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Benchmarking llama.cpp on Arm Neoverse-based AWS Graviton instances with ClearML

By Erez Schnaider, Technical Product Marketing Manager, ClearML In a previous blog post, we demonstrated how easy it is to leverage Arm Neoverse-based Graviton instances on AWS to run training workloads. In this post, we’ll explore how ClearML simplifies the management and deployment of LLM inference using llama.cpp on Arm-based instances and helps deliver up to 4x performance compared to x86 alternatives on AWS. (Want to run llama.cpp directly?

10 Simple Ways To Improve Your Internet Security in 2025

You may have read about hackers using ChatGPT to impersonate your grandma. If that story made you dig a little deeper, you may have learned about the hyper-realistic phishing scams being concocted with generative AI. And if you’ve really gone into the cyber-security weeds, you may have discovered the new breed of infostealer malware stealing passwords and browser log-ins. All sounds very concerning right? Well, it needn’t do.

Optimizing Supply Chains with Data Streaming and Generative AI

It’s a truism that global supply chains are complex. The process of sourcing raw materials, transforming them into finished products, and distributing them to customers encompasses numerous systems (e.g., ERPs, WMSs, and TMSs). All systems within “the supply chain” are trending in the same direction; they’re aiming to be more efficient, resilient, and agile. Various technological developments have facilitated this directional trend.

Flutter vs React Native: Which one should you opt for your Business?

Every day, thousands of new apps make their way into the mobile app world. Remember 2018? That’s when app downloads shot up by 9%, and smartphone users spent a jaw-dropping $100 billion on apps. Crazy, right? Now, let’s talk about custom app development and cross-platform apps. By 2018, their market had already crossed $7.5 billion. But why are we going on about 2018?

Deploy AI Infrastructure in 2025: Serverless GPUs, Autoscaling, Scale to Zero, and More!

We’re on a mission to simplify application deployment for developers and businesses worldwide, whether they're AI-driven models, full stack applications, APIs, or databases. Our next-generation serverless platform significantly accelerates your deployments and improves efficiency, enabling you to build more with less spend. 2024 was a major year for us, packed with crucial serverless milestones.

Event-Driven AI: Building a Research Assistant with Kafka and Flink

This post was originally published on Medium on Nov. 20, 2024. The rise of agentic AI has fueled excitement around agents that autonomously perform tasks, make recommendations, and execute complex workflows blending AI with traditional computing. But creating such agents in real-world, product-driven environments presents challenges that go beyond the AI itself.

EP 6: To Prevent the Artificial Charlatan, Data Management Has to be Fun

The AI explosion has led to non-stop hype cycles as the technology continues to develop. But AI is only as good as the data behind it. The threat of lousy data is bad AI. Andrew Brust, Founder and CEO of Blue Badge Insights, joins The AI Forecast to discuss the AI hype–and how to prevent what he calls an “artificial Charlatan” of bad AI. He emphasizes the dependent relationship between data and AI and the former’s role in the success of the latter. Specifically, he addresses the data governance conundrum, and why in order for data technology to be successful, it has to be fun.

Vector Databases: Why QA professionals Needs to Care About them in the Age of AI? | Toni Ramchandani

In the rapidly evolving age of AI, vector databases have become the backbone of modern systems, revolutionizing the way high-dimensional data is managed and queried. In this insightful session, Toni Ramchandani explores why QA professionals must adapt their skills and approaches to meet the unique demands of vector databases. Traditional testing methods fall short in addressing challenges like similarity search, vector indexing, and performance optimization.

6 Best Practices for Implementing Generative AI

Generative AI has rapidly transformed industries by enabling advanced automation, personalized experiences and groundbreaking innovations. However, implementing these powerful tools requires a production-first approach. This will maximize business value while mitigating risks. This guide outlines six best practices to ensure your generative AI initiatives are effective: valuable, scalable, compliant and future-proof.