2 ms·
In early 2020 I was doing a data science boot camp and one project was feeding in a bunch of scientific paper titles in a given area, then "predicting" a "next"
by kylebenzle 3y ago
In early 2020 I was doing a data science boot camp and one project was feeding in a bunch of scientific paper titles in a given area, then "predicting" a "next" future title, the idea was I could come up with ideas for future projects.
What we have now is exactly the same except with a MUCH bigger training set. I am using GPT4 everyday but still can't believe the nonsense hype around it. ALL of AI would be lucky to generate a few $million a year of actual income for people. At BEST these LLMs are great spell checkers and code template fetching assistants but thats as far as LLMs on their own will ever go.
Microsoft Word and Google Docs will have a built in "AI" spell checker that will dissapera into the background, and google search might get SLIGHTLY more relavent but thats it. No "AI revolution" is coming. I'd love to be wrong but looking at the details its hard to understand where people think this future revenue will come from.
- mechagodzilla 3y agoThe availability of the auto-text-firehose of LLMs will almost certainly make google search worse as it just gets overwhelmed with spam.
- cratermoon 3y agoWith all these models trained on a corpus of texts from the Internet[1], what's going to happen in 5 years when the internet is full of text generated after January 2022, the current cutoff data for ChatGPT? As an increasing proportion of training data is either pre-2002 or LLM-generated confabulations, when will it all collapse in on itself? Do these companies have any plans for how they are going to get accurate and factual input after their output dominates? 1. Corpora: https://commoncrawl.org/ https://commoncrawl.org/, https://www.english-corpora.org/ https://www.english-corpora.org/