Does generative AI have a place in the highly regulated world of life sciences, and can it produce value without compromising patient safety? In this
The majority of Generative AI pilots, often utilizing large language models (LLMs), don’t make it to production. After blazing through a successful Proof of Concept,
This Article at a Glance: Real-time, personalized conversations with your company’s proprietary data—that’s what retrieval augmented generation (RAG) is capable of. Level up your use
In this bonus episode of Talking AI, Omar Shanti, CTO of HatchWorks AI, breaks down how LangChain’s abstractions have both helped and hindered AI innovation.
Power LLMs with Your Data Sometimes it feels like we’re all in a race to effectively and affordably adopt AI. Only there are hurdles in
If you’re like us, always on the lookout for tools that take the hassle out of coding, you should test Codestral Mamba. Whether you’re here
Is AI-generated content really good enough to compete in the highly competitive world of search engine optimization? This was a question that Tim Hanson had
![Scientists in lab coats examine a large screen displaying "How to Train and Fine Tune a Multimodal LLM [+ Use Cases]" amid servers.](https://i0.wp.com/hatchworks.com/wp-content/uploads/2024/09/How-to-Train-and-Fine-Tune-a-Multimodal-LLM-Thumbnail.png?fit=768%2C656&ssl=1)
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
As AI rapidly develops so too does the vocabulary surrounding it. To effectively implement AI into your business, you’ll need to learn the lingo—AI Inference,
Gen AI promises to completely transform our world, from how we work to how we live. But do the core first principles in product management
