Planning as the Core Challenge in Agentic AI: Solving it with Reinforcement Learning By Anthony Alcaraz

Key Principles for Delivering AI Outcomes in Large Enterprises By Walid Mehanna

Using Semantics to Find Trends in Global Quality Data By Rex VanHorn

How SMEs Can Navigate the Data & AI Landscape By Frank Stadler

Creating Value at Scale with AI in Pharmaceuticals By Tomislav Ilicic

Enhanced Large Language Models as Reasoning Engines By Anthony Alcaraz

From RAG to RAR By James Duez

Essential Soft Skills for Data Scientists By Sandro Saitta

Data Quality in Relation to Algorithmic Bias By Gareth Hagger-Johnson

Common-Sense Leadership By Claus Villumsen

Davos 2024: Rebuilding Trust, Reclaiming Relevance and the Catalytic Effect of AI By Zana Aston

The Imperative of AI Constitutionalism: Building an Ethical Framework for a Brave New World By Sahaj Vaidya

Challenges and Opportunities in Clinical Trial Registry Data By Philipp Diesinger

Why Generative AI Projects Fail By Colin Harman

Fortifying Digital Frontiers: Wise’s Innovative Approach to Fraud Protection By Iaroslav Polianskii and Luca Traverso

Industry Case Study: Merck By Walid Mehanna

Artificial Intelligence for Artificial Languages By Francesco Gadaleta

The 5 Use Cases for Enterprise LLMs By Colin Harman

Data Science City: Warsaw

Could Rust Be the Future of AI? By Francesco Gadaleta

Rise of the Data Generalist: Smaller Teams, Bigger Impact By Tarush Aggarwal

Ethical and Sustainable Data By Sarah-Jane Smyth & Jasmine Grimsley

AI at Continental By Filipa Castro

Time Series Forecasting with Deep Learning in PyTorch (LSTM-RNN) By Zain Baquar

Using Open Sourced LLMs in Language By Bartmoss St Clair

Transforming Freight Logistics with Advanced Machine Learning By Luís Moreira-Matias

A Journey from Data Analyst to Data Science Leader By Rebecca Vickery

Navigating the Future of Ads: Large Language Models and Their Impact on Programmatic StrategiesBy Javier Campos

Measuring the Effect of Change on Physical Assets By Colin Parry

Leveraging Data for a Sustainable Competitive Advantage with GenAI By Michel de Ru

AI the World Can Trust By James Duez

Scalable Data Management in the Cloud By Jacques Conradie

With LLMs, Enterprise Data is Different By Colin Harman

The Path to Responsible AI By Julia Stoyanovich

The Biological Model By Pat McQuillan

The AI Revolution vs the Mobile Revolution By Rex Woodbury

The Dawn of Synthetic Data By Philipp M Diesinger

Data Science Platforms for Patient-Centred Drug Discovery By Benjamin Glicksberg

How Infusing Marketing with Data Science Can Lead to Better Marketing Decisions By Faisal Wasswa

Should You Industrialise your Data Science MVP? By Philipp M Diesinger

The Principles of an Effective Data-Driven Organisation By Pat McQuillan

What Is Causal Inference and Why Should Data Leaders and Data Scientists Pay Attention? By Graham Harrison

Risk Mitigation and the Future of Large Language Models in the Enterprise Market By Damien Deighan

Start Up: Interview with Tanmaiyii Rao

Digital Twins: The First Fruit of the Metaverse, Powered by Generative AI By Aakash Shirodkar

Building a Feature Platform Guided by Your Ethos By Andreu Mora

How AI Is Driving the Eradication of Malaria By Arnon Houri-Yafin

Embracing Neurodiversity: My Journey with ADHD and How Generative AI Propelled My Career in Data Science By Elle Neal

Charting the Evolution of Talent in Data Science at the Event Horizon of AGI By Lin Wang

From Humans to Hybrids: Preparing Your Workforce to Thrive in the Future By Philipp M Diesinger

Start Up: Interview With Tamanna Haque – Getting Into Data Science

How To Scale Data Science Pilots To Industrialise Your Data: Philipp M Diesinger

Should You Reassess Your Candidate Assessment In The Wake Of CHAT GPT3? By Damien Deighan 

Dr Anna Litticks: Things I Wish I knew Before Becoming a Data Scientist

Start Up – Ryan Kearns: How I Got Into Data Science

Mikkel Dengsoe: A highly Respected and Experienced Data Leader, Sheds Light on The Complex Relationship Between Team Size And Data Complexity