At the heart of modern data science, there is a division. On one hand, machine learning is in a race for scale. On the other hand and less loudly, a revolution is taking place in the backward direction: these are quantized models, edge inference, TinyML, and architectures that will survive on very limited resources.
Source: Silicon Darwinism: Why Scarcity Is the Source of True Intelligence | Towards Data Science
As part of its role in the Generative AI for Agriculture (GAIA) project, CABI is examining data governance issues to improve access to robust content for gen AI developers in a legal, equitable, and sustainable way. We are developing a model content license (MCL) intended as a standardized template that can be adapted to specific contexts by agritech AI developers and creators (e.g., publishers, creative copyright licensors, universities) or collective rights organizations.




Web publishers and news organizations could be given the power to stop Google scraping their content for its AI Overviews, under measures announced by the UK competition watchdog to loosen its grip on online search. Media organizations have experienced a drop in click-through traffic to their websites – and therefore their revenue – since Google started posting AI summaries at the top of search results.
Media companies expect web traffic to their sites from online searches to plummet over the next three years, as AI summaries and chatbots change the way consumers use the internet. An overwhelming majority are also planning to encourage their journalists to behave more like YouTube and TikTok content creators this year, as short-form video and audio content continues to boom.