The Knowledge Graph Conference reposted this
Graph semantics and AI trends strategist / Change consultant / Veteran researcher, analyst and reporter
A year ago, Denny Vrandečić of the Wikimedia Foundation, one of the key people behind Wikidata, made some telling remarks about when not to use LLMs during a keynote at the The Knowledge Graph Conference: “Why would you ever use a 96 layer LLM with 175 billion parameters to generate a multiplication, which is a single operation with a CPU? Just because an LLM can do these kinds of things doesn’t mean they should be. Why should you be generating knowledge again and again when you can just look it up in a confident way?…. It’s just not very efficient.” What's happened in the past year since Vrandečić made this observation? Platform providers such as Fluree are making it possible to harness the power of LLMs and knowledge graphs together in ways that allow more accuracy, efficiency and security. https://t.ly/MyPQ8
Horrifically inefficient.
"Enterprise Language Models" That's the fusion point our targeted initiatives should be aimed at. And, I rather expect it's where early enterprise-level AI ROI will actually be found. Great post Alan Morrison!
Alan Morrison - Makes sense. "Practical Intelligence" is the application of smarter thinking when engaging LLMs. A technology agnostic knowledge graph is a perfect partner to set enterprise context. LLMs are useful in small doses.
Driving AI Breakthroughs with RAG & KG | Seasoned open-source Julia #lowcode Framework, DB & Cloud Contributor
1moThis is because everybody is fantasizing about building one model AGI and that's not the right path