Groq’s Post

The Foundational Model Development Cheatsheet was prepared by foundation model developers, for foundation model developers, and serves as a guide to best practices, known limitations, and responsible habits. Contributors include Google, Hugging Face, EleutherAI, Massachusetts Institute of Technology, Stanford University CFRM, MLCommons, University of California Santa Barbara, Masakhane , and University of Washington. Check it out: #FoundationModels #AI

We’re excited to present the second video in our informative series, crafted by Nicolai Nielsen. In this video, Nicolai takes a deep dive into setting up and optimizing annotation workflows using our Keylabs Annotation Platform platform. He expertly balances the needs of both administrators and annotators, making complex processes accessible and efficient. https://lnkd.in/e7CBfhsG #dataannotation #datavalidation #imageannotation #videoannotation #datatraining #computervision #datacreation #datacollection

The Foundational Model Development Cheatsheet was prepared by foundation model developers, for foundation model developers, and serves as a guide to best practices, known limitations, and responsible habits. Contributors include Google, Hugging Face, EleutherAI, Massachusetts Institute of Technology, Stanford University CFRM, MLCommons, University of California Santa Barbara, Masakhane , and University of Washington. Check it out: #FoundationModels #AI

AI, they say. ML, they say. It's en vogue, but also a new software reality. But one more chat bot or virtual assistant won't impress anyone. You need to actually drive responsible AI by securing and delivering machine learning components as part of your software supply chain. MLOps isn't about just managing models, but your entire software ecosystem to deliver value securely, with speed. https://jfrog.com/mlops/

In his latest blog, VP of GenAI Naveen Rao shares why custom LLMs should be the de facto strategy for organizations looking to tap into the power of #GenAI (and why even small, domain-specific models can have a big impact). Read his insights on how to get started with custom LLMs - whether your approach is with RAG + open source or you're building your own. https://dbricks.co/3uCfOkE

🌟 Calling All Healthcare Professionals & Enthusiasts! 🌟 We’re on an exciting journey to revolutionize healthcare with the power of generative AI, and we need your valuable input! We’re gathering data to build a cutting-edge model designed to enhance and personalize healthcare services. But to make this a reality, we need your help. 📝 How You Can Contribute: ·     Take a few minutes to fill out the link below. ·     Review the graphs we've generated and ask any questions you'd like to know more about. ·     Share your general complaints or feedback on our current healthcare system. ·     Your insights will directly shape the future of AI in healthcare, helping us create a more efficient and patient-centered experience. Link: http://20.247.184.194/ Thank you for your time and contribution. Together, we can create a healthier tomorrow! 🌍💡 #HealthcareInnovation #GenerativeAI #HealthTech #AIforGood #PatientCare #DataDriven

The Foundational Model Development Cheatsheet was prepared by foundation model developers, for foundation model developers, and serves as a guide to best practices, known limitations, and responsible habits. Contributors include Google, Hugging Face, EleutherAI, Massachusetts Institute of Technology, Stanford University CFRM, MLCommons, University of California Santa Barbara, Masakhane , and University of Washington. Check it out: #FoundationModels #AI

The Foundational Model Development Cheatsheet was prepared by foundation model developers, for foundation model developers, and serves as a guide to best practices, known limitations, and responsible habits. Contributors include Google, Hugging Face, EleutherAI, Massachusetts Institute of Technology, Stanford University CFRM, MLCommons, University of California Santa Barbara, Masakhane , and University of Washington. Check it out: #FoundationModels #AI