Markus Strasser spent quite a while trying to build a business that extracted knowledge from academic papers: understanding the insights within them, building relationships between them, throwing up new and interesting connections, and generally automating much of the drudge work of sifting through the published knowledge within a given field.
His findings were dispiriting, and his business sadly failed. Part of the problem is that ideas alone don’t tend to lead to innovations; you need teams of people, and much of the knowledge within successful teams is implicit and not expressed in the papers themselves:
“But the complexity threshold kept rising and now we need to grow companies around inventions to actually make them happen… That’s why incumbents increasingly acqui-hire instead of just buying the IP and most successful companies that spin out of labs have someone who did the research as a cofounder. Technological utopians and ideologists like my former self underrate how important context and tacit knowledge is.”
Strasser’s essay is interesting not just as a deep dive into scientific knowledge and its structure, but also as a personal story of the pain of starting a business that turns out not to be viable:
“I’ve been flirting with this entire cluster of ideas including open source web annotation, semantic search and semantic web, public knowledge graphs, nano-publications, knowledge maps, interoperable protocols and structured data, serendipitous discovery apps, knowledge organization, communal sense-making and academic literature/publishing toolchains for a few years on and off… nothing of it will go anywhere.
“Don’t take that as a challenge. Take it as a red flag and run. Run towards better problems.”