Data quality headaches & progress

Apart from the fact that no one yet managed to extract knowledge from text in bulk, there are two main problems in unsupervised learning from large English text corpora: The availability of relevant, useful data and the quality of that data in terms of the suitability to be parsed by an automated text-to-knowledge converter. I […]

Super-AGI and the Source Quality Problem

I talk about hiding R&D secrets from my “competitors” but I’m not in this for the money. I wanted a challenge, something as useful-as-possible to do for my final years. Artificial General Intelligence can come into different flavors. Initially it will be rather mundane, powering customer service chatbots. More advanced embodiments may be used to […]

Good ideas aren’t a dime a dozen

I’ve learnt my lesson and won’t be disclosing my concrete ideas and algorithms because Academia and business will rip them off again. So you, non-“competitor”-reader, won’t be exposed to the nitty-gritty and instead get “evergreen” content – stuff that will remain relevant decades from now, if the world hasn’t been plunged into chaos by that […]

My first and second steps towards AI

I got an Acorn Atom for my sixteenth birthday, in 1981. 1 MHz, 8 bits, 512 bytes free RAM for BASIC or Assembly. One of my first programs was “AI”: I would enter: >Fido is a dog>Dogs have legs>Does Fido have legs? It would output: >Yes because Fido is a dog and dogs have legs. […]

Generalization and other innateness

I don’t particularly look up to any AI boffin, but so far I found three folks’ opinions carrying weight, when talking about how to achieve True AI and they’re all Jewish: Marvin Minsky, Gary Marcus and Jehuda Pearl. Even in the set of bad AI-related ideas, the best ones of those often also originate in […]