Blake Richards

@tyrell_turing · Montréal, Québec · joined 24 Apr 2013

Researcher at @mcgillu combining AI and neuroscience. Also on Bluesky (@tyrellturing.bsky.social) and Mastodon: @tyrell_turing@fediscience.org.

15 936Followers

1 847Following

23 079Posts total

40.7KViews on collected posts

โพสต์ล่าสุด

Blake Richards@tyrell_turing23 Sep

I’m beyond honoured to be named a 2026 @schmidtsciences Polymath. With US$2.5 million over five years, I’ll be able to pursue a highly interdisciplinary project that will combine quantitative and qualitative data to better capture human neurodiversity.🧠 https://t.co/kXjzjVUBEy 5.3K views · 131 likes · 7 reposts · 21 replies Open on X →

Blake Richards@tyrell_turing11 Sep

A new artificial life paper our from our Paradigms of Intelligence team! 🙂 This one explores the evolution of cooperation. 🧬 6K views · 70 likes · 6 reposts · 0 replies Open on X →

Blake Richards@tyrell_turing4 Sep

Check out our new paper from the Paradigms of Intelligence team. We show how you can modify a denoising model to get a system where continuing to roll-out the recurrent hidden state leads to consistent gains in reasoning problems. 12K views · 135 likes · 6 reposts · 2 replies Open on X →

Blake Richards@tyrell_turing11 Aug

1/15) What could drive AI agents to cooperate with each other, even if there is no chance for reciprocity or pay back? 🤔 🧵 Our team at Google, Paradigms of Intelligence, uncovered new paths to cooperation and a new game theory for foundation models 👇 https://t.co/ALq34NCcPN

6.9K views · 65 likes · 19 reposts · 2 replies Open on X →

Blake Richards@tyrell_turing13 Feb

A big thank you to the @foresightinst for supporting our research on neuro-foundation models! 3.2K views · 20 likes · 1 reposts · 1 replies Open on X →

Blake Richards@tyrell_turing13 Feb

We’re excited to support @evadyer and @tyrell_turing as they combine different ways of measuring neural activity to better model how the brain works. They will explore the development of a general-purpose, multiscale, multimodal model of human brain activity that learns shared h

7.4K views · 39 likes · 7 reposts · 0 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

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

ยอดดูมัธยฐาน6 425บัญชีนี้924ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %40.32%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %1.28%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	6 425	924	6.95×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	40.32%	3.62%	11.1×
อัตราการมีส่วนร่วม	1.28%	1.52%	0.84×

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

7.4K13 Feb

3.2K

6.9K11 Aug

12K4 Sep

6K11 Sep

5.3K23 Sep

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.63%13 Feb

0.68%

1.29%11 Aug

1.20%4 Sep

1.27%11 Sep

3.01%23 Sep

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

What the audience does

Likes63.5%460 in total

Reposts6.4%46 in total

Replies3.6%26 in total

Quotes0.6%4 in total

Bookmarks26.0%188 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.