How Can You Choose the Right AI Storage Solutions?
AI processes immense amounts of data, which requires fast storage to be effective This article discusses...
It’s no secret that artificial intelligence will continue to change the business landscape in the coming years, but just how important is AI? In a study by Accenture, 75% of executives stated they feel at risk of going out of business in five years if they don’t scale AI. These are pretty alarming numbers, so what is fueling this dependence on AI?
AI is showing its value in more and more industries. Its applications include endeavors as complex as machine learning algorithms that aid in healthcare diagnosis and customer prediction software that helps match up customers with products that appeal to them. In this article, we’ll look at 11 AI technologies that influence the industry as a whole.
Natural language generation (NLG) helps computers better mimic human behavior to interact with technology more naturally. For example, NLG is used to generate weather reports, patient reports, and image captions automatically.
Speech recognition uses AI to translate spoken language into text. Most of us are familiar with applications like Siri and Google Assistant. These applications allow people to perform many actions using their voice, like making reservations, asking questions, and issuing commands. Speech recognition is also an essential technology for making programs accessible to everyone.
Conventional processors don’t meet the needs of AI software, especially when you consider the need to scale as programs roll out. AI-optimized hardware is better suited to power deep learning and neural networks as it allows AI to leverage parallel processing capabilities.
Machine learning (ML) solutions are tools that allow computers to learn and make decisions. ML algorithms power most of the examples on this list since they are a vital component of artificial intelligence. Its uses include image recognition, speech recognition, spam filtering, fraud detection, and much more.
Virtual agents are often the first interaction for a customer in their support or purchasing journey. The agents are trained to make decisions based on a set number of responses from the user and leverage natural language technology to help them understand what the user wants. Virtual agents are important contributors to positive customer experiences and speedy conflict resolution.
Robotic process automation allows machines or software to perform repetitive tasks typically performed by a human. This type of automation is advantageous in manufacturing since it will enable a robot to interpret, communicate, and analyze data.
Peer-to-peer (P2P) networking allows computers and systems to connect without the aid of a server. This direct connection between devices allows for a faster communication, which is key to many powerful AI applications. Additionally, P2P networks can leverage blockchain technology to increase transparency and security.
Deep learning is inspired by the neural networks found in human brains. The goal of deep learning is to imitate humans and enable machines to learn by example. Neural networks have hidden layers that work together to perform predictive analytics. These hidden layers contribute to the function of the whole, much like the synapsis in our brains. This AI function is used in detecting objects, speech, languages, and making decisions. Its advantage is that it can work using data that is unstructured and unlabeled.
Text analytics takes enormous amounts of unstructured text and turns it into quantitative data to uncover insights, patterns, and trends. When combined with the power of text analysis, users get both a qualitative and quantitative view of the data. This technology is key to extracting insights in the retail industry and over social media.
CDNs and fog computing networks rely on AI software that helps them ward off attacks. This AI-powered software enables networks to detect, mitigate, or even eliminate threats to the network — significantly reducing downtime and the long-term ramifications of cyberattacks.
Many businesses use some form of marketing automation to automate the work their sales and marketing teams perform. AI is helping make this software more robust by performing complex tasks like segmentation, product recommendations, visual search, and predictive analytics.
Your business likely uses AI in some form or another today, even if it’s hidden within one of your marketing tools. The solutions we’ve reviewed in this article show that the demand for AI-powered solutions will only continue to grow. Companies that put AI on their business roadmap are more likely to successfully use these tools to keep their organizations viable for years to come.
Intequus specializes in helping companies build the artificial intelligence and machine learning infrastructure they need and maintain that hardware over its entire lifecycle. If you’d like to discuss how you can build out your artificial intelligence infrastructure, reach out to one of our experts.