TechTalk event at the Hub on 'AI - Solving the Paper to Data Problem'

An exclusive TechTalk physical event on how AI can be used with legal contracts in law, financial and professional services.

Dates
  • 17th May 2021
    5:30pm - 7:00pm

Location:

Digital Jersey Hub

Join Malcolm Mason and Phil Godley for a practical demonstration of applied AI with live code examples of using AI for legal contract digitisation, conducting large scale Q&A on legal documents, contract data extraction and the adoption of AI within the business.

The session will also cover an overview of AI, trends in AI, how Deep Learning and Natural Language Processing work, how AI can deliver real benefits in Financial Services and where we are heading with AI.

Format:

  • A combination of illustration and live code examples.
  • Duration is 90 minutes 5:30pm-7pm
  • Including presentation, live examples and open floor Q&A.

Speakers:

Malcolm Mason: Cloud and Data Consultant, Sure Business

Malcolm is a Cloud and Data consultant, and also delivers training focusing on deep learning, more specifically the algorithms that underpin this area. Malcolm started his career as a programmer, and has subsequently held IT roles in Air Defence, Telecommunications, Cloud and Security. Post completing an MSc in IT, he has worked in Product Management focusing on Software, Cloud, Managed Security and Data, before moving back towards technology as a consultant in Cloud and Data.

Phil Godley: Director & Advisor, Native Limited

Following a career in financial services, Phil is an investor, board member and advisor to growth companies. These include companies which have successfully solved unique business problems with enterprise artificial intelligence. Phil is a machine learning practitioner and has worked on global open source projects such as supporting the Society for Imaging Informatics in Medicine (SIIM) and the International Skin Imaging Collaboration (ISIC) by utilising computer vision and machine learning to identify skin cancer in images of skin lesions.

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