With the emergence of technological advancements, have you ever wondered on the nuance between organic life form (like humans) and silicon-based life form (like smart machines)? Yes! It’s high time when we accept inorganic- silicon-based artificial intelligence as another life form.
The reason behind it is that just like we learn and grow from everyday experiences and challenges, machines are also learning and evolving day by day. Many frontiers of AI (Artificial Intelligence) in the world describes machine learning as a training process to develop computers and machines that can act more like humans in every possible way. Artificial intelligence (AI), when applied on machines, is known as Machine Intelligence (MI) which is the intellect of computer system (or machine) mimicking the natural intelligence (NI) displayed by humans or other animals.
To put it in a simpler way, machine learning is a process where computers (machine) learn or are being trained by providing simpler to complex data forms as inputs to perform an assigned task based on particular algorithms or statistical models. The output is then critically examined for correctness. By recognizing patterns and drawing on experiences, machines can also learn how to manipulate inputs to get the desired output more efficiently and logistically. So, the iterative aspect of machine learning is the ability to adapt to new data independently.
Machine learning can be of three categories:
- Supervised: where machines depend on some form of external supervision.
- Semi-supervised: where external supervision is minimal and only needed for critical processes
- Unsupervised: where there is no need for any supervision whatsoever.
Artificial intelligence (AI) will have exponential growth in the coming years. As per 2016 report from CB Insights, equity financing in the AI space rocketed from $282 million to $2.4 billion from 2011 to 2015 with global equity funding for AI reaching $6 billion. AI already has its impact on nearly every industry ranging from logistics, manufacturing, and robotics to the Internet of Things (IoT), finance, healthcare, legal, agriculture and many more.
Defense industries are not far ahead in line in comparison. Although there have been extensive researches and developments in AI space of defense industries, it is only now on understanding the emergence and vast potential of machine learning defense industries are investing in it.
The advent of AI could change the limitations and characters of warfare at ground levels. Make no mistake for, in upcoming years, AI will be critical to military power in various operational fields. AI will be exploited and leveraged to not only overcome current challenges but also to enhance future capabilities in certain segments:-
- Advanced autonomous war machines.
- Intelligence gathering, processing and its analysis for defense strategies and decision-making.
- Simulated or augmented reality for enhanced military and other defense training.
- Cognitive Radio and Electronic warfare by enhancing defense networks and information systems
- Tactical applications such as minesweeping drones that are equipped with different imaging technologies like X-Ray, IR (Infra-Red), Thermal vision, etc.
Machine learning will provide rapid technological growth in military technology, drones, missile command, tech against terrorism and all relevant things affecting modern combat. ML (machine learning) professionals can help to overcome every limitation faced today due to technological lacking. Advanced machine learning and technologically superior AI provides a disproportionate advantage to otherwise technologically weak enemy as a disruptive technique. Today China and the United States of America have emerged as leaders of ML-based AI and are continuously utilizing comprehensive resources for the development of their commercial interest and national security.
President Trump while approving the National Defense Authorization Act (NDAA) to $717 billion funds for the next fiscal year, emphasized on artificial intelligence research in the US Department of Defense (DOD). Additionally, a segment of funds from the NDAA will be used to establish a Joint Artificial Intelligence Center (JAIC) under the DOD to support and oversee nearly 600 active AI projects. A National Security Commission on Artificial Intelligence will also be funded with $10 million budget to examine how AI can be leveraged for enhancing the national security. On May 3rd, 2016, the US Administration announced the formation of a new National Science and Technology Council (NSTC) Subcommittee on machine learning and Artificial intelligence, to help coordinate Federal activity in AI.
With the cusp of human intelligence and artificial intelligence, the defense as an industry will be revolutionized. High-value areas of machine learning (ML) for the defense community where ML professionals can contribute effectively include:
- connected fleet management,
- dynamic inventory optimization,
- dynamic maintenance management,
- predictive maintenance & services,
- Warranty analytics, etc.
During his interview with KPMG in Australia, Ian McDonald — Director of Technology Enablement in Defense and National Security, said:
“Intelligent automation is absolutely essential for the military. They cannot operate the capabilities they currently have to their full potential without it. At the moment, there are humans in the loop between those systems. You cannot respond within 16 minutes unless you are already in a state of high alert.”
Intelligent automation with the help of machine learning can rapidly consolidate and analyze all the data received from satellites, defense sensors, and other findings, providing an upper edge to the decision-making personnel for deciding next actionable step(s). Along with the advancements in the third and highest level of intelligent automation, “reasoning cognitive automation” military will be able to derive insights from comparably huge data sets, which can also include unstructured material such as any written text, audio, and video. In terms of administration ML professionals can help in the recruitment and training process.
Above all, it should be clear that no matter how advanced and automated a defense system is, it can never eliminate the manpower need and critical thought process. Machine learning based AI can provide light speed solutions and suggestions, but it can never replace a human judgment when it comes to actually decide whether to go with the suggestion. Human’s judgment and the final decision is and will always be above any AI for he is more humanly capable of making logical, ethical and more accurate to the situation decisions. Before fully integrating ML professionals can help to oversee and moderate the various strategic facets of AI, including autonomous weapons and as well as in cyber-defenses.
Wrapping Up
To sum it up, Machine learning has huge potential in defense and military industries. ML professionals can lead the path to unfold possibilities of machine learning implications based on their ability to exploit the AI. Machine learning is already being used at different levels, but more importantly, will play a critical role in strengthening the security and defense of a country in upcoming decades.
