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What’s The State Of AI In Cloud Computing? 9 Experts Share Their Insights

  • 28 September 2019
  • Sam Mire

The cloud has made our lives infinitely easier by storing our information remotely, but it's not been all peaches and cream. The cloud clears space on our devices while handling massive stores of information at a reasonable cost to the customer, but it's not an impenetrable safe for our data. Massive leaks of, um, sensitive photographs have been the most attention-catching scandals of the late 2010s, and they were made possible — at least in part — by flaws in cloud storage. 

But how has cloud computing evolved since the notorious iCloud photo leaks of 2014? Has security improved, or is the cloud still as vulnerable as our worst fears make it out to be?

These industry insiders filled us on in the state of cloud computing today. Here's what they said:

1. Nima Negahban, CTO of Kinetica

“- Organizations are still highly distributed and fragmented in the way they build and deploy AI models today. They need centralized structures for managing the creation, deployment, and auditing of their AI models.

– AI and cloud computing are intertwined. According to a study by LogicMonitor, AI will drive two-thirds of all public cloud use by 2020. Cloud computing reduces obstacles to adopting AI by providing ready-built systems, and once firms see the value AI brings, they are enthusiastic about expanding their investment in AI and the cloud.”

2. Brian Ray, Managing Director of Machine Learning for Maven Wave

“AI has reached a pivotal point where, when managed and coordinated correctly, problems are being solved at all levels throughout an organization. AI will become a core underlying technology more closely integrated with business process and consumers’ day-to-day life.”

3. Christine Livingston, AI Chief Strategist at Perficient

Cloud computing is enabling the widespread adoption of AI. For years, deployments of AI and machine learning stalled due to the lack of accessible computing power. While it has since become more cost-effective to create high powered processing units, not every organization is capable of maintaining an expansive data center. The scalability of cloud computing allows the distribution of processing power across many different enterprises and organizations, making AI much more accessible to a broader spectrum of users. 

There has also been a democratization of AI among vendors due to a commonly recognized shortage of data scientists. To remedy that reality, AI technology vendors are making the building blocks of AI more generally accessible by creating service-as-a-solution models made accessible through trainable APIs.”

4. Bret Greenstein, Vice President and Global Head of Artificial Intelligence at Cognizant

Bret Greenstein“The level and rate of innovation happening with the application of Machine Learning (ML) and AI technologies managing and optimizing workloads in cloud and multi-cloud environments is staggering. Every major cloud provider as well as the tools and hardware providers that work with the clouds have embraced, and are innovating with, AI. While the rate of cloud adoption by businesses is driving massive growth for the cloud providers in data and application workloads, it is exciting to see new sets of enterprise users being introduced to the tools and APIs used for machine learning as provided by AWS, Azure, Google, IBM, and others. However, it is important to note, that AI is certainly not constrained to the cloud as there is lots of great work happening on-prem in sensitive industries and on devices in mobile and IoT.”

5. Steven Mih, CEO of Alluxio

“Today’s businesses have become more data and AI-driven, and the cloud has become a critical part of a data platform that must keep up with increasing data sources and amounts of data. When it comes to cloud computing, many enterprises are integrating AI into their applications because of the immediate value it brings – real-time, smart data to better serve end-users. As a result, data/cloud engineers have a lot more to manage as reliance on AI-driven data grows. Analysts and scientists want data on-demand and expect job results immediately for interactive analysis, so engineers need to provide a platform that enables the users to serve themselves.”

6. Carl Hasselskog, co-founder and CEO of Degoo

“At this point AI is past being the new kid in cloud computing and we’re currently seeing companies start to implement AI technologies in more subtle ways that improve the experiences of customers without being intrusive or showy. When it comes to storage, for example, cloud providers have developed algorithms that best recommend photos, files and other documents they expect you to be searching for before you even realize it yourself.”

7. Jeff Looman, Vice President of Engineering at FileShadow

“Artificial Intelligence, particularly the subcategory of machine learning, is in widespread use within the cloud computing environment. Most users benefit from AI without even knowing it. Image content classification, facial recognition, identification of document semantics, sensitive information identification and credit card fraud detection are just some of the applications available for mere mortals.

Another AI application that we are seeing is in the management of the complex server clusters operating in the cloud. AI is being used to detect and manage system security, error detection, evaluation and notification of interrelated components before a systemic failure occurs, improving the availability of a system and making increasingly complex systems more reliable for end users.”

8. Rob Clyde, Board Director at ISACA 

“AI and cloud computing are closely linked. Developers and users can take advantage of AI as a Service (AIaaS) hosted in the cloud from many vendors, including large players like Google, IBM, Microsoft, and Amazon. Many types of AI require significant computing resources, which may be beyond the reach of many companies and solutions. By using an AI service in the cloud, like Google's Cloud Speech-to-Text API, adding AI to a product as a service is well within reach of most budgets. Additionally, many companies building their own AI or machine learning solutions will use the cloud to host it so that they can easily scale it up or down as needed, thereby avoiding a costly initial outlay for hardware. This is especially useful when projects are in the research, development and test phases.”

9. Michael Harrison, Managing Partner at Winterberry Group

“While we are relatively early on in the maturity curve of AI, the democratization of AI has allowed it to permeate throughout advertising and marketing. Winterberry Group's research shows that marketers continue to invest in AI/ML (Machine Learning). Historically AI was constrained due to computing power, but cloud computing has eliminated those constraints. AI has allowed marketers to begin shifting from focusing on execution to concentrate on strategy.”

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About Sam Mire

Sam is a Market Research Analyst at Disruptor Daily. He's a trained journalist with experience in the field of disruptive technology. He’s versed in the impact that blockchain technology is having on industries of today, from healthcare to cannabis. He’s written extensively on the individuals and companies shaping the future of tech, working directly with many of them to advance their vision. Sam is known for writing work that brings value to industry professionals and the generally curious – as well as an occasional smile to the face.