Local Ollama Models in VS Code Copilot Can't See Your Workspace Context
用 Ollama 本機模型跑 VS Code Copilot,竟然看不到你的工作區檔案
If you're using a local Ollama model with VS Code Copilot, you might run into a frustrating issue: the AI doesn't actually know what file you're working on. You ask it to edit or summarize your current file, but it's basically flying blind—it has no idea which file you're referring to. This is a context awareness problem where the local model isn't receiving the workspace information it needs to understand your coding environment. The issue appears to be a limitation in how Ollama integrates with VS Code's Copilot extension, preventing the model from accessing file paths, open documents, and other workspace metadata. If you're experiencing this, it's worth checking your model configuration and whether your Ollama setup supports the necessary context-passing features that cloud-based AI assistants typically have built-in.
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
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ChatGPT Images 2.0
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
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The "just wait 6 months" argument from 2025 survived exactly one iteration
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
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Mistral Medium 3.5 on AMD Strix Halo: Painfully Slow (Plan for Overnight Runs)
Someone actually tested Mistral Medium 3.5 on AMD's new Strix Halo chip, and the results are... not great. For a 48k-token prompt with 4k thinking tokens, it took about 2 hours just to get an answer about code architecture. Yeah, you read that right—two hours. The takeaway: if you want to run this locally on Strix Halo, queue it up before bed. The technical setup involved heavy optimization (Q5_K_XL quantization, GPU acceleration with -ngl 999, cache reuse), but even with all that tuning, it's still a crawl. Not exactly the "instant local AI" dream, but hey, at least it works.