QFM049: Machine Intelligence Reading List - January 2025

Source: Photo by Michael Dziedzic on Unsplash

QFM049: Machine Intelligence Reading List January 2025

This month’s Machine Intelligence Reading List tracks the ongoing realignment of the AI landscape, with a particular focus on employment shifts, the maturation of AI development practices, and the increasing presence of open-source challengers. It also highlights the philosophical and structural consequences of AI’s advance, both in the workforce and the economy.

AI’s effect on employment remains a focal point, with a World Economic Forum survey indicating that 41% of employers worldwide anticipate reducing staff due to AI by 2030. This aligns with concerns about automation replacing specific job categories while potentially creating new ones, though which industries will experience net growth remains uncertain. Similarly, Dustin Ewers argues that AI will not eliminate software development as an industry but rather reshape it, making development more efficient and shifting the skills in demand.

Open-source AI development continues to disrupt established players, particularly in the case of DeepSeek, a Chinese AI company whose open-source models rival OpenAI’s best at significantly lower costs. The rapid rise of DeepSeek has already caused shifts in market valuations, with Nvidia’s stock price taking a hit due to concerns about cheaper alternatives disrupting AI chip demand. Meanwhile, Berkeley researchers have demonstrated that replicating state-of-the-art AI models at a fraction of the cost is feasible, suggesting a broader shift towards commoditised AI.

On the technical front, infrastructure and platform design for AI systems remain key areas of discussion. Chip Huyen’s overview of generative AI platforms details how modular architectures, caching, and model orchestration ensure scalable, efficient AI applications. The AI Video Starter Kit offers a practical example, providing an open-source toolkit for integrating AI-driven video capabilities into web applications. Elsewhere, a shift toward AI-assisted software development is evident in the rise of Chat-Oriented Programming (CHOP), a methodology that re-frames coding as an interactive, AI-assisted process rather than a static workflow.

Beyond technical considerations, AI’s role in strategic decision-making and economic positioning is a recurring theme. Lukas Petersson’s two-part series, “AI Founder’s Bitter Lesson” and “No Power”, explores how vertical AI solutions struggle to establish defensible market positions, while horizontal AI models benefit from greater flexibility and scalability. This echoes Hamilton Helmer’s “7 Powers” framework, where only a few AI-driven businesses establish durable competitive advantages. Meanwhile, the strategic implications of AGI are explored in “Capital, AGI, and Human Ambition”, which questions whether advanced AI will entrench existing power structures or redistribute resources through mechanisms like universal basic income.

Finally, the role of AI in human creativity and cognitive augmentation remains an area of active debate. Brian Eno offers a critique, arguing that AI-generated content lacks the intentionality and provenance of human creativity. This stands in contrast to works like “The day I taught AI to read code like a Senior Developer”, which demonstrates how AI can enhance human expertise rather than replace it.

As always, the Quantum Fax Machine Propellor Hat Key will guide your browsing. Enjoy!

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Regards, M@

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Originally published on quantumfaxmachine.com and cross-posted on Medium.

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