AI is very important as it automates repetitive learning and discovery through data. But most people confuse AI with robot automation, AI is much different from hardware-driven, robotic automation in so many ways. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions.
AI is an enhancer to existing or future products, what it does is adds intelligence to these products, whether they are automobiles or a Netflix. In most cases, AI is not sold as a standalone product, it needs a purpose and the purpose is the product that it will make intelligent. It improves these products with AI capabilities, much like Siri was added as a feature to a new generation of Apple products or Google Assistant was added to Google products. Automation, conversational platforms, bots and smart machines can be combined with large amounts of data to improve many technologies at home and in the workplace, from security intelligence to investment analysis.
AI adapts, its constantly evolving through progressive learning algorithms to let the data do the programming. AI targets and finds structure and regularities in data so that the algorithm acquires a skill, basically the algorithm itself becomes a classifier or a predictor. Have you even went online and saw an advertisement for something that you were looking into?
Well whether its Google, Facebook, Amazon or any other platform that sells products or services, they all use AI in some fashion. Just like computer chess, the algorithm can teach itself how to do a number of things and we are just scratching the surface. Just like humans, a technique used by AI is called Back Propagation, basically it allows for the platform to adjust through human input and just training.
AI analyzes very deep data using neural networks that have many hidden layers. For example building a fraud detection system with five hidden layers was not even possible just a few years ago and now that has all changed due to the immense computer power that allows big data to be processed quickly. Its imperative that a lot of data is used in order for deep learning to take place, this is always why Big Data is Big Business. To train platforms to use deep learning you need big data, otherwise it becomes limited. The more data then it just increases the accuracy with each learning cycle.
AI achieves incredible accuracy through deep neural networks, to put this in simple terms, when you access Google search ,Google Assistant, Alexa, Google Maps etc, these are all based on deep learning. The more you use them you will find the more accurate they become. AI from deep learning has become a great asset to the medical industry as it uses object recognition and image classification to find cancer cells on an MRI, something that only a trained radiologist was able to do.
Keep in mind that the AI in itself isn’t the next frontier but it’s the large amounts of data that will make AI the next frontier. The players with the most data will be the leaders in the AI industry.
