34 CONTEXT 184 : JUNE 2025 SAMMY WOODFORD The world of generative AI For many tasks artificial intelligence (AI) can be of great use to the conservation professional, even if we have little idea of what the risks are or where this tool is taking us. When people refer to AI these days they are typically referring to ‘generative’ AI (or ‘genAI’) which is AI that generates content. This is based on an invention called a transformer. ‘Generative’ and ‘transformer’ are the G and T in GPT, and the P stands for ‘pretrained’, which refers to the massive amount of training data needed. A transformer is a type of neural network architecture. It was invented in 2017, although the present AI chapter is the latest in a field (deep learning) that has been chugging away quietly in the background for more than 60 years, albeit picking up over the past 12. Transformer architecture, in combination with greatly scaled size and training data, has heralded a rapid acceleration in the fields of natural language processing and computer vision. With the 2022 release of ChatGPT, a transformerbased chat bot that can answer questions with levels of sophistication hitherto reserved for science fiction, the technology entered the public consciousness. The ability to answer questions across a broad range of topics rather than only specialisms for which they have been trained, and in natural language indistinguishable from that of humans, marks out these ‘large language models’ from their predecessors. Currently the modalities and uses to which generative AI can be applied are being broadened and extended, with systems increasingly able to ingest, manipulate and produce music and sounds, images, video, text and geometry. The first image, generated using the image diffusion service Midjourney, shows a run-down, 1960s-style office development on a street. The second shows alterations added using ‘inpainting’ to simulate a new development and public realm scheme.
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