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Navigating Open Source Software: All Your Questions Answered

Open source software refers to computer programs with source code available for anyone to inspect, modify, and distribute. Unlike proprietary software, open source software is developed collaboratively by a community of developers. One of the main benefits of open source software is cost savings. Because the source code is freely available, organizations can use and customize the software without paying licensing fees, reducing costs, especially for large-scale deployments.

Beyond RAG basics: Advanced strategies for AI applications

Our recent virtual event with Cohere dove deep into the world of retrieval augmented generation (RAG), focusing on the critical considerations for building RAG applications beyond the proof-of-concept stage. Our speakers, Lily Adler, principal solutions architect at Elastic, and Maxime Voisin, senior product manager at Cohere, shared valuable insights on the challenges, solutions, and best practices in this evolving field of natural language processing (NLP).

Harness GenAI to enhance IT incident management

Advances in generative AI are rapidly transforming the IT operations landscape. According to Enterprise Strategy Group, 85% of organizations use or plan to deploy AI across many functional areas, including ITOps. AIOps platforms can apply advanced GenAI to quickly identify an incident’s root cause, impact, and recommend steps to resolution. When fed the correct information, AIOps gives IT teams immediate access to context-rich insights.

The 8 Best AI Tools for Productivity in 2024

Since the launch of ChatGPT in November 2022, the world has seen a huge shift in our personal, business, and creative lives. Although we often use AI daily, its addition to our lives has not been without problems. It has caused writer strikes and worries about how AI handles our data and what it means for privacy, and many people are worried about AI taking over their jobs.

AI in Telecommunications: Opportunities, Challenges, and the Role of Resolve

Artificial Intelligence (AI) is rapidly becoming an essential component of the telecommunications industry, driving significant changes in how networks are managed, optimized, and maintained. With the growing complexity of telecom networks, coupled with the rising demand for seamless connectivity, AI offers a range of solutions to address these challenges. From predictive maintenance and network optimization to enhancing customer service, AI is poised to transform telecom operations.

Machine Learning Inference Model at Scale with Graviton

Sharpen your machine learning knowledge with our upcoming virtual event, "Machine Learning Model Inference at Scale with Graviton." In collaboration between 2bcloud and Amazon Web Services (AWS), this event will provide you with a comprehensive, step-by-step tutorial on setting up a high-performance and cost-optimized machine learning inference environment, using Graviton processors.

Laptops vs Monitors and iPads: Choosing the Right Device for Your Needs

The debate over laptops, monitors, and iPads is significant for anyone looking to optimize their tech setup. Each device offers unique advantages depending on the user's needs. For those prioritizing portability, tablets like iPads excel, while larger monitors provide an immersive viewing experience ideal for productivity.

Isolating Bottlenecks: How to Determine If Your Slowdown Is Due to the Database or API

Every slowdown in your application can be traced to specific components like a database or an API, and quickly identifying the source aids the troubleshooting process. But when an API is underperforming, it may be difficult to tell whether the issue is with the API logic itself or an external service like a database that it interacts with before sending responses.
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Traffic-Driven Testing: All the Benefits of Shift-Right Testing with None of the Risk

The shift-right testing approach moves testing to later in your production cycle. Also known as "testing in production," with shift-right, you test software after it has been deployed. It gives you continuous feedback based on real-world user interactions. However, there are major drawbacks to the approach. For example, testing in production risks disrupting your user satisfaction and can mean you catch issues too late to respond to them effectively. It can also be difficult to test problems related to scale and traffic volume. Your tests are also difficult to repeat under the same conditions.