A Camel to Cars Moment. Over the last couple years, Ive spent an increasing amount of time diving into the possibilities Deep Learning DL offers in terms of what we can do with Artificial Intelligence AI. Some of these possibilities have already been realized more on this later in the post. And, I could not be more excited to see them out in the world. Through it all, Ive felt there are a handful of breath taking realities that most people are not grasping when it comes to an AI Powered world. Why the implications are far deeper for humanity than we imagine. Why in my areas of expertise, marketing, sales, customer service and analytics, the impact will be deep and wide. Why is this not yet another programmatic moment. Why the scale at which we can have to solve the problems is already well beyond the grasp of the fundamental strategy most companies follow We have a bigger revenue opportunity, but we dont know how to take advantage Lets buy more hamster wheels, hire more hamsters and train them to spin faster Today I want shed some light on these whys, and a bit more. My goal is to try to cause a shift in your thinking, to get you to take a leadership role in taking advantage of this opportunity both at a personal and professional level. Ive covered AI earlier Artificial Intelligence Implications On Marketing, Analytics, And You. ComputerWeekly/Hero%20Images/AI-artificial-intelligence-button-fotolia.jpg' alt='Artificial Intelligence Software For Pc' title='Artificial Intelligence Software For Pc' />Youll learn all about the Global Maxima, definitions of AIMLDL, and the implications related to the work we do day to day. If youve not read that post, I do encourage you to do so as it will have valuable context. AI/skinpromo-3.jpg' alt='Artificial Intelligence Software For Pc' title='Artificial Intelligence Software For Pc' />Artificial intelligence and UX Machine learning can surpass the performance of AB testing and psychology in tailoring websites and applications to users. In this post, Ive organized my thoughts into these six clusters There is a deliberate flow to this post, above. If you are going to jump around, it is ok, but please be sure to read the section below first. You wont regret it. Ready to have your mind stretched Lets go Whats the BFD Im really excited about whats in front of us. When I share that excitement in my keynotes or an intimate discussion with a companys board of directors, I make sure I stress two especially powerful concepts that I have come to appreciate about the emerging AI solutions Collective Continuous Learning Complete Day One Knowledge. Female Artificial Intelligence Software For Pc' title='Female Artificial Intelligence Software For Pc' />The above programming code was created by an artificial intelligence program, designed to write programs with selfmodifying and selfimproving code. The program. Tech of the Future, Today Breakthroughs in Artificial Intelligence Heres a look at some of the latest uses of artificial intelligence in todays world. Braina Brain Artificial is an intelligent personal assistant, human language interface, automation and voice recognition software for Windows PC that allows you to. Explainable Artificial Intelligence XAI concerns, in part, the challenge of shedding light on opaque machine learning ML models in contexts for which transparency. Two powerful concepts, Collective Continuous Learning and Complete Day One Knowledge, present a revolutionary opportunity for businesses optimization. Artificial consciousness AC, also known as machine consciousness MC or synthetic consciousness Gamez 2008 Reggia 2013, is a field related to artificial. AIBO Artificial Intelligence Robot, homonymous with aib, pal or partner in Japanese is a series of robotic pets designed and manufactured by Sony. They are crucial in being able to internalize the depth and breadth of the revolution, and why we strengths AI brings are a radical shift beyond what humans are capable of. The first eye opening learning for me came from the Google Research teams post on Learning from Large Scale Interaction. Most robots are very robotic because they follow a sense plan act paradigm. This limits the types of things they are able to do, and as you might have seen their movements are deliberate. The team at Google adopted the strategy of having a robot learn own its own rather than programming it with pre configured models. The one handed robots in this case had to learn to pick up objects. Initially the grasping mechanism was completely random try to imagine a baby who barely knows they even have a hand at the end of their shoulder. Hence, youll see in the video below, they rarely succeed at the task at hand. At the end of each day, the data was collected and used to train a deep convolutional neural network CNN, to learn to predict the outcome of each grasping motion. These learnings go back to the robot and improve its chances of success. Heres the videoPlay on You. Tube It took just 3,0. Whats intelligent behavior of a CNN powered one handed robot Among other things, being able to isolate one object a stapler to successfully pick up a Lego piece. Youll see that at 1. Play on You. TubeOr, learning how to pick up different types of objects a dish washing soft sponge, a blackboard eraser, or a water glass  etc. I felt a genuine tingling sensation just imagining a thing not knowing something and it being able to simply learn. I mean pause. Just think about it. It started from scratch like a baby and then just figured it out. Pretty damn fast. It truly is mind blowing. There were two lessons here. The first related to pure deep learning and its amazingness, I was familiar with this one. The second was something new for me. This experiment involved 1. While not a massive number, the 1. The end of day learnings by the convolutional neural network were using all 1. And, the next day, all 1. For a clear way for me to capture this lesson, I call this Collective Learning. It is very powerful. Think of 1. 4 humans learning a new task. Peeling an apple. Or, laying down track for a railroad. Or, programming a new and even more frustrating in flight entertainment menu for Air Canada who have the worst one known to mankind. Every human will do it individually as well as they can there will be the normal bell curve of competency. It is entirely possible, if there are incentives to do so, that the humans who are better in the group will try to teach others. There will be great improvement if the task is repetitive and does not require imaginationcreativityintrinsic intelligence. Video Symphonic Library there. There might be a smaller improvement if the task is not repetitive and requires imaginationcreativityintrinsic intelligence. In neither case will there be anything close to Collective Learning when it comes to humans. Humans also do not posses this continuous closed loop Do something. Check outcome success or failure. Actively learn from either, improve self. Do something better the next time. Collective Continuous Learning. An incredible advantage that I had simply not thought through deeply enough. Heres the second BFD. Machine Learning is already changing lots of fields, the one Im most excited about is whats happening in healthcare. From the ability to speed up discovery of new medicines to the unbelievable speed with which Machine Learning techniques are becoming particularly adept at diagnosis think blood reports, X rays, cancers etc. An example I love. Diabetic Retinopathy DR the fastest growing cause of blindness. If caught early, the disease is completely treatable. The problem Medical specialists capable of detecting DR are rare in many parts of the world where diabetes is prevalent. Using a dataset of 1. Googles  Accelerated Science Team trained a deep neural network to detect DR from retinal photographs. The results delivered by the algorithm black curve were slightly better than expert ophthalmologists colored dotsSpecifically the algorithm has a F score of 0. F score of the eight expert ophthalmologists was 0. As richer datasets become available for the neural network to learn from, as 3. D imaging technology like Optical Coherence Tomography becomes available all over the world to provide more detailed view of the retina, just imagine how transformative the impact will be. Literally millions upon millions of people at risk of blindness will have access to AI Powered technology that can create a different outcome for their life  and their families. A recent incredible article on this topic is in my beloved New Yorker magazine A. I. VERSUS M. D. You shouldread it. Ill jump to a part of the article that altered my imagination of possibilities. An algorithm created by Sebastian Thrun, Andre Esteva and Brett Kuprel can detect keratinocyte carcinoma a type of skin cancer by looking at images of the skin acne, a rash, mole etc. In June 2. 01. 5 it got the right answer 7.