tugdual
Joined 2 years ago
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Member since
Jul 18
Recent submissions
Comment · 4 months ago
Comment · 4 months ago
Absolutely incredible
Comment · 5 months ago
They’re not competing in the same domain - if you look at their business model it actually is much closer to ML consulting for companies (CMA CGM, ASML, Airbus…). The big three are trying to capture B2C mainly while Mistral is full focused B2B
Comment · 9 months ago
Love it !
Comment · 9 months ago
Comment · 9 months ago
The reason we're conflating them is because there is a strong correlation between "highly processed food" and "designed recklessly". If you look at Carlos Monteiro (The pioneer in this domain) he operationalized it with the NOVA metric. NOVA 4 being the closest to what you're talking about:
"Industrially manufactured food products made up of several ingredients (formulations) including sugar, oils, fats and salt (generally in combination and in higher amounts than in processed foods) and food substances of no or rare culinary use (such as high-fructose corn syrup, hydrogenated oils, modified starches and protein isolates)..." [1]
[1] https://en.wikipedia.org/wiki/Nova_classification
I highly recommend Chris van Tulleken's Ultra-processed people for a more indepth read on this fat correlation (excuse the pun :))
Comment · 1 year ago
Amazing work, I have a deep respect for this type of project where the underlying theme is perseverance !
Comment · 1 year ago
This is what my Master project was about, working in the case of Wolof. I've trained XTTSv2 and had solid results with less than 20h of paired data that wasn't of the highest quality either - hmu: [email protected]
Comment · 1 year ago
This is an interesting problem that has various challenges - currently most tokenization solutions where trainees using hype pair encoding where the most commonly seen combinations of letters were being selected to be a mapping. This meant that the majority of tokenization was English mappings meaning your LLM had a better tokenization of English compared to other languages it was being trained on.
C.f. https://medium.com/@biswanai92/understanding-token-fertility...
Comment · 1 year ago
Got a demo ?
Comment · 1 year ago
When Carlos Monteiro decided to operationalize UPFs by giving them a definition (laymans terms: UPF is one ingredient you wouldn't find in a traditional kitchen and wrapped in plastic) Kevin Hall from the US had the same reaction as you and decided to make a multi-million dollar experiment to disprove the definition proposed by Dr. Monteiro. Result: People who ate unprocessed lost weight, and the other group gained weight. (Groups were exchanged after 2 weeks and saw similar effects).
Comment · 1 year ago
They could be solving it with multimodal mixup, a technique making sure that there's no big latent gap between the two : https://arxiv.org/abs/2203.03897
Comment · 2 years ago
I actually did something similar using llama.cpp a while back, would be curious to see the speedup with this model.
Comment · 2 years ago
The closest thing I believe we have as a neutral social media platform is Telegram. You can follow people, talk to friends with a performant interface without having a company who's main goal financially is making you see ads.
There is very little parasocial relationship on the platform although this could definetly grow as channels become a medium for influencers.
https://computers.tugdual.fr/