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cloudera

The Evolution of LLMOps: Adapting MLOps for GenAI

Oct 22, 2024 By Meeta Dash In Cloudera
In recent years, machine learning operations (MLOps) have become the standard practice for developing, deploying, and managing machine learning models. MLOps standardizes processes and workflows for faster, scalable, and risk-free model deployment, centralizing model management, automating CI/CD for deployment, providing continuous monitoring, and ensuring governance and release best practices.
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Cigniti

AI's Impact on Human Intelligence: Are We Getting Smarter or More Dependent?

Oct 21, 2024 By Cigniti Technologies In Cigniti
Artificial Intelligence (AI) has become an inseparable part of our lives, revolutionizing industries, transforming workspaces, and influencing how we interact with technology. From virtual assistants like Siri and Alexa to advanced machine learning algorithms driving breakthroughs in medicine, AI is everywhere. But as AI continues to evolve, a growing question lingers: Is AI making us smarter or more dependent?
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iguazio

Gen AI for Marketing - From Hype to Implementation

Oct 20, 2024 By Sahar Dolev-Blitental In Iguazio
Gen AI has the potential to bring immense value for marketing use cases, from content creation to hyper-personalization to product insights, and many more. But if you’re struggling to scale and operationalize gen AI, you’re not alone. That’s where most enterprises struggle. To date, many companies are still in the excitement and exploitation phase of gen AI. Few have a number of initial pilots deployed and even fewer have simultaneous pilots and are building differentiating use cases.
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astera

The Defense Can Rest While AI Handles The Legal Documents

Oct 18, 2024 By Raza Ahmed Khan In Astera
What’s one thing all your favorite legal shows have in common? Whether it’s Suits or The Lincoln Lawyer, they rarely show the amount of paperwork lawyers have to handle on a daily basis. Understandably so, paperwork isn’t the most glamorous part of the job but that doesn’t mean it’s not crucial. In fact, lawyers deal with tens, if not hundreds, of documents on a daily basis during most parts of their job, such as discovery, research, or drafting.
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yellowfin

The History of Chatbots: A Timeline of Conversational AI

Oct 17, 2024 By Yellowfin Team In Yellowfin
From ancient Greek myths of talking statues to the modern-day Alexa and Siri, the concept of machines capable of understanding and responding to human language has captivated us for centuries. In recent years, this concept has evolved into AI chatbots, highly sophisticated tools that can read our queries and perform tasks ranging from customer service to automated alerts.
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databox

AI Adoption in SMBs: Key Trends, Benefits, and Challenges from 100+ Companies

Oct 17, 2024 By Databox In Databox
AI Adoption in SMBs: Key Trends, Benefits, and Challenges from 100+ Companies With larger competitors already using AI to streamline operations and gain a competitive edge, SMBs can’t afford to fall behind. But for many, adopting AI is easier said than done. Limited budgets, lack of in-house expertise, and the fear of wasting time and resources on the wrong tools often leave business owners stuck in decision paralysis.
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kong

RAG Application with Kong AI Gateway, AWS Bedrock, Redis and LangChain

Oct 17, 2024 By Claudio Acquaviva In Kong
For the last couple of years, Retrieval-Augmented Generation (RAG) architectures have become a rising trend for AI-based applications. Generally speaking, RAG offers a solution to some of the limitations in traditional generative AI models, such as accuracy and hallucinations, allowing companies to create more contextually relevant AI applications.
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Episode 11: The future of data lakes: Open table formats, metadata and AI | AWS

Oct 17, 2024 By Fivetran In Fivetran
Paul Meighan, Director of Product Management at AWS, shares how enterprises are increasingly looking for ways to integrate more data sources in their environment — especially with data lakes. From turning S3 buckets into databases to establishing better metadata layers, Meighan explores the rapid evolution of data lakes alongside data warehouses. He also explains the pivotal role AI, ML and GenAI workloads and applications will play in large metadata environments, driving innovative analytics and business insights.
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