Organizations are constantly looking to innovate without completely cutting their purse strings. What if your business could take advantage of the most advanced AI platform without the huge upfront time and investment inherent in building an internal data scientist team?
During Data Summit Connect 2020, Elliott Ning, cloud advisor, Google, discussed, “Cloud AI: From Data to Insight.”
To watch the video of Elliot Ning's presentation at Data Summit Connect 2020, go here.
“Many people thing AI is just machine learning,” Ning said. “AI is a broader category of subjects.”
Human intelligence is when people learn, think, and apply knowledge. People learn from experience to create, learn, and think about knowledge to solve problems whereas computers learn from information to solve problems, the backbone of AI.
Machine learning is to learn from patterns or predictions from a set of rules that have been configured by humans.
“The human brain is extremely complex so machines can only do a tiny fraction of this,” Ning said.
By 2021 75% of enterprise applications will use AI, according to Ning. The industry is also looking to use tools to create autonomous vehicles.
However, with AI fueled dreams comes the reality that deploying AI isn’t easy. Less than 14% of AI projects move out of production.
Companies need to identify the right business problem and deploy the right people to dig through the data, Ning said.
In order to simplify the AI process, businesses need to study the proper use case, organize the correct data, and utilizethe right tools, platforms, or services.
Structured data is likely to drive most of AI’s impact, Ning said. Structured data is processed so users don’t need a separate process. It’s organized and clean so queries can be run on this data quickly.
“We spend a huge effort making AI accessible for more people,” Ning said.
Google Cloud AutoML can build and deploy high quality custom machine learning models with minimum effort and machine learning expertise, Ning said.
Data needs to be accessible from both on-premise and cloud-based applications. Since cloud vendors charge for data movement, customers need to understand and control that movement. Also, there may be performance or security implications around moving data to or from the cloud.
Clay Jackson, senior database systems sales engineer, Quest Software Inc, discussed “Hybrid Cloud—Location Matters,” during his Data Connect presentation after Ning.
To watch the video of Clay Jackson's presentation at Data Summit Connect 2020, go here.
Deployment and service models are key to where to securely store sensitive data. A public cloud is the least expensive option. However, it can be the least secure, Jackson said.
A community cloud is more secure than a public cloud, but there may be some limits, including the cost. With private cloud users can choose between on premise or remote. It is the most secure environment, but it is the most costly option.
Webcast replays of Data Summit Connect presentations are available on the DBTA website at www.dbta.com/DBTA-Downloads/WhitePapers.