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

Postingan terbaru

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 →

Dibandingkan akun berukuran sama

6 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. tampil luas, tetapi sedikit penonton yang merespons.

Median tayangan3 440akun ini968median untuk 10K–100K

Jangkauan, %23.20%akun ini3.43%median untuk 10K–100K

Interaksi, %0.77%akun ini1.91%median untuk 10K–100K

Metrik	Akun ini	Median untuk 10K–100K	Rasio
Median tayangan per postingan	3 440	968	3.55×
Jangkauan (tayangan ÷ pengikut)	23.20%	3.43%	6.76×
Tingkat interaksi	0.77%	1.91%	0.40×

Akun lain pada rentang ini → Bandingkan dengan akun lain → Bagaimana tolok ukur ini disusun →

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.

Postingan terbaru

Dibandingkan akun berukuran sama

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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