InfoQ HomepageMachine Learning Content on InfoQ
- Posted by Michelle Brush on Nov 24, 2025
Humans in the Loop: Engineering Leadership in a Chaotic Industry
Michelle Brush discusses engineering leadership in the age of AI/ML and automation.
on Nov 24, 2025%2fpresentations%2fai-ml-jobs%2fen%2fmediumimage%2fmichelle-brush-medium-1761904230413.jpg&f=jpg&w=240)
Icon48:25 - Posted by Vivek Gupta on Nov 10, 2025
Growing and Cultivating Strong Machine Learning Engineers
Vivek Gupta explains how to nourish and cultivate Machine Learning engineers, detailing the unique production-ML skills required for scaling, governance, and LLMOps.
on Nov 10, 2025%2fpresentations%2fml-skills%2fen%2fmediumimage%2fvivek-gupta-medium-1761903010855.jpg&f=jpg&w=240)
Icon38:15 - Posted by Adi Polak on Nov 07, 2025
Achieving Precision in AI: Retrieving the Right Data Using AI Agents
Adi Polak discusses achieving precision in GenAI by moving beyond RAG to Agentic RAG. She details agent patterns, feedback loops, and using data streaming architectures to scale real-time AI.
on Nov 07, 2025%2fpresentations%2fai-precision-rag-agents%2fen%2fmediumimage%2fadi-polak-medium-1761732116601.jpg&f=jpg&w=240)
Icon50:00 - Posted by Iaroslav Amerkhanov on Aug 27, 2025
AI for Food Image Generation in Production: How & Why
Iaroslav Amerkhanov discusses how his team at Delivery Hero leveraged GenAI to generate food images, detailing the architecture, optimization, and business impact.
on Aug 27, 2025%2fpresentations%2fai-food-image-generation%2fen%2fmediumimage%2fiaroslav-amerkhanov-medium-1755673680242.jpg&f=jpg&w=240)
Icon44:46 - Posted by Victor Dibia on Aug 14, 2025
10 Reasons Your Multi-Agent Workflows Fail and What You Can Do about It
Victor Dibia discusses multi-agent systems, detailing how to build them with AutoGen, common failure points, and strategic approaches for senior software developers and engineering leaders.
on Aug 14, 2025%2fpresentations%2fmulti-agent-workflow%2fen%2fmediumimage%2fvictor-dibia-medium-1753425805213.jpeg&f=jpg&w=240)
Icon48:24 - Posted by Bibek Bhattarai on Jul 31, 2025
Maximizing Deep Learning Performance on CPUs using Modern Architectures
Bibek Bhattarai demystifies Intel AMX, explaining how this CPU architecture accelerates deep learning workloads via low-precision matrix multiplication and efficient data handling.
on Jul 31, 2025%2fpresentations%2fdl-cpu-architecture%2fen%2fmediumimage%2fbibek-bhattarai-medium-1752752658387.jpg&f=jpg&w=240)
Icon39:25 - Posted by Denys Linkov on Jul 01, 2025
A Framework for Building Micro Metrics for LLM System Evaluation
Denys Linkov discusses critical lessons for senior developers and leaders on building robust LLM systems and actionable metrics that prevent production issues and drive business value.
on Jul 01, 2025%2fpresentations%2fmicro-metrics-llm%2fen%2fmediumimage%2fdenys-linkov-medium-1751009162618.jpg&f=jpg&w=240)
Icon29:10 - Posted by David Berg on Jun 17, 2025
Supporting Diverse ML Systems at Netflix
David Berg and Romain Cledat discuss Metaflow, Netflix's ML infrastructure for diverse use cases from computer vision to recommendations.
on Jun 17, 2025%2fpresentations%2fml-netflix%2fen%2fmediumimage%2fdavid-romain-medium-1748590470447.jpg&f=jpg&w=240)
Icon49:00 - Posted by Sebastiano Galazzo on Apr 23, 2025
From "Simple" Fine-Tuning to Your Own Mixture of Expert Models Using Open-Source Models
Sebastiano Galazzo shares practical tips and mistakes in creating custom LLMs for cost-effective AI. Learn LoRA, merging, MoE & optimization.
on Apr 23, 2025%2fpresentations%2fmixture-expert-models%2fen%2fmediumimage%2fsebastiano-galazzo-medium-1744710295307.jpg&f=jpg&w=240)
Icon48:19 - Posted by Leo Browning on Apr 22, 2025
How Green is Green: LLMs to Understand Climate Disclosure at Scale
Leo Browning explains the journey of developing a Retrieval Augmented Generation (RAG) system at a climate-focused startup.
on Apr 22, 2025%2fpresentations%2frag-llm%2fen%2fmediumimage%2fleo-browning-medium-1741333444936.jpeg&f=jpg&w=240)
Icon47:29 - Posted by Stefania Chaplin on Apr 17, 2025
LLM and Generative AI for Sensitive Data - Navigating Security, Responsibility, and Pitfalls in Highly Regulated Industries
Stefania Chaplin and Azhir Mahmood discuss responsible, secure, and explainable AI in regulated industries. Learn MLOps, legislation, and future trends.
on Apr 17, 2025%2fpresentations%2fllm-ml-security%2fen%2fmediumimage%2fazhir-stefania-medium-1741181597784.jpg&f=jpg&w=240)
Icon43:50 - Posted by Anil Rajput on Apr 07, 2025
Unleashing Llama's Potential: CPU-Based Fine-Tuning
Anil Rajput and Rema Hariharan detail CPU-based LLM (Llama) optimization strategies for performance and TCO reduction.
on Apr 07, 2025%2fpresentations%2fllama2%2fen%2fmediumimage%2fanil-rajput-rema-hariharan-medium-1743448668469.jpg&f=jpg&w=240)
Icon48:11
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Resources
Build a "Hello World" tiny AI Agent (Blog)
In this article, we’ll show you a tiny AI agent built with Orkes Conductor. It can make sense of a user’s query, call a tool when it needs extra info, remember what happened along the way, and pull everything together into a final answer.Learn more.
The Future of Business Process Orchestration (on-demand webinar)
In this webinar, we’ll explore how process orchestration and Agentic AI are redefining automation, enabling businesses to integrate AI-driven decision-making, streamline workflows, and scale seamlessly.Watch Now.
Agentic Orchestration for e-Commerce (Case Study)
As part of its digital transformation, Naveo set out to build a next-generation platform that reimagines enterprise order processing through the lens of AI. The vision: shift from rigid automation to intelligent, autonomous orchestration powered by agentic AI.Learn more.
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