Artificial intelligence (AI) and machine learning (ML) are redefining the enterprise IT landscape, as across verticals see the potential for AI and ML to automate repetitive tasks and solve complex problems. But just how far does the potential of AI/ML reach?
GigaOm co-founder and CEO Ben Book recently appeared on an episode of the 7investing podcast with 7investing Founder and CEO Simon Erickson to discuss technology trends. He says most enterprises know that AI and ML will impact their business, but some are still trying to figure out just how the technology will work for them.
“The early adopters were webscale and high growth new industry and digital companies, like Google, Twitter, Uber, Facebook, investing in data scientists and other data-intensive industries such as finance and insurance,” says Book.
He says that while AI and ML have already made their mark in verticals … Read More »
High-performance object storage is a data storage architecture designed for handling large amounts of unstructured data. It has historically been known for its ability to store these massive amounts of information as objects, rather than files. But use cases have broadened in recent years as more organizations produce large amounts of data and want the ability to organize, manage, and search it.
“High-performance object storage is common in two scenarios,” says GigaOm analyst Enrico Signoretti. “On one hand, these types of systems are used to consolidate more workloads on a single system. On the other hand, they are used as interactive storage for highly demanding workloads that also present huge data sets, like in AI, HPC, or big data analytics.”
In his new GigaOm Radar Report for High-Performance Object Storage, Signoretti looks at the fast-moving market of high-performance object storage solutions and … Read More »
We are seeing increasing numbers of enterprise projects where data is produced, consumed, analyzed, and reacted to in real-time. In this way, the technology becomes aware of what’s going on inside and around it—making pragmatic, tactical decisions on its own. We see this being played out in transportation, telephony, healthcare, security and law enforcement, finance, manufacturing, and in most sectors of every industry.
Prior to this evolution, the analytical ramifications inherent in the data were derived long after the event that produced or created the data had passed. Now we can use technology to capture, analyze, and take action based on what is going on in the moment.
This category of data is known by several names: streaming, messaging, live feeds, real-time, and event-driven. In the streaming data and message queuing technology space, there are a number of popular technologies in use, … Read More »