Leveraging AI in Cybersecurity - Fighting Fire with Fire
Explore AI-driven strategies to fortify cloud workloads against evolving cyber threats, from development to runtime, ensuring comprehensive protection throughout the lifecycle.
Secure AI Transformation: What We Can Do Now and in the Future
Explore new threats, strategies, and best practices for securely transforming AI initiatives, focusing on safeguarding AI applications, development, data, and runtime environments.
Securing the Cloud - Taking Back the Attacker's Mindset
Explore cloud security challenges and adopt an attacker's mindset to strengthen defenses, improve team collaboration, and enhance incident response in cloud environments.
Machine Learning for Threat Classification: Addressing Class Imbalance and Explainability
Explore techniques for class imbalance, explainability, and best practices in machine learning for threat classification modeling.
From Model T to Machine Learning: Ford's MLOps and Hybrid Infrastructure Strategy
Explore Ford's AI/ML platform journey, from inception to present day. Learn about product strategy decisions, challenges, and organizational hurdles in modernizing a traditional company.
Apache Airflow: Where Data Engineers and ML Engineers Meet
Explore production-quality Generative AI pipelines using Apache Airflow. Learn to orchestrate workflows, integrate data engineering, and implement MLOps best practices for robust AI applications.
Beyond the Model Zoo - Optimizing Foundation Models for Your Application
Optimize foundation models for specific applications, exploring techniques beyond pre-trained models to enhance performance and efficiency in machine learning projects.
Defining Open-Source AI: Challenges and Opportunities in the Evolving Landscape
Explore the complexities of defining Open-Source AI, balancing innovation with core open-source principles in the evolving AI landscape. Engage in shaping a definition that reflects technological progress.
Reproducibility and Data Version Control for LangChain and LLM/OpenAI Models
Explore reproducibility and data version control for LangChain and LLM/OpenAI models using lakeFS. Learn to manage large datasets efficiently and achieve reproducibility in LLM applications.
Finetuning a Large Language Model on a Custom Dataset
Discover parameter-efficient finetuning techniques and optimizations for large language models using custom datasets, enhancing model performance at scale.
Deploying Generative AI Models - Best Practices and Interactive Example
Explore best practices for deploying generative AI models at scale, with an interactive example using UbiOps for serverless and cloud-agnostic implementation.
Learn Your Codebase: Fine-tuning CodeLlama with Flyte to Learn Flyte
Discover how to fine-tune LLMs on specific codebases using Flyte, an open-source orchestration platform. Explore multi-node, multi-gpu distributed training for efficient model adaptation with limited resources.
GraphQL and OpenTelemetry: Observing, Diagnosing, and Optimizing - Observability Clinic
Explore GraphQL's challenges and learn to observe, diagnose, and optimize using OpenTelemetry. Gain insights into problem patterns, instrumentation techniques, and future developments in this comprehensive guide.
What's New in Dynatrace - June 2023 - Releases v267 and v268
Explore Dynatrace's latest releases, including product updates, security enhancements, and infrastructure observability improvements. Gain insights through live demos and learn about recent product blog updates.
DQL Timeseries Command: Usage and Best Practices - Episode 11
Explore DQL timeseries command for metrics access in notebooks, dashboards, and automation. Learn contextualization, conditional formatting, and visualization best practices with expert guidance.
Dynatrace for AI Observability: Monitoring OpenAI, TensorFlow, and Other AI APIs
Gain insights into AI model behavior, performance, and costs using Dynatrace. Monitor OpenAI and TensorFlow APIs, optimize performance, and understand AI observability through practical demonstrations.
How to Design and Build Resilient Machine Learning Systems
Explore strategies for building resilient ML systems that gracefully handle real-world challenges. Learn to detect, mitigate, and overcome production-specific risks across various domains.
Bringing AI to Existing Databases Without Complex MLOps
Integrate AI seamlessly with existing databases, bypassing complex MLOps processes. Learn efficient techniques for enhancing data infrastructure with artificial intelligence.
What Does it Mean to be an AI Engineer in the World of Generative AI
Explore the evolving role of AI Engineers in the era of Generative AI, covering technical aspects and business strategies for both engineers and decision-makers.
Metric Forecasting with Dynatrace - Predictive IT Resiliency Automation
Explore probabilistic forecasting for cloud resource management. Learn mathematical models, leverage forecasts in Notebooks, and automate infrastructure scaling using Dynatrace's predictive IT resiliency.
Dynatrace Product Updates - April 2023 (Versions 263 and 264)
Explore Dynatrace's latest features in v263 and v264, including AppSec updates, DQL commands, UI improvements, and K8s enhancements. Learn about new monitoring capabilities and product developments.