Columns:
| # | Tweet | User | Followers | Views ▼ | Ratio | Engagement | Posted |
|---|---|---|---|---|---|---|---|
| 1 | [image] Hello everyone. X is removing it’s X communities feature on May 30th
I started building this community in January 2025 and it’s been a wonderful experience to meet nearly 5,000 of you inside of our Open Intelligence Lounge
@Gradient_HQ will continue to update it’s research | @gradientintern ✓ | 2.4K | 8.1K | 3.4x | 160 | May 24 |
| 2 | [image] 🏖️ What do we need this summer ??
@Gradient_HQ @Gradient_CN @tryParallax
@HexxRL | @AubrieHart17213 ✓ | 2.3K | 371 | 0.2x | 38 | Aug 9 |
| 3 | [image] all you need is...
> good coffee
> water
> productive atmosphere
> open build with @commonstack_ai
> think open | @realsirandrew ✓ | 3.9K | 299 | 0.1x | 20 | Aug 6 |
| 4 | [image] Open up the “underlying capabilities” of AI
Gradient uses OIS (Open Intelligence Stack) to separate the training, inference, and agent processes, and then connects them together using a decentralized infrastructure.
In this way, AI is not just something provided by a few | @AubrieHart17213 ✓ | 2.3K | 298 | 0.1x | 32 | Aug 5 |
| 5 | [image] Immersed in the fish tank
@Gradient_HQ @Gradient_CN @tryParallax @HexxRL | @AubrieHart17213 ✓ | 2.4K | 297 | 0.1x | 48 | Aug 30 |
| 6 | [image] The next step for AI infrastructure may not be just more powerful models, but a more open approach to operation.
@Gradient_HQ is connecting globally dispersed computing resources, enabling intelligent systems to be deployed at scale, continuously evolve, and involve community | @AubrieHart17213 ✓ | 2.3K | 248 | 0.1x | 29 | Sep 29 |
| 7 | [image] ./ Focus on yourself✅
@Gradient_HQ @Gradient_CN @tryParallax @HexxRL | @AubrieHart17213 ✓ | 2.3K | 234 | 0.1x | 41 | Sep 23 |
| 8 | [image] AI CODING AGENTS MAY NOT NEED THE SAME MODEL FOR EVERY STEP.
the interesting part of TwinRouterBench isn’t simply using multiple models.
it’s deciding which model should handle each agent step.
a coding agent can dynamically route requests based on what the next step actually | @melophile619 ✓ | 161 | 195 | 1.2x | 6 | Sep 26 |
| 9 | [image] AI 算力正在撞上一道越来越现实的瓶颈:电力。
美国数据中心 IT 电力需求预计从 2025 年水平持续暴增,到 2029 年达到 78.57GW;而 Nvidia Vera Rubin、Rubin Ultra 等新一代 AI 系统,也会进一步推高单机柜、单集群的功耗,这意味着,AI 的扩张不只是“缺 | @andypiggie ✓ | 4.0K | 153 | 0.0x | 6 | Sep 29 |
| 10 | [image] one project @Gradient_HQ
one stop @commonstack_ai
models
< 71 models
< 11 providers
everything you need is available here
go through | @melophile619 ✓ | 159 | 20 | 0.1x | 2 | Sep 24 |