Aoke Quant 奥克队长🚩ΙΧΘΥΣ

📢：做Binance队长4年了，很荣幸被邀请成为本次Binance KOL 越南活动，中国区的1/6参与者 🎁：这么久以来还没有宠过粉，为了宣传本次活动搞一波抽奖。评论+点赞+转发三连，活动结束后抽10位送出Binance周边 🌟：另外我自掏腰包，抽1位欧皇送出Binance滑板🛹 （PS：旅行活动的分享，会接龙在评论区）

哈哈哈，笑死

Software engineers have become the condom between Claude Code and production.

等了许久的特斯拉中国，车机语音服务，终于来了。 披露显示，接入了字节跳动的火山引擎 API，由豆包、DeepSeek 提供人工智能服务。 国外版则是 Grok。

大家好，我们即将迎来Seedance2.5，请允许我榨干Seedance2.0所有性能配合最新Kimi K3模型为这个人类历史上具有里程碑意义的视频模型画上一个完美的句号。【完整游戏流程请移步至评论区点击链接体验】

Hello people of Sol! I've reset usage limits for all ChatGPT Work and Codex users. Together with that, a quick update on GPT-5.6 Sol usage limits. Over the past few weeks, many of you have told us that Sol was using your Codex limits faster than expected. To be clear, we have not reduced usage on any subscription plans. We’ve been digging into what was happening and have landed several improvements. As a result, we expect your usage to last around 18% longer during typical use of Sol. Some of you should already see significantly larger improvements from today. Tomorrow, we’ll also restore the five-hour limit that we temporarily paused while investigating. Here’s what we found: - GPT-5.6 Sol is much more willing to work for longer, make additional tool calls, and coordinate complex workflows across tools and subagents. That makes it better at solving hard problems, but some tasks were using far more than we intended. - Sol also works harder at the same reasoning effort than previous models. High on Sol can use more tokens than High did on GPT-5.5. - Programmatic tool calling, also referred to as code mode, gives Sol much more flexibility to run tool calls in parallel or continue working while waiting. But it also led to more responses per turn, more cached input tokens, and higher usage than expected. - This was particularly noticeable when Sol was waiting for tool calls to finish or running many web searches. We’ve improved how we handle both cases and are continuing to make code mode more efficient. - The impact was also very uneven. The median user actually found Sol quite token efficient, while some power users working on harder tasks saw their usage drain much faster. We were very focused on average and median usage before launch and missed some cases where the long tail could use significantly more usage. Sol is a significant step forward in what Codex can do, but capability and efficiency do not always improve at the same pace, and some issues only become clear once people are using the model at real-world scale. We should have recognized this sooner and been more upfront about it. You keep pushing the frontier and we’ll keep improving efficiency and sharing updates as we go.

感动！过去 4 天 OpenAI 为 ChatGPT Work 和 Codex 用户，重置了 3 次额度。 用不完，根本用不完。 感谢同行间竞争，感谢中国 AI。

Hello people of Sol! I've reset usage limits for all ChatGPT Work and Codex users. Together with that, a quick update on GPT-5.6 Sol usage limits. Over the past few weeks, many of you have told us that Sol was using your Codex limits faster than expected. To be clear, we have not reduced usage on any subscription plans. We’ve been digging into what was happening and have landed several improvements. As a result, we expect your usage to last around 18% longer during typical use of Sol. Some of you should already see significantly larger improvements from today. Tomorrow, we’ll also restore the five-hour limit that we temporarily paused while investigating. Here’s what we found: - GPT-5.6 Sol is much more willing to work for longer, make additional tool calls, and coordinate complex workflows across tools and subagents. That makes it better at solving hard problems, but some tasks were using far more than we intended. - Sol also works harder at the same reasoning effort than previous models. High on Sol can use more tokens than High did on GPT-5.5. - Programmatic tool calling, also referred to as code mode, gives Sol much more flexibility to run tool calls in parallel or continue working while waiting. But it also led to more responses per turn, more cached input tokens, and higher usage than expected. - This was particularly noticeable when Sol was waiting for tool calls to finish or running many web searches. We’ve improved how we handle both cases and are continuing to make code mode more efficient. - The impact was also very uneven. The median user actually found Sol quite token efficient, while some power users working on harder tasks saw their usage drain much faster. We were very focused on average and median usage before launch and missed some cases where the long tail could use significantly more usage. Sol is a significant step forward in what Codex can do, but capability and efficiency do not always improve at the same pace, and some issues only become clear once people are using the model at real-world scale. We should have recognized this sooner and been more upfront about it. You keep pushing the frontier and we’ll keep improving efficiency and sharing updates as we go.