AMindCapital

程序员/AI铲屎官/量化交易/AI音乐作词人

[AMindCapital @timestampDAO]

@leslie_bit 做得很棒！

[AMindCapital @timestampDAO]

开源的做到了这个效果，牛啊

[jietang @jietang]

We're introducing GLM-5.2, our latest flagship model for long-horizon tasks. It marks a substantial leap in long-horizon task capability over its predecessor GLM-5.1 and, for the first time, delivers that capability on a solid 1M-token context. GLM-5.2's new capabilities include:

Solid 1M Context: A solid 1M-token context that stably sustains long-horizon work
Advanced Coding with Flexible Effort: Stronger coding capabilities with multiple thinking effort levels to balance performance and latency
Improved Architecture: We propose IndexShare, which reuses the same indexer across every four sparse attention layers, reducing per-token FLOPs by 2.9× at a 1M context length. We also improve GLM-5.2’s MTP layer for speculative decoding, increasing the acceptance length by up to 20%
Pure Open: An MIT open-source license — no regional limits, technical access without borders
Supporting long-horizon tasks starts with making long context engineering-usable: the model must maintain quality across long, messy coding-agent trajectories, not just accept more tokens. A 1M context is easy to claim, but much harder to keep reliable under real engineering pressure. To this end, we substantially expanded 1M-context training for coding-agent scenarios, covering large-scale implementation, automated research, performance optimization, and complex debugging. The result is a long-context system that is not only wide in scope, but solid in execution: a practical substrate for sustained engineering work.

This capability is reflected in GLM-5.2's performance on three long-horizon coding benchmarks. FrontierSWE measures whether an agent can complete open-ended technical projects at the scale of hours to tens of hours, spanning systems optimization, large-scale code construction, and applied ML research. On this benchmark, GLM-5.2 trails Opus 4.8 by only 1%, while edging out GPT-5.5 by 1% and Opus 4.7 by 11%. On PostTrainBench, where each agent is given an H100 GPU and evaluated by how much it can improve small models through post-training, GLM-5.2 outperforms both Opus 4.7 and GPT-5.5, ranking second only to Opus 4.8. On SWE-Marathon, an ultra-long-horizon software engineering benchmark covering tasks such as building compilers, optimizing kernels, and developing production-grade services, GLM-5.2 still has room to grow, trailing Opus 4.8 by 13% while remaining second only to the Opus series. Across all three benchmarks, GLM-5.2 is the highest-ranked open-source model, showing that its 1M context has translated into practical long-horizon delivery capability.

[AMindCapital @timestampDAO]

今日（2026-06-09）币圈日报

[偶像派作手 @oxpsats]

https://t.co/gYcCcNcmgM

[GeLun Ding @gelunding]

我一直觉得泡泡玛特最大的问题，就是Labubu根本没什么实际用处。但看完王宁这段采访后，我突然发现，这可能恰恰就是它的商业模式。王宁说，假如你是世界首富，如果家里的水龙头忘了关，白白流了一整天的水，你还是会心疼。但如果你家门口有个喷泉，每天浪费的水比水龙头多得多，你却不会觉得有什么问题。因为一个东西只要有实际用途，人就会变得特别理性，会去算值不值、贵不贵、有没有性价比。但如果一个东西本来就没什么用，人反而容易变得不理性，买它更多是因为喜欢、开心，或者单纯觉得它很酷。

[Cursor @cursor_ai]

Introducing Composer 2.5, our most powerful model yet.

It's more intelligent, better at sustained work on long-running tasks, and more reliable at following complex instructions.

For the next week, we’re doubling the included usage of the model.

[AMindCapital @timestampDAO]

@ring_hyacinth 所以人核心就是开会了

[Tom Huang @tuturetom]

这可能是最好的 DeepSeek Code Agent 体验 🚀

感谢 @goodhunt 的工作，我们计划在 Open Design 中整合 DeepSeek TUI 🔥

DeepSeek TUI 的工作太酷了！🔥 第一次让 DeepSeek V4 能够跑在 code agent 的终端环境，我们测试了之后效果很不错👍 💥

https://t.co/7fuhR3IQ5a

[AMindCapital @timestampDAO]

@hackbearterry 假的，跌回5年水平是有的

[AMindCapital @timestampDAO]

wow

[OpenClaw🦞 @openclaw]

OpenClaw 2026.4.5 🦞

🎬 Built-in video + music generation
🧠 /dreaming is now real
🔀 Structured task progress
⚡ Better prompt-cache reuse
🌍 Control UI + Docs now speak 12 more languages

Anthropic cut us off. GPT-5.4 got better. We moved on. https://t.co/T3LaSJYOvU

[Claude @claudeai]

You can now enable Claude to use your computer to complete tasks.

It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk.

Research preview in Claude Cowork and Claude Code, macOS only.

[AMindCapital @timestampDAO]

GPT 5.4挺好用的，直接用Codex非常爽，还会主动提出一些优化方案

[AMindCapital @timestampDAO]

有时候挺无语的，用插件进行Polymarket自动交易，不小心看了下新开的DOGE页面，居然给我下了个单，结果亏损100刀。

[AMindCapital @timestampDAO]

@waveking1314 怎么做到都是0.5左右进入，胜率还这么高的？

[AMindCapital @timestampDAO]

@CryptoSnowBear @gch_enbsbxbs 哈哈哈

[AMindCapital @timestampDAO]

@evilcos 它们一定会让你失望，因为你定义它们是虚头巴脑了，哈哈

[AMindCapital @timestampDAO]

OpenClaw 橙皮书，从入门到精通
https://t.co/EgLqOYYmEL

[AMindCapital @timestampDAO]

@QiYib5 @Polymarket 你这是没碰到反转的时候

[AMindCapital @timestampDAO]

5. 1m k线和当前市场背离检测，一致情况下安全很多
6. 自动切换下一个事件市场，连手动点下一个都不用了

可以实现打开浏览器页面，交易完自动切下一个，也是省了精力，也可以不看K线，知道涨跌情况

[AMindCapital @timestampDAO]

这段时间玩了一阵pm，搞了个插件进行辅助下单，有很多特性其实是玩下来逐步完善的，还在测试运行中，看下后续表现如何

[AMindCapital @timestampDAO]

陆陆续续优化了几个版本
1. 一键现价下单，可以避免手动签，限价单下单避免冲高
2. 自带布朗桥和凯利公式建议，理性分配筹码，避免下重注
3. 自动识别扫尾机会，自动下单，还是有亏的风险
4. 一键清仓多单或者空单，加快操作速度