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Test driven development is a beast to tame. I like TDD but in the past it was quite difficult to achive, at least in a pure-consultant approach with a "turn key" framework behind.
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Sometimes you need to fix a production defect. To do it, you need to mirror a specific set of data, and do a test to proof the bug and then fix it.
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This week was very hot because Google published Gemma, a smal-size LLM, and also Nvidia has a rush on stock market, with a evaluation around 2000 BILLIONS dollars. Last but not least, Mistral.ai published a service for its more advanced model, which can also run on-prem.
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Generative artificial intelligence (GenAI) is artificial intelligence capable of generating text, images or other data using generative models, often in response to prompts.
Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics. This similarity is probability-based.
At low level, these systems are based on Transformer deep-learning architecture and are called generative pre-trained transformer (GPT) first defined in 2018 (for a complete description refer to Wikipedia)
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