RSI Is Closer Than People Think, Per Tae Kim

29 Jul 2026 · 31 min
TBPN

29 Jul 2026 · 31 min

0:00

In this hour‑long podcast, host Jordi Hays (with co‑host Speaker A) interviews AI analyst Tae Kim to dissect the current state of the AI market and its near‑term trajectory. Kim opens by noting his recent bullish calls on CPUs, memory, and NVIDIA, which coincided with a market rally. He then outlines the prevailing negative sentiment, attributing it to geopolitical shocks (Iran war), media‑driven FUD, and mixed signals from Meta’s reorganization and cap‑ex plans. The conversation shifts to open‑source dynamics, highlighting NVIDIA’s coordinated push against Anthropic and the mixed reactions from major players (Google, Amazon, Apple, OpenAI). Kim defends NVIDIA’s CUDA moat, emphasizing supply‑chain control, component pre‑paying, and co‑design advantages. A major theme is the looming compute crunch: SK Hynix, AMD’s Lisa Su, and hyperscaler growth all point to demand far outpacing supply, driving massive cap‑ex and potential compute hoarding. Kim argues that this demand fuels the rise of agentic AI and recursive self‑improvement (RSI), which he believes could materialize within 3‑9 months, dramatically increasing compute consumption. He discusses the KIMI model (2.8 trillion parameters) as a catalyst for new use‑cases, likening its impact to the earlier DeepSeq hype. The hosts also explore NVIDIA’s recent $50 billion Texas data‑center lease, interpreting it as a headline‑driven distraction rather than a financial burden, and they debate whether energy or chip bottlenecks will constrain growth. Finally, they consider NVIDIA’s expanding equity stakes in the AI ecosystem, suggesting the company may become a trillion‑dollar‑plus holder of strategic assets. Throughout, Kim balances optimism about exponential revenue growth for hyperscalers with caution about market over‑reaction to sensational headlines.

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