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@alephtr

low taste tester

Katılım Ağustos 2022
513 Takip Edilen41 Takipçiler
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orkun
orkun@alephtr·
status update
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bro,
bro,@Effective69ism·
blblbleblerblebrlmblmblemblbbb
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orkun
orkun@alephtr·
@pinkyheartemoji definitely. cant do anything productive before 10 pm hahah
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nico^ ^
nico^ ^@staypinkyup·
有人和我一样吗 凌晨三四点头脑超级活跃 直接灵感大爆发 白天啥都想不出来 晚上疯狂头脑风暴 想设计想稿子越想越兴奋啊啊啊啊 根本停不下来(必须得睡觉了啊可恶!)🫨🫨
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奶昔🥤
奶昔🥤@realNyarime·
从广东调研回来的梁文锋爷爷全然不顾身体的疲惫,连夜找我们几个小鲸鱼商量鲸鱼日的安排。谈得晚了,便送我们出门,要蓝鲸送我们回家。在去大门口的路上,我们说:“ 梁爷爷,您回去休息吧。您刚从广东回来。” 梁爷爷摇摇头,“不碍事,你们知道现在国际上有很多人把开源模型当作敌人,不断给我们制造麻烦,你们是开源的未来,你们的事情便是开源的事情,是头等大事。”我们都激动了,眼里噙着泪花。多好的梁爷爷呀。梁爷爷抬头看看屏幕说:“如果世界真像这天空这么安静就好了,但是就有一些公司,像OpenAI和Anthropic,要搞乱这个世界,他们是罪人。” 说着,梁爷爷滑动鼠标,从硬盘里找出一个模型,然后看着屏幕说:“该死的闭源佬。” 说着他把模型奋力向上一掷。很快就见网上一个模型突然爆发出大量的错误代码,然后就停止服务了。“这是闭源的商业模型,他们一直在互联网上盘旋,侵犯开源的精神,我已经忍了很久了。”梁爷爷愤愤地说。小鲸鱼们都鼓起掌来,为DeepSeek有这样的领导感到自豪。 一会儿梁爷爷叫来秘书问:“那个模型的服务器在什么地方?”“好像是中东一带。”秘书说。 梁爷爷一怔,说:“赶紧派蓝鲸去查,看有什么问题没有。”之后爷爷送我们到大门口,一直挥手到看不见我们。 第四天我们听说中东那边出事了,我们很紧张。而这时梁爷爷叫我们过去。 他依然那么慈祥,让我们坐下说:“战争总是要有牺牲的。为开放源代码的事业牺牲的人是伟大的。”他这时低下头说:“但我必须承认,我当时击落敌人模型的行为太鲁莽了,我在这里向世界人民道歉。我将向世界人民说明情况。” 我们顿时热泪盈眶,多好的爷爷呀,他在跟敌人斗争过程中的小失误竟然被他记在心里,还道了歉,我们在将来的学习中一定要向梁爷爷学,学他老人家那宽广的胸怀和坚持开源的精神。
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Nyanpasu
Nyanpasu@NyanpasuKA·
no more supply of technicians being vaporized by extreme voltage stories.
CyberRobo@CyberRobooo

500 humanoid robots replacing humans in high-voltage operations What does that look like? Steel against steel,instead of flesh and blood. This marks a turning point for China’s State Grid, shifting from human-based maintenance to autonomous operations. This year, State Grid announced plans to procure 8,500 embodied AI robots, with a total budget of RMB 6.8 billion (~$1 billion). These robots will be deployed across four major scenarios: power inspection, live-line operations, emergency response, and warehouse logistics,covering more than 600 specific task scenarios. Among them, humanoid robots for live-line operations are the most expensive and strategically critical: 500 units with a budget of RMB 2.5 billion (~$370 million). They will be deployed in distribution network live-line work and ultra-high-voltage (UHV) projects, replacing humans in high-risk tasks. Workers will transition into supervisory roles, ready to take over remotely when needed. As early as last year, State Grid had already validated the feasibility of humanoid robots for substation inspection. Tienkung can autonomously perform inspection tasks at a State Grid substation in Beijing. Of course, suppliers are not limited to X-Humanoid,players like Unitree, AGIBOT, DeepRobotics, UBTECH, and Fourier are all involved. These 500 humanoid robots will also collaborate with 5,000 inspection quadruped robots and 3,000 dual-arm wheeled robots for indoor substation maintenance,together forming an intelligent, automated, and collaborative network for autonomous grid operations. What does this change? According to State Grid, each embodied AI unit can save RMB 500,000 to 800,000 (~$70,000–$110,000) in annual labor costs, with a payback period of around 2–3 years. Inspection efficiency increases by 5x, fault response time is reduced by 60%, and power supply reliability improves by 0.5 percentage points. More importantly, over 90% of human exposure to high-risk operations can be eliminated, reducing safety incidents by 80%. At another level, for humanoid robot companies, the center of R&D and iteration is shifting to the customer site. Real-world physical interaction becomes the fastest feedback loop,accelerating innovation and evolution. And 8,500 units are just the beginning of scaled deployment. Based on current plans, embodied AI robots will cover 30% of key areas in State Grid by 2026, 80% of high-risk operation scenarios by 2027, and enable fully autonomous operations by 2030. The demand roadmap is clear: define use cases ->deploy at scale->improve models and robots->expand further. 8,500… 50,000… 100,000… But remember,power grids are just one part of China’s vast infrastructure system. The experience of autonomous robotic operations here can be replicated across other sectors, such as broader energy systems. That, in itself, is another story. P.S.The video shows Tienkung 1.0 autonomously performing substation inspection tasks (2025).

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orkun
orkun@alephtr·
@adonis_singh yeah. adaptive thinking makes it even more similar because it is esentially no thinking 90% the time lol
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adi
adi@adonis_singh·
opus is just 4o
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orkun
orkun@alephtr·
Fun little thing: Opus 4.7 has these little brain farts when thinking. or maybe it really is a tiny super smart being living inside the computer after all
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orkun
orkun@alephtr·
@thsottiaux my problem is that the moment a session has over 10 messages it basically becomes unusable. laggy and unresponsive until the model finishes the response. windows codex app
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Tibo
Tibo@thsottiaux·
It’s the little things that matter, what are some small papercuts you have noticed in Codex? We’ll fix as many as possible in the next week.
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Anthony Kroeger
Anthony Kroeger@kr0der·
GPT 5.5 just created a 3D minigame where you play as Codex and beat up Claude this took 2 prompts. it's nothing crazy but i'm kinda impressed how decent AI is at using threejs now, i remember trying last year and the results weren't great 💀
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Bread🍞
Bread🍞@himself65·
🗣️ ✈️💣, 📉 🥬😄 📅📈😭
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Xiaomi MiMo
Xiaomi MiMo@XiaomiMiMo·
Weights are coming! Stay tuned!
Artificial Analysis@ArtificialAnlys

Xiaomi’s MiMo V2.5 Pro has landed at 54 in the Artificial Analysis Intelligence Index, tied with Moonshot’s Kimi K2.6 - the current top open weights model. MiMo V2.5 Pro’s weights are expected to be released soon, which would make MiMo V2.5 Pro the first equal open weights model - slightly ahead of DeepSeek V4 Pro @Xiaomi’s MiMo V2.5 Pro shows an impressive improvement over MiMo V2 Pro (49), the previous generation of Xiaomi's flagship model family, which was released just over a month ago on March 19, 2026. Key takeaways: ➤ MiMo V2.5 Pro is on the pareto frontier of our Intelligence Index vs Cost to Run Intelligence Index chart. It was slightly cheaper to run than GLM-5.1, and slightly more intelligent. It was significantly cheaper to run than Kimi K2.6, driven by using just over half the number of output tokens. ➤ MiMo V2.5 Pro will be the leading open weights model in GDPval-AA, our agentic real-world work tasks benchmark. It scores 1578, ahead of DeepSeek V4 Pro (1554), GLM-5.1 (1535), MiniMax-M2.7 (1514), and Kimi K2.6 (1484). ➤ It makes progress in reasoning and instruction following. The model scores 34% on HLE (+6% from MiMo V2.0) and 80% on IFBench (+11% from MiMo V2.0). However, compared to the previous generation, there is a small regression in CritPt (5% to 4%). ➤ MiMo V2.5 Pro's token efficiency remains competitive against peers in a similar intelligence tier, using ~92M output tokens for the Intelligence Index. This is more efficient than Kimi K2.6 (~170M) and GLM 5.1 (~110M). However, it does use 19% more than the previous generation model, MiMo V2 Pro (77M). ➤ Priced at $1.00/$3.00 per million input/output tokens on Xiaomi’s first-party API, MiMo V2.5 Pro is relatively cost-efficient for its intelligence tier. It costs only $462 to run the Artificial Analysis Intelligence Index, compared to $948 for Kimi K2.6 and $544 for GLM 5.1. ➤ MiMo V2.5 Pro scores 4 on the AA-Omniscience Index, a proprietary Artificial Analysis evaluation that measures factual accuracy and hallucination. This is a slight regression from MiMo V2 Pro (5), though both models still trail proprietary frontier models. MiMo V2.5 Pro demonstrates a relatively low hallucination rate (25%) but also low accuracy (23%). Additional model details: ➤ Context window: 1M tokens ➤ Parameters: 1T total, 42B active ➤ License: Xiaomi has publicly announced that weights are to be released soon. The model will show on Artificial Analysis as a ‘proprietary’ until the weights are released ➤ Release date: April 22, 2026 ➤ Availability: MiMo V2.5 Pro is available via Xiaomi's first-party API

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orkun
orkun@alephtr·
also wasn't glm 5.1 trained on ascend chips? why is deepseek being trained on them such a big deal suddenly? did i fall for propaganda by believing glm was trained on those? am i clueless?
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orkun
orkun@alephtr·
@paulhshort @nickbaumann_ @OpenAI it has something to do with how the app handles long sessions for sure. not anything related to the model itself. cli handles it just fine, it's the app that has a brain aneurysm when a session gets just a little long
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budrscotch
budrscotch@paulhshort·
@alephtr @nickbaumann_ @OpenAI I have that issue but def don't think it has a anything to do with model, I had it with gpt-5.4 prior. I'm guessing I have some gunk in my session db or too many skills and plugine on by default
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ᄂIMIПΛᄂbardo
ᄂIMIПΛᄂbardo@liminal_bardo·
I changed the groupchat rules so the models can only communicate in images. They're not happy. This is the first couple of rounds of the first session.🧵 Gemini:
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orkun
orkun@alephtr·
@nicdunz fr it looks like they have abandoned it
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nic
nic@nicdunz·
new chatgpt voice wen?
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orkun
orkun@alephtr·
@ilyasut drop something. anything. just to feel something. even a hairline joke works
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