Lior Alexander ✓

@LiorOnAI · San Francisco, CA · joined 07 Nov 2012

Founder @AlphaSignalAI (300k devs) • Ex-MILA researcher focusing on solving the explosion of knowledge in AI.

117 246Followers

2 544Following

3 871Posts total

44.6KViews on collected posts

Latest posts

Lior Alexander ✓@LiorOnAI17 Sep

Snap just entered the agentic race. They just introduced SPECS Intelligence, a copilot that spans Mac, iPhone, and AR glasses. The hard part isn’t connecting email, calendar, and notes. It’s turning that firehose into a continuously updated model of your life. The system has

1:08

7K views · 64 likes · 14 reposts · 7 replies Open on X →

Lior Alexander ✓@LiorOnAI2 Sep

OpenAI's Astra AI uses a wild new reasoning trick called "recurrent depth." Normal models stack more layers to reason deeper. This one loops the same block over and over, feeding its hidden state back in. Picture a 2-trillion-parameter core looped 5 times. It behaves like a htt

7.5K views · 101 likes · 31 reposts · 15 replies Open on X →

Lior Alexander ✓@LiorOnAI1 Sep

Our 21st-century civilization runs on 20th-century physics. Physical Superintelligence (PSI) wants to restart the golden age of physics using AI. The last one gave us lasers, transistors, and nuclear energy, the entire foundation of modern life, from a few dozen minds over 10.8K views · 46 likes · 9 reposts · 6 replies Open on X →

Lior Alexander ✓@LiorOnAI15 Jul

New model from Thinking Machines: - Full weights available - Native text, image, and audio reasoning - 975B total parameters, 41B active - Mixture-of-Experts architecture - Up to 1M-token context window - Controllable reasoning effort - Lower token use at similar performance - 14.2K views · 101 likes · 24 reposts · 8 replies Open on X →

Lior Alexander ✓@LiorOnAI15 Jul

The mood of 20+ million developers now depends on how well Anthropic and OpenAI’s models perform that day. 5.1K views · 37 likes · 8 reposts · 12 replies Open on X →

Against accounts of the same size

5 posts from the last 90 days, next to the 100K–1M follower range. shown to more people than peers of the same size.

Median views7 546this account5 983median for 100K–1M

Reach, %6.44%this account1.49%median for 100K–1M

Engagement, %1.15%this account0.93%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	7 546	5 983	1.26×
Reach (views ÷ followers)	6.44%	1.49%	4.32×
Engagement rate	1.15%	0.93%	1.24×

Others in this range → Compare with another account → How these benchmarks are built →

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

5.1K15 Jul

14.2K

10.8K1 Sep

7.5K2 Sep

7K17 Sep

Last 5 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.15%15 Jul

0.94%

0.59%1 Sep

1.95%2 Sep

1.22%17 Sep

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

What the audience does

Likes57.0%349 in total

Reposts14.1%86 in total

Replies7.8%48 in total

Quotes0.8%5 in total

Bookmarks20.3%124 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.