As we head into 2024, AI continues to evolve at breakneck speed. The adoption of AI in large organizations is no longer a matter of “if,” but “how fast.” Companies have realized that harnessing the power of AI is not only a competitive advantage but also a necessity for staying relevant in today’s dynamic market. In this blog post, we’ll look at AI within the enterprise and outline six key predictions for the coming year.
OpenAI DevDay 2023 is upon us. We're excited by what some of the announcements mean for Continual and will be revealing more about Continual soon. In the meantime, you can watch the livestream and replay here: There's never been a better time to build an AI copilot for your application.
Exploratory testing is a dynamic, flexible methodology emphasizing simultaneous learning, testing strategy, and execution. Unlike traditional scripted testing, exploratory testing enables testers to actively explore software applications using their intuition, creativity, and experience. By assuming the end-user role, testers interact with the software in real-time, identifying potential issues and uncovering usability problems that scripted tests might overlook.
Generative AI (GenAI) and large language models (LLMs) are disrupting the way we work at a global scale. Snowflake is excited to announce an innovative product lineup that brings our platform’s ease of use, security and governance to the GenAI world.
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.
At Next ‘23, Exabeam, Dun & Bradstreet, Optimizely and LiveRamp shared how they use BigQuery and Google Data and AI Cloud for data monetization.
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.
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.
