AI & Machine Learning
Forever Junior: The Skills AI Can’t Develop For You
Told to use AI but still ‘keep a hand on the wheel’? AI writes code, but it can’t make Seniors. Here’s how Junior can use agents and still evolve.
From Copilot to Code Agents: How GenAI Is Changing Engineering
Explore how GenAI is reshaping software engineering: from Copilot and code agents to automated review, QA, guardrails, and human judgment.
Introducing CLEPR, our model for semantic understanding
Discover CLEPR, Criteo’s deep learning model for semantic search and product retrieval, improving relevance and retail media performance at scale.
Beyond the demo: Why agentic evaluation matters
Agentic systems powered by LLMs can be incredibly impressive in demos. With a few well-crafted prompts, they can demonstrate reasoning, calling tools, and solving complex tasks [1]. Demos are effective at showcasing what’s possible. Production environments, however, are where those capabilities are tested at scale and under real-world conditions. The same agent that performs perfectly…
The Gumbel‑Max Trick Made Intuitive
When we work with machine learning models, we constantly turn probabilities into discrete choices. Which ad do we show? Which action do we sample in a reinforcement learning policy? Which word comes next in a language model? All these problems share the same core operation: We have a list of options, each with an associated…
Leveraging Commerce Data for Outcome-Based Relevancy in Agentic Recommendation Systems
Learn how commerce data improves outcome-based relevance in agentic recommendation systems, delivering 37% better retrieval and 60% better SKU re-ranking.
Video Ads: Introducing video interactivity in production
At the end of 2024, Criteo’s Video R&D team started working on a new goal: adding recommended products on top of videos, so that each display delivered to someone on the Open Web would become the most relevant possible. Over the last two decades, Criteo has continuously advanced its recommendation engine. Good news: From now…
Criteo Boosts Ad Performance with Latest AI Advancements
Abstract. Everyone talks about AI today, and it seems AI has become an off-the-shelf tool providing plug-and-play capabilities. However, when addressing the hardest problems, such as those arising in the Commerce Media and AdTech industry, things are far more complex and require advanced AI (more specifically, machine learning) expertise. In this post, we share the…
How RecSys & LLMs Will Converge: Architecture of Hybrid RecoAgents
Recommender systems have become critical infrastructure in commerce. Their role is not only to surface relevant items but also to shape how users explore, compare, and decide. Improvements in recommendation translate directly into superior business outcomes: higher engagement, more conversions, stronger loyalty, and more efficient allocation of marketing budgets. Over the last couple of years,…
Agents, APIs, and Advertising: Lessons From Engineering Our MCP Server
MCP, Model Context Protocol, has made quite some noise in the past year as it promises a simpler, user-driven, integration of tools into Large Language Models (LLMs). At Criteo, we believe that MCP will be key to empowering our clients and giving them the control to create and manage advertising campaigns in a new way:…
