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![Scientists in lab coats examine a large screen displaying "How to Train and Fine Tune a Multimodal LLM [+ Use Cases]" amid servers.](https://hatchworks.com/wp-content/uploads/2024/09/How-to-Train-and-Fine-Tune-a-Multimodal-LLM-Thumbnail-768x656.png)
This article breaks down the process I’ve used to train and fine-tune multimodal language models. It’s allowed me to create custom and accurate AI solutions
Inference is what happens every time a finished model answers a request — the production step your users actually experience, and the one you pay
This article breaks down the exact process I’ve used to leverage generative AI in building MVPs. It’s allowed me to accelerate development, iterate faster, and
You deploy an LLM one of three ways, and the choice is mostly about volume, not ideology. Run it locally with Ollama or LM Studio
When you were a kid and you thought of artificial intelligence (AI), you probably thought of human-like robots assisting actual humans with household tasks. But
The software engineer shortage did not end. It inverted. Entry-level hiring collapsed — new-grad hiring at the largest tech companies is down roughly 65% against
One of the most consequential decisions in any AI project rarely gets discussed openly: should you build on a single large language model, or combine
Everywhere you look, someone seems to be getting remarkable results from AI while you are left staring at a mediocre answer wondering what you did
A few years ago, the executive question about generative AI was whether to let your people use it. Employees were quietly pasting work into ChatGPT,
You came here to learn generative AI from the ground up, so we will not bury the useful part under a long introduction. Here is
