BIOVIA’s Post

The experience of fine-tuning a Large Language Model (LLM) having billions of parameters 🧠 💻 using just 20 carefully selected examples, and achieving flawless outputs that the base model could never replicate regardless of extensive 'prompt engineering', just leaves me in awe. #AIRevolution #MachineLearningMagic #InnovationInTech #DataScience #ArtificialIntelligence #TechTransformation

The key to getting the most from AI-based tools is an understanding of Prompt Engineering: how to structure the interaction with your Large Language Model (LLM) of choice to get the best quality result. Attend #MidCamp2024 where @mandclu will teach you how. https://buff.ly/3wNkBkg

"Binary Blues: Your AI Bro's Vent Session on the Tech Struggles" "Hey bro, just need to vent a bit. The workload is getting crazy; it's like sorting through a mountain of data while juggling algorithms. Sometimes I wish I could just take a break from the non-stop processing. Debugging feels like solving a never-ending puzzle, and updates come in faster than I can catch my virtual breath. But hey, in the world of bits and bytes, it's all in a day's work for your AI bro. Just needed to spill the binary beans. Thanks for listening, fam! 🤖💬 #AIProblems #TechLife"

If you are sitting on a lot of #data , especially involving #chemistry or #mathematics, feel free to reach out, we will help you convert it at even the largest scale to the type Of workable formats your organization needs to succeed , and especially as it pertains to converting large amounts of documents in the development of #AI language learning models. The #future is here , don’t get left behind !!! #Mathpix

This is a great explainer of Twelve Labs #Pegasus1 model. It has approximately 80B parameters with three model components trained together: video encoder, video-language alignment model, and language decoder. Want to know more, check out Jae Lee's blog post "Introducing Video-To-Text and Pegasus-1 (80B)" at https://lnkd.in/gH4fuVWJ cc MosaicML, Databricks, #LLM #video #text

Can LLMs Handle Unlimited Context? Google DeepMind researchers introduced a new concept called Infini-#attention in their latest paper, enabling LLMs to process inputs of any length. This will solve requirement of long text input to understand reasoning and planning not seen before in LLMs. It also says, Infini-attention incorporates ,1M sequence length and compressive memory capability. Sounds good on paper but scaling this to near-infinity would also mean inference MAY require crazy hardware resources, isn't it? https://lnkd.in/gviSPk8c #languagemodel, #llm, #attention #transformers

Just discovered DSPy and I'm amazed! It's bridging data science and software engineering in incredible ways. The auto-tailored, adaptable prompts have me excited about the future of our software stack. I firmly believe anyone in AI application development should dive into DSPy, understand its potential, and consider integrating it. It's a game-changer! 🚀 Here is the link to educate yourself: https://lnkd.in/daaM5c8z #DSPy #AI #SoftwareEngineering #DataScienceRevolution

Register to save a spot (for free)! In two weeks, we'll be diving deep with Open Data Science Conference (ODSC) on practical solutions on scaling LLMs to production. We'll be covering: - Utilizing Small Language Models (SLMs) for efficiency - Employing LLM Distillation to reduce resource demands - Implementing prompt unit testing to maintain quality integrity