo recognition using a 1080 camera for photos and stills. Lots of knock offs are even cheaper.  “Toy Drones” are just $50! Five years ago, the DJI basic drone would have been a top of the line $5K drone, if even available.

Part of the attractiveness of the consumer world is scale. The other factor is that the consumer world is filled with willing beta testers and relatively low liability costs. The consumer world is an agile one where cycles occur very quickly. A typical enterprise development cycle is 18 months. In the same time in the consumer world, you’d see a major hardware, firmware, and at least 30+ releases of software.

The demand for new and the tolerance for risk is high in the consumer market. Recent releases of drones from reputable consumer companies come with lots of complaints on the internal boards of them not flying well, not following waypoints, and simply flying away. In the business world, failure to perform would be a breach of contract and might result in loss of property or life. In the consumer world, the drone manufacturer can just send a firmware update, a letter, a coupon, award you status on their web site as hero or pioneer, or at worst – replace the drone. It’s a trivial price enabling those dipping into the consumer world to advance faster than those in the business world.

While scale makes the money, it is the willing beta tester that enables advancement. Haven’t you signed up to be a beta or an alpha tester. I know I am for many of IBM’s early release programs. We have marvelous internal site called “Technology Adoption Program” where individuals submit their software inventions. Many have become key enablers of IBM’s business. They grew up fast by being adopted and depended on by IBM’s business.

What else might bubble up? Virtual Reality has real possibilities for training. Augmented Reality with heads up displays and glasses will be welcomed the field. Giving schematics, UV and Infrared vision, and more to workers. What will make it become easily affordable and useful – another Pokemon Go that plays with glasses pushing it onto millions of users’ foreheads.

3D printing is coming of age, but I can see point where 25% of households have plastics printer and your hardware store has a metal one. No inventory of 500K parts – just print it. Lots more like LED lights, Home Automation, Sports Fitness, etc. will bubble up.

Finally, Artificial Intelligence (AI) may be the biggest winner from the bubble up effect of the consumer. The key to AI is having huge knowledge base or corpus and lots of training. Where better than the consumer market with a potential of 7 billion users – the population of the world – to train your AI. Whether it is Siri, Alexa, Cortana, Watson, or Google, these companies’ AI programs will benefit from the consumer training it. You get a voice interface and they get you to train their AI.

What do you think will be the next big bubble up technology from the consumer world to the enterprise world?

 

 

Our 2 fears of Artificial Intelligence (AI)

We have two (2) overarching fears of AI. AI domination is the most irrational fear where AI becomes smarter than organic intelligence and wipes out or subjugate the organic life forms. This plays out in number of number of science fiction works like “Transformers”, “Terminator” and “I, Robot”. In “I, Robot”, the AI unit is claiming to do it in service of humanity. I’d argue AI domination is the least likely scenario of doom and maybe in dealing with our second fear, we can solve our AI domination fear, too.

The second fear is that of misuse of AI. I’d argue that is the same argument has been used against every technological advancement. The train, automobile, nuclear fission, vaccines, DNA, and more have all been cited for ending the world. I suspect someone said the same thing against the lever, wheel, fire, and bow. Each has changed the world. Each has required a new level of responsibility. We’ve banded together as humans to moderate the evil and enhance the positive in the past. Ignoring it or banning it has never worked.

Amazon, DeepMind/Google, Facebook, IBM, and Microsoft are working together in the “Partnership on AI” to deal with this second fear as described by the Harvard Business Review article “What will it take for us to trust AI” by Guru Banavar. It is a positive direction to see these forces coming together to create a baseline set of rules, values, and ethics upon which to base AI. I’m confident others will weigh in from all walks of life, but the discussion and actions needs to begin now. I don’t expect this to be the final or only voice, but a start in the right direction.

I hope the rules are as simple and immovable as Issac Asimov’s envisioning of the  3 laws of robotics on which the imagined, futuristic positronic brains power AI robots. Unfortunately, I doubt the rules will be that simple. Instead they will probably rival international tax law for complexity, but we can hope for simplicity.

The only other option is to stop AI. I don’t think it is going to work. The data is there and collecting at almost unfathomable rate. EMC reports stored data growing from 4.4ZB in 2013 to 44ZB in 2020. That is 10^21 (21 zeros) bytes of data. AI is simply necessary to process it. So unless we are going to back-out the computerized world we live in, we need to control AI rather than let it control us. We have the option to decide our fate. If we don’t then others will move forward in the shadows. Openness, transparency, and belief in all of human kind have always produced the best results.

In the process of building the foundation of AI, maybe we can leave out worst of human kind – lust for power, greed, avarice, superiority. Maybe the pitfalls in humans can simply NOT be inserted in AI. It will reflect our best and not become the worst of human kind – a xenophobic dictator.

Putting the AI genie back in the bottle will not work. So I think the Partnership on AI is a good first step.