Hotel Metropol, Belgrade
18th-22nd November 2024
DSC Europe 24 SCHEDULE
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Ivo Andric B
NLP
Revolutionizing Information Access: All World Knowledge in Billions of Connected Nuggets
NLP
Decline of traditional web with emerging generative AI and social media platforms drastically change the way we access information. This talk will present YottaAnswers’ mission of bringing access to high quality and diverse information to people all over the world, enabling them to acquire sound knowledge. We built Yottaanswers Smart Answer Engine technology with tens of billions of possible answers to questions and integrated it into a product that self-explores knowledge leveraging Generative AI.
09:30
–
10:00
Revolutionizing Information Access: All World Knowledge in Billions of Connected Nuggets
Miodrag Vladic
Co-founder & Lead Software Engineer @ YottaAnswers
Overcoming Loneliness with LLM Dating Assistant
NLP
Business talk
Intermediate
In today’s AI-driven world, every industry is racing to harness the power of AI and LLMs, and social discovery is no different. Social Discovery Group builds innovative dating and entertainment apps aiming to solve the problem of loneliness. Have you ever felt hesitant about what to say to a match? We’re building an AI assistant that helps our users communicate more effectively with potential matches, overcoming shyness and fear of rejection. This talk will describe our approach to developing, testing, and iterating on this LLM-powered assistant – from data analysis and model training to A/B testing and real-world deployment.
10:00
–
10:30
Overcoming Loneliness with LLM Dating Assistant
Dani El-Ayyass
Head of AI Transformation @ Social Discovery Group
How AI Automates International Trade, Boosts Profitability – and Where It Fails: A Practical Talk
NLP
Technical talk, Business talk
Intermediate
In his insightful presentation, Peter Piehler will explore how AI supports critical processes in international trade, helping companies to future-proof their operations, minimize risks, enable transactions, and maximize profits. He will also shed light on the current limitations of AI and the reasons behind its failures. The talk will delve into why AI does not replace natural language processing (NLP) and why NLP is essential for delivering high-quality performance. Mr. Piehler will discuss the implementation of quality assurance and plausibility checks for AI-supported responses. The advantages of argumentative AI over traditional prompt-and-respond approaches will be examined. Technologies will be introduced, and experiences shared, with the hope of passing on the enthusiasm for open-source AI. To conclude, Mr. Piehler will venture a forecast on how technology is transforming the software industry market, specifically for software in international trade.
10:30
–
11:00
How AI Automates International Trade, Boosts Profitability – and Where It Fails: A Practical Talk
Peter Piehler
CEO @ PST.AG
Intelligent Interfaces and operating systems
NLP
Technical talk
Advanced
The promise of AI-based automation is the future in which work is carried out by fleets of interacting digital and embodied agents. However, for such a vision to be viable in practice, a digital ecosystem must exist to mediate between agents—digital and biological. We created a hybrid toy operating system, combining the non-deterministic language capabilities of the current generation large language models with traditional programming language interpreters to arrive at a new multi-interpreter approach. We explore agentic program prototypes—a new hybrid kind of app written in a hybrid natural-programming language which blurs the line between a prompt, a program and a user-interface. Our early experiments and toy models indicate a clear pathway towards future operating systems in which agent- and user-interfaces are negotiated by the very agents orchestrated by the operating system.
11:00
–
11:30
Intelligent Interfaces and operating systems
Igor Sevo
Head of Artificial Intelligence @ HTEC
Keynote: Fighting AI with AI
Keynote
Technical talk, Business talk, Research talk, Educational talk
Intermediate
How do we tell what’s true and what’s not? In a world where artificial intelligence presents both promises and perils, we find ourselves in a unique position: harnessing the very technology that threatens to undermine truth and authenticity to defend against it. In this presentation, we’ll discuss How Do Deepfakes Work? Real-life examples of fraud perpetrated using deepfake techniques. And what can be done? [Deep Fake Voice Detection (Behavioral Signals)]
12:00
–
12:45
Keynote: Fighting AI with AI
Rana Gujral
CEO @ Behavioral Signals
Keynote: Data-Driven Success: Securing Executive Buy-In for a Game-Changing Data Strategy
Keynote
Business talk
Beginner to Intermediate
In today’s data-driven landscape, aligning your data strategy with organizational objectives is critical for achieving sustainable growth and gaining competitive advantage. This session explores the process of developing a robust data strategy that not only supports and enhances your company’s strategic goals but also delivers tangible value across the enterprise. Learn how to effectively communicate the importance of data initiatives to senior leadership, ensuring executive buy-in and support. We will delve into best practices for identifying key performance indicators, integrating data insights into decision-making processes, and demonstrating ROI to stakeholders. Join us to discover actionable steps to create a cohesive data strategy that drives business success and secures the commitment of your executive team.
12:45
–
13:30
Keynote: Data-Driven Success: Securing Executive Buy-In for a Game-Changing Data Strategy
Amie Bright
VP Enterprise Data & Insights @ GitLab
Keynote: All About Biases in Artificial Intelligence
Keynote
Karen Pesse, a globally recognized leader in STEM and sought-after international speaker, addresses in her talk various topics such as biases, data gap, and its influence in artificial intelligence. A graduate in Nanotechnology Engineering and holding a Master’s in Sustainable Materials Engineering from Ghent University, Karen has received nearly 20 awards for her outstanding contributions. Named Data Activist for Women in STEM by NATO, she hopes to shine a light on how biases are affecting technology today and what we need to do to build safer technology for the future.
14:30
–
15:15
Keynote: All About Biases in Artificial Intelligence
Karen de Sousa Pesse
Senior Executive @ Salesforce
Where there’s a will, there’s a way: The mad genius of LLMs as classifiers
NLP
Technical talk
Beginner
Have you ever wanted to build a trillion-parameter labelling machine? And by that I mean, would you use a Large Language Model to solve a classification problem?
It’s an unlikely fit for an LLM. Classifiers typically need to be fast, accurate, and interpretable. LLMs are slow, random black-boxes. Classifiers need to output a single label. LLMs never stop talking.
And yet, there are good reasons to use LLMs for such tasks, and emerging architectures and techniques to do so. Many real-world use cases need a classifier—whether it’s their end goal or just a step in a larger process—and many data and product development teams will soon find themselves wondering, could GPT handle that?
If that sounds like you, then join me for a deep dive into how we’re tackling this issue while building a next generation conversational assistant at Switzerland’s largest telecommunications provider. I’ll cover:
– Why reducing language to labels is conceptually problematic, but practically useful
– Why classification with LLMs is a weird idea, but you might want to do it anyway
– Possible approaches and architectures
– Customer intent detection as a real-world use case
– Universal challenges, and our lessons learned so far
It’s an unlikely fit for an LLM. Classifiers typically need to be fast, accurate, and interpretable. LLMs are slow, random black-boxes. Classifiers need to output a single label. LLMs never stop talking.
And yet, there are good reasons to use LLMs for such tasks, and emerging architectures and techniques to do so. Many real-world use cases need a classifier—whether it’s their end goal or just a step in a larger process—and many data and product development teams will soon find themselves wondering, could GPT handle that?
If that sounds like you, then join me for a deep dive into how we’re tackling this issue while building a next generation conversational assistant at Switzerland’s largest telecommunications provider. I’ll cover:
– Why reducing language to labels is conceptually problematic, but practically useful
– Why classification with LLMs is a weird idea, but you might want to do it anyway
– Possible approaches and architectures
– Customer intent detection as a real-world use case
– Universal challenges, and our lessons learned so far
15:15
–
15:45
Where there’s a will, there’s a way: The mad genius of LLMs as classifiers
Katherine Munro
Data Scientist, Conversational AI Engineer @ Swisscom
Empowering Sales with Intelligent BI Agents: DWH, LLM, and RAG Integration
NLP
Technical talk, Business talk
Intermediate
In today’s data-driven business landscape, traditional BI tools often fall short, requiring specialized knowledge and struggling with complex queries on large-scale databases. Our innovative approach bridges this gap by seamlessly integrating Data Warehouses, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
This cutting-edge system empowers sales professionals to interact with complex data using natural language, eliminating the need for SQL expertise. By leveraging AI, we’re enabling rapid, context-aware insights, allowing users to access and interpret data more efficiently.
Join us to explore how this integration is transforming the way sales teams make data-driven decisions, marking a leap forward in accessible, intelligent business analytics.
This cutting-edge system empowers sales professionals to interact with complex data using natural language, eliminating the need for SQL expertise. By leveraging AI, we’re enabling rapid, context-aware insights, allowing users to access and interpret data more efficiently.
Join us to explore how this integration is transforming the way sales teams make data-driven decisions, marking a leap forward in accessible, intelligent business analytics.
16:00
–
16:30
Empowering Sales with Intelligent BI Agents: DWH, LLM, and RAG Integration
Simun Sunjic & Lovro Matosevic
Senior Software Developer @ Atomic Intelligence & ML Engineer @ Atomic Intelligence
VerifAI: Biomedical Generative Question-Answering engine with verifiable answers
NLP
Technical talk, Research talk
Intermediate
In this talk, we will present our work on VerifAI system, an open-source biomedical question-answering system with unique mechanism to verify answers and detect hallucinations in generated answers. Namely, sciences, especially life sciences, have a low tolerance for non-factual information, and therefore many practitioners have been skeptical of using available tools, such as ChatGPT. While providing references to the information sources is a step in the right direction, it may not be enough, and even referenced generated answer may contain hallucinations. Therefore, we have developed a set of methods that on top of advanced RAG, combining lexical and semantic search capabilities and fine-tuning LLM with performance efficient fine-tuning method, such as LoRA, verify the answer and detect any remaining hallucinations. In order to increase efficiency, we have used quantization to improve latency and decrease hardware requirements for hosting the product. We will in detail discuss these techniques. The code, models and datasets generated during the project have been published in open-source and open science manner.
16:30
–
17:00
VerifAI: Biomedical Generative Question-Answering engine with verifiable answers
Nikola Milosevic
Science Fellow @ Bayer
Ivo Andric A
Applied Data Science,
Data Platforms
Modern Web Data Extraction: Techniques, Tools, Legal and Ethical Considerations
Applied Data Science
Educational talk
Intermediate
To satisfy the need for data in generative and traditional AI, in a rapidly evolving environment, the ability to efficiently extract data from the web has become indispensable for businesses and developers. This presentation delves into the methodology and tools of web crawling and web scraping, with an overview of the ethical and legal side of the process, including the best practices on how to crawl politely and efficiently and use the data to not violate any privacy or intellectual property laws.
09:30
–
10:00
Modern Web Data Extraction: Techniques, Tools, Legal and Ethical Considerations
Domagoj Maric
AI Customer Delivery Manager @ Pontis Technology
How to Encourage Children to Read Books? LLMs for Education and Fun!
Applied Data Science
Technical talk
Beginner to Intermediate
Children who read books regularly grow up to be better-educated adults with higher earning potential and stronger emotional intelligence. But how can we encourage them to read books? In this talk, you will learn how SoftwareOne leveraged Large Language Models and AWS Cloud to create the Book Aligned Activities AI Engine for Worldreader, a US-based non-profit organization. This AI Engine allows Worldreader to create engaging and creative book activities for children in Kiswahili and English, reducing the development time from weeks to minutes.
10:00
–
10:30
How to Encourage Children to Read Books? LLMs for Education and Fun!
Ewelina Kucal & Maciej Dziezyc
Data Scientist @ SoftwareOne & Senior Data Scientist @ SoftwareOne
Predicting Retention on the BBC Sounds Service Using Historic User Dynamics
Applied Data Science
Technical talk, Business talk
Intermediate
Accurately predicting customers’ propensities to remain with a service allows businesses to stage informed and targeted marketing campaigns in the hope of retaining individuals for longer and to reduce subscriber attrition. Moreover, retention probability can be used in downstream tasks as a metric in A/B tests (e.g. in evaluating recommender systems). Launched 6 years ago, BBC Sounds is a streaming and download service which provides users with live radio, on demand audio and podcasts. With its weekly audience figure peaking at over 5 million users in the first quarter of 2024, the BBC would greatly benefit from having a way of identifying its most loyal listeners who are likely to stay with the Sounds service at different distances into the future. Often times, retention modellers focus on engineering and employing static features (e.g. age range, income, location, etc.) to estimate the probability of someone staying with or leaving a service. In this work, we model a user churning from or remaining with BBC Sounds as a simple binary classification problem, but use a flexible framework to leverage the information included in a user’s historical temporal features. For example, we use the number of minutes consumed, as a timeseries, leading up to a retention/churn event, amongst other dynamic attributes to predict the probability of an account continuing to use the service. We investigate the efficacy of using such temporal numerical features alongside and without static features to predict the probability of retaining a user at different intervals into the future (N=7, 30 and 90 days). We evaluate the performance of different temporal machine learning architectures (convolutional and/or recurrent neural networks) and compare them with static alternatives (e.g. XGBoost). We also explore how different feature engineering techniques help or hinder model performance on held out (test) data. Our results elucidate the optimal way of predicting retention for BBC Sounds, alongside the optimal amount of temporal history required to maximise model performance.
10:30
–
11:00
Predicting Retention on the BBC Sounds Service Using Historic User Dynamics
Ryan Timms
Senior Data Scientist @ BBC
Building up the Bosch Semantic Data Lake
Applied Data Science
Technical talk
Advanced
Creating the Bosch Semantic Data Lake as a solid foundation that synergizes Data Lakes and Knowledge Layers as Semantic Data Lake, that offers scalable data management platform for the flexible analysis (e.g., reporting, machine learning, stream analytics) of all kinds of data (e.g., batch & stream, structured & unstructured, raw & aggregated) with Semantic Metadata Management and Semantic Data Modelling, making it a Semantic Data Lake suited for large-scale batch/stream storage and processing that is scalable and cost efficient.
11:00
–
11:30
Building up the Bosch Semantic Data Lake
Sofija Pervulov
Technology Data Steward, Data Architect @ Bosch Digital
14:30
–
15:15
Panel: How gender imbalance is holding back the future of AI?
Moderator: Marija Novakovic, Panelists: Jovana Petrovic & Olga Mirkovic Maksimovic
Program Director @ DSC Franchise & Game Math Designer @ Playstudios Europe & Chief Operating Officer @ Videobolt
The path to Effective Data Migration – Overcoming Challenges and Ensuring Success
Data Platforms
Business talk, Technical talk
Beginner to Intermediate
This talk will provide actionable insights on managing data migration projects. We will be discussing lessons learned from multiple migration to public or hybrid cloud. We will not be focusing on implementation details. Instead we will cover key strategies for ensuring a smooth migration, addressing common challenges and optimizing costs. Key Points: Accelerating data analysts’ transition to self-service infrastructure. Upskilling and training initiatives for data scientists. Implementing audit logs, Ensuring GDPR compliance and security. Why it’s important and why it’s tricky. Enhancing data science workflows with MLOps tools and processes. Tool selection based on team skillsets. Various migration types aka why lift and shift is not optimal. Vendor lock-in. This session is designed for CTOs, CDOs, and data leaders looking to streamline their migration processes.
15:15
–
15:45
The path to Effective Data Migration – Overcoming Challenges and Ensuring Success
Marcin Szymaniuk
CEO @ TantusData
Personalized Insights and Engagements using Customer Data Platforms for Enterprises to make data driven decisions
Data Platforms
Technical talk, Business talk
Intermediate to Advanced
How Personalized Insights and Engagements using Customer Data Platforms and Enterprise Data Hubs are of utmost importance for Enterprises to make data driven decisions to be a market leader
16:00
–
16:30
Personalized Insights and Engagements using Customer Data Platforms for Enterprises to make data driven decisions
Pratul Kumar Chakravarty
Senior Practice Manager @ Adobe Systems
Lavender
Responsible AI,
Transforming industries with AI
Fostering Trust in AI-Driven Finance
Responsible AI
Technical talk, Business talk
Intermediate
In an era where AI plays an increasingly pivotal role in finance, fostering trust through transparency and accountability is essential. This session explores how responsible AI practices, especially model interpretability and explainability, can strengthen stakeholder confidence in AI-driven financial solutions. Attendees will gain insights into practical approaches to making machine learning models more transparent, ethical, and aligned with regulatory standards, enabling trust and fairness in AI applications.
09:30
–
10:00
Fostering Trust in AI-Driven Finance
Orsalia Andreou
Data Scientist @ Erste Group
Open Data for Everybody: Social Action, Peace Tech, and Making Open Data Outreach More ‘Open’ for Communities
Responsible AI
Educational talk
Beginner to Intermediate
What if I told you about something that could empower our third sector and activists to enhance their capacity? From gathering evidence for funding tenders to campaigning for crucial social issues and much more? It’s called open data, yet many in social action remain unaware of it. Primarily shaped by corporate entities, open data seems tailored only for technologists, alienating the third sector. But in reality, it’s a powerful tool for social change, bolstering civil society, and creating resilient communities.
In this presentation, Nathan Coyle delves into the findings from his book, highlighting the obstacles that have prevented the widespread use of open data. His research uncovers the systemic issues within governmental institutions that lead to ineffective policies. Nathan will also cover how we can bolster peacebuilding initiatives, focusing on their specific requirements and demonstrating how we can shape data governance to enhance the accessibility of open data.
We need to shift our perspective on open data, viewing it as a powerful tool for social good that can drive positive change within our communities. By doing so, we can empower activists and the third sector, helping them build capacity, secure necessary funding, and influence policy-making processes.
The session will also look at peace technology, examining its applications and the stories that need to be told. Furthermore, we will explore how the social tech community in Serbia can advocate for more open and accessible data from providers, thereby supporting social activists and peacebuilding organisations.
Nathan’s first book, Open Data for Everybody: Using Open Data for Social Good, is now available through Routledge: LINK
In this presentation, Nathan Coyle delves into the findings from his book, highlighting the obstacles that have prevented the widespread use of open data. His research uncovers the systemic issues within governmental institutions that lead to ineffective policies. Nathan will also cover how we can bolster peacebuilding initiatives, focusing on their specific requirements and demonstrating how we can shape data governance to enhance the accessibility of open data.
We need to shift our perspective on open data, viewing it as a powerful tool for social good that can drive positive change within our communities. By doing so, we can empower activists and the third sector, helping them build capacity, secure necessary funding, and influence policy-making processes.
The session will also look at peace technology, examining its applications and the stories that need to be told. Furthermore, we will explore how the social tech community in Serbia can advocate for more open and accessible data from providers, thereby supporting social activists and peacebuilding organisations.
Nathan’s first book, Open Data for Everybody: Using Open Data for Social Good, is now available through Routledge: LINK
10:00
–
10:30
Open Data for Everybody: Social Action, Peace Tech, and Making Open Data Outreach More ‘Open’ for Communities
Nathan Coyle
Senior Peace Tech Advisor @ Austrian Centre for Peace
2025: year of Ai dilemma – ethics, regulations and innovations
Responsible AI
Educational talk
Intermediate
Over the past decade, machine learning has seamlessly integrated into every facet of our daily lives, revolutionizing how tasks are executed with unprecedented efficiency and cost-effectiveness. This surge in machine autonomy, however, has brought forth a conundrum reminiscent of the Oppenheimer Dilemma – the profound responsibility accompanying great technological power. The maxim “with great power comes great responsibility” resonates ever more deeply in this era of accessible machine learning, where even novice developers can wield immense influence. From granting access to transformative financial resources to shaping social media narratives that can polarize beliefs, the scope of machine influence is vast and impactful. As AI technologies burgeon and come under increased scrutiny, the landscape of AI development undergoes a profound shift. The entire data science lifecycle must now integrate principles of responsible AI, encompassing fairness, accountability, privacy, and transparency. Professionals adept at implementing these principles are increasingly sought after by employers. Furthermore, it’s imperative to address issues like hallucination, monetization, robustness, reliability, and attribution within a broader Responsible AI framework. Moreover, principles like human-centricity, planetary inclusivity, safety, and societal well-being must not be overlooked. This imperative extends beyond current technologies to include emerging frontiers like General AI. Principles of fairness, explainability, transparency, robustness, stability, safety, and privacy must be rigorously upheld in the development of General AI. Embedding these foundational pillars ensures that the potential of these advanced systems is harnessed ethically for the collective good of humanity. Prioritizing these principles not only mitigates potential risks but also cultivates an environment where Genl AI can flourish in alignment with our values and aspirations for a better future. Beside the above, the main dilemma that will be at the centrestage will revolve around Regulations vs. Innovation, Global Coordination, Wealth Inequality, Reliability, Social Impact and Control. These dilemmas are interconnected and multifaceted, requiring collaborative efforts from technologists, policymakers, ethicists, and the public to navigate. The year 2025 is seen as a critical juncture as the pace of AI development accelerates and its integration into various aspects of society becomes more pronounced.
10:30
–
11:00
2025: year of Ai dilemma – ethics, regulations and innovations
Sray Agarwal
Director Responsible AI @ Fractal
AI Trustworthiness – A Path Toward Mass Adoption in Critical Industries
Responsible AI
AI’s ability to process vast amounts of data, images, audio, and tables, has unlocked transformative applications across industries.
In critical sectors such as healthcare, transportation, space, and defense, where failure is not an option, software and systems must adhere to stringent safety and regulatory requirements. For AI adoption to succeed in these domains, it must meet the same mandates.
Global regulations, such as the EU AI Act, are establishing clear frameworks that balance safety and innovation. Two essential attributes, robustness and explainability, are key to building the trust necessary for widespread adoption.
This keynote will explore advanced techniques and tools that help businesses develop and deploy AI solutions meeting technical, regulatory, and performance demands, ensuring trustworthiness and safety in high-stakes environments.
In critical sectors such as healthcare, transportation, space, and defense, where failure is not an option, software and systems must adhere to stringent safety and regulatory requirements. For AI adoption to succeed in these domains, it must meet the same mandates.
Global regulations, such as the EU AI Act, are establishing clear frameworks that balance safety and innovation. Two essential attributes, robustness and explainability, are key to building the trust necessary for widespread adoption.
This keynote will explore advanced techniques and tools that help businesses develop and deploy AI solutions meeting technical, regulatory, and performance demands, ensuring trustworthiness and safety in high-stakes environments.
11:00
–
11:30
AI Trustworthiness – A Path Toward Mass Adoption in Critical Industries
Arnault Ioualalen
CEO and R&D director @ Numalis
Panel: Path of Data & AI Challenges
Panel
Data is the common theme between radiology, infrastructure needed for AI projects and law. Our speakers will share their insights and perspective when it comes to data and AI challenges. From information stored on physical paper, data processing and post-training, many challenges impact the success of the project. Join our fireside and experience a dynamic discussion.
14:30
–
15:15
Panel: Path of Data & AI Challenges
Moderator: Boban Poznanovic, Panelists: Ivana Sesis & Anja Beric & Dejan Grubisic
Chairperson @ Serbian AI Society & Radiology AI advisor – Senior Medical Image Expert @ UNDP Serbia & Attorney At Law @ Zunic Law Firm & Research Scientist @ Meta
Advanced Techniques for Time Series Forecasting and Anomaly Detection in Radio Networks
Transforming industries with AI
Technical talk
Advanced
In the telco industry, time series forecasting and anomaly detection are essential for maintaining network performance and optimizing resource management. This presentation explores advanced time series analysis and forecasting techniques, which aid in improving capacity planning, optimizing CAPEX investments, and enhancing energy efficiency. Additionally, it delves into the use of standard statistical methods for identifying anomalies in network data, enabling proactive issue resolution. By leveraging these approaches, it is possible to ensure balanced, efficient, and data-driven management of network resources.
15:15
–
15:45
Advanced Techniques for Time Series Forecasting and Anomaly Detection in Radio Networks
Jelena Tomic & Ivana Jovovic
ML Engineer @ A1 & ML Engineer @ A1
Application of AI technologies in nuclear power plants
Transforming industries with AI
Technical talk
Intermediate to Advanced
Example of several AI use-cases deployed and used in Slovak nuclear power plants improving maintenance and operation. Topics would include experience of deployment, human interaction & rugulator aspect for AI solutions.
16:00
–
16:30
Application of AI technologies in nuclear power plants
Peter Kertys & Maros Buban
Head of Data Science @ Slovenské elektrárne & Solution Architect @ Slovenské elektrárne
How to build a Data Experimentation Platform when you have no Platform team
Transforming industries with AI
Technical talk, Business talk
Beginner to Intermediate
The talk will concentrate on a simple truth that many startups are unique in their needs but require a not-so-unique experimentation platform when moving to a scale-up stage. Quite often, the companies have enough internal expertise to implement the data solution on their own – the solution that ranges from a split service and product integration(s) to a userbase segmentation, an easy metrics framework, and a reporting automation. The topic would be of interest to prodcut leaders, data engineers, data scientists, and even platform teams aspiring to build a core infrastructure in place and to further scale the product growth past product-market fit. In fact, taking experimentation in your own hands could become a competitve advantage. And getting there in a two-sided marketplace is not much more difficult than in any other product-led company.
16:30
–
17:00
How to build a Data Experimentation Platform when you have no Platform team
Vladislav Metelev
Head of Data @ Wheely
Tesla B – DSC:X
AI & Data Product Development
Balancing Personalization and Experimentation: The Art and Science of A/B Testing in a Customized World
AI & Data Product Development
As product teams strive to deliver personalized experiences that cater to individual user preferences, the challenge of maintaining standardized A/B testing conditions becomes more complex. This talk explores the intersection of personalization and A/B testing, presenting actionable frameworks and best practices for running experiments without compromising user experience or test validity.
From segmenting user groups to using multi-armed bandit algorithms, we’ll dive into advanced techniques that enable organizations to optimize personalized experiences while ensuring accurate, data-driven insights.
You’ll learn how to scale A/B testing efforts across multiple teams and product lines, overcome challenges like data inconsistencies, and create a culture of experimentation that balances the need for both personalization and standardization.
Whether you are a Product Manager, Data Scientist, or Marketing Professional, this session will equip you with the tools to seamlessly integrate personalization with your experimentation strategy for maximum impact.
From segmenting user groups to using multi-armed bandit algorithms, we’ll dive into advanced techniques that enable organizations to optimize personalized experiences while ensuring accurate, data-driven insights.
You’ll learn how to scale A/B testing efforts across multiple teams and product lines, overcome challenges like data inconsistencies, and create a culture of experimentation that balances the need for both personalization and standardization.
Whether you are a Product Manager, Data Scientist, or Marketing Professional, this session will equip you with the tools to seamlessly integrate personalization with your experimentation strategy for maximum impact.
09:30
–
10:00
Balancing Personalization and Experimentation: The Art and Science of A/B Testing in a Customized World
Joy Chatterjee
Lead Data Scientist @ DCMN
Navigating the AI Project Lifecycle
AI & Data Product Development
Artificial Intelligence (AI) projects present unique challenges that set them apart from traditional IT initiatives. For leaders steering these endeavors, it’s crucial to ask the right questions at each phase—from problem definition and data acquisition to model development, deployment, and maintenance—to ensure alignment with business objectives and successful outcomes. This presentation offers a concise guide to these critical inquiries, equipping leaders with the insights needed to effectively navigate the complexities of AI projects. Join us to explore the structured roadmap that transforms innovative ideas into operational AI solutions.
10:00
–
10:30
Navigating the AI Project Lifecycle
Luka Anicin
CEO & Artificial Intelligence Consultant @ Datablooz
Future of the future: creating an AI product beyond hype
AI & Data Product Development
Technical talk, Business talk
Intermediate
When a company creates one of a bunch of AI products, what should distinguish it from competitors? We know the initial AI hype is behind us, the real things are happening now and now everyone is asking: what`s next?
Let’s talk about GitLab Duo, our AI baby. We ramped it up in an aggressively narrow timeframe, with a vision to provide the highest quality experience for our users. At the moment, many questions are opened about the future of its development.
Join me to examine the landscape of AI products in the DevSecOps world and the trajectory of future expansion. We are delighted to share the experience we have on the top of the product with more than 30 million users.
1. Why do we jump into the unknown area with LLM and AI development?
2. What is the approach that will become a success story for AI product development – yes you guess, it is an iterative approach
3. How to leverage dogfooding – and what is dogfooding – Tip: it is not about the dog or the food
4. When to pivot your development without regret – yes, it is because of FinOps, but not only that
5. How to measure your success – people often forget to measure what they are doing and are they will reach the goal
I promise – no fluff, no buzzwords. Solely a first-face story from the GitLab Data Team member, created from sweet and pain from the world leader of DevSecOps platform creator, remote work champion and one of the most transparent company in history.
Let’s talk about GitLab Duo, our AI baby. We ramped it up in an aggressively narrow timeframe, with a vision to provide the highest quality experience for our users. At the moment, many questions are opened about the future of its development.
Join me to examine the landscape of AI products in the DevSecOps world and the trajectory of future expansion. We are delighted to share the experience we have on the top of the product with more than 30 million users.
1. Why do we jump into the unknown area with LLM and AI development?
2. What is the approach that will become a success story for AI product development – yes you guess, it is an iterative approach
3. How to leverage dogfooding – and what is dogfooding – Tip: it is not about the dog or the food
4. When to pivot your development without regret – yes, it is because of FinOps, but not only that
5. How to measure your success – people often forget to measure what they are doing and are they will reach the goal
I promise – no fluff, no buzzwords. Solely a first-face story from the GitLab Data Team member, created from sweet and pain from the world leader of DevSecOps platform creator, remote work champion and one of the most transparent company in history.
10:30
–
11:00
Future of the future: creating an AI product beyond hype
Radovan Bacovic
Staff Data Engineer @ GitLab
Integrating AI into office software
AI & Data Product Development
Innovations in Artificial Intelligence have led to it becoming an integral part of society and finding applications in a variety of fields. In this session, we will cover AI implementation into office software; highlight what benefits AI can bring to users when working with documents; take into consideration various markets in terms of using the leading AI providers.
11:00
–
11:30
Integrating AI into office software
Ali Haidar
Technical Support Engineer @ ONLYOFFICE
Keynote: The Art of Telling Stories with Data
Keynote
Join us for a dynamic and entertaining keynote session on Data Storytelling with Gulrez Khan, Data Science leader at PayPal and Award Winning Author. Gulrez is known for infusing his presentations with humor and personal stories, making the learning experience both engaging and enjoyable. You’ll be inspired by Gulrez’s insights and experience as he guides you through the process of turning numbers into narratives. Discover how to craft compelling stories that bring your data to life, and learn how to share your insights in a way that engages, educates, and inspires your audience.
12:00
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12:45
Keynote: The Art of Telling Stories with Data
Gulrez Khan
Data Science Leader @ PayPal & Award Winning Author
Panel: Data-Driven Transformation: Powering Growth and Efficiency Across Industries
Panel
Technical talk, Business talk
Beginner to Intermediate
In today’s rapidly evolving landscape, data and analytics have become essential for driving growth, enhancing customer experiences, and streamlining operations. This panel brings together industry leaders from telecom, energy, and banking to discuss the strategic role of data in their organizations and how it supports both innovation and efficiency. Panelists will share insights into how data strategies vary across sectors, the impact of AI and machine learning on transforming established systems, and the challenges of scaling data initiatives in large organizations. Attendees will gain a firsthand look at how these companies are using data to shape their future, overcome industry-specific challenges, and remain competitive in a data-driven world.
14:30
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15:15
Panel: Data-Driven Transformation: Powering Growth and Efficiency Across Industries
Moderator: Vid Stimac, Panelists: Goran Pavlovic & Dmitrii Pshichenko & Tiago Peixoto
Project Manager, Digital Innovation @ UNDP & BI, Big Data and Analytics Director @ A1 & CTO @ NIS & Senior Public Sector Specialist – Digital Government/GovTech Coordinator for the Western Balkans @ World Bank
How Alice, our intelligent personal assistant, learned to understand people with speech impairments
AI & Data Product Development
Alice is Yandex’s virtual assistant, designed to answer questions, play music, assist with daily tasks, and manage smart home devices. Powered by the advanced YandexGPT neural network, Alice received a significant upgrade in July 2024, enhancing its ability to recognize voice requests from individuals with speech disorders, such as stuttering, cerebral palsy, stroke, or trauma.
This improvement was achieved through additional training of the neural network. During this process, Alice was exposed to hundreds of thousands of audio recordings provided by people with speech impairments. As a result, the accuracy gap between recognizing standard speech and speech with impairments was reduced by an average of 20%.
This improvement was achieved through additional training of the neural network. During this process, Alice was exposed to hundreds of thousands of audio recordings provided by people with speech impairments. As a result, the accuracy gap between recognizing standard speech and speech with impairments was reduced by an average of 20%.
15:15
–
15:45
How Alice, our intelligent personal assistant, learned to understand people with speech impairments
Anastasia Shapedko
Project lead, Technologies for Inclusion @ Yandex
How to effectively manage AI/ML projects
AI & Data Product Development
Use case
Advanced
Understanding the complexities of AI project management is crucial as it directly impacts the alignment of AI initiatives with organizational goals. In this session, Ana Stojković Knežević will explore the specialized frameworks necessary for managing AI projects effectively. Participants will learn about Data Driven Scrum (DDS), a methodology tailored for AI that enhances project efficiency through flexibility and iterative learning. Key takeaways include strategies for balancing technical and business requirements, the importance of staying updated with AI trends, and practical steps for implementing DDS.
16:00
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16:30
How to effectively manage AI/ML projects
Ana Stojkovic Knezevic
Project Manager @ Protech
AI Integration in Legacy Industries: Navigating the Path to AI Transformation
AI & Data Product Development
Transformational talk
Intermediate to Advanced
Explore the transformative power of AI in traditional industries, examining successful integrations and the unique challenges faced. This talk highlights how companies in sectors such as manufacturing, healthcare, and finance are leveraging AI to innovate and improve efficiency, while addressing the cultural, technical, and regulatory hurdles of adopting new technologies in established environments.
16:30
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17:00
AI Integration in Legacy Industries: Navigating the Path to AI Transformation
Marija Matokanovic
Product Owner Lead @ Andritz Digital Factory
* this program is not final and is subject to change, full schedule will be available soon