What is cognitive computing?
The quest to create a computer that thinks like a human being is almost as old as computing itself. Since the 1950s, research into artificial neural networks has meant that artificial intelligence is increasingly a matter of science fact rather than science fiction. Cognitive computing, building on these principles, uses advanced machine learning algorithms and highly advanced artificial neural networks to mimic the way the human brain works.
Today, artificial intelligence is being used to automate the processing of large amounts of data. Cognitive computing systems are able to teach themselves to do a range of complex tasks. Although many cognitive systems need the data they use to learn to be carefully tagged and formatted by human subject matter experts. More recently, cognitive computers have been developed that can learn from unstructured content. This paves the way for artificial intelligence to be able to fully automate its own learning process; an important step on the journey towards more independent AI.
How will this affect how humans work?
These systems aren’t about to replace humans in the workplace any time soon. They work best as an adjunct to human creativity, assisting with decision making by taking over a variety of repetitive but complex data analysis tasks normally undertaken by humans. Improving on the performance of less advanced data mining algorithms, cognitive computers are able to understand context and nuance better than ever before, produce reports based on the recipients requirements, highlight actionable information, and more.
Artificial intelligence can now free up valuable human capital to concentrate on decision-making, intuition, and creative problem-solving. The workflows that cognitive computing can automate are processed faster by machines than humans, and being completely scalable are ready to deal with ever-increasing amounts of data globally. Cisco predicts large increases in the volume of data in the next few years; no organization can afford to ignore the processing and analysis capabilities of cognitive computing.
Some examples of current work automated by artificial intelligence include improved diagnosis of diseases, advanced threat protection, real-time redaction of sensitive information, improved search results, and more intuitive chat bots. The ability to generate reports on the fly, based on current data from a number of sources, and then present them in a customized format with action points highlighted is just one of the things these systems can do. Even this one ability can be tailored to work for many different industries.
What are some other things cognitive computing can do?
Another thing that cognitive AI is good at is monitoring the patterns of action and inaction that frequently result in data breaches . The system can then take action with no recourse to human intervention, reacting information from sensitive documents, and alerting security personnel in real time. Currently data loss due to human error alone accounts for a large proportion of incidents overall, both by number of incidents and by overall cost.
If you think the idea that thinking machines will be everywhere within the next eight years sounds far-fetched, current research indicates that there will be a huge increase in the number of cognitive computing systems in regular use over the next 8 years. It’s estimated that by 2025 the global market will be worth USD $49.36 billion, with around 40% of that market being natural language processing something Coseer’s self-training cognitive computer is optimized for. With reduced training times, and higher accuracy rates than our competitors, we’re ready at Coseer to help you discover how cognitive computing can transform your workplace. Get in touch today to arrange a demonstration.