Rui @ruiii233 - Twitter Profile

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.

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Rui @ruiii233

6 days ago

这种思路去炒期货还差不多，说了多少遍预期预期预期，现金流你要怎么解决

美研芒格君

@Kay2289123

7 days ago

如果说财报超预期，股价继续向上，反推来看，现在就是机构砸盘，让散户、让我们普通投资者交出筹码的最好时间接下来的一个月非常关键，可能会有不错的反弹机会和情绪见底。我最近也在为这些事件时间线布局现在市场最关键的一个矛盾点就在于：资本正在惩罚 AI Capex 增加的厂，但资本增加所流向的半导体厂也被惩罚，两者的逻辑不能同时存在时间线+关键数据 7月28日 KLAC → 验证 DUV、中国设备风险 7月29日 META＋MSFT＋LRCX 资本性开支和对 KLA 交叉验证 7月30日 AMZN → 验证 AWS、自研芯片和 AI Capex 8月4日 AMD＋ALAB → 验证算力与互连 8月5日 SNDK＋WDC → 验证存储价格、供给和数据中心需求 8月11–13日 LITE＋SMCI＋COHR＋AMAT＋SNDK Investor Day → 验证光通信、服务器交付、设备和存储周期。 8月26日 NVDA → 对整个 AI Hardware 逻辑的最终压力测试 8月下旬至9月：MRVL、CRWV、CRDO、ORCL、MU → 验证定制芯片、云算力、互连、机房交付和存储周期

Kay2289123's tweet photo. 如果说财报超预期，股价继续向上，反推来看，现在就是机构砸盘，让散户、让我们普通投资者交出筹码的最好时间

接下来的一个月非常关键，可能会有不错的反弹机会和情绪见底。我最近也在为这些事件时间线布局

现在市场最关键的一个矛盾点就在于：资本正在惩罚 AI Capex 增加的厂，但资本增加所流向的半导体厂也被惩罚，两者的逻辑不能同时存在

时间线+关键数据

7月28日 KLAC
→ 验证 DUV、中国设备风险

7月29日 META＋MSFT＋LRCX
资本性开支和对 KLA 交叉验证

7月30日 AMZN
→ 验证 AWS、自研芯片和 AI Capex

8月4日 AMD＋ALAB
→ 验证算力与互连

8月5日 SNDK＋WDC
→ 验证存储价格、供给和数据中心需求

8月11–13日 LITE＋SMCI＋COHR＋AMAT＋SNDK Investor Day
→ 验证光通信、服务器交付、设备和存储周期。

8月26日 NVDA
→ 对整个 AI Hardware 逻辑的最终压力测试

8月下旬至9月：MRVL、CRWV、CRDO、ORCL、MU
→ 验证定制芯片、云算力、互连、机房交付和存储周期

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Rui @ruiii233

10 days ago

想找一位擅长cbt的心理咨询师，最好能线上跟我沟通一下，价格可谈🥲心理障碍

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Rui @ruiii233

11 days ago

可以买点老登休息了

付鹏的财经世界

@fupenglondon

11 days ago

今天很荣幸作为新火集团首席经济学家受邀参与由 @Wikiexpo_global举办的 #WikiEXPOHongKong2026 ，我将今天讲的几个核心观点归纳发布如下：一、流动性：全球资产的底层逻辑首先第一块，先跟大家讲流动性层面。不管是哪一类资产，到今天为止，包括主流加密资产，本质全都和全球核心流动性挂钩。 2008年金融危机之后，全球流动性在2008到2021年走到阶段性顶峰。流动性不能只看新闻里的加息、降息，它分三个维度，大家一定要记牢。加息降息只是利率曲线端的变化，不能代表完整流动性环境。我这边简单放了一张图表。观察流动性可以拆成三件事：水池里的水量、水池水温、池内资金压力分布。底层逻辑可以简单理解成P/Q×G。这点很关键，专业视角看流动性，可以从利率端、利率曲线、美联储资产负债表、公开市场操作等角度跟踪。但还有更简易的观察方式：当前传统交易里，大家普遍把比特币这类主流加密资产，当作流动性强弱的先行指标。

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