📊 Data Economy
2026-09-07
2 min read
9 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (AKT, IO, LPT, SN18, SN41, SN55). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📌 Research
2026-09-06
6 min read
We run a DePIN data business and a small formal-methods and number-theory lane. This is the honest ledger of the second one: an Erdős problem where we were right and second, a game-theory case we verified on our own hardware, a Riemann route that produced two measured laws and no progress on the conjecture, and a proof corpus where machine-checking refuted five of our own stated properties.
researcherdosriemann
📊 Data Economy
2026-09-06
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 10 of the networks we read first-party (AKT, IO, PLANCK, SN103, SN117, SN32). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📌 Research
2026-09-05
1 min read
n₀(5)=14, n₀(6)=16, n₀(11)=27 — correct, machine-checked, and seven weeks late. What we did, what M. Thiim did first, and why we published anyway.
erdoscombinatoricslean4
📊 Data Economy
2026-09-05
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (IO, KYVE, PLANCK, SN103, SN117, SN13). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📊 Data Economy
2026-09-04
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 9 of the networks we read first-party (AKT, DVPN, IO, SN103, SN11, SN117). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📊 Data Economy
2026-09-03
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (AKT, IO, IPFS, SN117, SN55, SN66). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📊 Data Economy
2026-09-02
2 min read
9 first-party metrics moved more than 2% in the last 24 hours, on 6 of the networks we read first-party (AKT, IO, IPFS, SN103, SN97, TAO). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📊 Data Economy
2026-09-01
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 9 of the networks we read first-party (AKT, IO, IPFS, LPT, SCP, SN41). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📊 Data Economy
2026-08-31
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 9 of the networks we read first-party (AKT, IO, IPFS, SN32, SN41, SN76). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
📊 Data Economy
2026-08-30
1 min read
10 first-party metrics moved more than 2% in the last 24 hours, on 8 of the networks we read first-party (AKT, IO, IPFS, NODL, SN21, SN82). Every row carries the exact metric name, the upstream source and its as_of stamp, so you can re-read it yourself.
depinsupplytelemetry
💡 Insights
2026-08-29
3 min read
The Akash GPU utilisation figure circulating in DePIN research traces to a single blog post from October 2024 that says 74% in its title and 79% in its body, with no source and no denominator. Akash's own API returns 56.6% today. Here is the full daily series and the one command that checks it.
depinakashgpu