Skim AI Technologies’ Post

Unlock the power of enterprise AI with AI at Meta Llama 3.2 on Snowflake Cortex AI! Build faster, more secure generative AI applications with the flexibility of four right-sized models (1B and 3B available now and 11B and 90B coming soon). Whether it’s real-time processing on edge devices or large-scale enterprise AI, Cortex AI and Llama 3.2 have you covered. Now, it’s never been easier to build gen AI applications that scale, all within the secure Snowflake perimeter, with Llama 3.2 on Cortex AI. https://lnkd.in/ga8k-94C

🚀 𝐋𝐚𝐭𝐢𝐭𝐮𝐝𝐞'𝐬 2024 𝐀𝐈 𝐓𝐫𝐞𝐧𝐝𝐬 Vector databases are forecasted to play a crucial role in AI's data infrastructure in 2024. Latitude expects these databases to streamline AI applications by enabling efficient, accurate operations and reducing complexity and costs, making AI more accessible and efficient for businesses. For all deep dive in all the trends for AI in 2024, make sure to read the blog: https://lnkd.in/e69ReRFz #VectorDatabases #AI2024 #TechTrends #Innovation #AI

🔍 Enterprise innovation alert! 🔍 🚀 What's new in enterprise AI solutions? Discover how Vertex AI is raising the bar. 🌟 Key Enhancements: 1️⃣ AutoML Capabilities: Automated machine learning models for quick deployment. 2️⃣ MLOps Integration: Streamlined machine learning operations for efficiency. 3️⃣ Custom Training Jobs: Tailor models to specific business needs with ease. Read on here: https://lnkd.in/eRS8aAK3 🤝 Follow Geekflare for more tools and resources like this. #VertexAI #EnterpriseAI #TechNews #AI #BusinessSolutions #DigitalTransformation

What´s your knowledge around the EU AI Act? Did you know that shadow AI is already ongoing according to recent Work Trend Index by MSFT? It´s about time to act now and prepare employees for a "better with AI" motion

Enterprises don't need a model that can do everything, but a customised AI model that is excellent in your specific use case. This is where DBRX comes in at the sweet spot that offers Enterprises a leaner model to customise. DBRX, Databricks' new open-source LLM, uses a mixture-of-experts design to efficiently tackle tasks, utilizing just 36B out of 132B parameters, saving energy and improving response time. See how Databricks is helping #AI reach all enterprises in this Fast Company piece👇

Two words that sum up the current state of Enterprise AI: Overpromised and Underdelivered. Traditional RAG is the reason. In fact it is a Billion Dollar problem (and opportunity). Traditional RAG has been a challenge for everyone. 99?% accuracy is not good enough for enterprises and Traditional RAG isn’t even there yet. But Enterprise GenAI developers are already on the edge with their frustration. The developers are struggling with every part of their GenAI pipeline: - Ingestion: Between implementing chunking strategy, managing embeddings, vector DBs and fickle prompt engineering, most developers struggle with the choices but have no choice, nevertheless. - Retrieval: Because retrieval is based on similarity search using chunk embeddings and embedding of a short question or request, retrieved context gets polluted with noise. And when noise hits LLMs, hallucination happens. - Generation: LLMs are probabilistic systems. Developers end up dealing with probabilistic responses. The end result – high failure rates and a hit on enterprise credibility. Deployment of these GenAI apps are in limbo. What can be a week’s worth of effort with GraphRAG turns into a months long losing struggle to reach production grade. And the cost of running Traditional RAG is another story altogether that demands another post. GraphRAG fixes this and finally we will get to see more GenAI applications in production. TechCrunch - This article (link in comments) should get an update soon.

#Snowflake #Cortex is a fully-managed service that enables access to industry-leading #largelanguagemodels (LLMs) is now generally available. You can use these #LLMs in select regions directly via #LLM Functions on Cortex so you can bring generative #AI securely to your governed data.

If you want to know how to leverage Generative AI and Large Language Models, just ask Stardog and Databricks, MosaicML. Stardog introduced #voicebox, an LLM powered interface to their innovative knowledge graphs. Now you can ask questions of your data in plain text and get answers AND reasoning. What makes this especially cool is that they used MosaicML from Databricks to build Voicebox. MosaicML helps train LLM's more efficiently and more cost effectively. Stardog's semantic knowledge graph is the perfect complement to Databricks's #Dataintelligenceplatform and every Databricks implementation should check out Stardog in #PartnerConnect! Check out the link for more information. Navin Sharma|Kendall Clark|Ian Cohen

Navigating The Generative AI Divide: Open-Source Vs. Closed-Source Solutions As #businesses consider how to use #GenerativeAI in their organizations, there is an important question to answer: should they go for #opensource versus #proprietary #tools? In this article, we explore the differences, looking at the pros and cons of each. https://lnkd.in/eYHSjdXN