This is good in combination with Hugging Face's Synthetic data: save money, time and carbon with open source.
Note that this is only for fine-tuned data, not content included in the prompt.
According to Betteridge's law of headlines:
Any headline that ends in a question mark can be answered by the word no.
It's a little in the weeds of how these tools work, but generative AI tools are based on "tokens," individual units of text or information. Usually the tokens are developed organically by the model itself, but in this case, the tokens were developed by the team at Baichuan, and they're very revealing of the model's... biases? I don't think I'd call them a bias, just... a reflection... of... something.
Read the responses.
Running models locally is wild! I've seen people talk about it plenty before, but the video really sold it to me.
I need to go buy a fancier mac! I've always prided myself on using old cheap Airs buuuuut maybe that era is over.
Oh boy, Meta just open-sourced a few models which actually seem kinda wild, the big ones (for us) being:
MusicGen generates music from text-based user inputs. All of the generic background music you could ever want is available on-demand, with plenty of samples here.
AudioGen generates sound effects from text-based user inputs. Find examples here of things like "A duck quacking as birds chirp and a pigeon cooing," which absolutely is as advertised.
In the same way stock photography is being eaten by AI, foley) is up next.
Many, many, many of the papers that I link to here are about how a model is performing. But unless it's the ones where GPT got into MIT or became king of doctors or masters of all law, most of the more fun recent papers have been about "self-report studies," where polls typically given to humans are given to LLMs instead:
I will discuss three high-profile papers that I believe might have some of these problems. I am not saying that everything about these papers is wrong or that these papers are bad overall (at least not all of them). Especially the first paper is quite good in my opinion. But I have my doubts about some of their findings and I think that pointing them out can illustrate some of these pitfalls.
This is great! This is how it should be!!! And what's that? You want sass?
I find the use of this tool to be a shaky idea right out of the gate. The authors of the paper claim that their work is based on the political spectrum theory, but I am not aware of any scientific research that would back the Political Compass. To my knowledge, it really is merely a popular internet quiz with a rather arbitrary methodology.
Go forth and read the paper itself (which I guess technically isn't a paper, but it's basically a paper)
News reports focusing on clinical trials and drug development data, using models that are focused on detail recency/relevance and accuracy. We can at least agree on this header:
AI-Generated News ≠ Journalism
Read the post – at the bottom is an invitation to apply for journalists or biotech folks.
