▼Compute Scarcity Sets the Pace of AI Rollout

Score history

Daily conviction score, 0 to 100. Higher means the thesis is more strongly corroborated.

Now 43 · -2 since Aug 27 · ranged 41 to 43

Showing the last few days. Unlock full score history.

Why the conviction moved

• Aug 25
  Strengthened +2

  Nvidia's Groq 3 LPX enters full production with cloud provider Nebius named as first customer and deployment promised before the end of 2026, i.e. allocation of a scarce new rack class is being announced customer-by-customer. Who gets the first racks, and when, again sets what agent products can ship.

• Aug 25
  Strengthened +3

  Xiaomi's AI Cube runs entirely on three in-house Xring chips rather than imported accelerators, with 1.22 TB/s near-memory bandwidth doing the work that HBM-rich data-center parts normally do. Domestic silicon aimed at local inference is a route around allocation and export limits rather than a queue for them.

• Aug 24
  Strengthened +3

  Microsoft has taken delivery of the first production Vera Rubin NVL72 racks as Nvidia declares full production, with Vera CPUs paired to Rubin accelerators carrying up to 288GB HBM; the next chip generation reaching a hyperscaler first is itself evidence that accelerator supply timing continues to gate who can expand AI capacity.

Showing the last 2 days. Unlock the full record.

Source trail

• Supporting · August 25, 2026

  Nvidia Puts Groq 3 LPX Into Full Production and Claims 30x More Agent Throughput Per Megawatt

  Nvidia's Groq 3 LPX enters full production with cloud provider Nebius named as first customer and deployment promised before the end of 2026, i.e. allocation of a scarce new rack class is being announced customer-by-customer. Who gets the first racks, and when, again sets what agent products can ship.

  NVIDIA Blog (Groq 3 LPX, NVLink Fusion, Spectrum-X)

• Supporting · August 25, 2026

  Xiaomi Shows a 150-Watt Desktop That Runs 120-Billion-Parameter Models on Three In-House Chips

  Xiaomi's AI Cube runs entirely on three in-house Xring chips rather than imported accelerators, with 1.22 TB/s near-memory bandwidth doing the work that HBM-rich data-center parts normally do. Domestic silicon aimed at local inference is a route around allocation and export limits rather than a queue for them.

  AI ML Big Data (Telegram)