13 Areas Of Artificial Intelligence and Machine Learning To Keep An Eye On in the Workplace.
28% of IT leaders surveyed by Tech Pro Research already have experience with AI in their business.
Additionally 42% are working on adding machine learning and AI to their business with 26% planning on implementing it within the next year.
More and more businesses are beginning to integrate artificial intelligence. Pretty soon using artificial intelligence and machine learning will be the norm rather than the exception.
Artificial intelligence (AI) and Machine Learning (ML) are being called the next frontier of business with major corporations like Google and Baidu spending between 20–30 Billion dollars a year on R & D and deployment.
AI and ML are already making a huge impact in areas like finance, telecom, and the medical field. Even if your business has not yet made the leap into AI or ML, you need to start paying attention to the trends in them, unless you want to get left behind.
These are 13 areas of artificial intelligence and machine learning to keep an eye on in the workplace.
- Capsule Networks. Currently convolutional neural networks are used to process visual information. This is a problem because convolutional neural networks have difficulty determining the spatial hierarchies between simple and complex objects. This leads to a high rate of misidentification and misclassification. Enter the capsule network which processes visual information in the same way as the brain. Capsule networks could lead to a huge reduction in identification errors on things like X Rays. Some experts even predict capsule networks leading to as much as a 50% reduction in error. That would be huge for medical technology and may lead to the demise of Xray technicians.
- Probabilistic Programming. Probabilistic programming seeks to close the gap between representative models and reality. Probabilistic programming is a high level language which allows programmers to reuse models, support interactive modeling and generally allow a programmer to create models that automatically solve themselves. With probabalistic programming you need less programmers and less data.
- Automated Machine Learning. Right now the process of developing machine learning is extensive and expensive. It requires time, experts, training and patience. Automated Machine Learning (AUTOML) seeks to create machine learning that works automatically bridging the gap between business owners and those with deep programming backgrounds and allowing everyone access to machine learning.
- Digital Twin. A digital twin is almost exactly what it sounds like. A virtual model designed to replicate a physical or psychological system. Digital twins have been used to monitor windmills and industrial systems but are slowly being used by more and more businesses to model everything from systems to customer behavior.
- Improved Decision Making. One of the challenges of incorporating more advanced AI and ML into the workplace is creating programs that can make decisions in real time. For example in order to create a self driving car you need to figure out how to program it to drive safely without staying stuck at a stop sign forever. Programs like If this then drive will become more popular and will create a new architecture of decision making AI and ML.
- AI and data science skills will be the new hot skill in the job market. The same way that coding and web development were among the most sought after skills of the aughts, AI and Data science skills will become the new hot skills in the job market.
- Artificial Immune Systems in Digital Security. Inspired by the immune system of humans, artificial immune systems are intelligent programs which use ML and AI to learn from system attacks and come up with better responses mimicking the memory and learning of vertebrate immune systems. Many experts expect this to become the new norm for digital security in the next few years.
- Reinforced Learning. The most general purpose of all ML techniques, reinforced learning (RL) uses very little data and can be trained via simulation. RL has been used by machines to learn complex games such as chess, Atari and GO.
- AI will enter the defense and auto spaces soon. Responsible for engineering defense technology for the US government, the Defense Advanced Research Project Agency (DARPA) is already in the process of working with Boston Dynamics to develop “disaster relief” robots which could easily be used for combat purposes over the next few years. Additionally everyone from Google to startups like nuTonomy are busy trying to be the first to market with a comp;eyely self driving car. It’s quite possible that all defense related and driving from commuting to long haul trucking may soon be done by robots.
- AI will start creating content. For the last few years content creators such as video producers and writers thought that they would be safe when AI and ML started to destroy jobs. Turns out that isn’t the case, as tools like Wibbitz are allowing brands to automatically create videos from written content. As search engines like Google continue to reward video with search ranking, look for more and more brands and businesses to turn to automated content creation.
- Intelligent digital mesh. Introduced by Gartner the idea of the intelligent digital mesh is that through AI and ML a foundation will be built for a blending of the physical and digital world into a platform independent world where companies will battle for market dominance. Of the top 10 trends Gartner recognized almost all of them play into the digital mesh concept.
- DIY AI. Another interesting trend to watch in AI is the emergence of do it yourself (DIY) AI market as consumers are embracing the more customizable and cheaper alternatives to products such as Amazon’s Alexa and Apple’s homepod. It will be interesting to see if any of the DIY AI developers end up advancing the science in ways the traditional R and D teams have not.
- The AI arms race will heat up even more. As of the last available numbers the United States was responsible for 66% of the investment in AI in 2016 with China coming in second at 18%. Look for this race to heat up similarly to the space race of the 1960s as both China and the US jockey for position in the new AI economy. Expect heated competition internationally for top data scientists and top dollar being thrown around to acquire new and potentially game changing AI companies such as Nest.
As you can see AI is here to stay and the top companies in the world are investing in it. That means that no matter what business you are in, you need to stay on top of these trends.
AI and ML are doing everything from creating content to improving decision making and companies like WorkFusion and others are helping companies get in on the ground floor before the digital mesh ensnares us all and it’s too late to take advantage of the early mover advantage.