The adoption of artificial intelligence and more importantly machine learning is rapidly gaining traction in almost all industries.
Companies have quickly realized the benefits associated with the adoption of this groundbreaking technology, especially when it comes to staying relevant and ahead of their competition.
For instance, Splunk is one of the companies in software making space that appears to be improving its products in line with developments in artificial intelligence.
Splunk recently unveiled the latest upgrades to its leading analytics suites with the focus being on AI and machine learning advances.
The company dated several suites including Splunk Cloud, Splunk User Behavior Analytics (UBA), Splunk Enterprise, Splunk IT Service Intelligence(ITSI) as well as a new Experiment Management Interface designed for its Machine Learning Toolkit(MLTK).
According to Splunk, the new Machine Learning Toolkit interface makes it stress-free to view, control, analyze and oversee the status of machine learning experiments. What’s more, this toolkit also comes with new algorithms that are important not only in recognizing patterns but also in determining the ideal predictors for training machine learning models.
All Splunk’s machine learning algorithms are based on several functions including alerting, business optimization for demand, analysis of historical data, carrying out investigations for security incidents, inventory, and providing predictive tools for both operations and maintenance.
Also, according to the multinational software maker, the advancements in machine learning depend on these algorithms in a bid to assist customers in investigating, monitoring and building better intelligence through their data.
Aside from updating its flagship suites, Splunk also upgraded its UserBehavior Analytics platform using new machine learning models and enhancements to already available models that focus on assisting customers in spotting security threads more quickly.
In addition, the software maker went ahead to expand its integration capabilities with both cloud-native and open source software technologies from Kubernetes, Docker and Apache Kafka.
According to Tim Tully, the chief technology officer of Splunk, the company’s new artificial intelligence improvements such as the capacity to correlate activity data and metrics allow customers to obtain answers from machine data more efficiently.
He also added that Splunk’s recent wave of innovation is geared towards providing customers with all the necessary tools that they need to convert artificial intelligence (AI) into actual intelligence.
Founded in 2003, Splunk prides itself on being a multinational corporation that is involved in making software for finding, overseeing and evaluating big data from machines through a web-style interface. In addition, the San Francisco, California-based company’s mission entails making machine data accessible throughout an organization by diagnosing issues, recognizing data patterns, providing intelligence for business operations and offering data metrics.
Splunk has several groundbreaking products including Splunk Storm, Hunk, Splunk IT Service Intelligence, Splunk Insights and the latest one dubbed Splunk Industrial Asset Intelligence. The recently introduced product gets information from industrial Internet of things (IIoT) data and then avails it to users. As a multinational entity, Splunk boasts of operations in various parts of the world including Australia, Asia, the Middle East, African and several regional bases in Europe.
Source Zdnet
