The Impact of AI Engineering & Deep Learning on Business
The interview of Vyacheslav Dodatko, CEO and Co-founder of Anadea, on the topic of top Business and Technology predictions is originally published in CIO Applications and CIO Applications Magazine - an enterprise technology magazine that reaches out to about 200.000 qualified print and digital subscribers in the U.S.
AI Engineering & Deep Learning Silent Revolution in Software Development
The most important trend in the coming years will be AI engineering and a silent revolution in software development caused by Deep Learning. I believe that deep learning will have a tremendous impact going forwards. Deep learning AI development is finally helping make the applications we see in fiction come to life in the real world.
What’s more, thanks to movements in the market, stronger Internet technology, and Cloud computing, smaller companies are able to enjoy the sort of deep learning tools that were once only available to blue-chip industry giants.
Video Processing Using Neural Network
Things as simple as neural network processing of the video feeds from cameras in superstores mean that merchants can examine consumer behavior and use it to refit their shops and reorganize their product placement to stimulate more sales. Where automated thief detection was once the fevered dream of science fiction writers, we now have systems that can flag potential thieves for further examination as they leave the store.
Accessibility
Accessibility is now a staple of modern development. Creating a piece of software without accessibility functions would be like creating a car with no door handles. Yet, where integration used to be a problem or used to require the addition of bulky chunks of coding, accessibility can now be integrated and enhanced with deep learning technology to make app or web solution suit people with a range of disabilities and impairments.
Information Security
Information security is both a very difficult element in modern development, while also becoming more and more vital because lawmakers are insisting on tighter and tighter controls. Thanks to brilliantly crafted AI, modern monitoring has taken on a whole new dimension of accuracy and timely detection. Everything from anomaly detection to identifying fraud patterns has been improved to the point where deep learning technology is fighting the battle on a whole new front. Halting and preventing attacks has never been so advanced.
Wearables
Wearable technology is a novelty to demand, and an irreplaceable mainstay of the health and wellbeing industry. Not only is such technology used to help administer medication and treatments, but is also used to monitor overall health, track recovery progress, and even ensure timely doctor visits. Such technology is helping in all areas, from eldercare routine maintenance procedures to rehabilitation.
The potential of wearable devices goes far beyond healthcare. Businesses are shrugging off the novelty of things like video feeds in smartwatches, to actually having their staff conference remotely from around the world. Startups are building apps that help people in business with everything from maintaining a better posture, to swinging their golf clubs correctly when they play.
Natural Language Processing (NLP)
The advances in natural language processing are finally starting to show through in a meaningful way as companies have tried and failed for years to help a computer understand the meaning of written text rather than simply interpreting it.
Proceeding the theme of natural language processing, recently Anadea DL-team took the “contact us” form on our website anadea.info, which had a built-in spam filter. It was working through giving false positives from time to time, marking a valid inquiry as spam. And with the help of the NN model, we can now automatically analyze and sort incoming messages into several categories, and so far the DL-powered system has correctly identified every single message (no false positives).
“Is there a limit to deep learning? Are the opportunities endless? I am very excited to be part of the deep learning revolution.
Being here to witness and experience the breakthroughs we see every year and watching as AI grows and becomes more advanced. It leaves me encouraged and optimistic for our future.”
Does Everyone Need DL Features?
If we wish to harness the sheer power of deep learning (modern neural networks), we need to start reexamining our whole approach to software development. AI cannot be compartmentalized. It cannot be considered an additional extra or a tool. Deep learning technology needs to sit at the heart of all software development if we wish to push the boundaries and move forwards with any real sense of progress.
Deep learning models and frameworks shouldn't be thought of as something to plug into an existing application, they should be used by seasoned professionals who fully understand the potential of deep learning concepts.
What It Takes to Successful DL Projects
To gather and diligently prepare the dataset, to train a model (or select a pre-trained model), to validate results, and integrate the model with the software/application, a team needs to build its foundation on deep learning technology. At Anadea, we pride ourselves on adding ModelOps and DataOps to the more traditional DevOps engineers, and as always, we are prepared for any market change.
Over the past twenty years, I have seen innovations flourish and fizzle, and I have to admit that AI deep learning technology is the most exciting yet. We have helped breathe new life into projects and push the boundaries of innovation thanks to our expert use of deep learning technology. The possibilities seem endless, and we think that is marvelous.
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