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Inside LLMs: understanding tokens
When we talk about LLMs, we find ourselves faced with concepts that are not always necessarily understood. After all, you can use GPT-4 very well without understanding what tokens or temperature are. However, when we seek to go further in the use, it is necessary to understand these different concepts and this is what we […]
Vector databases: chronicle of a foretold death
For several months now, we have heard a lot about these new "Vector Databases" which would be the "memory" of Large-Language-Models. Pinecone ($128M), Qdrant ($28M), Croma ($18M), there are several dozen startups raising millions and fighting in the hypothetical vector search market. In this article, we'll look at how vector databases are more of a […]
The real revolution brought by Google’s Gemini models
Those who spill ink about the authenticity of Google's video on Gemini's multimodal performance or its performance compared to GPT4 are missing the true revolution inside Google announcement. The market is today dominated by large (very large) LLMs. From Mistral to GPT4, including LlaMa 2, all these models whose performance is regularly compared to different […]
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