On the horizon we will find more and more applications for AI with telecoms, high tech and financial services leading the way. Developers bridged many of the unknown gaps in skills to develop AI systems and faster than anticipated. Most businesses are now using chatbot systems for customer service in industries like banking healthcare, and retail shopping.
A most notable, and interesting increase is the building out of Machine Learning platforms that compliment AI especially in academic universities. Building out massive libraries for deep learning and massive neural networks to support research, it's no wonder the academic communities are on fire about this technology. Also adding smart content that helps students get digestible materials to study, cram and practice with. AI does a very good job at heavy administrative lifting for institutions and educators, and with today's legal and financial systems, the paperwork that must be filed continues to mount. Outside the classroom has experienced a boom of its own with tutoring mentoring and teaching fundamentals to those who might be struggling in their academics. There are even pay services that can take a student through an entire core course before they even take it. AI has come along way and in the both the business and academic environments, the pressure is enormous to be the first to provide useful but innovative solutions or offer a particular service to customers.
From a professional experience, I have seen this massive connection from the outside world back to academic institutions. Not only for the institution, with capability like professor reach back, student grading and curriculum building, but also for organizations and think tanks to tap a large population of faculty and student research, curriculum and national and international teaching and learning resources. Think tanks are ramping up their efforts to use AI. A think tank, unlike many organizations, apply most of their time focusing on answering the dilemmas of the day. They have staff that spend their entire day trying to come up with solutions and or possible answers to wicked problems. Recently a task force of former government officials, academics and representatives from industry was formed to explore how the government should embrace AI and work better with industry and institutions. Companies are watching how AI and ML support reduced staffing and refocusing budget dollars elsewhere as a model for the future of smart business, and smart academic systems.
A series of projects have happened at Air University that might predict how we can supplement Augmented Reality with a little Artificial Intelligence and even Machine Learning to get to the “experience” quicker and more in-depth than traditional role play or scenario-based learning. I've talked to hundreds of students of the years and the common theme is how the experience helps them but also how the experience connects them to things they need but didn't know they needed. Areas like leadership experience, effective listening, strategic and design thinking at the application level is emotional and can be applied in any environment.
Not only can software be adapted to students, but faculty can focus on more research and curriculum needs as AI can help grade papers and projects, help make curriculum better, and supplements the delivery of helpful feedback and my favorite, how we interact with information. Role Play scenarios have been around in education for decades but it involves each person to know what to do and how to respond according to their assigned role, that is very tough when you are learning. With AI the student interact with a system that knows all the roles, and can adapt to all scenarios within a given setting, so it shows an immediate and relative answer to an unknown (for the students at the time) problem. Its no secret that AI will grow and become more and more a part of our lives, and if you know anything about AI you will agree that it has already creeped into your life, business, and or learning environments.
Just a few months ago we can see that in the photography world companies are putting AI based algorithms into their software to speed up tasks as well as get the user closer to real progressive change and handling the details. A rudimentary but monumental example is with smart phone apps like photoshop express and social media apps like Instagram. The user can select a “style” for a particular photo and the app makes all the necessary detailed changed to create that style. Apps sift through hundreds of small tasks very quickly to provide a fast and glorious experience. Even though it limited in photography right now, the future looks promising as AI gains acceptance and the right development is applied for the right purposes.
Look at office software for example, improving the speed and efficiency in which we craft our emails, documents and even plan our days spell check and grammar check.
What does the future hold? With the U.S. Military having success with AI for Autonomous weapon systems decades ago to closer than a decade ago, companies began to use AI for processing, sifting, and managing the “big data” boom. This is pretty much what started the spin offs of AI to other areas.
Some predict that AI includes process discovery where sensors are embedded to predict an optimal path for interacting with a system, program, learning module or business transaction.
We know that our GPS navigation has improved beyond expectation over the last decade, now cars will not have to be asked, but programmed for your most travelled destinations and alert you of any issues and reroutes along the way...before you ask. Another example are small flying drones with cameras that have been completely revamped to know where you can and cannot fly, and even in terms of altitude and specific geo location, keeping us and others safe without even knowing or thinking.
A huge role for AI will be in the cyber world, in defense and resolving issues in a proactive and expeditious manner, while we sleep, play or focus on other tasks. Predicting and eliminating potential hazards and worse, damage to systems will be a big imperative in 2019 and beyond. We will see a decline in the excitement of the topics that surround AI and ML in 2019, but mainly because companies and institutions will have already implemented their AI or ML strategies and will be focused on its improvement for their future competitive advantage.
Another area on the rise for 2019 will be using AI for coaching networks, because they can forever improve by being continuously pumped with new and creative ideas for use in interactive coaching scenarios. Machine learning will need to supplement this by learning these new concepts along the way and try and predict new ways of coaching through progressively matching themes, words, and concepts used before.
So, 2019 will be a banner year in terms of how AI and ML will be used to create new ways to support our thirst for the “experience” as well as serve more and more data to develop and the draw a new landscape for us.
If you have ideas, creative uses for AI and ML or just want to jump in the fray about what is discussed here, please tell us in the comments! We welcome any and all voices to further our understanding and collaborate with others.
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