SemiAnalysis (@SemiAnalysis

SemiAnalysis

2,443 posts

SemiAnalysis

@SemiAnalysis_

Joined January 2024

SemiAnalysis
@SemiAnalysis_
12h
SLOP ALERT: Claude Code UI is complete slop. In the in-app file tree, when u click on a .png, it opens it as a base64-encoded file instead of rendering the image. We’d rather Anthropic not release the desktop app than release an L desktop App. Tons of bugs.
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SemiAnalysis
@SemiAnalysis_
16h
Replying to @SemiAnalysis_
Obviously this is way worse than API overall. However, explicitly nerfing subscriptions leads to huge public backlash, and the rapidly falling cost of intelligence means you'll be able to profitably serve Opus 4.8 level models for $20/month in the near future. We therefore think
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SemiAnalysis
@SemiAnalysis_
16h
Replying to @SemiAnalysis_
The margin on a subscription plan is a function of the average utilization. If we assume both companies have 75% API gross margins, this results in the following subscription margins. (3/4)
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SemiAnalysis
@SemiAnalysis_
16h
Replying to @SemiAnalysis_
Recently, we purchased one of each Anthropic/OpenAI subscription plan and randomly ran long horizon coding tasks until we exhausted the weekly limit. It's widely believed that a $200/month plan maxes out at ~$2000/month worth of tokens (assuming API pricing). However, we found
1.2M
SemiAnalysis
@SemiAnalysis_
16h
What's the better business model for an AI lab, subscription or API? (1/4)🧵
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SemiAnalysis
@SemiAnalysis_
20h
DeepSeek is going heavy-asset. On June 9, the company posted an opening for IDC planning engineers, a role explicitly scoped to the design and delivery of MW-to-GW scale infrastructure. It follows April's hiring of data center O&M engineers in Ulanqab, Inner Mongolia. Taken
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SemiAnalysis
@SemiAnalysis_
23h
Replying to @SemiAnalysis_
Full breakdown with Jordan Nanos (@JordanNanos), Jeremie Eliahou Ontiveros (@JeremieEO), Joey Brookhart (@SaasquatchC), and Crystal Huang (@egg1459) on SemiAnalysis Weekly:
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SemiAnalysis
@SemiAnalysis_
23h
AI market beat 2025 expectations by massive margins. But here's what's wild about the composition of this beat.
00:00
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SemiAnalysis
@SemiAnalysis_
Jun 10
HISTORY LESSON: In 1968 the US, USSR, UK, France, and China signed the Nuclear Non-Proliferation Treaty, declaring nuclear weapons too dangerous for any more countries to build. All five already had them. Everyone else had to submit to inspections while the cohort pinky-promised
NomoreID
@Hangsiin
Jun 9
When Fable 5 is used for frontier LLM development, it does not notify the user and instead limits the model’s capabilities through methods such as prompt modification, steering vectors, and PEFT. Anthropic estimated that this would affect approximately 0.03% of traffic.
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SemiAnalysis
@SemiAnalysis_
Jun 10
Replying to @SemiAnalysis_
And every next-gen win in inference is a datacenter win. CPO, copper backplanes, NVL scale-up domains, better pJ/bit, better perf/watt — none of that ships in a laptop chassis. The steel mill gets cheaper per ton every year. The village furnace can only get so hot! (4/4)
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SemiAnalysis
@SemiAnalysis_
Jun 10
Replying to @SemiAnalysis_
Inference Production is likely a more scale oriented game than even steel manufacturing. Bigger models push capability frontiers (Opus 4.5 made Agentic possible), and local LLMs create and serve tokens at a scale that is unlikely to be commercially viable. (3/4)
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SemiAnalysis
@SemiAnalysis_
Jun 10
Replying to @SemiAnalysis_
Mao made every village build a steel furnace to out produce the UK's raw steel outputs. Farmers melted tools into brittle pig iron that was unusable. Meanwhile steel mills cranked away. Steel and Tokens have massive economies of scale. Today that is akin to buying M5 macs for
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SemiAnalysis
@SemiAnalysis_
Jun 10
Local LLMs are the Great Leap Forward for Inference. Every laptop is it's own datacenter, sovereignty over your own tokens, and the people can seize the means of token generation. And that's why it's destined for poor results. (1/4)🧵
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