Ollama 分享了 Levie 对开放权重模型的乐观看法：这些模型成本更低、表现接近前沿，还能针对性微调，对 AI 应用层是大利好。
Ollama 转发了 Aaron Levie 的观点，指出开放权重模型在特定任务上已取得 SOTA 结果，并在编码等部分领域接近前沿水平。Levie 强调，开放权重模型与前沿模型之间的边际差距若能保持而非扩大，将创造更多 AI 应用价值。他还提到，使用更便宜或针对特定任务微调的开放模型可优化成本，同时前沿模型仍可用于规划、编排等复杂工作。
Let’s go open models! ❤️
Let’s go open models! ❤️ Aaron Levie @levie Pretty remarkable what’s happening with open weights AI right now. We’re seeing models achieve SOTA results on specific tasks, and getting close to frontier on some areas of coding and other domains. The more that open weights is able to maintain only a marginal gap from the frontier, instead of a widening gap, the more value that can be created with AI. Incidentally, this is actually fine for the frontier labs as well; if we can lower the cost of an overall task then AI usage goes up in general. You’re still likely using frontier models for planning, orchestration, reviewing, and other parts of work. But this is all very good for the applied layer of AI, which is now in a great position to cost optimize workloads with cheaper models or use tailored open models post-trained for specific tasks to improve performance. 🔗 View Quoted Tweet 💬 4 🔄 4 ❤️ 72 👀 5772 📊 9 ⚡