News
Welcome to the News community!
Rules:
1. Be civil
Attack the argument, not the person. No racism/sexism/bigotry. Good faith argumentation only. This includes accusing another user of being a bot or paid actor. Trolling is uncivil and is grounds for removal and/or a community ban. Do not respond to rule-breaking content; report it and move on.
2. All posts should contain a source (url) that is as reliable and unbiased as possible and must only contain one link.
Obvious biased sources will be removed at the mods’ discretion. Supporting links can be added in comments or posted separately but not to the post body. Sources may be checked for reliability using Wikipedia, MBFC, AdFontes, GroundNews, etc.
3. No bots, spam or self-promotion.
Only approved bots, which follow the guidelines for bots set by the instance, are allowed.
4. Post titles should be the same as the article used as source. Clickbait titles may be removed.
Posts which titles don’t match the source may be removed. If the site changed their headline, we may ask you to update the post title. Clickbait titles use hyperbolic language and do not accurately describe the article content. When necessary, post titles may be edited, clearly marked with [brackets], but may never be used to editorialize or comment on the content.
5. Only recent news is allowed.
Posts must be news from the most recent 30 days.
6. All posts must be news articles.
No opinion pieces, Listicles, editorials, videos, blogs, press releases, or celebrity gossip will be allowed. All posts will be judged on a case-by-case basis. Mods may use discretion to pre-approve videos or press releases from highly credible sources that provide unique, newsworthy content not available or possible in another format.
7. No duplicate posts.
If an article has already been posted, it will be removed. Different articles reporting on the same subject are permitted. If the post that matches your post is very old, we refer you to rule 5.
8. Misinformation is prohibited.
Misinformation / propaganda is strictly prohibited. Any comment or post containing or linking to misinformation will be removed. If you feel that your post has been removed in error, credible sources must be provided.
9. No link shorteners or news aggregators.
All posts must link to original article sources. You may include archival links in the post description. News aggregators such as Yahoo, Google, Hacker News, etc. should be avoided in favor of the original source link. Newswire services such as AP, Reuters, or AFP, are frequently republished and may be shared from other credible sources.
10. Don't copy entire article in your post body
For copyright reasons, you are not allowed to copy an entire article into your post body. This is an instance wide rule, that is strictly enforced in this community.
view the rest of the comments
The two of you are using the word "generalist" differently. You don't need your tool-using language model to be able to wax poetic about ancient egyptian burial practices. That's why ChatGPT will become useless. It's too large and expensive to continue running without subsidies, and it's too useless for serious tasks. You can get away with a small local model that knows nothing about ancient egypt if all you need is to translate natural language into tool calls.
You're absolutely right about that, and if we're able to build a model that's as capable as GPT and friends at parsing natural language, without simultaneously training it on everything from poetry to programming, that's a major win. My current understanding of the field is that in order to build/train the models that are able to robustly parse natural language and "understand" the intent behind a series of instructions well enough to translate them to the correct tool calls, we need a very large and varied training set. I'm using "generalist" as a term to refer to the models that you can interact with in natural language across a wide variety of tasks. Those models are extremely powerful if you can also connect them to tools that solve problems deterministically, so that you get around the problem that they don't really "understand" anything at all, while taking advantage of the fact that they're extremely well suited for translating natural language to a selected set of pre-defined actions.
I think a major challenge going forward is that interpreting natural language requires a large set of training data. So training specialised models that can also interact with natural language is by nature difficult.