According to @karpathy, text diffusion for language can be implemented with a vanilla transformer using bidirectional attention that iteratively re-masks and re-samples all tokens on a noise schedule. Source: @karpathy. He states diffusion is the pervasive generative paradigm in image and video, while autoregression remains dominant in text and audio shows a mix of both. Source: @karpathy. He adds that removing heavy formalism reveals simple baseline algorithms, with discrete diffusion closer to flow matching in continuous settings. Source: @karpathy. He explains that autoregression appends tokens while attending backward, whereas diffusion refreshes the entire token canvas while attending bidirectionally. Source: @karpathy. He notes bidirectional attention yields stronger language models but makes training more expensive because sequence dimension parallelization is not possible. Source: @karpathy. He suggests it may be possible to interpolate or generalize between diffusion and autoregression in the LLM stack. Source: @karpathy. For traders, the actionable takeaway is the compute cost trade-off of bidirectional text diffusion versus autoregression, which directly affects training efficiency assumptions. Source: @karpathy.

According to @karpathy, earlier predictions that computer vision would quickly eliminate radiology jobs have not materialized, with the field growing rather than shrinking. Source: @karpathy on X, Sep 25, 2025. According to @karpathy, the reasons include narrow benchmarks that miss real-world complexity, the multifaceted scope of radiology beyond image recognition, deployment frictions across regulation, insurance and liability, and institutional inertia. Source: @karpathy on X, Sep 25, 2025. According to @karpathy, Jevons paradox applies as AI tools speed up radiologists, increasing total demand for reads rather than reducing it. Source: @karpathy on X, Sep 25, 2025. According to @karpathy, AI is likely to be adopted first as a tool that shifts work toward monitoring and supervision, while jobs composed of short, rote, independent, closed, and forgiving tasks are more likely to change sooner. Source: @karpathy on X, Sep 25, 2025. For traders, this framing highlights gradual AI integration and expanding workloads in regulated, high-risk domains, a narrative relevant to AI-linked equities and AI-themed crypto projects tied to compute utilization. Source: @karpathy on X, Sep 25, 2025. Full post reference is the Works in Progress article shared by @karpathy. Source: @karpathy on X, Sep 25, 2025.

According to Andrej Karpathy, participating in a vibe coding hackathon enabled rapid development of a web app with integrated authentication, payments, and deployment, showcasing how modern frameworks streamline full-stack builds for non-web developers (source: @karpathy, Twitter, May 1, 2025). This highlights the trading advantage for crypto projects and tokens related to no-code, low-code, and Web3 infrastructure, as faster build cycles can lead to more rapid project launches and ecosystem growth.