Domino Data Lab, a leading Enterprise MLOps platform trusted by over 20 percent of the Fortune 100, announced its new Nexus hybrid Enterprise MLOps architecture that will allow companies to rapidly scale, control and orchestrate data science work across different compute clusters — in different geographic regions, on premises, and even across multiple clouds.
Domino Data Lab Announces Hybrid MLOps Architecture to Future-Proof Model-Driven Business at Scale
Automation Is An Essential Priority for the Future of Enterprises
In this sponsored post, Eric Herzog, CMO, Infinidat, discusses how virtually every IT decision-maker is looking to automate at some level, either today or in the future. Starting the autonomous automation of enterprise data and storage can catapult an organization forward and give its leaders valuable learnings and insights into the path of automation, which will only expand on the horizon.
10 Must-Have Capabilities of an Enterprise AI Platform
[SPONSORED POST] With the ten must-have capabilities of an Enterprise AI platform outlined in this paper from Veritone, organizations can position themselves for rapid adoption of AI and ML at scale without requiring custom “from-scratch” model development, extensive AI expertise, or single-model dependency. Data-driven organizations use AI and ML, either natively within applications or infused into applications, to obtain better insights into the content that drives their business and automate content-centric processes for greater efficiency. But the proliferation of AI projects, ML models, APIs, and data sets to enable these processes present serious challenges that stand in the way of successful AI and ML deployments.
10 Must-Have Capabilities of an Enterprise AI Platform
With the ten must-have capabilities of an Enterprise AI platform outlined in this paper from Veritone, organizations can position themselves for rapid adoption of AI and ML at scale without requiring custom “from-scratch” model development, extensive AI expertise, or single-model dependency.
How Feature Stores will revolutionize Enterprise AI
In this contributed article, Monte Zweben, CEO and co-founder of Splice Machine, discusses Feature Stores which are a new MLOps technology being adopted by cutting-edge companies like Uber, Airbnb, and Netflix, and for good reason. A Feature Store is a system made specifically to automate the input, tracking, and governance of data into machine learning models.
Driving ROI Through AI
This new report from ESI ThoughtLab was conducted alongside our friends over at DataRobot as well as a coalition of other AI leaders. The report shows that despite high adoption rates of AI in enterprises, ROI in AI still remains a work in progress and will take skill, scale, and time.
Video Highlights: Delivering the Enterprise Data Cloud
In the video presentation below from the O’Reilly Strata Data Conference, Arun Murthy, co-founder of Hortonworks and current CPO of Cloudera, discusses how enterprises can extract and act on big data.
Building Powerful Enterprise AI Infrastructure: How to Design Enduring Infrastructure for AI
Our friends over at cloud-neutral colocation data center company Interxion have published a whitepaper titled, “Building Powerful Enterprise AI Infrastructure: How to design enduring infrastructure for AI,” which details the requirements of an ideal infrastructure environment when it comes to reaping the benefits of today’s growing volume of data and enabling AI at scale. By automating repetitive processes, delivering new strategic insights, and accelerating innovation, AI has the power to revolutionize business.