
Ron Argent
Cognition Foundry
Founder & CEO
20th June 2019 London
Spin outs, start ups and research groups
University incubators are at the forefront of AI development within the UK. With so many innovative ideas it is a great starting place, however turning these big idea’s into into profitable viable businesses requires a wide range of resources and skill sets including:
This is why having the right partnerships in place can help accelerate the process to give the idea the best chance of success.
Join us in London 20th June from 3.30pm to 8.30pm to find out more how our collaboration of partnerships can provide the skill set required to get the big idea into a commercialised viable business, how AI projects should be planned and deployed and why Infrastructure really does matters
George Sandeman Room, Tabbit Hen 21-23 St. Swithin’s Lane, London, EC4N 8AD
Simply put there is no hiding the explosion of AI and its applications. As AI, automation and machine learning push the boundaries in almost every single industry, businesses will have to embrace the technology and understand that it is a force for good. We will be taking a deep dive into some of the fascinating use cases and what this means for businesses around the world.
Turning that great idea into reality takes many different forms of resources and skill sets – Ranging from the much needed compute power need to run POC’s and production environments to business strategy, marketing, commercial thinking and much more. We have helped start up transform into viable businesses with our partnerships and collaborative approach. We will be taking a deep look into how we achieved this and how you too can leverage our skills, expertise and network to help accelerate your incubator start ups.
AI workloads, and especially deep learning systems, which process large amounts of data, are extremely demanding and require powerful parallel processing capabilities, and benefit from specific configurations. This is where advance compute power can play a vital role in not only the results and speed in which algorithmic models can be deployed in, but also can have major cost implications later down the line if the infrastructure is not designed to cope with growth.
Once you have gone so far down the road in your development it can become a challenge and time consuming to have to rethink and deploy a new infrastructure strategy, sometimes resulting in having to remodel or rewrite code.
We will be looking at why and how infrastructure can effect your results, performance, security and costs of your AI initiatives and how to implement an infrastructure strategy to support your future requirements as your grow.
We will also be taking a deeper look at the how OEM alliances such as IBM have helped universities with their Infrastructure strategy and environments to move away from a siloed approach, reducing complexity and costs whilst providing enhanced superior compute power that is required to run advanced AI initiatives and meets the need of running large research projects.
Cognition Foundry
Founder & CEO
TES Enterprise Solutions
Business Development Director
TES Enterprise Solutions
Client Success Leader
IBM
Power Systems CTO
IBM
Machine Learning Engineer / Systems AI
TES Enterprise Solutions
AI, Machine Learning, Deep learning Specialist
IBM
IT Economics Team
TES Enterprise Solutions
Innovations Leader
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