Reiner Pope ✓

@reinerpope · Mountain View, California · joined 02 Jul 2011

CEO and founder, @MatXComputing, developing high throughput chips tailored for LLMs

18 773Followers

458Following

185Posts total

3.6MViews on collected posts

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Reiner Pope ✓@reinerpope31 May

2^100 sounds impossibly large to count to. But $1B of chips and datacenter space and power can get you there in 2 years. 2^100 is only large if you don't allow parallelism. 8.7K views · 28 likes · 1 reposts · 8 replies Open on X →

Reiner Pope ✓@reinerpope30 May

there is a pretty (in?)famous story here from harvey friedman on ultrafinitism friedman goes up to esenin-volpin, a hardline ultrafinitist, after one of his lectures and then posits to him that if the number 2^100 doesn't exist, then surely he believes that somewhere on the line 32.8K views · 146 likes · 8 reposts · 6 replies Open on X →

Reiner Pope ✓@reinerpope20 Apr

@reinerpope @itsclivetime @dylan522p this was really good! also lmao that this is my living room 4.9K views · 42 likes · 0 reposts · 3 replies Open on X →

Reiner Pope ✓@reinerpope20 Apr

@itsclivetime @dylan522p https://t.co/MHlCX0XTe4 7.3K views · 18 likes · 0 reposts · 1 replies Open on X →

Reiner Pope ✓@reinerpope20 Apr

Intelligence per picojoule, with @itsclivetime and @dylan522p (0:00) Intro (1:22) What is codesign? (2:49) Codesign example: Swish vs ReLU (4:22) Are DeepSeek papers codesign? (6:45) Predicting where ML research will go (8:06) Should researchers hate your chips? (9:34) Can you h 148K views · 624 likes · 55 reposts · 12 replies Open on X →

Reiner Pope ✓@reinerpope15 Apr

I chatted with @ysmulki about MatX, chip design and where silicon designed for LLMs is headed (8:17) Tightly coupling SRAM and HBM on one chip (14:03) More MoE FLOPS, smaller KV cache load (16:08) Numerics: from 32-bit to 4-bit (19:02) Targeting both training and inference https 72.3K views · 326 likes · 46 reposts · 16 replies Open on X →

Reiner Pope ✓@reinerpope24 Feb

@reinerpope Congrats!! 2.8K views · 9 likes · 0 reposts · 0 replies Open on X →

Reiner Pope ✓@reinerpope24 Feb

@reinerpope If HBM is used for long-context support, how will this chip deliver low latency and high memory bandwidth for agentic reasoning workloads with many tokens? If maximizing SRAM with a lot of HBM is done here, I don't know how this stands out from Sambanova. As the tot 19.7K views · 17 likes · 0 reposts · 1 replies Open on X →

Reiner Pope ✓@reinerpope24 Feb

We’re building an LLM chip that delivers much higher throughput than any other chip while also achieving the lowest latency. We call it the MatX One. The MatX One chip is based on a splittable systolic array, which has the energy and area efficiency that large systolic arrays 3.1M views · 2.3K likes · 200 reposts · 121 replies Open on X →

Reiner Pope ✓@reinerpope24 Feb

Read more in @business: https://t.co/xtyQnYE1xl 56.8K views · 109 likes · 5 reposts · 0 replies Open on X →

Reiner Pope ✓@reinerpope24 Feb

An AI chip startup founded by two Google alumni has raised more than $500 million in a new round to compete with Nvidia https://t.co/TisTEZIRLE 189.1K views · 289 likes · 30 reposts · 12 replies Open on X →

Reiner Pope ✓@reinerpope5 Oct 2025

We serialize key/value maps and send them over the Internet or write them to disk all the time. Why don't we keep them in hashmap layout on the wire, so the receiver doesn't have to rebuild the table? https://t.co/1zmJD59OpE 2.7K views · 17 likes · 1 reposts · 0 replies Open on X →

Reiner Pope ✓@reinerpope4 Oct 2025

Sometimes a more complex algorithm actually *is* faster in practice. This seems to be true of cuckoo hashing, provided you engineer it carefully. https://t.co/smB0Jx2f3w 4.5K views · 22 likes · 2 reposts · 1 replies Open on X →

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

4.5K4 Oct

2.7K5 Oct

189.1K24 Feb

56.8K

3.1M

19.7K

2.8K

72.3K15 Apr

148K20 Apr

7.3K

4.9K

32.8K30 May

8.7K31 May

Last 13 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.58%4 Oct

0.67%5 Oct

0.18%24 Feb

0.20%

0.09%

0.32%

0.55%15 Apr

0.47%20 Apr

0.26%

0.92%

0.50%30 May

0.44%31 May

Reactions — likes, reposts, replies and quotes — divided by views.

What the audience does

Likes55.2%3 941 in total

Reposts4.9%348 in total

Replies2.5%181 in total

Quotes1.7%118 in total

Bookmarks35.7%2 549 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.

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Growth & engagement

Views per post

Engagement rate per post

What the audience does

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