To find out how AI is implemented in financial services firms, WBR Insights interviewed senior data executives across Europe and North America in Q1. The Artificial Intelligence report consists of the following parts:

  • Part 1: Navigating the Crossroads of AI Adoption
  • Part 2: Building Gen AI Apps for the Enterprise
  • Part 3: Measuring the Impact and Value of AI
2024-FIMA-LP-guide-cover2

"In the finance sector, Large Language Models are predominantly utilised through Retrieval Augmented Generation, a method that infuses new, post-training knowledge into Large Language Models. This process involves encoding textual data, indexing it for efficient retrieval, encoding the query, and employing similarity algorithms to fetch relevant passages. These retrieved passages are then used with the query, serving as a foundation for the Large Language Model to generate the response."

From the topic:

Advancing AI Reasoning: The Synergy Between Knowledge Graphs & Language Models

By Vahe Andonians, Founder, Chief Technology Officer, Chief Product Officer, Cognaize

2024-fima-vahe-headshot1

Schedule an Exclusive Conversation with our Founder

Dive deep into your ambitions and challenges, receiving tailored insights from the very heart of our innovation engine.

Large language models have exploded onto the scene in recent months, sparking enthusiasm among technologists along with scepticism from critics who dismiss them as a fleeting gimmick.

However, these systems signify a monumental leap in AI that much of the public and many business leaders are failing to fully grasp.