Curious how this will work in practice as vectors are specific to a given embedding model, and could be domain-specific for better results. Could it lead to industry standard embedding models, with regular (costly) upgrades?
GPT3 has shown how ML can be trained on multiple unstructured data sources to produce structured information on demand.
Iterate a few more versions from here, so that the models are stronger at producing the correct structured data, and the impact on every office job will be profound.
I.e. instead of training a generative model on text from the internet, train it on every single excel file, sql database, word document and email your company stores. Then query this model asking it to generate Report X showing Y and Z.
When you step back and consider it, 99% of office jobs are about producing structured data from unstructured data sources. The implications of this are being hugely underestimated.
Apple purchased NextVR last year. They had previously been screening NBA matches (and theatre/comedy) on the Quest. They were one of my favourite apps..