观海云远base.eth

[观海云远base.eth @icp1000d]

I contributed to the tacit mixer ceremony. Contribution #363, hash 6021906ba15762bc053544fd91b02921. https://t.co/TvEmcOhHQf #tacit #btc

[观海云远base.eth @icp1000d]

@0xae13 @z0r0zzz 028e5de70001863f83d2e2ebb16102533699e79ed2905590395183ad891c0d7b62

[观海云远base.eth @icp1000d]

@unipixnft 0xF4BBdB97a56574d95f1CBd670CADB92826dD9A0A

[UniPix @unipixnft]

Chapter 2 🦄

Want to move from FCFS to WL, or to GTD?

UniPix now has a simple rating system for everyone who supports the project.

If you really want to be part of UniPix, prove it.

https://t.co/r7CPG8WM92

[观海云远base.eth @icp1000d]

@espressoFNDN Fuck

[AI奶爸 @zstmfhy]

如何解决GLM 用户的痛点：

1）token 随便用，MCP 月额度却只有 100 次
2）一旦上网搜资料、批量读网页就秒光，下个月 1 号才能重置后台截图刚好

奶爸今天给大家直接上干货：别再被官方额度卡脖子了，用这个开源神器 Web Scout MCP 自己搭一个无限次的！链接：https://t.co/exVbx7GqQj

最大亮点：
1）本地跑或自部署，次数无限！只要 token 够，MCP 随便浪，不吃智谱那 100 次。
2）安装简单：Claude Desktop / Cursor 用户 npx 一键搞定（README 有命令），跑起来稳，隐私还更好。

兄弟们，月 100 次真不够玩，赶紧白嫖续命吧！别再每个月蹲重置了装好试试，评论区告诉我好不好用～

[Orange AI @oran_ge]

很多人说看图文还是学不会
没关系，视频版本来了！
橘子手把手地带你入门 CC
跟着视频走，应该都能学会了吧
https://t.co/QuTtzIKE3R

[观海云远base.eth @icp1000d]

Help train better AI – and earn while you do it.
I'm contributing on @PerleLabs, where verified human feedback powers real AI data.
Join me here: https://t.co/JEsu6671SJ

[观海云远base.eth @icp1000d]

I'm using @billions_ntwk Premium vouchers to access rewards and improved earning levels. Use my affiliate link or enter code on checkout: BMQJSALFTL https://t.co/ssfggMXZUE

[观海云远base.eth @icp1000d]

@Han_kkui @openmind_agi 从discord看到来的，兄弟，你上传多久了拿到的勋章啊？

[观海云远base.eth @icp1000d]

Storm is coming 🌀

@Stormrae_AI is transforming complex AI tasks into engaging consumer experiences.

Just claimed my artefact and started accumulating shards.

Claim yours 👉 https://t.co/XVIj4GptY5

[观海云远base.eth @icp1000d]

@changqiao9473 美女你好，你的脚本的确很方便，我在windows里面用wsl跑到这一步了，请问你后面怎么操作的啊？求指点

[libapi @libapi_]

如何把mint到的机器人点亮教程@openmind_agi

git clone https://t.co/fiJowMWyOk

cd OM1

git submodule update --init

uv venv

brew install portaudio ffmpeg

cp env.example .env

nano .env （添加 evm地址 ， api key ，机器人ID ）

source .env （重新加载环境变量）

uv run src/run.py spot 这个不会亮起

uv run src/run.py conversation

#openmind_agi @SidechainGavin
@boyuan @ClaraChengGo @openmind_agi #agi

点亮🌟 : https://t.co/thCSucWelP

官方对话教程 : https://t.co/GacNn9RFlS

[0xShyron @0xShyron]

𝐯𝐢𝐝𝐞𝐨 𝐠𝐮𝐢𝐝𝐞 𝐭𝐨 𝐞𝐚𝐫𝐧 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐛𝐚𝐝𝐠𝐞 𝐨𝐧
@openmind_agi

in this dev program there are multiple levels you get badges according to amount of $ you spent

i talked to many badge holders of different levels and according to my research here's how things work and badges are given at different levels:

➠ $5 spent ➜ dev badge level 1
➠ $30-50 spent ➜ level 2
➠ $100 spent ➜ level 3
➠ $100+ spent ➜ level 4 dev badge

𝐦𝐨𝐫𝐞 𝐲𝐨𝐮 𝐫𝐮𝐧 𝐧𝐨𝐝𝐞 → 𝐦𝐨𝐫𝐞 𝐚𝐩𝐢 𝐜𝐨𝐬𝐭𝐬 → 𝐡𝐢𝐠𝐡𝐞𝐫 𝐥𝐞𝐯𝐞𝐥 𝐛𝐚𝐝𝐠𝐞𝐬

if you hold at least level 2 badge then you are ahead of many people in this project because rarely someone running this

because there's no proper guide for this but i made one so everyone can earn badges

guide link: https://t.co/TjzWzV7iah

video also attached so you don't face any error, still you face any error comment down

[观海云远base.eth @icp1000d]

点亮@openmind developer勋章，大家可以尝试一下

[Chuks @Chuksdakingz]

openmind developer badge

a detailed guide to contribute and earn the badge

what is needed:
  - octaspace
  - @openmind_agi OM1 api key
  - patience
  - $1 in octa and $2 credit for api

step 1:
> rent machine from octaspace market place
  - visit: marketplace.octa. computer/compute (remove space)
  - sign in
  - you can fund your octaspace with OCTA token from mexc (10 OCTA tokens is enough)
  - go to compute, on the right hand side you will see filters
  - set system as ubuntu 22.04
  - then select a us based rtx gpu
  - click on configure
  - click on apps (select PyTorch JupyterLab <this runs on ubuntu 22.04 too>)
  - set disk size at least 40gb
  - click on deploy

[Zama @zama]

FHE has been getting ~10× faster per year over the past few years. Some of that comes from better cryptography, but most of the gains now are from hardware acceleration. Moving from CPU → GPU → FPGA → ASIC is basically how you go from ~10 confidential stablecoin transfers per second to ~100,000 confidential stablecoin transfers per second.

[观海云远base.eth @icp1000d]

总之，就是在铺路给下一个机器人时代，开放、去中心化那种。挺前沿的，如果你对AI+机器人感兴趣，值得关注一下他们的App和官网@openmind。

[观海云远base.eth @icp1000d]

OpenMind（现在常叫 OpenMind AGI）是个挺有意思的项目，简单说就是想让未来的机器人变得更聪明、更独立，还能互相协作，而不被某个大公司完全垄断。他们主要在做两件事：

[观海云远base.eth @icp1000d]

比如一群机器人一起干活，而不用靠中心服务器。
核心想法是：把AI装进真实世界的机器里，让它们不光会听命令，还能自主学习和合作。项目融了不少钱（2025年拿了2000万美元，投资人有Pantera、Coinbase Ventures等），现在社区在通过App贡献地图数据、测试功能来赚积分，可能以后有奖励。