BigQuery query queues introduces a dynamic concurrency limit and enables queueing based on available slot capacity and how many queries are running.
Generative artificial intelligence (AI) is a game-changer, bringing with it the promise of unparalleled efficiency and the potential for entrée into new markets. As generative AI continues to soar in popularity, organizations are eager to tap into its transformative power. However, this enthusiasm should come with a side of caution. It’s critical that organizations develop a strong generative AI policy so the allure of new technology doesn’t lead to devastating mishaps.
Have you heard the phrase “AI won't replace humans - but humans with AI will replace humans without AI”? I personally love this quote because it perfectly encapsulates the nature of the anticipated workforce shift from the rise of generative AI. As I wrote back in 2017, the power of AI is not about machines supplanting human abilities, but rather about a symbiotic relationship between humans and AI. I think the Star Trek analogy I used then is standing the test of time…
As users now expect applications to provide instant updates, live chats, and dynamic content, modern web development requires the ability to deliver realtime experiences and communication between users and servers. WebSocket is a communication protocol that allows full-duplex two-way communication between a client and a server over a single TCP connection. The connection persists unless it is explicitly told to disconnect or in case of network or server failure.
Search functionality is an interesting but complex area when it comes to testing. A search functionality is by definition a search engine, which deals with vast amounts of data and an underlying search algorithm built on complex statistical models. That’s not to mention the ever-increasing user expectations for the search feature to understand nuances in human language, capable of handling misspellings, synonyms, and natural language queries.
In this article, we'll show how you can use Elixir's profile.eprof mix task to evaluate and improve code performance in your Elixir application. You'll see how we used the profiling mix task to lower reductions in our instrument/3 function and custom instrumentation functionality, both key parts of our Elixir integration.
