{"id":44338,"date":"2025-10-10T18:21:58","date_gmt":"2025-10-10T17:21:58","guid":{"rendered":"https:\/\/newsblogs.ihbc.org.uk\/?p=44338"},"modified":"2025-10-10T18:21:58","modified_gmt":"2025-10-10T17:21:58","slug":"context-184-under-the-spotlight-ihbcs-accessible-cpd-for-conservation-professionals-offers-insights-into-the-world-of-generative-ai","status":"publish","type":"post","link":"https:\/\/newsblogs.ihbc.org.uk\/?p=44338","title":{"rendered":"Context 184 under the spotlight: IHBC\u2019s accessible CPD for Conservation Professionals, offers insights into \u2018The world of generative AI\u2019"},"content":{"rendered":"\n
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IHBC\u2019s members\u2019 journal Context<\/em><\/a> in June 2025 \u2013 No. 184<\/a> \u2013 focussed on \u2018Leaders of conservation thought\u2019, but also included Sammy Woodford on \u2018\u2019The world of generative AI\u2019.<\/p>\n\n\n\n\n\n\n\n

Sammy Woodford writes:<\/p>\n\n\n\n

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.<\/p>\n\n\n\n

When people refer to AI these days they are typically referring to \u2018generative\u2019 AI (or \u2018genAI\u2019)which is AI that generates content. This is based on an invention called a transformer.\u2018 Generative\u2019 and \u2018transformer\u2019 are the G andT in GPT, and the P stands for \u2018pretrained\u2019, 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 than60 years, albeit picking up over the past 12<\/p>\n\n\n\n

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 transformer-based chat bot that can answer questions with levels of sophistication hitherto reserved for science-fiction, the technology entered the public consciousness\u2026.<\/p>\n\n\n\n

The ability to answer questions across abroad 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 \u2018large language models\u2019 from their predecessors\u2026.<\/p>\n\n\n\n

\u2026<\/p>\n\n\n\n

The two images in this article were generated completely using the image diffusion service Midjourney. This uses text, or text and images in combination, to produce a picture. The initial image was designed to resemble a photograph of a 1960s office development in an English high street.<\/p>\n\n\n\n

Using Midjourney\u2019s \u2018inpainting\u2019 tool, in which an area of an image can be selected and re-generated using a different instruction, I carried out the following changes:..<\/p>\n\n\n\n

\u2022Replaced the highway in the foreground with a public realm scheme consisting of paving, planters with plants, and wide pavements.<\/p>\n\n\n\n

\u2022Replaced two of the central buildings to simulate a new development of attractive, modern, colourful houses in a row, with gabled roofs<\/p>\n\n\n\n

\u2022Replaced the ground floors of this development with a row of shop fronts to simulate a mixed-use development<\/p>\n\n\n\n

\u2022Added a pair of street trees with autumn colours into two of the planters.<\/p>\n\n\n\n

There are numerous intricacies and it is not as simple as this makes it sound. A few architects have become quite technically proficient with this sort of program, and in the public sector generally, there is an impetus to understand AI, though it is still very niche.<\/p>\n\n\n\n

See HERE<\/a> for the full article online and in <\/em>Context<\/em> <\/em>184<\/em><\/a><\/p>\n\n\n\n

Context<\/em> <\/em>184<\/em><\/a>: CONTENTS<\/p>\n\n\n\n

Themed Articles<\/strong><\/p>\n\n\n\n