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?
I'm wondering the same thing. Standardization would be interesting but I wouldn't bet on it. Maintaining different vector columns for different models might work well?
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.
Nah. When AI is able to do all what you have said, requirements will just get harder and humans will still have to put hours to make something done. Just like 30 years ago it wasn't feasible to implement streaming music over the internet in a weekend, and now any teenager can do so by just 'npm install'ing... AI will only open the door to even more complex problems to solve.
Both of those things can be true... it's not just one or the other. There are plenty of jobs right now that are more menial tasks which will definitely be replaced by this, and I feel for those older folks in those positions because they'll most likely lose their jobs / be impacted by this.
Exactly. People forget that there used to be (up to about thirty years ago) a large number of people employed as "file clerks". Their job was to file and retrieve on demand paper documents in filing cabinets. When relational databases became practical, this information was stored and retrieved electronically and the entire job of "file clerk" was made obsolete.
Consider "report generator" as one category, throw in "Buzzfeed writer" and "Stack Overflow copy/paster", and a clear bimodal distribution emerges. The human touch is still necessary to add context and distinguish fact from plausible hallucination, but experts can now scale their contributions 10x as a result of immediate access, minimal latency, and reduced communication costs.
We're moving towards a world of chair-fillers at one end, and maestros at the other. The clearest difference between labor in 2022 and 2026 will be the hollowing-out of the middle.
The value of a human is in reacting to changing requirements, considering context and in understanding other humans. AI cannot do any of that reliably.
Some office tasks can be automated and those that can don't need AI anyway - they need properly labelled data, databases and some coding.
AI will be very good at creating the illusion of competence. AI cannot actually ensure competence or verify it. That will remain the domain of humans.
>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.
This has already been possible for decades using old-fashioned automation (Python scripts etc.), assuming the data entry is designed for this.
Honestly, I think the reason managers have teams of people reporting to them is not just to give them unbiased information.
Part of it is probably ego stroking, but I suspect the humans in the loop are doing some sort of analysis too, and reporting qualitative patterns that an AI might not pick up on.
Deep thinking work will not go away. From trades to tech. It'll change work for sure, but it's not going to obliterate workers jobs.
I'm no luddite, but I've seen enough rocky digital transformations to know that human beings don't operate like manufacturing pipelines. Automation and AI assisted automation will be harder to generally implement.
But what I do feel confident about is that there will be a large mass of consultants who'll sell and expensive dream to a lot of mid tier businesses. The next big flex for business IT will be to have a notch on your belt for a failed AI automation project.
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..
