dotConferences

Introducing dotAI 2026's Full Speaker Lineup on Sept 17 in Paris:
-Ziv Ilan - AI Labs at @nvidia
-@spolu - Co-Founder at @DustHQ
-Marta Garnelo - Chief Science Officer at @Fundamental
-@dlouapre - AI Scientist & Educator at @huggingface
-Ian Massingham - Head of Applied AI, EMEA Startups at @AnthropicAI
-Pierre-Edouard Lieb - AI Deployment Manager at @OpenAI
-Patrick Brosset - Developer Relations PM at @MicrosoftEdge
-Gaëtan Brison - AI Manager at @doctolib
-Pierre-Louis Cedoz - Head of Research at @hcompany_ai
-Guillaume Vernade - Senior Developer Advocate at @GoogleDeepMind

Lightning talks speakers:
-Guillaume Blaquiere - Group Data Architect at @CarrefourFrance
-@gregqualls - Head of PM & Content at @upsundotcom, Co-Builder of askcodex.ai
-Léo Arsenin - Solutions Engineer at @Cloudflare
-Hélène Philippe - Machine Learning Researcher at @raidium_med
-@ngxson - Software Engineer at @huggingface
-Aygalic Jara - PhD researcher at Université Paris-Saclay × SCIAM

Talk titles dropping soon, follow along for the full schedule!

Grab your ticket now dotai.io

What if your local LLM could answer faster without changing the model you’re running?

In “llama.cpp - Faster and Easier for Everyone!” Xuan-Son Nguyen takes us inside speculative decoding: how llama.cpp drafts tokens to speed up inference, using methods like draft models, n-grams, MTP and DFlash / DSpark. The talk wraps up with a live demo - and a look at how quickly you can get started.

@ngxson is a software engineer at @HuggingFace, a core maintainer of llama.cpp and a contributor to open-source LLM tooling and on-device AI.

🟡 Replay here: youtube.com/watch?v=bq1cSr…

What if an AI could use a website without guessing where to click?

In “WebMCP: Stop Scraping the Web, Start Calling It,” Patrick Brosset explores a more reliable way for AI agents to get things done online. Instead of interpreting pages and guessing at clicks, agents can use explicit tools - with structured calls that developers and users can inspect. The talk looks at how this approach could make web workflows less brittle, even as interfaces change.

Patrick is a Developer Relations PM at @MicrosoftEdge. He’s spent more than two decades building web apps and working to improve interoperability, developer experience and tooling across Firefox and Chromium.

🟡 Enjoy the replay: youtube.com/watch?v=3NDly3…

As AI agents write more code, how will developers decide what to trust?

In “Will the Future of Code Be Formal or Informal?”, Stanislas Polu looks at a new bottleneck for software teams: reviewing agent-generated code. He explores whether agents could make formal methods practical, and whether developers might one day move beyond code altogether.

His argument: the future probably lies between prose and proof, with code supported by focused, structured natural-language contracts that people can review and agents can check.

@spolu is co-founder of @DustHQ, which helps enterprises build AI agents using internal data and tools. Before that, he worked on reasoning and automated theorem proving at OpenAI and co-founded TOTEM, later acquired by Stripe.

Watch: youtube.com/watch?v=eg8u-0…

When the question is “What happens next?”, maybe don’t ask a language model to write you an essay about it.

In “AI for Prediction: Why You Need a Statistician, Not a Philosopher,” Kevin Scaman explores why language models and tabular models excel at different things. Through simple experiments, he looks at where LLMs fall short on prediction - and how models trained on structured data can help with decisions like forecasting demand, spotting risk or predicting customer churn.

Kevin is an ML researcher at @Fundamental, where he works on tabular foundation models. Before that, he was a research scientist at Inria Paris, an Associate Professor at École Polytechnique and led an optimization-for-ML team at Huawei’s Paris lab. He also received a NeurIPS Best Paper Award in 2018 for his work on distributed optimization.

🟡 Replay: youtube.com/watch?v=EbUa-L…