How can you implement an AI strategy in your business?
We are already seeing surprising success stories of applying AI, to unusual applications. Hugo Larochelle, Google Brain
Whilst millions of dollars are being invested in deep learning research and implementations, it's not just companies with this amount of financial backing that are benefiting from its capabilities. Similarly, we mustn't assume that only technology companies can benefit from its application. Part of the reason that AI has been able to spread so quickly is due to the affordability of setting up models - Kimberly Powell from NVIDIA explains that 'to implement AI, a business needs three components: data, algorithms, and computation.' In today's business ecosystem, each aspect is amply available and inexpensive.
Next week at the Deep Learning Summit in Montreal (October 10 & 11), experts from IBM, Accenture, and Thales Group will be running workshops exploring the implementation of AI and DL in a variety of industries and businesses of different sizes. These interactive sessions have just been added to the agenda, and they will provide a platform for discussions on the cognitive era, AI strategy for the workplace and explainable by design AI. Entrepreneurship, technology and science will come together to solve some of the world's greatest challenges. The world's leading figures in the industry will be presenting at the summit including Yoshua Bengio, Yann LeCun and Geoffrey Hinton.
There are limited tickets remaining so register here for your chance to hear the latest advancements in Deep Learning from a global line-up of experts. Workshop leaders will include:
Adel El-Hallak and Michael Gschwind who will speak about the journey to the cognitive era with IBM and how to leverage deep learning to win the AI arms race.
While Deep Learning has widely been accepted as one of the most exciting developments in computer science of the past fifty years, many organizations find themselves struggling with just how to get started. This session will highlight some of IBM's recent accomplishments and will also illustrate that regardless of where you are in your journey to the cognitive era, IBM has the breadth of revolutionary technology offerings, and depth of data science expertise to help your organization leverage deep learning and win the AI arms race.
David Sadek from Thales Group will lead a workshop titled "Explainable by Design AI is the Real Challenge".
Artificial Intelligence capabilities are set to become pervasive and to spread across a span a various systems including air, ground and sea transportation vehicles. Yet Machine Learning algorithms and their derived features do not provide any means to insure and enforce Safety and Security which is the number 1 driver and priority to certify new technologies on board critical transportation systems: “deployable AI can only be achieved with Explainable AI”. To cope with the inherent unpredictability and the lack of guarantees of Machine Learning black boxes, Industry, Academia and Regulations Agencies have to work jointly to design and develop frameworks and Explainable by design AI to allow deployable AI features onboard Aircrafts, Ships and any ground transportation vehicles.
Shyam Thyagaraj, Managing Director at Accenture will lead a workshop on "the stepping stones in an AI strategy" for the workplace.
Join Shyam Thyagaraj as he shares some insights from Accenture’s most recent research and learn how to “boost your AIQ”. The theory will be followed by a real business use case. This session will include a casual discussion-style lecture from Shyam as well as a facilitated group ideation session to help participants define and share their own insights around how startups to big companies can better collaborate in this space to truly capture the value of AI.
Register now for the Deep Learning Summit in Montreal on 10-11th October.
If you can’t attend the summit in Montreal, check out our Deep Learning Summit in San Francisco on 25-26th January where you can learn from experts from Netflix, Amazon, Google Brain, DeepMind, MIT and more.