| IMHO The problem (for us) with this approach are the logical consequences: 1) if AI large model become more powerful avoiding language, embeddings of AI state become even more tied to the model they originate than now Consequence: AI progress stalls, as AI user companies need to invest increasing amount of money to reindex their growing corpuses. This is already a problem, it becomes more of a lock-in mechanism. If this is overcome... 2) Embeddings become a viral mechanism: it makes sense for a large company that commands a market to impose to its suppliers to use the same AI models, because they can transfer state via embeddings rather than external formats. This allows to cut down decisions mechanisms that otherwise require expensive coordination mechanism. Something similar will happen within companies IMHO: https://rlupi.com/okr-planning-as-belief-revision 3) Eventually this potentially results in another exponential growth and lock-in mechanism, also at the expense of most tech people as more and more is done outside our interface with AI (i.e. programming and software architecture improvements will it self move below language level, we'll have to reverse engineering increasingly opaque improvements). 4) It ends with the impossibility of AI alignment. --- I have written a bit about it in the past at the start of the year, when I had a burnout. So, I deleted those confused ramblings. You can stil find it on archive.org: https://web.archive.org/web/20240714153146/https://rlupi.com... |