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The Software Architects' Newsletter
November 2024
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Welcome to the InfoQ Software Architects' Newsletter! We bring you essential news and experience on emerging patterns and technologies from industry peers each month.

This month, we focus on "The AI Shift: Evolving Roles for Software Architects". Roles, patterns, and practices from this topic span the entire "diffusion of innovation" graphs in our 2024 reports: InfoQ Software Architecture and Design Trends Report and InfoQ AI, ML, and Data Engineering Trends Report. We also cover this topic in our Generally AI podcast series with Anthony Alford and Roland Meertens.

Key challenges remain. Large language models (LLMs) have become a common feature in nearly every corner of the industry, but significant innovation opportunities remain to take LLMs beyond glorified chatbots. AI safety and security will also continue to be important in the overall management lifecycle of language models.

News

QCon SF 2024 - Why ML Projects Fail to Reach Production

At QCon SF 2024, Wenjie Zi of Grammarly presented the challenges inherent in machine learning projects. She began by citing daunting statistics: historical studies show failure rates as high as 85%, with recent research indicating little improvement. This high failure rate highlights a significant issue in the field: despite advances in AI technology, applying these technologies effectively in business contexts remains a substantial challenge.

Techniques and Trends in AI - Powered Search by Faye Zhang at QCon SF

At QCon SF 2024, Faye Zhang gave a talk titled Search: from Linear to Multiverse, covering three trends and techniques in AI-powered search: multi-modal interaction, personalization, and simulation with AI agents.

Moumita Bhattacharya also spoke at QCon SF about state-of-the-art search and ranking systems at Netflix. She gave an overview of the typical structure of these systems and followed with a deep dive into how Netflix created a single combined model to handle both tasks.

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Timescale Bolsters AI - Ready PostgreSQL with pgai Vectorizer

Timescale recently expanded its PostgreSQL AI offerings with pgai Vectorizer. This update enables developers to create, store, and manage vector embeddings alongside relational data without needing external tools or additional infrastructure.

Meta Releases NotebookLlama: Open-Source PDF to Podcast Toolkit

Meta has released NotebookLlama, an open-source toolkit designed to convert PDF documents into podcasts, providing developers with a structured, accessible PDF-to-audio workflow.

As an open-source alternative to Google's NotebookLM, NotebookLlama guides users through a four-step process that converts PDF text into audio content without needing prior experience with large language models (LLMs) or audio processing. The toolkit offers a practical way for users to experiment with LLMs and TTS models to create conversational, audio-ready content.

Architectural Intelligence - The Next AI

Thomas Betts recently summarized his presentation from the iSAQB Software Architecture Gathering 2024, Architectural Intelligence - The Next AI on InfoQ. He argued that architects can augment their decision-making and communication skills with AI, leading to better design and understanding among stakeholders.

Betts emphasized that architects must separate AI hype from real software and design systems based on tangible components such as LLMs, not a vague vision of AI. Determining how, where, and when to use AI elements comes down to traditional trade-off analysis.

First, determine if AI software is a good fit for an application. Like any technology, AI can be used creatively but inappropriately. Second, decide how to use AI effectively; consider the trade-offs of using an AI-as-a-service API versus self-hosting.

Sponsored

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Case Study

Being a Responsible Developer in the Age of AI Hype

Justin Sheehy's keynote at the InfoQ Dev Summit in Boston, Being a Responsible Developer in the Age of AI Hype, tackled the growing influence of AI and the responsibility developers hold in shaping its trajectory. Sheehy urged software architects to engage with perspectives outside their field, emphasizing that developers wield significant power through their decisions. As the hype around AI continues to grow, Sheehy called for developers to navigate the current landscape with clarity, ethical awareness, and accountability to ensure their choices benefit society and avoid harm.

Sheehy first delved into the mechanics of AI, particularly the large language models (LLMs) like GPT-4, emphasizing their foundational purpose: predicting the next token in a sequence. While LLMs exhibit remarkable capabilities, they lack understanding, reasoning, and consciousness. Sheehy explained that these systems operate purely on probabilistic models of past data, making them powerful but fundamentally limited tools. The persistent misunderstanding of their capabilities - often framed as "sparks of general intelligence"-has fueled unrealistic expectations. He cautioned against conflating text synthesis with intelligence or meaning and stressed the importance of clear-eyed evaluation over sensationalism.

Developers using AI systems must approach them with a deep sense of responsibility, Sheehy advised. He outlined several practical guidelines: avoid sharing sensitive data with AI services, exercise caution when incorporating AI-generated content into products, and prioritize transparency about how AI is used. Sheehy highlighted ethical concerns tied to the training and operation of these systems, including their reliance on low-paid human labor and the biases embedded in training datasets. He also urged developers to question the growing trend of "AI washing", where products are labeled "AI-powered" for marketing purposes, often at the expense of meaningful innovation.

Sheehy concluded by addressing the need for accountability and alignment in AI development. Developers must take responsibility for the consequences of AI-driven decisions, ensuring their systems are helpful, honest, and harmless-Anthropic's "3 H's" framework. While true AGI remains speculative, Sheehy argued that ethical considerations should guide today's AI practices. He encouraged developers to focus on creating solutions to real problems, communicate honestly about their capabilities, and minimize harm. By grounding their work in these principles, developers can harness their influence to build a future prioritizing human well-being over technological hype.

This content is an excerpt from a recent InfoQ article by Justin Sheehy and Renato Losio, "Being a Responsible Developer in the Age of AI Hype."

To get notifications when InfoQ publishes content on these topics, follow "AI, ML & Data Engineering", "Machine Learning", and "Generative AI"

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Sponsored

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