Blog: Tech at the Edge: Automation for All, Mind-Transforming Trends + Deploying Machine-Learning Models
NEW YORK — April 25, 2019 — In our lead story, companies in nearly every sector are increasingly leveraging time-saving “software robots” — enhanced by artificial intelligence and machine learning — to automate tasks like communications and customer service.
“The vision that we are driving towards is automation for all” according to Kashif Mahbub, VP at Automation Anywhere. “You don’t have to be somebody who is proficient at coding. You don’t have to be somebody who is just doing one part of the business. Anybody should be able to pick it up.”
Last week, we examined automation’s potential impact on job creation, and how it could actually lead to “super jobs”. We also looked at the characteristics of tasks that could potentially be “automatable”. This week we want to advance that discussion into new directions.
So naturally we pivot towards artificial intelligence, which is transforming a broad set of business functions. In fact, some believe AI’s impact on business will be greater than the internet.
AI is different from human intelligence. It is basically any device (or even digital tool) that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.
But how does AI’s proverbial “rubber” hit the road? AI is touching things like individualized customer marketing, employee screening, smart products, efficient data collection, as well as automated customer support. The potential applications are boundless.
In fact, AI has begun to change organizational processes on a scale that the re-engineering movement of thirty years ago could only imagine, reports Forbes. Leaders of businesses that don’t move quickly to capitalize on the power of AI will be left behind.
This takes us to a really good question: Why are many companies still hesitant to apply artificial intelligence to their corporate strategy?
Our answer has many complicated layers. For starters, the learning curve for technologies on the edge like AI can be downright terrifying. But beyond the skill set needed to implement AI, there is research pointing to an almost non-specific fear of competition from machines. Or maybe better said, our egos are getting in the way of getting help in areas of need. Look at it this way: no human team can gather data, analyze, and make decisions with the speed and scale of machines.
Don’t just listen to us, look at the evolution of AI in powering marketing, sales and customer support. Leveraging AI’s power in other areas is simply IT evolution.
Next, let’s check out our top three “tech at the edge” trends:
1.) Save-to-transform mindset: Rather than focusing solely on cutting cost, the emphasis here is to invest in digital technologies and innovations that extend market reach, service quality, operating efficiency, use of talent, and the overall customer experience. In addition to fueling both cost savings and revenue growth, these improvements can make a business more resistant to digital disruption and economic downturns by providing a stronger foundation for defense-oriented cost management activities — activities that are sure to be needed at some point in the future.
2.) Robotic process automation: Used to automate repeatable tasks such as system monitoring, the distribution of software basic technical support the provisioning of IT equipment and workload scheduling. It can be implemented quickly and at a low cost. Interestingly, the global RPA market is expected to grow from current estimates of around 200 million dollars to nearly 700 million dollars by 2025.
3.) Intelligent automation (IA): Tools enabled by cognitive technologies such as machine learning and natural language processing have more of a transformative potential. For example IA can allow for immediate answering of customer queries and can also improve compliance with complex legislation by automatically reviewing documentation.
And finally we want to look at a tool available today that is helping companies build, train, and deploy machine learning models fast.
SageMaker (from Amazon Web Services) enables developers and data scientists to utilize machine learning models at any scale. This is a “fully-managed” service offered by AWS so it removes the complexity that gets in the way of successfully implementing machine learning across use cases and industries.
From running models for real-time fraud detection, to virtually analyzing biological impacts of potential drugs, to predicting stolen-base success in baseball, SageMaker covers the entire machine learning workflow.
You simply choose an algorithm, train the model, tune and optimize it for deployment, make predictions, and take action.
Specifically, SageMaker offers “one-click deployment” which means users can deploy with auto-scaling clusters spread across multiple zones to deliver both high performance and high availability. It also reduces inference costs up to 75% by provisioning just the right amount of GPU performance you need.
The service also extends fully-managed hosting with auto scaling so your production infrastructure is able to perform health checks, apply security patches, and conduct routine maintenance.
“Incorporating machine learning into our systems and practices is a great way to take understanding of the game to a whole new level for our fans” according to MLB CTO Jason Gaedtke. “Delivering machine learning services creates new opportunities to share never-before-seen metrics.”
Technology at the Edge is produced by Tech Rally Media in New York City. and sponsored by RestonLogic, cloud wizards leveraging over 10 years experience helping companies automate, transform and build highly-secure and stable systems. RestonLogic offers a complete suite of IT and cybersecurity solutions from managed services to strategic advisory. Visit RestonLogic to book a strategy session today.