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Ryan Shea ✓

@ryaneshea · USA · joined 02 Mar 2010

AI+bio experiments: https://t.co/JbiVsGf0Qi. Fmr Senior Advisor @US_FDA. 10+ unicorn investor. Cofounder @Stacks. MechE/CS @Princeton. NJ Math League State Champ.

30 178Followers
3 831Following
12 826Posts total
1MViews on collected posts

โพสต์ล่าสุด

Reminder that OpenRouter token consumption is not even remotely representative of token use across the industry. 1. Historically, OpenRouter has had smaller shares of OpenAI and Anthropic tokens because it was the router that engineers would use for the long tail of requests but 994 views · 8 likes · 2 reposts · 5 replies Open on X →
Wait, so Pantheon was prescient after all? Artificial Intelligence requires obscene amounts of compute to discover effective but inefficient networks. Meanwhile, Uploaded Intelligence let's us take systems from nature that vastly surpass AI's on a per byte and per watt basis. 275K views · 4.2K likes · 228 reposts · 85 replies Open on X →
https://t.co/cQAPPPzVrm
1.4K views · 8 likes · 0 reposts · 0 replies Open on X →
Astra estimates the probability of a Millennium Prize problem being solved in 2026 as 0.7% https://t.co/9hCL76QVML
37.3K views · 692 likes · 16 reposts · 26 replies Open on X →
As you can see below, Kimi K3 is one of the main models Bitcoiners are using to patch their software and improve industry security. GLM-5.2 was the model that HuggingFace used to patch its software when it was being hacked. Bitcoiners and HuggingFace are not using OpenAI and 10.6K views · 117 likes · 19 reposts · 8 replies Open on X →
red teaming bitcoin: - we’ve written multiple harnesses and we’re launching a huge wave of reviews against many core bitcoin projects: crypto libs, wallets, infra, … - situation is extremely bad. - we’re averaging on the order of 1 critical exploit per hour per person. - we’ve 290.6K views · 2.4K likes · 328 reposts · 122 replies Open on X →
Today I’m launching AI IQ — frontier AI models, scored on the human IQ scale. Instead of endless leaderboard tables, AI IQ shows: • Where models land on the IQ bell curve • How frontier IQ is changing over time • How models compare on IQ and EQ • What intelligence costs in http
425.3K views · 1.5K likes · 223 reposts · 162 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

6 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงต่อคนมากกว่าบัญชีขนาดเดียวกัน.

ยอดดูมัธยฐาน23 932บัญชีนี้924ค่ามัธยฐานของ 10K–100K
การเข้าถึง, %79.30%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K
การมีส่วนร่วม, %1.46%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K
ตัวชี้วัดบัญชีนี้ค่ามัธยฐานของ 10K–100Kอัตราส่วน
ยอดดูมัธยฐานต่อโพสต์23 93292425.9×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)79.30%3.62%21.9×
อัตราการมีส่วนร่วม1.46%1.52%0.96×

บัญชีอื่นในช่วงนี้ →   เปรียบเทียบกับบัญชีอื่น →   ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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

425.3K12 May
290.6K4 Aug
10.6K
37.3K8 Sep
1.4K
275K14 Sep
99416 Sep

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.46%12 May
1.02%4 Aug
1.40%
1.99%8 Sep
0.57%
1.64%14 Sep
1.51%16 Sep

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

What the audience does

Likes66.8%8 905 in total
Reposts6.1%816 in total
Replies3.1%408 in total
Quotes1.8%240 in total
Bookmarks22.2%2 965 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.

บัญชีที่คล้ายกัน