Episode Details
Back to Episodes“My Assessment of Compute Verification in Plan A (+ open questions)” by jacob_drori
Description
Overview
These are my non-expert notes on the compute verification section of AIFP's Plan A. I cover interconnect limits, memory wipes, network taps + replay, and ZKPs. For the most part, the sections can be read independently. I restrict my attention to inference-only verification: ensuring that compute is used for inference, not training. For each method suggested by AIFP, I ask:
- How much can it slow down training?
- How much overhead does it add to inference?
- What sensitive information does it require adversaries to share with each other?
AIFP estimates that the fraction of the world's compute that is unmonitored might be kept as low as 0.1% (this is the optimistic, low end of their 80% confidence interval). So my target for inference-only verification is to slow down training by 1000 times – any more hits diminishing returns as unmonitored compute dominates – with much less than 1000x overhead on inference and little sharing of secrets.
I won’t discuss how much a 1000x reduction in effective training compute would actually benefit humanity. The answer depends greatly on algorithmic progress rates; I wish labs would publish the rates they’re seeing internally.
Interconnect Limits
In a datacenter, accelerator racks are [...]
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Outline:
(00:12) Overview
(01:35) Interconnect Limits
(05:09) Memory Wipes
(07:16) Network Taps and Replay
(08:29) Trusted Replay
(12:04) Untrusted Replay
(14:02) Zero-knowledge Proofs
(17:02) Appendix: Notable Omissions
The original text contained 8 footnotes which were omitted from this narration.
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First published:
July 30th, 2026
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Narrated by TYPE III AUDIO.
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