K2view’s Post

On 14th November, Jim Sterne will talk about the impact of Generative AI for digital analysts. He will start from the ground up, so if you are also a beginner, this is the place to be. https://ow.ly/UR3F50PRRKl #MASConf #marketinganalyst #marketinganalytics #workshop

I love this chart for two reasons. First, it shows how serious Manufacturers and Retailers - both process driven industries - have become about embedding ML into their business. ML is mainstream. Second, even industries that are less process driven and more experimental such as Financial Services (evaluating companies or investment hypotheses) and Health and Life Sciences (drug discovery) have refined their approaches. The initial wave of Machine Learning is over and companies are extracting real value.

Great news on organizations quickly becoming more efficient with putting machine learning models into production: Based on the ratio of (the number of) logged ML experiments to actually deployed/registered models, the average efficiency increased by a factor of 3 in only 14 months! The data for this evaluation stems from MLflow (as open source MLOps platform). And looking at the results separately, the number of registered models even increased by a factor of 10 (!) within a single year. The number of companies registering at least one model was up by 210%! All in all, great data to show that the GenAI wave also accelerates ML production adoption in general! Thanks Databricks for the insightful report! #mlflow #ml #ai

Learn how you can Get Started using Generative #AI and generate your own large language model (LLM) to harness your own data to improve your productivity. This is an Amazing presentation on Gen. AI by Ginger Grant RSVP Now with link in the post below Follow Adriano da Silva to Learn about Microsoft Fabric, Data Architecture, Data Engineering, and AI using Databricks, Azure Synapse, Snowflake, Power BI, and more. #DataAnalytics #DataEngineering

11x more AI models successfully made it into production in the last year. Data and AI is hard but many of our customers are realising the value from their use cases having developed a robust approach to MLOps and actually getting them into production! Based on recent customer engagements had a gut feeling this was the case but it’s great to see this analysis of our customer base and the stats behind it.

Interesting post to review for any Data Professionals that are responsible for building and putting ML models into production! Our data shows that organizations have become 3x more efficient at putting ML models into production in just 14 months. They're spending fewer resources on experimental models that never provide real-world value. We break down these trends and more in the State of Data + AI, which examines usage data from our 10,000+ global customers. https://dbricks.co/3KB4OIK Activate to view larger image,

In a recent article on R&D - Research & Development World, Stravito's CEO Thor touched on our newly announced Assistant. “Early uses of generative AI for insights have shown us that getting the best results requires asking the right questions and receiving summarized answers based on contextualized, easily provable data,” Philogène continued. “By making Stravito Assistant more conversational and context-aware, we’ve ensured users can easily navigate a knowledge space and reduce time-to-insight securely and transparently.” (Read the full article in the comments.) If you are interested in seeing what this looks like in action, you can join our masterclass, Turn Insights Into Action with Stravito Assistant, on Tuesday, April 30 @ 9 am ET. Sign up below: https://lnkd.in/gSrsnEiR

In the era of AI, applications like vector databases have immense scope for growth. Especially since they are critical to managing large chunks of data. But what exactly are they, and how are they the key to bridging the gap between AI models and raw data? More details in our blog: https://hubs.li/Q01_LJcV0 #VectorDatabases #AIModels #ArtificialIntelligence

This is a great chart which shows just how efficient it is to get your data science team set up on databricks. If you want to see more DS projects make it to production, the right platform is the key! At Tempered AI, we have experienced consultants that can help your team accelerate adopting MLOps on Databricks.

Read our latest Ipsos Views on Text Analytics as we draw on our 15 years of experience and using our AI framework from Truth, Beauty and Justice, we outlined 5 key lessons when applying LLM-powered Generative AI tools. The article can be found here: https://lnkd.in/gxh2HZuV #textanalytics #generativeai #customerexperience