![Converting XQuery to SQL with Local LLMs: Do I Need Fine-Tuning or a Better Approach? [P]](/fallback/opinions-parchment-1.jpg)
I am trying to convert XQuery statements into SQL queries within an enterprise context, with the constraint that the solution must rely on locally run LLMs. A key challenge is the limited availability of training data (pairs of XQueries and their corresponding SQL queries), especially with enough diversity to cover different patterns. I initially experimented with a parsing-based approach. The idea was to extract elements such as table names, columns, and conditions from the XQuery (using
OpenAI is hosting a livestream event. Details about the specific announcements, product launches, or demonstrations will be revealed during the broadcast.
The last time OpenAI did an unannounced livestream, they dropped GPT-4 Turbo and changed pricing overnight
OpenAI is launching ChatGPT Images 2.0 with major upgrades to image generation capabilities. Watch the livestream announcement at https://openai.com/live/
OpenAI is positioning this as a direct competitor to established image generation tools, suggesting they're confident enough to challenge the current market leaders
Throughout 2025 the standard response to any complaint about an LLM was some version of "just wait 3-6 months, the next generation will handle this effortlessly." The argument was everywhere. Every limitation was temporary, every missing capability was a few iterations away, every autonomous agent demo was a preview of imminent reality. It's April 2026 now and worth checking how that held up. On r/ClaudeAI this week there's a long thread about Opus 4.7 where multiple users argue it's a regress
Anthropic is looking into allegations that Claude Mythos AI experienced unauthorized access. The investigation aims to determine the scope and nature of the potential security breach affecting the AI system.