The Future of Artificial Intelligence
Recent innovations in artificial intelligence are unprecedentedly changing the digital landscape and people's lives. For the first time in history, human intelligence will be replaced by artificial machines. This change is accelerated by sophisticated technologies based on artificial intelligence, machine learning and deep neural networks.
We will review the latest artificial intelligence technologies, key trends and the future of our world as a whole.
AI Chips
Major chipmakers are striving to develop AI-based chips that speed up the execution time of AI-dependent applications. AI applications such as speech recognition and computer vision involve complex mathematical calculations that make it difficult for processors to run these applications. AI chips will be a revolution in the future development of technology.
Flying Autonomous Vehicles
Companies such as Airbus and Uber Technologies are investing in the development of unmanned aerial vehicles. They are designed to improve transportation in densely populated areas, enable fast cargo delivery and economical air travel. Even Amazon has launched a drone delivery initiative to improve its service.
Level 5 Autonomous Driving
Level 5 autonomous driving means full automation of the vehicle. This means the vehicle can operate completely without human intervention. Level 5 vehicles must be able to collect data about their surroundings and manage all driving tasks in various conditions.
Fully autonomous vehicles will allow people to use their travel time more efficiently. Various concepts with a gym or a workplace installed in the vehicle are already emerging.
Facial Recognition
Thanks to extensive research in facial recognition, a type of biometrics, it will remain an important part of how AI shapes the future. Facial recognition will be widely used because it is the "fingerprint of the future". New research is emerging on detecting people even by analyzing their heartbeat. As detection accuracy continues to improve, the use of facial recognition is expanding exponentially.
Conversational AI Platform
Conversational AI platforms offer APIs for developers so that third parties can create and customize dialogue user interfaces and virtual assistants such as Google Assistant, Bixby and Siri. Assistants or chatbots can be stopped or turned off.
Currently, conversational AI platforms include a messaging style, a rule-based chatbot, and text-to-speech for customer service. Efforts are underway to enable chats to handle more complex cases and better understand user intent.
Edge AI
Edge AI involves using AI methods such as machine learning, deep neural networks, computational logic and optimization of IoT (internet of things). IoT and AI can work together in three different ways: IoT data is used as input for an AI system, AI methods are applied to an IoT system, or AI and IoT methods are combined for mutual benefit.
Research and trials are currently underway on using edge AI in autonomous navigation, network availability and video analytics.
Autonomous Mobile Robots
Next-generation autonomous mobile robots will operate independently, without human intervention, using advanced sensors, navigation and intelligence. The new type of robots will have several motion and sound detectors, as well as the ability to move on their own (even across floors with obstacles such as cables) and to respond to unexpected scenarios. This technology will bring many new things to manufacturing.
Connected Home
A connected home is designed to automate domestic space. Multiple devices and applications are linked to multimedia entertainment, home security, monitoring, energy management and healthcare. Virtual assistants (Amazon Echo and Google Home) have made the connected home concept popular.
Today, machine learning methods and analytics engines are being tested to go beyond the programmable home and create an intelligent home powered by AI technologies in the future.
Smart Workspace
A smart workspace uses IoT, artificial intelligence, space mapping and smart buildings to revolutionize the workplace by introducing new ways of working, collaborating, planning and coordinating. To adopt this concept, organizations will have to change the design of their workspaces and understand the complex interaction between people and physical space.
AI PaaS (Platform as a Service)
AI PaaS offers tools for building AI models, APIs, prediction models of various types and general data classification. The cloud-based approach of AI PaaS is disrupting the established market of on-premises platforms for data analysis and machine learning. In the future, AI PaaS aims to enable rapid creation and deployment of AI solutions.
All technologies of the future are moving behind artificial intelligence, from smart devices to smart homes. In the near future, AI will literally be everywhere in our daily lives. If a company from any industry wants to "upgrade" and enter a new era, it must implement core AI services: machine learning, natural language processing, computer vision and deep learning.
