Signal to BuildSIGNAL TO BUILD中文Owner sign in ↗Find the mechanisms, cases and conditions in each episode. Start with a topic, follow a guest, or read chronologically to see how perspectives change.
Dates refer to original episode releases. An episode may have multiple topics; roles and claims retain their historical context.
Guests / narrator：莫傑麟
Asked whether AI has a bubble, the opening answer is yes. The ensuing conversation repeatedly distinguishes technical value, expectations inside prices, infrastructure payback, who ultimately receives money and whether founders survive until another financing round.
Guests / narrator：莫傑麟
Listen: 00:59–09:27. The guest recalls monthly token consumption growing more than 20% over the previous month, without supplying the statistical institution, sample, or consistent measurement definition. The number explains his starting observation; it is not a verified industry growth rate.
Guests / narrator：莫傑麟
After reaching the United States, Qu noticed rapid changes in how people discussed Chinese and American assets. He asks why two years of pessimism could reverse suddenly and how long new optimism might last.
Roles reverse in this episode: Mo asks and Qu mainly answers. Qu favors participating early while warning against sprinting just after the start. These positions are compatible. Time, attention and learning can receive serious commitment while money, staffing and scale require staged evidence.
Guests / narrator：莫傑麟
The episode places Sora’s first demonstrations within a larger question: why can compute and model narratives advance before many mature applications exist? The guests distinguish technical progress, competitive position and application demand.
Guests / narrator：莫傑麟
The conversation begins with a contrast: people sound pessimistic while working harder. Perhaps effort has not disappeared; familiar rewards simply arrive more slowly. If so, the task extends beyond changing mood to recognizing feedback cycles, revising evaluation and preparing capabilities.