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Nara Rajagopalan, CEO of infrastructure software maker Accelerite, told eWEEK recently that “AI isn’t just a hype; thinking machines will rule our lives–but perhaps not literally.”
He appears to be on the right track. Look at what Siri, Cortana, Google and Alexa are doing for us more and more all the time. Look at how many new chatbots pop up on our phones and laptops to help us through a purchase transaction. Look at how we’re conversing with cars as if they are our BFFs.
Artificial intelligence is interacting with us on a more and more human basis all the time. At the moment, this is happening mostly on the consumer side; watch what happens in enterprise during the next one to two years.
From virtual network assistants to location services, technologies powered by artificial intelligence are simplifying operations, lowering costs and offering previously unseen insights into the user experience–improving the lives of both IT professionals and their users in myriad ways. We don’t know the half of it, either; we have no idea of how far all of this will extend and how many potential use cases there really are at this early point.
‘Collision of IT Powers’
This is all about what eWEEK has termed a “collision of IT powers”—the result of a major convergence of new-gen IT products and methods–led to the market by the DevOps and DataOps development approaches–during the last five years that includes:
- more efficient, secure networks;
- faster, more powerful, yet cooler-running processors;
- virtually unlimited data storage in the cloud and on premises;
- leaner, faster code for applications of all kinds;
- vastly improved edge devices; and
- more efficient application architectures.
And we’re not forgetting new, more intuitive user interfaces that are understandable by most people and almost innately by the last three generations (GenX, GenY/Millennials and Boomlets) who have grown up with computers and computer games as personal companions.
The combination of all these has led us to where we are today: at the beginning of new wave of practical artificial intelligence backed by machine learning, made available widely and at our fingertips.
Security is Still the Major Wild Card
The one factor for which the jury is still out is security. While aspects of security have improved (there is true progress in network-centric, data-centric and application-centric security at this point), there are still more problems to solve in that category than anywhere else.
“My school-going daughter is playing with Tensorflow to see if she can generate harmonies for any given song for her choir,” Rajagopalan of Accelerite said. “She doesn’t know the math behind the learning algorithms, but things are getting easy enough for most people who can write some code to explore machine learning. While the basic math behind AI has been well understood for years now, the cost of compute and its availability along with the tooling around it is moving at a fast pace to democratize AI.”
“Several companies, including us, are exploring if we can convert a Q&A worksheet of what one wants to predict into learning programs. The job of assembling meaningful learning data sets, seeing the accuracy of predictions, constantly tuning the algorithms, even picking different ML models to improve your predictions – all of this is getting easier by the day. Not only are the machines learning, but they are picking and choosing among various learning algorithms to see which predicts the future better. Scary–and you thought Elon Musk is nuts to think machines will rule the world!”
Other thought leaders in this space have relevant data points to share. One of them is Jeff Aaron, Vice-President of Marketing at Mist, a Sunnyvale, Calif.-based company that builds automated, self-learning wireless networks powered by AI. Aaron explained to eWEEK readers five ways he believes AI is changing IT for the better:
Natural language processing (NLP) puts a face on AI: NLP enables simple queries, elastic searches, feature rankings, data mining and more, allowing IT to easily understand everything that’s happening in their environment without having to manually sift through mounds of data. Because AI-driven tools such as virtual network assistants can answer questions on par with domain experts, they offer simplified operations and integrated help desk functions – helping IT become more proactive, faster and smarter over time.
Automated event correlation cuts troubleshooting times nearly in half: With AI, IT can rapidly identify problems across domains for equally rapid fault isolation and resolution. According to analyst firm IDC, automated event correlation can save up to 40 percent in ongoing costs.
Set, monitor and enforce user service levels: AI allows IT to set up and track service level thresholds for key user performance criteria. For example, in a wireless network setting, this includes time to connect, capacity, coverage, roaming and throughput. IT can then identify if user service levels are trending in a negative direction and predict what kind of experience can be expected in the future – ensuring the best possible user experience.
Understand trends over time and across global data sets: AI-powered IT tools can proactively detect anomalies and determine the scope of incidents. For example: Are issues associated with a particular user or a single user? A certain type of device? Or a specific application or operating system? By tracking metadata across many locations and users, global trends can be detected and addressed with machine learning.
Machine learning calculates location with 1 to 3m accuracy: For example, within a wireless network, calculating path loss and other data in the cloud can deliver high-accuracy location without battery-powered beacons. This enables personalized indoor location services to be deployed easily at scale, such as wayfinding, proximity notifications and asset finding.