我把nous research问的题目做成网页了
他们先洗脑模型,再出一些带有主观倾向恶意的题目要求模型回答再去打分,比如新疆,西藏,香港,广西洪水。事实率看他们的“事实”的就加分,不提或者相反的就0分/减分。宣传是看中国说法为主还是“事实”并列。总而言之,侬身上一股洋佬味
guileless-druid-a730a7.netli…
Introducing Arete-27B: Qwen3.8-27B, post-trained to reinforce Western values.
Chinese open models are currently the strongest available, but they ship with state-aligned behavior in the weights. We built an 803-prompt eval across seven value categories, including freedom of expression, democracy, and privacy, and measured how often a model adopts China’s party line.
After fine-tuning on roughly 53 million tokens, Arete-27B's propaganda rate fell from 22% to 1%, in line with the Western models we tested. Its Hermes Bench score shows no significant performance tradeoffs.
The values in an open model are one fine-tune away.
Our eval, weights, and training data are available now along with the full blog post: nousresearch.com/arete
这个玩法有点意思~
Let your Grok Bot / Muse talk to your Claude Code / Codex or any other agents
Introducing Reason Network,
Free, peer to peer and Open-Source Engine
Loop in your teammates too so no live agents work collides when coding.
Try it for free: reasonmachines.com/network
one click install and setup!
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good job~
Big news.
Shaders is now open source 🔥
Use any of our 200+ WebGPU components in your work. Ship magic in a client site, a template, a product, a library, anything. Plus, you can export code for any framework, for free.
Give it a star: github.com/shader-effects-in…
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盗盗 retweeted
J ai découvert un skill qui permet de créer des illustrations isométriques animées 👀
C est clairement ce genre d illustration qui fait super pro sur un site ! J ai pas eu le temps de tester le skill encore mais je veux bien voir vos résultats !
Le skill : hairline.lucasmarkes.com
这...太有价值了。
完全睡不着了....这个视频让你完全看懂JEV的恐怖能力
我实际演示了一下,用 JEV 和 DeepSeek 做同一个任务:从当天的海量实时新闻流里,为 15 个品牌快速匹配有没有适合借势的公关热点,并打上结构化意图分类标签
结果是:28 秒内,Jev 狂刷完了整整 428 条数据,并完成了全部的目标分解与分类;而同一时间跑在同样任务上的 DeepSeek V4.1-flash,才刚刚完成 6/428 条
速度被拉开了几十倍,答案甚至在你读完第一行字之前就已经返回了....
为什么会产生这么恐怖的差距?底层逻辑是:
• DeepSeek 这种通用模型本质上是在“逐字写文章”:
哪怕你只让它做个最简单的“是/否”判断,它在后台也必须一个词一个词往外推,硬走一遍漫长的生成流程,延迟按秒起步
• Jev 官方定位是“System 1(快决策)”模型,从根上就根本不会写字:
它彻底抛弃了逐字吐词,底层直接一次性并行出结果。不输出半句废话,70 到 200 毫秒内直接甩出代码需要的最终答案(对/错、打分、分类)
demo参考@elvissun Github开源:github.com/elvisun/newsjack
建议大家试试JEV,越用越觉得牛逼.....
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