In recent years we have been witnessing a tsunami of changes in the information technology and the fastest rate of change in almost every aspect of our social life and business. A few observations:
- Intelligent cell phones are widespread and social media is connecting people in real-time. There are more active cell phones than there are people!
- Technology companies have been replacing not just brick and mortar companies such as Blockbusters but are now replacing the traditional Taxi cab companies and transportation companies, food delivery etc. Even FedEx could be vulnerable
- Ecommerce is now 5% of the $4.3 Trillion in total US retail sales. For clothing and footwear, almost 20% goes to ecommerce
- Intelligent devices are in people's homes, connected to the internet (IoT), from washing machines to vacuum cleaners and refrigerators
- Personal shopping assistants in the form of robots in a number of stores already; and people's avatar's help shoppers on line to pick the right make up and clothing items.
These changes have come about due to both hardware technology (speed and memory), as well as scientific approaches that we collectively refer to as Artificial Intelligence (AI). The objective of AI is to
make systems and devices as close to humans as possible, not just
intelligence but emotions too are targeted. Even facial expressions of feelings are now being detected and used for decision making. Intelligence in every aspect of our lives can be guided by machines from the right amount of water in our washer to the number of shipments of an item to a location for storage or sale. As data becomes so readily available in real-time then systems are needed to make sense of it all. Stock market is a good example of such intelligence. Every morning the same data is available to everyone everywhere.
People who make the best decisions the fastest are the winners in the financial markets. They do this by highly optimized algorithms and AI techniques. According to IDC in 2011 we created 1.8 zettabytes (or 1.8 trillion GBs) of information. In 2012 it reached 2.8 zettabytes and IDC now forecasts that we will generate 40 zettabytes (ZB) by 2020. Now a days it is not uncommon to have 500 TV channels. How do you know you are watching the "best" program at any point in time unless you examine each, in which case it is over before you get to it! In other words you need systems that can help you to make quick decisions based on all the information available to you.
At Adexa, areas that are of relevance to us in AI are
- Machine learning and inference techniques
- Optimization algorithms including planning and scheduling
- Big data and techniques to uncover hidden information that may not be obvious
Our interest in this context has to do with how their combination can be used to make better and more efficient supply chains, faster and more profitable. As an example, Starbucks is connecting every coffee machine to its IoT system to collect the data so that there is no latency in information needed as to what to buy and what to distribute. In fact by doing so this data collection might reveal different habits of different regions in the type of coffee preferred as well as what people buy with their coffee. As soon as we are aware of such information, the next step is to plan to get what is needed and to schedule to source it, make it, deliver it and do it in an optimized manner in the least amount of time and cost.
Learning systems in AI are intended to make software more and more intelligent by learning from its environment. As an example, given a model of supply chain of a company, it must have the capability to constantly change since the supply chain is dynamic and the company being modeled is constantly changing. In some cases the changes are subtle such as demand falling slowly over time, or more obvious, such as losing a customer or a supplier. How would the models of the supply chain understand these changes and relate to them? Currently this is accomplished with a lot of help form their users. However we are now in a position for systems learning about such behaviors and changing themselves by understanding the changes in the environments in which they operate.
In summary, the systems used in businesses over the next decade or so will be very different from your average ERP and APS systems much the same as the changes that took us from the "green screens" to the "Apple" like interfaces except that this time it will be much more than just a change in user interface. It will lead to making "personal assistants" available to everyone in every aspect of life affordable with the use of intelligent systems which can also understand emotions, desires as well as profits! The era of decision automation not just mechanical automation is upon us!