Rephonic
Artwork for SemiAnalysis Weekly
NVIDIA
Artificial Intelligence
TSMC
GPU Clusters
AI Datacenters
Memory (DRAM, HBM)
Claude Code
Inferencex
Vera Rubin NVL72
Chipbook
Goodput
Torchpass
Electricity Prices
Memory (dram/semiconductor Memory)
Semiconductors
Memory
AMD
Co-Packaged Optics
Torch FT

Everything semiconductors and AI

Covering the spectrum

PublishesWeeklyEpisodes12Founded3 months ago
Number of ListenersCategory
Business

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Artwork for SemiAnalysis Weekly

Latest Episodes

Jordan Nanos (@JordanNanos), Howie, and Myron Xie break down the economics of Cerebras's IPO on the eve of their public debut, examining their OpenAI and Amazon deals that have shifted the company away from Middle Eastern investor concentration towar... more

OpenAI was in serious trouble at the beginning of this year. Anthropic's Claude Opus 4.5 release had triggered a wave of developers to start using Claude Code, pushing Anthropic's revenue past OpenAI's on a like-for-like basis by April. OpenAI's GPT ... more

This episode features Jordan Nanos (@JordanNanos) and Daniel Nishball (@dnishball) breaking down the economics of GPU clusters through real-world data and experience. Joined with Kang Wen Cheang and Zane Fong, the team discussed moving beyond theoret... more

This week the team from ChipBook (formerly Chips & Wafers) joins. Jordan Nanos talks with Chaim Eisenberg and Simi Sherman as they explore how they build the ChipBook with open source data, and how that drives investment decisions. This episode dives... more

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Recent Guests

Chaim Eisenberg
ChipBook team member at SemiAnalysis
ChipBook / Semi Analysis
Episode: Ep. 009 - Using Open Source Data To Drive Investment Decisions (ChipBook) | Chaim Eisenberg, Simi Sherman, Jordan Nanos
Simi Sherman
ChipBook team member at SemiAnalysis
ChipBook / Semi Analysis
Episode: Ep. 009 - Using Open Source Data To Drive Investment Decisions (ChipBook) | Chaim Eisenberg, Simi Sherman, Jordan Nanos
Daniel Nishball
Co-host, AI researcher and engineer
SemiAnalysis
Episode: Ep. 008 Claude Code Psychosis: How SemiAnalysis Is Token Mogging Meta | Dan Nishball, Sam Harshe, Jordan Nanos
Sam Harshe
Co-host, AI researcher and engineer
SemiAnalysis
Episode: Ep. 008 Claude Code Psychosis: How SemiAnalysis Is Token Mogging Meta | Dan Nishball, Sam Harshe, Jordan Nanos
Jeremie Eliahou Ontiveros
Lead data-center energy modeler for SemiAnalysis
SemiAnalysis
Episode: Ep. 004 - The Impact of AI Datacenters On Consumer Power Costs (Datacenter, Energy) | Jeremie Eliahou Ontiveros, Jordan Nanos, Doug O'Laughlin
Cam Quilici
Member of InferenceX team
InferenceX
Episode: Ep. 002 - InferenceX 2.0 Release (Technical Staff) | Cam Quilici, Bryan Shan, Doug O'Laughlin, Jordan Nanos
Bryan Shan
Member of InferenceX team
InferenceX
Episode: Ep. 002 - InferenceX 2.0 Release (Technical Staff) | Cam Quilici, Bryan Shan, Doug O'Laughlin, Jordan Nanos

Host

Jordan Nanos
Host of SemiAnalysis Weekly; Senior analyst/engineer focused on memory, AI compute, and semiconductor industry dynamics.

Chart Rankings

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Apple Podcasts
#94
Israel/Business
Apple Podcasts
#201
Hong Kong/Business
Apple Podcasts
#245
South Korea/Business

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Ep. 002 - InferenceX 2.0 Release (Technical Staff) | Cam Quilici, Bryan Shan, Doug O'Laughlin, Jordan Nanos
Q: How do these optimizations translate to real-world costs and deployment?
MTP and related optimizations significantly reduce cost per million tokens and increase tokens per second per user, enabling cheaper operation and potential end-user savings, while still allowing benchmarking to reflect real-world configurations, such as multi-node setups and mixed hardware fleets.
Ep. 002 - InferenceX 2.0 Release (Technical Staff) | Cam Quilici, Bryan Shan, Doug O'Laughlin, Jordan Nanos
Q: Why is there a 2.0 release and what are the major changes from 1.0 to 2.0 moving to InferenceX?
2.0 expands beyond single-node benchmarks to include disaggregated pre-fill, wide expert parallelism, speculative decoding, and broader hardware support (GB200/GB300) with multi-node testing, aiming for a more nuanced, production-like view of frontier inference and improved throughput and cost metrics.

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Frequently Asked Questions About SemiAnalysis Weekly

What is SemiAnalysis Weekly about and what kind of topics does it cover?

A deep-drequent look at the intersection of semiconductors, AI compute, data center economics, and grid infrastructure. The episodes emphasize memory scarcity, AI model deployment, and the evolving economics of AI hardware, with frequent focus on memory pricing, data-center power, and the demand drivers behind hyperscalers and enterprises. Discussions often blend technical detail with real-world implications for pricing, procurement, and policy-level macro effects, including energy markets, grid design, and industry leadership shifts. A recurring strength is the ability to translate dense hardware and energy topics into practical implications for operators, utilities, and software/systems teams, punctuated by hands-on case studies, dashboar... more

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SemiAnalysis Weekly launched 3 months ago and published 12 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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Recent guests on SemiAnalysis Weekly include:

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2. Simi Sherman
3. Daniel Nishball
4. Sam Harshe
5. Jeremie Eliahou Ontiveros
6. Cam Quilici
7. Bryan Shan

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