Analytics

Telecommunications Data Monetization Strategies in 5G and beyond with Cloudera and AWS

The world is awash with data, no more so than in the telecommunications (telco) industry. With some Cloudera customers ingesting multiple petabytes of data every single day— that’s multiple thousands of terabytes!—there is the potential to understand, in great detail, how people, businesses, cities and ecosystems function.

Fine-Tuning a Foundation Model for Multiple Tasks

In this video we discuss the reasons why fine-tuning is needed to create mroe contextual accurate LLMs, and the methods that you can do to accomplish this. We also give a demo of our newest Applied ML Prototype (AMP) which demonstrates how to implement LLM fine-tuning jobs that make use of the QLoRA and Accelerate implementations available in the PEFT open-source library from Huggingface and an example application that swaps the fine-tuned adapters in real time for inference targetting different tasks. Learn more at cloudera.com#ai #ml.

Building Airtight Data Security Architecture in Growing Businesses

In the second installment of Mavericks of Data, we have an engaging discussion with Mahesh Krishnan, CTO of Fujitsu Australia and innovator, thought leader, author, speaker, and passionate technologist who has over 30 years of experience in the IT sector. Mahesh talks about his role within Fujitsu, the recent developments and key considerations in data security, setting up data security within growing businesses and the challenges revolving around data sensitivity.

FinOps Camp Episode 3: Considerations for Mapping your FinOps Adventure

FinOps Camp Episode 3: Considerations for Mapping your FinOps Adventure Program elements, use cases, and principles to manage cloud data costs Join SanjMo Principal and Founder Sanjeev Mohan and Unravel VP of Solutions Engineering Chris Santiago as we share considerations for mapping your FinOps Adventure.Creating a solid FinOps strategy is crucial to navigating the rapidly-evolving world of cloud services.

MLOps Live #24: How to Build an Automated AI ChatBot

In this MLOps Live session, Gennaro, Head of Artificial Intelligence and Machine Learning at Sense, describe how he and his team built and perfected the Sense chatbot, what their ML pipeline looks like behind the scenes, and how they have overcome complex challenges such as building a complex natural language processing ( NLP) serving pipeline with custom model ensembles, tracking question-to-question context, and enabling candidate matching.