Thoughtful reflections on the rapid evolution of artificial intelligence – exploring how AI is shaping creativity, technology, and the future of human potential.
AI-ready backends require three capabilities: streaming response support, vector storage access, and async concurrency. These capabilities work together to create a robust and efficient backend that can handle the demands of large language models. Streaming response support is a game-changer…
The next major AI wave is shifting from public chatbots toward internal enterprise AI tools. For too long, businesses have been experimenting with public-facing chatbots, often with limited success. However, the real potential of AI lies in its ability to…
When it comes to Large Language Models, understanding determinism is crucial for ensuring the reliability and consistency of their outputs. One common misconception is that temperature controls all aspects of an LLM, from floating-point arithmetic to GPU parallelism and batch…
Vector databases have become a crucial component in modern AI systems due to the limitations of traditional SQL search. These databases are now used in various applications such as internal knowledge assistants, semantic search, and long-term AI memory. But what…
AI-generated applications are accelerating the shift from manual coding to automated software creation. This shift is making the no-code/low-code/full-code debate more relevant than ever. Business needs for faster delivery are driving the growth of no code in the age of…
AI coding has shifted from autocomplete to autonomous agents that plan, write, test, and refactor code end-to-end. The key question is not if developers change-it’s which role they evolve into. AI impacts developers in multiple ways. On one hand, it’s…
Imagine a world where AI coding agents can magically boost your productivity by up to 30%, but the more you rely on them, the more they hinder your speed and accuracy. Sounds like science fiction, right? Not quite. This is…
Is everything fine or is AI replacing software engineers? There is lately often medialized decrease of software engineers in the last few years. You might be wondering if the fears of job displacement in the tech industry are a new…
The adoption of AI in the engineering world has reached a boiling point. We’re not talking about early adopters or pioneers – we’re talking about the norm. Around 90% of engineering teams are now using AI tools daily, making it…
Resilience engineering is crucial for LLM reliability in production environments. This involves handling various types of failures, such as rate limits, timeouts, and model-specific errors, to ensure a seamless user experience. When it comes to Large Language Models, reliability is…
