Generative AI is unlocking new ways to drive innovation, improve productivity and derive more value from data. For organizations to fully capitalize on this potential, it’s critical that everyone — not just those with AI expertise — is able to access and use generative AI.
Enterprises see embracing AI as a strategic imperative that will enable them to stay relevant in increasingly competitive markets. However, it remains difficult to quickly build these capabilities given the challenges with finding readily available talent and resources to get started rapidly on the AI journey.
In November of 2014, when NodeSource was still a small consulting group, my teammates Dan Shaw, Rod Vagg, and I were having dinner after a customer engagement, discussing how to bring Node.js production deployments to the same level of polish and tooling capability of the other runtimes our customers were already employing.
At Next ‘23, Exabeam, Dun & Bradstreet, Optimizely and LiveRamp shared how they use BigQuery and Google Data and AI Cloud for data monetization.
Cloud transformation is ranked as the cornerstone of innovation and digitalization. The legacy IT infrastructure to run the business operations—mainly data centers—has a deadline to shift to cloud-based services. Agility, innovation, and time-to-value are the key differentiators cloud service providers (CSP) claim to help organizations speed up digital transformation projects and business objectives.
The software industry has evolved more quickly in 10 years than most industries do in 1,000, yet we continue to grapple with the basic elements of date and time. Practically all our apps rely on time in some way, and when our users are spread all over the world it can be fiendishly difficult to get the timestamps right. Kotlin language, the dominant Android programming language, provides native classes (or blueprints) to help us deal with date and time.
To ensure a frictionless AI/ML development lifecycle, ClearML recently announced extensive new capabilities for managing, scheduling, and optimizing GPU compute resources. This capability benefits customers regardless of whether their setup is on-premise, in the cloud, or hybrid. Under ClearML’s Orchestration menu, a new Enterprise Cost Management Center enables customers to better visualize and oversee what is happening in their clusters.
