In the 1980s, the architect, theorist and teacher Bernard Tschumi penned an essay “Spaces and Events,” which later appeared as a chapter in his influential book Architecture and Disjunction. In it he outlines an approach to architectural design, at least in a studio teaching context, that elides the literary with the pictorial, to the extent…More
Category Archives: Artificial Intelligence
From text to image via LLM
Text and writing are important components in creating architecture. To put it more strongly: text is deeply intertwined with the production of architecture, serving as more than a mere communication tool. Text impacts design thinking, theory, history, and the way the built environment is constructed — materially. As in my previous posts, I’m seeding this…More
Share your expertise
Google’s NotebookLM utilizes the RAG methodology for document interrogation, allowing users to gain insights from multiple texts simultaneously, while the University of Edinburgh has introduced its ELM built on ChatGPT for educational use. Both tools enhance understanding in specialized fields by enabling easy document uploads and tailored responses, benefiting users in architecture, law, and healthcare.More
Smashing the context window
In natural language processing LLMs, the “context window” is the range of text around a target word or phrase that constrains the sequence of text processed in calculating positional and attentional encoding, and hence prediction of the text that follows. A larger context window allows the AI model to capture more subtle relationships and dependencies…More
AI profiles you
In 2009, an academic received feedback through a 360-degree process, similar to analyzing their blog content with AI. The blog, started in 2010, includes 741 posts exploring technology, culture, and design. Using AI, the author inferred insights on personality and product interests, reflecting their intellectual pursuits and the evolution of digital analysis.More
Post-creative AI
There’s a phase of production after an author completes a manuscript (draft or final) when the author might need to compile an index, summaries for publicity, and other “extra-authorial tasks”? The main creative task of writing is complete and the tasks that follow could be undertaken by editors or others, or even an AI. In…More
Easy reading
I continue a discussion of my manuscript AI and Language in the Urban Context: Conversational AI in Cities (Routledge). See previous post: Too much feedback. I asked Google’s NotebookLM, “Would the average reader have any difficulty following the technical/mathematical explanations?” The AI responded: Readability of Technical/Mathematical Explanations The sources [actually, the manuscript] suggest that the…More
Too much feedback
Google has introduced an AI-driven document analysis platform called NotebookLM. You upload a document to the NotebookLM server via its website (notebooklm.google.com). The LLM generates a summary of the entire document and suggests some questions of the kind you see in textbooks that test a reader’s comprehension of the content. These are not generic questions,…More
AI fever dreams
Reinstating Panpsychism: Cities and the Machinery of Mind in the Age of AI City: A sprawling, feverish organ of matter and thought, a monstrous convergence where steel skeletons fuse with the blood and minds of the masses. It pulses with an energy both alien and intimate, a grand machinic beast, dreaming its electric dreams. To…More
AI explains itself
I’m catching up with Yuval Harari’s latest book Nexus: A Brief History of Information Networks from the Stone Age to AI. He alerts readers to the challenge posed by the spread of opaque algorithms that are increasingly responsible for deciding on our behalf: bank credit, purchase choices, health, governance. In the face of this obfuscation…More