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Good question.
Training a large language model completely from scratch requires massive infrastructure, billions of tokens of data, and hundreds of millions of dollars. Very few organizations in the world can currently do that.
Veta Origin’s approach is different.
We build on top of existing frontier models and combine them with:
• African-focused datasets
• Retrieval systems for local knowledge
• Fine-tuning and alignment for African languages and context
• Application-layer intelligence designed for African users
So the goal isn’t just another base model.
The goal is AI that actually works for Africa in language, context, culture, and everyday use.
Over time, we plan to continue expanding our infrastructure and research capabilities.
This is step one.
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Did you really build a large language model from the ground up or you fine tuned a pre-trained model on say “african data” ?
Because we all know the cost in building an LLM from scratch.
The infra.
The data
The time
The money
Veta Origin@vetaorigin
@starboy_abefe Bring it on 🔥
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@Kalshi tells @TheBlock__ "no immediate plans" to list college athlete transfer bets
But it did seek permission...
Kalshi also says it also once certified an extinct animal market contract... but then didn't list it.
theblock.co/post/383188/ka…
[[In Nov, rival @Polymarket posted a market for @NCAA basketball player transfer... polymarket.com/event/will-pj-…]]
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