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
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.





The free lunch will come to an end for artificial intelligence in 2026. Over the past decade, developers from Google to Alibaba have largely been helping themselves to the internet buffet, devouring copyrighted material without permission or payment. Make no mistake, however: the bill is coming soon. Consider it AI’s Napster moment.
IP acquisition is only the first step – one quickly followed by potentially overwhelming blocking and tackling. A typical catalog requires ingesting data from hundreds of platforms and sources spanning DSPs, sub-publishers, CMOs, and social media platforms, often in conflicting formats. And that’s just a working list of initial considerations to properly collect associated IP revenues, with downstream payouts and revenue splits another major area of concern.