Providing a generally-accepted definition of what qualifies as artificial intelligence (AI) has become a hot topic of debate in recent times. Some have rebranded AI as “cognitive computing” or “machine intelligence”, while others interchange AI with “machine learning”. However, AI is not one technology. It is in fact a broad field constituted of many disciplines, ranging from robotics to machine learning. Generally, the ultimate goal of AI, most of us affirm, is to build machines capable of performing tasks and cognitive functions that are otherwise only within the scope of human intelligence. In order to get there, machines must be able to learn these skills automatically instead of having each of them be explicitly programme. AI has become a topic of conversation in more and more companies who have come to see AI as a technology that is influencing their lives today. Indeed, the popular press reports on AI almost everyday and technology giants, one by one, articulate their significant long-term AI strategies.
While several investors are eager to understand how to capture value in this new world, the majority are still scratching their heads to figure out what this all means. There are several variants as for the major AI areas, but in this article I will pay attention to the following ones:
Natural Language Processing – the ability of computers to communicate with people in natural language.
Computer Vision – the analysing of images to find features of the images.
Knowledge based systems – systems that contain a ‘database’ of knowledge and can help in finding information, making decisions and planing.
Robotics – Create devices that can manipulate and interact with its environment.
Machine Learning – analysing data and treads to help with a task latter.
Automatic Programming – the creation of programs from a programmer’s specification.
Intelligent computer-aided instruction – customising the tutoring of a student to fit the students learning style
The hottest AI technologies which can be applied in these areas are:
Speech Recognition: transcribing and transforming human speech into format useful for computer applications. Currently used in interactive voice response systems and mobile applications. Sample vendors: NICE, Nuance Communications, OpenText, Verint Systems.
Decision Management: engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning. Sample vendors: Advanced Systems Concepts, Informatica, Maana, Pegasystems, UiPath.
Robotic Process Automation: using scripts and other methods to automate human action to support efficient business processes. Currently used where it’s too expensive or inefficient for humans to execute a task or a process. Sample vendors: Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, WorkFusion.
Text Analytics and NLP: Natural language processing (NLP) uses and supports text analytics by facilitating the understanding of sentence structure and meaning, sentiment, and intent through statistical and machine learning methods. Currently used in fraud detection and security, a wide range of automated assistants, and applications for mining unstructured data. Sample vendors: Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, Synapsify.
Biometrics: enabling more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Currently used primarily in market research. Sample vendors: 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo.
Machine Learning Platforms: providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train, and deploy models into applications, processes, and other machines. Currently used in a wide range of enterprise applications, mostly `involving prediction or classification. Sample vendors: Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, Skytree.
AI (Artificial Intelligence) is one of those technologies with the potential to reshape how we live, move, and work. AI is also commonly called “the electricity” of the 21st century, so let’s have a look at the key technology and business trends that will shape the evolution of AI market.Considering that some of the largest entities in the world are focused on advancing AI tech, it is all but certain that in the nearest future we will see significant advancements in the space. The following trends are among the hottest ones at the moment:
Automated machine learning (AutoML): model creation without programming
Developing machine learning models requires a time-consuming and expert-driven workflow, which includes data preparation, feature selection, model or technique selection, training, and tuning. AutoML aims to automate this workflow using a number of different statistical and deep learning techniques.
Automation and artificial intelligence is not trying to replace the people, but rather reduce human error and push the people up the value chain so that they are more strategic in the equation rather than rather than lower down the value chain where a simple error could cost tens of millions of dollars on a construction site, for example.
With the rise of Internet-connected devices we’ve got more and more sensors that understand more and more about us, and in 2018 they’re all going to connect together even more. So your fridge knows what’s in your fridge, and your thermometer knows what temperature it is, and your radio knows what day it is. This will all combine together and be able to give more inputs into the platforms and services that you use. For example, your Spotify will know it’s raining and will offer you a raining playlist, and your training app will know that it’s sunny outside and will tell you to go do your sprints outdoors rather than indoors. All of these devices that are all in themselves smart can connect together and create a greater picture of the context that you’re currently in and create a better response to that with the services giving you what you want at that particular moment in time without you having to ask.
Big Data & Analytics
Artificial intelligence is an ability to manage and illustrate vast volumes of data much quicker and much more accurately than human beings. With the continuing growth of the Internet of Things will come an enormous increase in the amount of data that is collected an ever-increasing number of connected devices as well as the need for a way to process and analyze this data.