QFM041: Machine Intelligence Reading List - November 2024

Source: Photo by julien Tromeur on Unsplash

This month's edition of the Machine Intelligence Reading List starts with: Graph-based AI model maps the future of innovation that explores an approach leveraging category theory to identify creative connections across disciplines. This technique not only enhances material science but also underscores AI's growing ability to support interdisciplinary discovery. Similarly, Archetypes of LLM apps categorises large language model (LLM) applications, offering insights into how foundational and advanced technologies, like retrieval-augmented generation and autonomous agents, are reshaping industries by improving efficiency and decision-making.

The concept of accessibility and ease of implementation emerges as a recurring theme. Agentic Websites and Apps demonstrates how no-code platforms enable non-technical users to harness AI capabilities for dynamic, personalised applications, streamlining workflows such as on-boarding and sales automation. This trend of lowering barriers is echoed in We can all be AI engineers – and we can do it with open source models, which argues for the democratisation of AI engineering through open-source models and simple development tools. Together, these articles reveal a shift towards making sophisticated AI tools accessible to a broader audience.

The practical implications of AI in professional settings are also examined. How AI-Powered Vertical SaaS Is Taking Over Traditional Enterprise SaaS highlights the growing importance of specialised, industry-specific SaaS platforms that leverage AI to deliver tailored, efficient solutions. Similarly, AI is the Future of Development, But Not as I Imagined offers a personal perspective on AI's transformative role in software development, moving beyond automation to augment strategic thinking and problem-solving.

The infrastructure supporting AI-driven applications continues to evolve. Model Context Protocol (MCP) Quickstart introduces a universal framework for integrating AI with local and remote resources, addressing inefficiencies in early large language models by offering a standardised protocol for managing context and tool usage. Meanwhile, OCR: Document to Markdown illustrates how specific tools are adapting to niche needs, such as converting images into structured markdown for seamless digitisation.

Finally, the broader societal and economic implications of AI are considered in Artificial Intelligence and the Future of Work. This report examines how generative AI technologies like ChatGPT are reshaping labour markets, balancing opportunities for increased productivity with concerns about job displacement and inequality.

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

QFM041: Machine Intelligence Reading List - November 2024

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