Zephyr

@zephyr_z9 on X

Writes about AI and Revenue. 65% of posts open with an observation. A typical post reaches 329 likes.

Remix their style

Posts: 17
Likes: 11K
Typical: 329
Best: 3.7K

What they write about

AI: 82%
Revenue: 24%

How they open

observation: 65%
number: 24%
curiosity gap: 6%

Every post of theirs in the library

Zephyr@zephyr_z9

OpenAI cut Luna prices from $1/$6 to $0.2/$1.20 A 5x price cut OpenAI begins the price war, with the goal of crushing the Chinese players Not going after Anthropic's margins yet

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Zephyr@zephyr_z9

"Sam Altman believes OpenAI will have an internal system that will qualify as AGI by the end of 2026." So, 10T-15T is all u need for AGI This also means that a bunch of companies will have an AGI-level model by H1 2027 in the US & China

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Zephyr@zephyr_z9

The reason why I'm saying all this is becuz the whale is processing 600B tokens & outputting 150B tokens per day on 300 H800 nodes (2400 H800s) 100x (240K) will get u 60T tokens & output of 15T tokens per day The world does not have this high AI demand

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Zephyr@zephyr_z9

So Meta, Google, Anthropic, SpaceX, and OpenAI will raise around $350B-$400B from the public markets in the next 9-12 months At this rate, Amazon & Microsoft will join the party too We might even see $550B-$600B raised from the public markets

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Zephyr@zephyr_z9

Amazon/AWS being a defence contractor was the main reason Based on what Axios has reported, USG didn't want the model to be released publicly Ant refused and they were/are using AWS infra to deploy it If a major cybersecurity incident occured, then Amazon would get sued

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Zephyr@zephyr_z9

GLM 4.7 was 32B active, while GLM 5 is 40B active Inference is also cheaper due to DSA Meanwhile, they have increased the price substantially to increase gross margins As a proud Zhipu shareholder since IPO, I approve

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Zephyr@zephyr_z9

Wenfeng is devious China can meet all its AI demands in less than 250K GPUs And yes Jevon's paradox got fucked in the ass

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Zephyr@zephyr_z9

Nobody will buy Chinese EUV machines (outside China) due to low throughput and NatSec reasons The story isn't "ASML lost its monopoly" It's about Huawei or Cambricon being able to get their 2/3nm AI GPUs fabbed at a higher cost (rn they can't get it)

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Zephyr@zephyr_z9

Well, Nvidia has to sell 10M chips to lots of companies next year I'm pretty sure OpenAI will be super satisfied if 25%-35% of the compute deployed by them uses Jalapeno and its successors in 2028 and beyond They don't need/have to scale like Nvidia/Rubin

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Zephyr@zephyr_z9

2.5x speedup and 6x price increase Small batch size Total throughput of the system takes a giant hit on increasing tokens/user/sec

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Zephyr@zephyr_z9

$38 Billion in operating profit At this rate, Samsung might hit $240 Billion in operating profit this year The implications for Korean Won will be very interesting

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Zephyr@zephyr_z9

This is going to have some very profound effects E-Commerce and the Gig Economy have generated lots of jobs globally in the last 20 years Self-driving cars, automated warehouses, and drone deliveries will reverse that

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Zephyr@zephyr_z9

Hyperscalers are now acquiring energy infra companies We are in uncharted territory Hyperscalers going for more vertical integration 🤔🤔 I expect other hyperscalers to go for some acquisitions as well

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Zephyr@zephyr_z9

"Apple’s in-house AI server chips are expected to enter mass production in 2H26, with its own data centers planned to come online in 2027. This likely means Apple’s demand for on-device AI could start to grow more meaningfully from 2027 onward." Very important point

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Zephyr@zephyr_z9

"new robot ban" Basically the same approach that the FCC took with Chinese drones U can import all the current Unitree robots, but new robot models are not allowed

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Zephyr@zephyr_z9

I will certainly own Anthropic stock Zhipu will probably IPO next year Minimax, Moonshot, OpenAI, and Anthropic will probably IPO in the 2027-2029 window Lots of foundation model labs will be available

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Zephyr@zephyr_z9

OK. But why was Jensen pumping 80B-100B few weeks ago?? More Jensen Math/Finesse? "The total investment required for each gigawatt of AI Data center capacity has risen from $30B five years ago to around $60B today."

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