New communications systems are being developed at an ever-increasing pace. The amount of data flowing through these systems is also increasing at a faster pace, with the adoption of IoT and Artificial Intelligence (AI) in our daily lives. These two factors have created unprecedented opportunities for machine learning to support new communication systems.
Machine learning has the ability to automatically detect patterns in data and make predictions based on that data. This can then be used to improve user experiences and lead to new communication systems that become more effective, faster and easier to use.
Some examples of this would be speech recognition or language translation, or even chatbots that aid users with queries or tasks within a chat system. AI is another area where machine learning can help improve existing communication systems.
AI largely consists of algorithms that learn from examples and apply features based on what they see as opposed to just one example. For example, if you talk about AI chatbots you will likely hear about neural networks or deep learning, which are specific types of AI that work with neural networks.
A third type we’ll mention briefly is reinforcement learning, which typically involves playing games to train artificial intelligence programs and create more effective bots in future communication systems such as online shopping carts or online banking platforms.
What is Machine Learning?
Machine learning is a growing field that uses algorithms to teach computers to perform tasks by building models from large amounts of data. These computers can then be “trained” to make correct predictions based on examples. These programs can then be used to create new systems that use these algorithms to make predictions and improve existing systems through automated “onboarding”.
Machine learning is not a new concept, it has been around for a while, and it has seen tremendous growth in recent years due to the adoption of large-scale IoT and AI. Machine learning has been around for a long time, but it has only recently begun to be used to its full potential due to the wide adoption of AI and IoT.
One of the early uses of machine learning was in speech recognition, where the computer would identify speech and understand what word or words were being spoken.
This was a huge step forward, as it enabled computers to “hear” language and understand what is being said to them. Today, AI-based speech recognition systems can accomplish amazing things, such as being able to complete tasks such as recognizing and creating word suggestions for a variety of topics or languages, understanding a person’s voice and delivering the appropriate response.
AI has also seen use in text-to-speech synthesis, where the computer “reads” text and converts it into sounds or speech. This can be used to create voice-overs for video or podcasts, or it can be used to generate text in different languages or accents.
Some systems also allow the user to “train” the system to produce better text to speech, meaning that the computer is able to learn to sound more like a human being.
AI Support for Existing Communication Systems
Machine learning can also be used to support existing communication systems. One example would be language translation. A machine learning system can be set up to “listen” to language and understand the concepts being discussed. Using that understanding the system could create a “speaking” version of the language that is more accurate than a human could achieve.
This ability to “read” language and produce a more accurate “speaking” version would greatly benefit hearing-impaired people, such as the elderly or people with disabilities.
Machine learning is a growing field that uses algorithms to teach computers to perform tasks by building models from large amounts of data. While still in its infancy, machine learning can make significant contributions to communication systems.
By automatically detecting patterns in data and making predictions based on that data, it can improve the user experience and lead to new communication systems that become more effective, faster and easier to use.