Unix News

  Many Companies Hold Vast Data but Are Unprepared for LLM Fine-Tuning: How to Solve It and What to Do About It In today’s data-driven world, companies across various industries generate and store vast amounts of data. From customer interactions and sales transactions to sensor readings and user-generated content, organizations are sitting on treasure troves of information. However, when it comes to leveraging this data for fine-tuning large language models (LLMs), many companies find themselves unprepared. The growing need for AI-powered solutions requires adapting these models to specific organizational needs—a task that demands both the right infrastructure and expertise. The Challenge: Vast Data, But Lacking Readiness for LLM Fine-Tuning Large language models, such as OpenAI’s GPT or Google’s Bert, have revolutionized industries by providing AI capabilities for natural language understanding, generation, and analysis. However, these models are typically pre-trained on generalized d

  T he Compute and Performance Engineering teams at Netflix regularly investigate performance issues in our multi-tenant environment. The first step is determining whether the problem originates from the application or the underlying infrastructure. One issue that often complicates this process is the "noisy neighbor" problem. On Titus, our multi-tenant compute platform, a "noisy neighbor" refers to a container or system service that heavily utilizes the server's resources, causing performance degradation in adjacent containers. We usually focus on CPU utilization because it is our workloads’ most frequent source of noisy neighbor issues, read more 

I ncident response and digital forensics play crucial roles in understanding, mitigating, and preventing security events. However, a common pitfall that can undermine even the most sophisticated investigative efforts is the practice of “cherry picking” – selectively choosing evidence that supports a predetermined conclusion while ignoring contradictory information. Whether you’re a seasoned cybersecurity professional or new to the field, understanding the dangers of cherry picking is crucial for conducting thorough and accurate investigations. Let’s dive in and explore why a holistic approach to evidence gathering and analysis is essential in today’s complex threat landscape, read more...