Ben observed that to make an AI product 10% better than before now requires spending 100% more tokens, meaning optimisation gains are shrinking.
Snapshot · God Mode Podcast
Ben observed that to make an AI product 10% better than before now requires spending 100% more tokens, meaning optimisation gains are shrinking.
Where this was said
At 46:00 · chapter starts 45:52
The Elon Corner is the episode's most speculative and entertaining section, combining confirmed calls with forward-looking chess moves. The $380 billion compute contract between Anthropic and SpaceX gets recapped first — a deal that now looks like both parties building leverage over each other. The dark fiber analogy resurfaces: unlike the 2000s telecom bust, every GPU in production today is being utilized, which is why the bubble thesis doesn't quite fit. SpaceX's acquisition of Cursor is flagged as a sleeper story: Rik has been getting near-unlimited auto-mode use from Cursor since the deal, routing through both the Composer model and Grok 4.5. The most intriguing speculation is Ben's 4D chess framing around Grok: if Elon open-sources Grok, it instantly makes every proprietary frontier model look overpriced by comparison. Grok is already one-tenth the cost of Claude and ChatGPT. Combined with Elon feeding all of SpaceX's engineering history into the next model, the hosts suggest Grok could become the default go-to model for anyone unwilling to pay frontier prices.
If Elon makes Grok open source, it could be a decisive competitive strike: Grok is already one-tenth the price of Claude and ChatGPT, and open-sourcing it would let anyone run it on commodity compute. Ben calls it a 'badass 4D chess move'.
Quickly forming opinions on how the Twitter algorithm and platform worked allowed the speaker to grow rapidly on the platform.
There are more than 90,000 Flock surveillance cameras currently in use around the United States.
A 2023 report estimated that 10 million Americans own Ring cameras, roughly 1 in 5 households having a video-enabled doorbell.
The ImageNet dataset collected 15 million images to drive machine learning, becoming a cornerstone of the modern AI revolution.
A Stanford graduate student benchmarked human performance on the ImageNet 1,000-category challenge at roughly 4% error rate, a figure AI surpassed by 2016.
From the 2012 ImageNet breakthrough, it took only about 3–4 more years for AI algorithms to surpass human performance in naming 1,000 object categories.
Flock's surveillance network scans more than 20 billion license plates per month across the United States.
OpenAI's Sora, released in January 2024, demonstrated AI's ability to generate realistic video from text prompts, marking a key milestone in video generation.
AlphaGo's Move 37 against Lee Sedol was a move that human Go masters had never considered, illustrating a unique form of AI creativity within constrained mathematical rules.
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