Mạnh 100 (❖,❖) ✓

@lon_rong14459 · joined 21 May 2025

Passion for blockchain Project analysis, trend updates. @DecibelTrade

21 363Followers

20 476Following

66 771Posts total

25.9KViews on collected posts

Neueste Beiträge

Mạnh 100 (❖,❖) ✓@lon_rong144595 Sep

@lon_rong14459 @axisrobotics Nghe thú vị quá, 10 buổi thực tế mà không chạm được mục tiêu nào nhưng thêm mô phỏng thì lại hiệu quả hơn hẳn nhỉ 😄 8 views · 2 likes · 0 reposts · 2 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144595 Sep

@lon_rong14459 @axisrobotics The real breakthrough is data efficiency. Simulation can turn a small set of real demonstrations into far more useful training. 11 views · 2 likes · 0 reposts · 0 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144595 Sep

@lon_rong14459 @axisrobotics ngl that 0 to 17 jump with just 50 sim trajs is wild 26 views · 5 likes · 0 reposts · 0 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144595 Sep

Simulation data gets more interesting when it makes limited real world data go further. In an @axisrobotics × Booster experiment, 10 real demonstrations alone resulted in 0/20 target contacts. Add 50 task aligned simulation trajectories, and that moved to 17/20. What stands ht 4.3K views · 185 likes · 14 reposts · 120 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

🔆🔆gAxis @axisrobotics Đã xong lễ , quay lại cày cuốc nào ae axis oi task hiện tại đang chú trong dât chất lượng hơn, có nhiều task hơn, với đó là số lượng ae bào task nhiều hơn nên khá cạnh tranh Pool thưởng: 1,500,000 Axis Points trong event trên bai nần ae https://t.co/LBXJ 4.1K views · 37 likes · 3 reposts · 25 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

A model is capable of reasoning. However, @GenLayer does not leave a single model to make the judgment alone. When a task is defined in natural language, evaluators receiving the same information may still reach different verdicts. That is why the system requires adjudication, 919 views · 119 likes · 4 reposts · 44 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

@lon_rong14459 Yes, right sim per stage beats chasing max fidelity everywhere 7 views · 1 likes · 0 reposts · 0 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

@lon_rong14459 fast iteration and high fidelity don’t have to compete with each other 8 views · 1 likes · 0 reposts · 0 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

@lon_rong14459 using both simulators for different stages makes a lot of practical sense 18 views · 1 likes · 0 reposts · 0 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

Not every robot simulation needs to optimize for the same thing. Axis uses MuJoCo for broader, faster task generation, while Isaac Sim handles more targeted, high fidelity scenes. I like this approach because robotics data has different needs at different stages. Sometimes you 5.3K views · 210 likes · 8 reposts · 126 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144594 Sep

Axis đang dần thay đổi cuộc chơi referral Có một thay đổi nhỏ trong Creator Program nhưng nếu theo @axisrobotics đủ lâu sẽ thấy nó đáng chú ý hơn con số 1.05x hay 1.10x. Axis đã hạ đáng kể ngưỡng ban đầu của Referral Multiplier: • 5 Trajectories hợp lệ từ https://t.co/YpnwKQp 3.7K views · 23 likes · 5 reposts · 11 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144593 Sep

I usually trade small volumes on Decibel and always set tp and sl orders for every trade. But this time, I forgot to set a Stop Loss. As a result, I got liquidated for the first time in August. simply a risk management error. What I didn't expect was the Liquidation Rebate. h 1K views · 125 likes · 4 reposts · 47 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144593 Sep

A full human trajectory isn't always necessary. In a recent @axisrobotics experiment, 660 corrections were collected, but only 161 verified snippets made it into training. Each was around 0.8 seconds. What I find interesting is the idea of capturing only the moment where the h 3.3K views · 147 likes · 3 reposts · 82 replies Open on X →

Mạnh 100 (❖,❖) ✓@lon_rong144591 Sep

A success rate alone doesn't tell me much about a robot policy. @axisrobotics now lets users inspect policies directly through the Hub, including their success rate, checkpoints and success heatmap. The heatmap is probably the part I find most useful. It shows where a policy h 3.1K views · 163 likes · 4 reposts · 86 replies Open on X →

Im Vergleich zu Konten gleicher Größe

14 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit über das eigene Publikum hinaus gezeigt, und es reagiert.

Medianaufrufe974dieses Konto924Median für 10K–100K

Reichweite, %4.56%dieses Konto3.62%Median für 10K–100K

Interaktion, %10.31%dieses Konto1.52%Median für 10K–100K

Kennzahl	Dieses Konto	Median für 10K–100K	Verhältnis
Medianaufrufe pro Beitrag	974	924	1.05×
Reichweite (Aufrufe ÷ Follower)	4.56%	3.62%	1.26×
Interaktionsrate	10.31%	1.52%	6.78×

Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →

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

3.1K1 Sep

3.3K3 Sep

3.7K4 Sep

5.3K

919

4.1K

4.3K5 Sep

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

8.13%1 Sep

7.14%3 Sep

17.09%

1.14%4 Sep

6.54%

5.56%

12.50%

14.29%

18.17%

1.65%

7.35%5 Sep

19.23%

18.18%

50.00%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes62.5%1 021 in total

Reposts2.8%45 in total

Replies33.2%543 in total

Quotes0.6%10 in total

Bookmarks0.9%15 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.

Neueste Beiträge

Im Vergleich zu Konten gleicher Größe

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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