Check out the newest Veritas Education update:
Veritas Alta Archiving: Administrationis now available for registration! Take this new course and gain the necessary skills required to leverage Veritas Alta Archiving to perform data discovery for your organization’s compliance needs. In Veritas Alta Archiving: Administration, you will learn how to configure and use Veritas Alta Archiving using the Veritas Alta View Compliance & Governance console to capture, ingest, supervise, and discover data. The course is designed to enable compliance officers and corporate legal IT personnel to meet supervision and discovery requirements while reducing compliance risk and controlling costs. The course includes simulations that enable you to learn new skills and transfer those skills into your working environment: Veritas Alta Archiving: Administration is available in the following delivery methods: Instructor-led training (ILT) – 3 days Virtual Instructor-led Training (VILT) – 3 days Self-paced More information on training delivery methods, class availability and registration instructions can be foundhere. If you have any questions, please contact education.system@veritas.com.Intro to Large Language Models: Pre-training, fine-tuning, and RAG
Generative AI Fundamentals: In the Generative AI development process, understanding the distinctions between pre-training, fine-tuning, and RAG (Retrieval-Augmented Generation) is crucial for efficient resource allocation and achieving targeted results. Here’s a comparative analysis for a practical perspective: Pre-training: • Purpose: To create a versatile base model with a broad grasp of language. • Resources & Cost: Resource-heavy, requiring thousands of GPUs and significant investment, often in millions. • Time & Data: Longest phase, utilizing extensive, diverse datasets. • Impact: Provides a robust foundation for various AI applications, essential for general language understanding. Fine-tuning: • Purpose: Customize the base model for specific tasks or domains. • Resources & Cost: More economical, utilizes fewer resources. • Time & Data: Quicker, focused on smaller, task-specific datasets. • Impact: Enhances model performance for particular applications, crucial for specialized tasks and efficiency in AI solutions. RAG: • Purpose: Augment the model’s responses with external, real-time data. • Resources & Cost: Depends on retrieval system complexity. • Time & Data: Varies based on integration and database size. • Impact: Offers enriched, contextually relevant responses, pivotal for tasks requiring up-to-date or specialized information. So what? Understanding these distinctions helps in strategically deploying AI resources. While pre-training establishes a broad base, fine-tuning offers specificity. RAG introduces an additional layer of contextual relevance. The choice depends on your project’s goals: broad understanding, task-specific performance, or dynamic, data-enriched interaction. Effective AI development isn’t just about building models; it’s about choosing the right approach to meet your specific needs and constraints. Whether it’s cost efficiency, time-to-market, or the depth of knowledge integration, this understanding guides you to make informed decisions for impactful AI solutions. Save the snapshot below to have this comparative analysis at your fingertips for your next AI project.Check out the newest Veritas NetBackup training update
Veritas NetBackup 10.3: Differencesis now available for registration! Take this new course and stay current with all the latest capabilities of NetBackup 10.3. In Veritas NetBackup 10.3: Differences, you will learn about all the new features and enhancements made to Veritas NetBackup 10.3, covering Alta Data Protection, Kubernetes Support, and more. It is designed for the data protection professional tasked with deploying, configuring, maintaining, and managing a NetBackup 10.3 environment. The course also includes practical hands-on lab exercises to apply your new skills in a virtual NetBackup domain: Veritas NetBackup 10.3: Differences is a self-paced, modular course, with lab exercises and is available in the following delivery methods: Learning Lab – Self-paced lesson guide with 6 months of lab access More information on training delivery methods, class availability and registration instructions can be foundhere. If you have any questions, please contact education.system@veritas.com.
