Artificial Intelligence (AI) is rapidly transforming the way that global industry players are doing business. With the infusion of AI into so many areas of business and commerce, we are seeing the evolution of everything from more intelligent products to laser-like focused customer offerings. AI is fundamentally changing how suppliers, manufacturers, and customers interact and collaborate.
So, what does this mean for original equipment manufacturers (OEMs)? Simply put, they have two choices. They can adapt their solutions by incorporating AI-powered business functionality, or face losing out to other progressive AI-focused OEMs in this ever-evolving competitive landscape.
It has become readily evident that Artificial Intelligence (AI) is everywhere nowadays. It has become systemic in certain niche applications, especially so in the pharma and healthcare industry, as well as in the retail space. However, where the critical mass opportunity comes into play for OEMs is when they can create repeatable AI solutions that are transferrable to multiple markets and industries. To do this successfully it is ultra-important for OEMs to understand the two key subsets of artificial intelligence, and the respective roles they play in developing these broad-based industry solutions. These two subsets are machine learning and deep learning.
Machine learning is at the core
Machine learning is essentially a component of AI. Machine learning is a system that possesses the ability to continuously update and modify itself as it is presented with new or additional information. Because machine learning is a dynamic process in and of itself, it allows the computer network to learn without having to be programmed. As such, these systems are completely self-sufficient since they require no human intervention. Absent the need for human involvement, machine learning systems can process the data they collect in order to make a determination in fractions of a second. A machine learning system can decipher in seconds what previously may have taken weeks for a human to analyze and process. In the end, machine learning program;s ultimate goal is to maximize the likelihood of their predictions to be as accurate as possible, while eliminating errors.
Deep learning is the next key phase
While machine learning is a component of AI, deep learning can be seen as a subset of machine learning. The easiest way to describe deep learning is that ideally it functions like a virtual version of the human brain. One key area of differentiation for deep learning is that it can build neural networks. These neural networks usually lead to significantly more accurate results than those delivered by machine learning. Deep learning also possesses the ability to learn from unstructured data. Deep learning systems are best known for parlaying their results to build upon their systems layer by layer as they assimilate each new round of data. Unlike machine learning, because deep learning can leverage their neural networks, this empowers them to make increasingly complex decisions without ever requiring the input of humans.
A golden opportunity for OEMs
For OEMs, the future is now when it comes to artificial intelligence. There is not a business or industry that is not looking to incorporate AI capabilities into their organization at some level. The rapid-fire integration of AI along with machine learning and deep learning is becoming pervasive. According to a new report by Grand View Research, the global artificial intelligence market size is expected to reach $390 billion by 2025. The market is anticipated to expand at a CAGR of 46.2% from 2019 to 2025. As such, those OEMs that are “skating to where the puck is going” in the AI, machine learning and deep learning space will in the end, take a disproportionally larger share of this exponentially growing marketplace.