LLMs through my last 3 professions: an interdisciplinary approach

James Donahue

We have heard a lot about LLMs from tech experts, but what do an economist, an English teacher, and a tourism manager have to say about it? Fortunately, I've been all three and would love to share my ...

Quantum Machine Learning with Qiskit

Artem Konotpchyk, Manta Ribkauskyte

Quantum Machine Learning (QML) combines quantum computing and classical machine learning, but its practical value is often misunderstood. In this hands-on workshop, we will explore QML using Qiskit, b...

AI & Ethics

PJ Hagerty

It's been in the news, everywhere. Artificial Intelligence is the next thing in the evolution of technology. While it's probably not the end of everything as some sources say, it's likely true to chan...

Reading the Mind of an LLM

Luca Baggi, Gabriele Orlandi

What if you could watch an AI’s thought take shape? For years, LLMs have been impenetrable "black boxes," but we are finally beginning to find ways to see how the ghost in the machine actually works. ...

Friend or Foe? AI at Play in Cybersecurity

Cheuk Ting Ho

AI is a double-edged sword in cybersecurity. This talk explores its dual role. Why AI excels: Vast open-source training data and profit-driven, coding-optimized models make AI a fast, multi-domain ex...

Stop Guessing: Build Feedback Loop for Prompt Engineering

Tadas Goberis

Most teams iterate on prompts by eyeballing outputs and hoping for the best. This talk presents a different approach: connect your prompt to a measurable downstream outcome, build a test set, and let ...

From OpenAI to DeepSeek: New Scaling Laws for LLMs that can Reason

Luca Baggi

With o1, OpenAI ushered a new era: LLMs with reasoning capabilities. This new breed of models broadened the concept of scaling laws, shifting focus from train-time to inference-time compute. But how d...

Attacking Toughest and Messiest Tech Challenges with AI

Egidijus Pilypas

Legacy migrations, tangled integrations, undocumented business logic – every team has that category of work nobody wants to touch. This talk shares practical lessons from using AI to tackle exactly th...

Lightning Talks

TBD

Measuring Experiments in LLMs: A/B Tests and Automated Testing

Özge Çinko, Kader Miyanyedi

Even small changes in LLMs can impact output quality, safety, and user experience. In this talk, we’ll show how to log experiments with Langfuse, automate tests with Pytest, and enrich them using Hypo...

Beyond the Prompt: Building Research Agents in Python

Simona Skiotytė

LLMs can answer questions, but can they conduct research? Real research requires planning, data gathering, synthesis, and refinement. This talk explores Python patterns for orchestrating multi-step wo...

Software Development Now Costs Less Than Minimum Wage

Geoffrey Huntley

The cost of software development has fallen to $10.42 an hour—less than minimum wage. A burger flipper at Macca's earns more. What does it mean to be a software developer when everyone in the world ca...

Vibe reverse engineering of old games and new hardware

Piotr Migdał

Reverse engineering binaries once required deep expertise. Today, AI models like Opus 4.6, GPT-5.3-Codex, and Gemini 3.1 Pro change the rules. Watch how pairing AI with the NSA's Ghidra decompiler or ...

XAI - Explainable AI tools and techniques

Viraj Sharma

In this talk, I propose to discuss the problem of building explainable AI with the two approaches - causal vs correlational. I will talk about what mech interp in LLMs. As a way to understand how mode...

AI and Agency: As Developers, We Decide The Future

Tadas Korris

AI systems are not neutral; they encode values that are opaque and separate from people. As developers, we are making decisions that shape who has power, who is surveilled, who is replaced, and who ge...

From Data Collection to Partner Delivery: Shipping a Paraphrasing Skill on Small Language Models

Marat Saidov

I'll discuss building capabilities on top of on-device language models, with Rewrite as a case study – a publicly available paraphrasing skill that is widely used across Microsoft's products. I'll cov...

Context Engineering with DeepAgents: Write, Select, Compress, Isolate

Antanas Daujotis

Context Engineering is the new prompt engineering. As agentic workflows grow, just appending messages to a list causes context poisoning and latency spikes. In this talk, we'll look at a better archit...

AI-Assisted Development in Practice: Chatbot + Agentic Testing from Scratch

Alex Marmuzevich

GenAI-based projects are easy to prototype, but hard to test. In this hands-on workshop, we will build a simple AI chatbot from scratch and, in parallel, create an AI agent that tests it during develo...

Death by a Thousand Prompts: Can Our Disclosure Standards Survive AI Slop?

Jarek Potiuk

AI-generated "slop" is overwhelming vulnerability triage and burning out maintainers. This session focuses on building a unified framework to identify and "black-hole" synthetic noise at scale. We wil...

What It Means to Be a CTO in an AI Startup Today

Fabien Vauchelles

**I haven't written a single line of code in over a year.** As CTO of an AI startup, I've fully embraced vibe coding: orchestrating AI to generate production-ready code. 🔍 **Highlights** 1. **Th...

Engineering Complex AI solutions: Observability and Testing of multi-Agent Solutions

Dmitri

As AI agents evolve from simple chatbots to complex multi-agent systems utilizing Model Context Protocol (MCP), manual validation becomes impossible. During this talk, I will demonstrate the process o...

Beyond Basic RAG: Boosting Accuracy with Hybrid Search and Fusion Algorithms.

Piti Champeethong

Retrieval-Augmented Generation (RAG) often produces incorrect results when relying solely on vector-based similarity. While vector search is strong, it fails on exact keywords, acronyms, and domain-sp...