By Russ Banham
Business loves acronyms, and there’s been no bigger acronym recently than AI. AI, of course, lets companies optimize their operations, business models and customer experiences around data-driven insights, while developing products and services that align more closely with customer needs.
Now that leading cloud service providers are providing AI-driven machine learning and deep learning training platforms—customized to business user data and accessed as cloud-hosted application programming interfaces—companies of all sizes can seize the benefits of AI.
By offering an alternative to on-premise AI solutions, cloud providers are giving small businesses the same advantages their larger counterparts are looking to exploit. Among the valuable AI tools at their disposal are natural language processing, image recognition, translation, search functions and data analytics.
“For many types of AI problems, companies can derive benefits much more quickly than before,” says Carlos Morales, senior director of deep learning systems at Intel and an executive staff member of the technology company’s AI Products Group. “If there’s a process in a business that required the hiring of many data engineers and scientists, AI as a service in the cloud is a way to get things done without relying on so many of these individuals.”
For larger business entities, AI can serve more complex business needs, according to Morales’ colleague Binay Ackalloor, who leads Intel’s Enterprise Business Development Group for AI Products.
“In my work with companies across the spectrum, an analyst or researcher might say, ‘What if I apply AI to this particular problem, and if we see good results we can get the company’s management to buy in to move the project forward?’” Ackalloor says.
In this business-use scenario, AI is a means toward firming up returns on an investment in ongoing research.
“By using AI to analyze the data, you may learn that it can help you move certain products X% faster at Y% less cost to make Z% customers happier,” Ackalloor explains. “The CEO and top brass now have crucial information to move the project to the next milestone.”
AI Cloud Considerations
Five years ago, deployment of AI-enabled business technologies was limited by cost, as well as by the availability of the expertise that development required. Few companies had the right skill sets on staff to work with line-of-business professionals in identifying valid use cases, locating relevant data, building an application, and assessing the costs and benefits of running it.
Cloud-based AI has altered this paradigm for the better.
First of all, many companies already have their data in the cloud, making it vastly easier to transfer massive data volumes for AI analytical purposes.
“If a business has already invested in the ‘cloudification’ of business processes and data management, then it’s a no-brainer to do machine learning and deep learning on the platform,” says Morales.
“A business running 24/7 across the world on different platforms can put in place a robust pipeline to manage all the data produced—not just its own data but third-party data, too,” he says.
Cloud-based AI addresses the need for specialized technical expertise, too, since most cloud providers have scores of data scientists and data engineers on hand to build and service AI applications. They also maintain the infrastructure and DevOps teams necessary to maintaining the highly dependable services that modern businesses require.
“Many cloud environments run on Intel® Xeon® processors designed for next-generation data centers that are being used for AI,” says Ackalloor. “These processors help to greatly improve the performance of those cloud environments as compared to just a couple generations ago.”
Lastly, the cloud has an easy-to-maintain infrastructure.
“A large data science team shouldn’t have to spend time managing data, services and servers instead of doing data science,” Morales says. “In such cases, you’re better off paying a cloud provider.”
Some sectors that confront data privacy regulations will have a difficult time using cloud-based AI, however. Healthcare is prime among them. Hospitals are likely to use on-premise servers in their AI endeavors.
“Regulations put a heavy burden on the healthcare sector to guarantee the privacy of their patients and then audit that data,” Morales says. “Consequently, many healthcare facilities don’t trust cloud providers with that data yet.”
One Step At A Time
AI is a major plank in many companies’ digital transformations. Opportunities are available to digitize and analyze truly massive structured and unstructured data elements, with the goal of generating business insights that lead to a competitive edge.
At present, roughly 2.5 quintillion bytes of data are produced each day, the data equivalent of covering the earth with pennies side-by-side five times over. By 2025, this figure will increase fivefold, according to a study by the IDC.
All that data is a gold mine of enterprise information, assuming a company has invested in AI-enabled technologies to ferret out the desired insights. That expense hasn’t stopped most midsize to larger businesses from moving forward with their transformations. Cloud providers can help large, medium and small businesses alike in pursuing these goals.
A company looking to get its feet wet can migrate its data to the cloud and use an AI application to speed up processing tasks. Larger entities can deploy other AI apps to cull rapid insights from their data for business decision-making purposes.
Intel makes all this easy by offering free cloud computing training and services to businesses through its AI Developer Cloud. The company collaborates with leading cloud infrastructure providers like Alibaba, Microsoft, Amazon Web Services and Google to power AI applications on Intel hardware. It’s also working with partners such as C3 whose Software as a Service (SaaS) analytics platforms run on the leading cloud service provider infrastructures.
Intel also enjoys a long track record working with next-generation AI startups.
The varied benefits of cloud-based AI make it “inevitable that the cloud is how most companies will use machine learning, deep neural networks and other AI tools,” he adds.
“We’ve invested more than $1 billion in support of AI product innovation and technology adoption, as well as in innovative AI companies through Intel Capital,” Ackalloor says.
Added up, it looks as if cloud-based AI services could be the entryway to many companies’ digital transformations and data mastery.
As Morales emphasizes, “No longer is this out of reach for many businesses.”
Russ Banham is a Pulitzer-nominated financial journalist and best-selling author.