SAS at AI Summit 2020

AI Ireland: The roadmap to creating an AI island…

05th March 2020

Artificial Intelligence has become mainstream and is fuelling more and more aspects of businesses and day-to-day life.  Beyond the hype, the question is how data-driven innovation can be brought to life and put in action to resolve real business problems. What steps are needed to move AI out of the lab and into business operations to realise the desired outcomes?

This annual Artificial Intelligence Summit will focus on experts breaking down complex AI topics in a clear way so that business leaders can maximise the AI opportunities ahead of their competitors.

The SAS team will be available throughout the day. Join us to play our #detectthedefect game and a chance to win an Alexa Dot!

Agenda

There is a full agenda of sessions which can be seen here

One not to miss is the SAS Session: (details as shown below)

Thursday, March 05
Key themeModelOps: Operationalising AI: 
10:05
  • When 50% of models never make it into production, what can you do to improve the odds?
  • Moving from the lab, to validation, testing and production
  • Ensuring the ethical FATE (Fairness, Accountability, Transparency and Explainability) of AI
  • Banking Use Case of AI for Credit Risk
 

Meet our AI Expert

 
 

Dr Iain Brown
Head of Data Science for SAS UK&I
BIO

Croke Park, Dublin

Ireland

Direction

Successful execution of an analytics, and thereby AI strategy, needs the right balance of choice and control.

Choice

Creativity and innovation flourish in open spaces. You need flexibility and freedom to attract the best analytical talent, use a wide variety of techniques and develop processes that work best. You need the flexibility to use multiple programming languages and analyze any data in any environment and to keep up with accelerating demands.

Control

Analytics chaos can creep up. Once you lose control of your data, you lose trust in the system and its outputs. Transparency, governance and security become essential for maintaining trust in models and analytical results. Becoming even more critical as you scale development, monitoring and refinement of analytics applications and their associated processes.

At the intersection of data, software, and ingenuity, the future is being redefined. After all, when curiosity meets capability, progress is inevitable.

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