Regardless of whether an engineering team is colocated, remote, or hybrid, they face the same inherent communication pitfalls. This article explores strategies to address them.
We are excited to announce a tech preview of Cloudera AI Inference service powered by the full-stack NVIDIA accelerated computing platform, which includes NVIDIA NIM inference microservices, part of the NVIDIA AI Enterprise software platform for generative AI. Cloudera’s AI Inference service uniquely streamlines the deployment and management of large-scale AI models, delivering high performance and efficiency while maintaining strict privacy and security standards.
Originally created in the 1890s, the Swiss army knife was a logical solution to officers’ need to be able to repair their weapons, open their canned food, and cut things as needed. Since then, simple items that offer multiple solutions to achieve a goal are often referred to as being the Swiss army knife of their kind.
Open source file and table formats have garnered much interest in the data industry because of their potential for interoperability — unlocking the ability for many technologies to safely operate over a single copy of data. Greater interoperability not only reduces the complexity and costs associated with using many tools and processing engines in parallel, but it would also reduce potential risks associated with vendor lock-in.
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In an era where artificial intelligence (AI) is reshaping enterprises across the globe—be it in healthcare, finance, or manufacturing—it’s hard to overstate the transformation that AI has had on businesses, regardless of industry or size. At Cloudera, we recognize the urgent need for bold steps to harness this potential and dramatically accelerate the time to value for AI applications.
As software developers, we all write lots and lots of lines of code while building an application. But to ensure that each and every components work perfectly in the software, we really need to do some unit testing. This ensures proper functionality and reliable performance of our product. These testing of individual components is known as Unit Testing. For the dynamic nature and the ease of writing tests alongside the code, Python can be a viable option for unit testing of our software.
We’re thrilled to announce the launch of Tosca Copilot, a generative AI assistant that enhances productivity by optimizing test portfolios, explaining complex test cases, and providing actionable execution insights. Tosca Copilot is an add-on to Tosca Commander and is designed to make your testing lifecycle more efficient and effective.
As software releases are expected to happen faster, testers are placed under more pressure. Pressure to find and eradicate bugs earlier in the release cycle, to avoid them being costly and delaying release timelines. That said, if companies want to stay ahead of the competition, it's important from the outset their testing processes are free from risks and vulnerabilities. Can automated testing best ensure thorough validation? How can team procedures proactively avoid risk?
Organizations leveraging cloud data warehouses like Snowflake require the ability to efficiently manage and optimize their data connections. Without this, data teams will face challenges with various use cases, such as workload distribution and environment testing. Recognizing the need for greater flexibility and control over data connections, ThoughtSpot developed a powerful new feature: Multiple Configurations per Connection.