Guohao Li 🐫 ✓

@guohao_li · San Francisco, CA · joined 14 Aug 2018

Founder @Eigent_AI / @CamelAIOrg. Scaling RL Environments for Agents. Prev Oxford, KAUST, ETHz, Intel, Kumo.

14 832Followers

5 273Following

2 678Posts total

3.6MViews on collected posts

Últimas publicaciones

Guohao Li 🐫 ✓@guohao_li3 Sep

what if we run out of ideas for benchmarking models? https://t.co/o0u5ktYUXS

4.4K views · 25 likes · 0 reposts · 7 replies Open on X →

Guohao Li 🐫 ✓@guohao_li2 Sep

looks strong. can't wait for the open weight releases! 1.2K views · 12 likes · 0 reposts · 1 replies Open on X →

Guohao Li 🐫 ✓@guohao_li2 Sep

Gemini 3.8 is now on Eigent! ⚡️ 1.7K views · 16 likes · 0 reposts · 0 replies Open on X →

Guohao Li 🐫 ✓@guohao_li2 Sep

Gemini 3.8 now on Eigent! ⚡️⚡️⚡️ We handed it a real finance analyst's job: value Equinix vs Digital Realty, Damodaran-style, straight from SEC filings. A team of agents researched, checked FX, and built the DCF, then handed back an Excel file you can actually poke at. Click a

1:20

2.8K views · 15 likes · 2 reposts · 0 replies Open on X →

Guohao Li 🐫 ✓@guohao_li27 Aug

program the physical world via model hardware standard. it is more exciting than a new fable model release 4.1K views · 31 likes · 0 reposts · 1 replies Open on X →

Guohao Li 🐫 ✓@guohao_li27 Aug

Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. Read more: https://t.co/XQ2y9EW7Af https://t.co/kgyCvZ6iYc

2:12

3.2M views · 11.2K likes · 1.4K reposts · 535 replies Open on X →

Guohao Li 🐫 ✓@guohao_li9 Jan

Frontier labs spend millions purchasing RL environments for training terminal agents. But we decided to open source it. Introducing SETA: Scaling Environments for Terminal Agents, the largest open source training RL environments for terminal agents. We released: - 400 termianl 221.3K views · 753 likes · 91 reposts · 26 replies Open on X →

Guohao Li 🐫 ✓@guohao_li9 Jan

https://t.co/fp18lxrUo2 155.7K views · 112 likes · 14 reposts · 7 replies Open on X →

Frente a cuentas del mismo tamaño

6 publicaciones de los últimos 90 días, junto al rango de 10K–100K seguidores. llega a mucha gente, pero pocos de esos espectadores reaccionan.

Visualizaciones medianas3 440esta cuenta968mediana de 10K–100K

Alcance, %23.20%esta cuenta3.43%mediana de 10K–100K

Interacción, %0.77%esta cuenta1.91%mediana de 10K–100K

Métrica	Esta cuenta	Mediana de 10K–100K	Proporción
Visualizaciones medianas por publicación	3 440	968	3.55×
Alcance (visualizaciones ÷ seguidores)	23.20%	3.43%	6.76×
Tasa de interacción	0.77%	1.91%	0.40×

Otras cuentas de este rango → Comparar con otra cuenta → Cómo se construyen estas referencias →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

155.7K9 Jan

221.3K

3.2M27 Aug

4.1K

2.8K2 Sep

1.7K

1.2K

4.4K3 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.09%9 Jan

0.40%

0.44%27 Aug

0.79%

0.67%2 Sep

0.96%

1.07%

0.75%3 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.91%.

What the audience does

Likes60.6%12 121 in total

Reposts7.7%1 548 in total

Replies2.9%577 in total

Quotes4.2%845 in total

Bookmarks24.5%4 906 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Últimas publicaciones

Frente a cuentas del mismo tamaño

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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