How Small Businesses Can Leverage Artificial Intelligence Posted on : Sep 21 - 2017

Artificial intelligence (AI) may seem like the newest and hottest trend coming out of Silicon Valley, but this type of technology has actually been around for quite a while. The first work done in this area dates back to the 1950s. The early work done on AI focused on translation. Throughout the cold war, IBM created systems to translate Russian to English. Ever since then, there have been advances in this fields along with boost and boom cycles, known as AI Winters. We can find a few examples of AI technologies in the 1970s and 1980s, such as micro-world and expert systems. Today, AI is more accessible to all kinds of organizations. Understanding its evolution allows me and my team to create better services and solutions to our clients and partners.

I think we are currently undergoing another hype cycle. However, this time might be different due to three factors: advancements and breakthroughs in machine learning, data available to train models, and computational power. Such progress has motivated corporations and startups to make significant investments in this technology. Hence, AI solutions are becoming more ubiquitous in our daily operations. Small-business leaders should understand the implications, how to implement this technology, and the types of use cases artificial intelligence can help streamline — along with the benefits it can bring to their organizations.

So, what is machine learning and how does it impact general AI? Machine learning is an AI technique that aims to get computers to behave like humans. Within this technique, deep learning, an algorithm where data structures are modeled on the human brain, is making a lot of progress.

Data is the new oil. Its quantity and quality continue to improve. Thanks to this massive amount of datasets available, deep learning models are getting more sophisticated and reliable. The last piece of the puzzle is computing power. Thanks to Moore’s law (the notion that computational power doubles every 18 months), we have now access to more powerful and cheaper processing capacity to train deep learning models and implement artificial intelligence solutions.

Like hardware, the cost of AI development is coming down as the supply of professionals and development tools increase. We have seen this phenomenon before, with the commoditization of web development.  View More