Tony Zhao ✓

@tonyzzhao · Mountain View, CA · joined 16 Dec 2018

Co-founder and CEO @sundayrobotics. Stanford PhD dropout, ex Deepmind, Tesla, GoogleX

147 774Followers

1 006Following

948Posts total

651.8KViews on collected posts

Son gönderiler

Tony Zhao ✓@tonyzzhao11 Aug

Welcome to the team Ashley! Excited to work together. 22.7K views · 70 likes · 2 reposts · 3 replies Open on X →

Tony Zhao ✓@tonyzzhao10 Aug

life update: i joined @sundayrobotics and i am beaming with joy! ⭐ i fell in love with robotics when i was 13, and this week made it feel full circle. i’ve wanted an in-home robot since i was a kid, one that could help my loved ones in their day to day so we had more time for ht 58.3K views · 519 likes · 7 reposts · 68 replies Open on X →

Tony Zhao ✓@tonyzzhao25 Jul

the comment section on our 3 hour (15 hours wall clock) memo folding video is hilarious https://t.co/pnacWIYsJF 24.3K views · 287 likes · 7 reposts · 14 replies Open on X →

Tony Zhao ✓@tonyzzhao23 Jul

We are lucky to have you Henry!! 2 years and so much done! 13K views · 45 likes · 0 reposts · 4 replies Open on X →

Tony Zhao ✓@tonyzzhao23 Jul

2 years @sundayrobotics today! kinda wild I’m still learning faster here day-to-day than I did building my own startup https://t.co/QTWxvQmTBx 20.6K views · 57 likes · 1 reposts · 4 replies Open on X →

Tony Zhao ✓@tonyzzhao22 Jul

Cecilia is a force of nature. So excited to be working with her! We're building out our Business Strategy & Ops team. If you want to help turn frontier robotics technology into a durable business, Cecilia's team is the one to join. 25K views · 141 likes · 3 reposts · 4 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

@tonyzzhao So cool, can't wait to have one at my place 9.7K views · 75 likes · 2 reposts · 2 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

This fall, ACT-2’s first Solve enters homes through our Beta Program, the final step towards fully autonomous home robot deployment. Full technical report: https://t.co/oVR2TAdlHg 103.3K views · 188 likes · 18 reposts · 7 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

Laundry is our first Solve of many. Our recipe is so general that scaling data and compute gives us predictable improvements. Unlocking one Solve accelerates the next Solve. The same ACT-2 model is learning to vacuum, organize toys, zip clothing, and turn pants inside out. http 27K views · 165 likes · 10 reposts · 5 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

Quantitatively, we measure the generalization gap as the difference between in-domain and out-of-domain performance. As we scale up pretraining, the gap falls sharply. This makes in-house performance a reliable predictor of performance in the wild. https://t.co/9g7W0WETNt 58.6K views · 177 likes · 12 reposts · 2 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

This property allows us to hill-climb performance in our office, and trust those gains to hold in unseen homes Our fleet of Memos runs in parallel to rapidly advance reliability, quality, and speed. Left: fleet-scale improvement in-house Right: Memo working across unseen homes 32.4K views · 144 likes · 7 reposts · 1 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

We found a general recipe for Solves: scale pretraining, then hill-climb with minimal in-house data. For the first time, one fine-tuning example can teach a new behavior that generalizes. Below: 4 folding strategies, learned from one example each and tested on held-out setups. h 170.3K views · 323 likes · 28 reposts · 3 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

We call this a Solve. Progress in robotics is difficult to measure because demos vary by setup. Demo ≠ Solved. A Solve declares two boundaries: scope and adaptation cost. Without both, 99% has no context. https://t.co/UfiQUTiVRC 35.5K views · 147 likes · 4 reposts · 3 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

Tons of emergent behavior along the way: - Picking up clothes off the ground - Handling baby wear to 8XL shirts - Robustness against adversarial disturbances and lighting https://t.co/Cot6EezF4t 17.3K views · 229 likes · 8 reposts · 2 replies Open on X →

Tony Zhao ✓@tonyzzhao16 Jul

We completed the most rigorous generalization test to date. Across 785 trials in 31 unseen environments, ACT-2 achieved 99.1% success in laundry folding. ACT-2 also achieved human-level fold quality: receiving an average rating of 4.72/5, with 98.3% earning four or five stars. h 33.9K views · 241 likes · 14 reposts · 7 replies Open on X →

Aynı büyüklükteki hesaplara karşı

Son 90 güne ait 2 gönderi, 100K–1M takipçi aralığıyla yan yana. geniş kitleye gösteriliyor, ama izleyenlerin azı tepki veriyor.

Medyan görüntülenme40 485bu hesap5 983100K–1M için medyan

Erişim, %27.40%bu hesap1.49%100K–1M için medyan

Etkileşim, %0.68%bu hesap0.93%100K–1M için medyan

Ölçüt	Bu hesap	100K–1M için medyan	Oran
Gönderi başına medyan görüntülenme	40 485	5 983	6.77×
Erişim (görüntülenme ÷ takipçi)	27.40%	1.49%	18.4×
Etkileşim oranı	0.68%	0.93%	0.73×

Bu aralıktaki diğer hesaplar → Başka bir hesapla karşılaştır → Bu kıyas değerleri nasıl kuruluyor →

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

17.3K16 Jul

35.5K

170.3K

32.4K

58.6K

27K

103.3K

9.7K

25K22 Jul

20.6K23 Jul

13K

24.3K25 Jul

58.3K10 Aug

22.7K11 Aug

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

1.41%16 Jul

0.44%

0.22%

0.50%

0.34%

0.69%

0.21%

0.81%

0.59%22 Jul

0.31%23 Jul

0.38%

1.29%25 Jul

1.02%10 Aug

0.33%11 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes80.9%2 808 in total

Reposts3.5%123 in total

Replies3.7%129 in total

Quotes2.2%77 in total

Bookmarks9.6%335 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.

Son gönderiler

Aynı büyüklükteki hesaplara karşı

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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