Lost in the talk about OpenAI is the tremendous amount of compute needed to train and fine-tune LLMs, like GPT, and Generative AI, like ChatGPT. Each iteration requires more compute and the limitation imposed by Moore’s Law quickly moves that task from single compute instances to distributed compute. To accomplish this, OpenAI has employed Ray to power the distributed compute platform to train each release of the GPT models.
In today's data-driven world, product analytics is crucial in understanding user behavior, improving product features, and driving business growth. However, product analytics alone may not provide a complete picture of user interactions and business performance. Integrating product analytics with other data sources and systems is essential to gain deeper insights and make more informed decisions.
Chances are high that you've previously worked with Express, as it's been the go-to web framework for Node.js developers since its release in 2010. However, in recent years, newer web frameworks have emerged, and Express's development has slowed down significantly. Fastify is a relatively new player on the scene, but it's quickly gaining popularity due to its speed and unique features. If you're still using Express, you might wonder if it's worth switching to Fastify.
Practical advice for starting your journey to analytics excellence.
In my previous post on scaling Kong deployments with and without a database, we covered the concepts of deploying Kong with and without a database, as well as using decK, distributed, and hybrid deployments. In this article, we take a tour of some of the possible Kubernetes deployments of Kong. Kubernetes (K8s) is the container orchestration war winner. While there are still deployments using other engines, we see K8s far more.
PHP is a popular server-side programming language used to build dynamic websites and applications. With the release of PHP 8.0, there are several exciting new features that developers can take advantage of to improve their code and make it more efficient. One such feature is named arguments, which allows developers to specify function arguments by name rather than just by position.
Data is core to decision making today and organizations often turn to the cloud to build modern data apps for faster access to valuable insights. With cloud operating models, decision making can be accelerated, leading to competitive advantages and increased revenue. Can you achieve similar outcomes with your on-premises data platform? You absolutely can.
When writing your test automation scripts, it can be especially difficult to write code that adequately identifies visual defects. Typical functional tests do a poor job capturing all visual changes and they also leave you with lengthy and flaky code. And when your code becomes flaky, it becomes unreliable.
In part one of this series, we introduced Elixir test factories and fixtures. Then in part two, we explored using data generation functions. Now we'll look at some of the best Elixir libraries to use for your test data. But before we do, let's quickly discuss why test data libraries can be helpful.
