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AI and Software Development: Preview of Sessions at InfoQ Events

AI is reshaping software development. At InfoQ's upcoming events, senior software developers will share their practical applications and ethical considerations of this transformative technology. Here's a preview of what you can expect:

InfoQ Dev Summit Boston (June 24-25)

Keynote: Being a Responsible Developer in the Age of AI Hype

Justin Sheehy, chief architect @Akamai, will address developer responsibilities in the rapidly evolving AI landscape. His keynote will focus on navigating the hype around AI, using AI systems wisely, and creating AI solutions that minimize harm. Learn how to discern hype from reality to build trustworthy AI applications.

Best Practices for Deploying Large Language Models in Production

Francesca Lazzeri, principal director of data science and AI @Microsoft, author of several books on applied machine learning and AI, will delve into the intricacies of deploying large language models (LLMs) in real-world settings. This session will share the latest best practices for LLM deployment, covering critical aspects such as computational costs, data quality, model robustness, user satisfaction, and ethical considerations. Learn about selecting the right model, optimizing performance, and ensuring a scalable, secure infrastructure.

InfoQ Dev Summit Munich (September 26-27)

Taking LLMs out of the Black Box: a Practical Guide to Human-in-the-Loop Distillation

Ines Montani, co-founder & CEO @Explosion, will share practical solutions for integrating state-of-the-art NLP models into real-world applications. This session will explore methods for distilling LLMs into smaller, more manageable components that maintain transparency and data privacy.

Efficient DevSecOps Workflows with a Little Help from AI

Michael Friedrich, senior developer advocate @GitLab, will cover enhancing DevSecOps workflows using AI. This talk will explore practical prompts, custom LLMs, and AI agents to streamline tasks such as MR reviews, security analysis, and CI/CD pipeline debugging.

Leveraging Open-Source LLMs for Production

Andrey Cheptsov, founder and CEO @dstack, will explore the benefits and challenges of using open-source LLMs in production. This session will highlight the economics of fine-tuning and hosting these models, serving frameworks, and key open-source LLM options.

Creating Your Own LLM from Opensource Models

Sebastiano Galazzo, CTO @Synapsia AI, will guide attendees through creating custom LLMs from open-source models. The talk will cover techniques such as LoRa, quantization, and mixing models to develop a Mixture of Experts model.

QCon San Francisco (November 18-22)

Track: Getting Started in Machine Learning

This track, hosted by Susan Shu Chang, principal data scientist @Elastic, author of "Machine Learning Interviews," will provide a comprehensive introduction to machine learning. Attendees will gain an understanding of both theoretical concepts and practical tools essential for ML development.

Track: Generative AI in Production & Advancements

Hien Luu, senior engineering manager @DoorDash & author of Beginning Apache Spark 3, speaker, and conference committee chair, will host this track focusing on the latest advancements in generative AI. The sessions will explore real-world applications of generative AI across industries and discuss the challenges and opportunities in leveraging AI-generated content, data, and code.

Join us to learn from senior software developers pushing the boundaries to help you stay ahead in the evolving AI software development landscape.

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