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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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
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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
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@reinerpope @itsclivetime @dylan522p this was really good!
also lmao that this is my living room
4.9K views · 42 likes
· 0 reposts · 3 replies
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@itsclivetime @dylan522p https://t.co/MHlCX0XTe4
7.3K views · 18 likes
· 0 reposts · 1 replies
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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
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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
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@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
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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
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Read more in @business:
https://t.co/xtyQnYE1xl
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· 5 reposts · 0 replies
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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
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· 30 reposts · 12 replies
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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
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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
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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%
0.09%
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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