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

Posts recentes

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 →

Em comparação com contas do mesmo porte

6 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para muita gente, mas poucos desses espectadores reagem.

Mediana de visualizações3 440esta conta968mediana para 10K–100K

Alcance, %23.20%esta conta3.43%mediana para 10K–100K

Engajamento, %0.77%esta conta1.91%mediana para 10K–100K

Métrica	Esta conta	Mediana para 10K–100K	Proporção
Mediana de visualizações por post	3 440	968	3.55×
Alcance (visualizações ÷ seguidores)	23.20%	3.43%	6.76×
Taxa de engajamento	0.77%	1.91%	0.40×

Outras contas desta faixa → Comparar com outra conta → Como estas referências são construídas →

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.

Posts recentes

Em comparação com contas do mesmo porte

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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