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Which Trends Are Shaping AI In Cloud Computing? 7 Experts Share Their Insights

  • 29 September 2019
  • Sam Mire

Trends aren't just for Twitter. Every industry, from real estate to retail, is subject to trends. Fail to keep tabs on these trends, and companies risk losing their connection with the very customers that keep the doors open and the lights on. Companies that sell cloud computing services are no different from Wal-Mart or H&M in at least one respect: the need to cater to customers' wishes and embrace the latest industry trends, and using the latest technologies AI included — is critical to keeping customers happy.

These industry professionals summed up what they see as the foremost trends in cloud computing. Here's what they said:

1. Nima Negahban, CTO of Kinetica

“One trend to watch for is in edge computing. Edge computing refers to data analysis, including AI, that occurs on a device, rather than being sent off elsewhere for processing. As the IoT matures the incentive will increase to invest in edge computing to further enable a massive network of interconnected devices.”


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

Bret Greenstein“There are several AI in cloud computing trends that matter. The first is the growth of AI optimized hardware and Virtual Machines (VM) in the cloud for AI training. GPUs in the cloud and specialized VM’s for deep learning are allowing faster design and testing of AI systems in the cloud. The second trend is improved tools and services — image recognition, natural language processing, TTS/STT, and other ML services are all improving in leaps and bounds.. They are more accurate and take less space and processing then they did in the past.”


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

“AI is bringing new functionality to operations that in the past have not been inherently user-friendly or intuitive. In the world of cloud storage, platforms are becoming more experiential for users, now more valuable to them in ways beyond their conventional role of purely existing for storage purposes. AI is capable of (securely) utilizing user data to provide a more personalized touch to various cloud functions whether it be saving information or organizing and reviewing files and photos.”


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

“Hands down, the enablement of Deep Learning. Deep Learning has seen many innovations this year including: functionality to better recognize speech and images, and to classify information real-time into categories; as a reusable piece of software that performs predictions time and time again, consistently and accurately; as an output of more sophisticated machine learning platforms allowing their building, testing, and deployment.”


5. Steven Mih, CEO of Alluxio

“We see a lot around the disaggregated data stack when it comes to managing AI data. Over time systems have become more distributed, hardware has become much faster, and a ton more AI-driven data needs to be managed. Add cloud computing to that, and today the data stack that most innovative companies like Uber, Twitter, etc are building is a fully disaggregated stack. Each core element of the original relational database management system is now a standalone layer. Storage engine options range widely from HDFS to cloud object stores to on-prem object stores. Table catalog choices range from Hive Metastore on premises to AWS Glue on AWS. Data orchestration technologies have emerged as the buffer pool layer.”


Christine Livingston, AI Chief Strategist at Perficient

A huge trend right now is the democratization of AI, but another major theme to watch is the adoption of natural language processing, a subset of AI. Within the next year, there’s going to be widespread adoption of natural language processing systems, such as intelligent automation and virtual assistants, which are driven primarily by unstructured content. This trend is more so applied to AI, but it will be made that much more accessible and possible by cloud computing.”


6. Michael Harrison, Managing Partner at Winterberry Group

“The #1 trend is the availability and relative ease of implementation of AI. Ad Tech and Marketing Tech providers have invested heavily in integrating AI into their platforms. While technology is working to decrease the reliance on data science and engineering professionals, these individuals are critical to successful implementations of AI. There is a shortage of individuals with analytics and ML skills limiting the adoption of AI.”


7. Jeff Looman, Vice President of Engineering at FileShadow

“The most significant trend in AI is managing the proper use of each application. As new applications go live, reaction from the public shapes its adoption or rejection. Facial recognition software is one example of this public adjusting usage. We like facial recognition when used on our personal machine to identify a family member in a photograph but not while sitting at a stoplight or walking in an airport.

As facial recognition is applied in more public arenas, class action lawsuits are being filed to prevent its use— getting governments involved to monitor and police applications and putting a microscope on companies that may or may not be using AI-generated information properly. The rise of GDPR and CCPA are direct responses of individuals pushing back against improper use of “their” data— including facial recognition.”

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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.

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