Will AI take away jobs or make us more efficient?
Employee Experience Series If you’re waiting to see how AI is changing the way we work, it already has. Just
Procuring & Building for AI Transformation in 2023
AI transformation including generative AI is one of the top priorities for CEOs. Though AI is critical for enterprises its
Which Quantization Method is Right for You?(GPTQ vs. GGUF vs. AWQ) | by Maarten Grootendorst | Nov, 2023
Exploring Pre-Quantized Large Language Models Throughout the last year, we have seen the Wild West of Large Language Models (LLMs).
Unlocking the Power of Big Data: The Fascinating World of Graph Learning | by Mathieu Laversin | Nov, 2023
Harnessing Deep Learning to Transform Untapped Data into a Strategic Asset for Long-Term Competitiveness. Photo by Nathan Anderson on Unsplash
Understanding Instrumental Variables | by Matteo Courthoud | Nov, 2023
How to estimate causal effects when you cannot randomize treatment Cover, image by Author A/B tests are the golden standard
The Moat for Enterprise AI is RAG + Fine Tuning — Here’s Why | by Barr Moses | Nov, 2023
To succeed with generative AI at scale, we need to give LLMs the diligence they deserve. Enter RAG and fine
Philosophy and Data Science —Thinking deeply about data | by Jarom Hulet | Nov, 2023
Part 1 : Determinism Photo by ‘HH’ on Pexels.com Data science is a very technical, in-the-weeds type of work. We
Create your Vision Chat Assistant with LLaVA | by Gabriele Sgroi | Nov, 2023
Get started with multimodal conversational models using the open-source LLaVA model. Photo by Izabela Kraus on Unsplash Large Language Models
Teaching is Hard: How to Train Small Models and Outperforming Large Counterparts | by Salvatore Raieli | Nov, 2023
|MODEL DISTILLATION|AI|LARGE LANGUAGE MODELS| Distilling the knowledge of a large model is complex but a new method shows incredible performances