Enterprise AI

AI is revolutionizing the way organizations work, challenging industries to rethink business models and providing the means for companies to embrace data-driven decision-making like never before. However, getting started with AI isn’t easy. No matter how sophisticated your machine-learning algorithms, they’re only as good as the data that feeds them.

Success depends on an organization’s ability to apply an architected multicloud model and approach to how it accelerates toward AI through mastering four levels: collecting data, organizing data, analyzing data with AI everywhere and infusing AI-driven business processes. It’s this type of model that has differentiated the successful from the struggling among AI early adopters.

During this session, get a behind-the-scenes look at how companies are leveraging open source, managing the full AI lifecycle, and the essential lessons they’ve learned along the way, all focused to help you on your journey to AI.

• What are the fundamental buildings blocks needed for build a digital organisation using AI, ML & DL in terms of people, skills and tech?
• Discussing the role of other companies within the process, from start-ups to big ticket providers.
• Examining digital transformation from both industrial and business information perspectives.
• Real life examples of successful transformations from across Enterprise.

Being an Intelligent Enterprise is key to winning in the experience economy.  Having the visibility, focus, and agility to drive outcomes such as delivering exceptional customer experiences, empowering employees more effectively and driving new revenue streams and business models are just some of the outcomes made possible by being an Intelligent Enterprise.  The deep incorporation of “AI” into applications and end to end processes will change the way companies do business, for the better.  How can you get started, with pragmatic next steps, and clear ROI?  Learn how businesses who get it right are using technologies such RPA, Conversational AI, and Machine Learning to delight customers and deliver superior customer experience.

This keynote will discuss several use cases of Google’s AI-First approach. The presentation will show in-depth new innovations in Algorithms, Computation and Solutions that help Google solve many challenging AI/ML problems

• How machine learning is making unstructured data accessible  

Making AI auditable and explainable in the real world is hard but not impossible.  We’ll show you how to make AI auditable today and get you ready to embrace the latest breakthroughs in explainable AI tomorrow.
With algorithms making more and more decisions in our lives, from who gets a job, to who gets hired and fired, and even who goes to jail, it’s more critical than ever to get our intelligent systems talking to us so people can step in when things go wrong.

In the coming decade, organizations will face incredible pressure from regulators and the general public and that means every team needs a plan in place to find and fix mistakes fast or risk a PR nightmare and face financial consequences.

But you don’t have to wait until it’s too late, you can make your AI/ML systems auditable and transparent right now with a combination of new technologies and infrastructure specifically designed for audibility and a few classic IT techniques your team already knows and knows well

Modern AI methods have dramatically improved the accuracy of computer vision recognition. In this talk, we will show examples of what is possible with AI-based computer vision using new deep learning methods and then present various industrial use cases, ranging from sports highlights, to retail video analytics to industrial asset inspection.

Artificial intelligence is not purely “artificial.” The ideal approach amplifies human intuition with machine intelligence to create a powerful multiplier effect. That’s augmented intelligence. In this session, Elif will talk about the wonder of how human brains works. She will use analogies between how the brain processes information and data analytics. She will cover the recent product innovations that combines the power of Associative Indexing technology with Cognitive capabilities, enabling 3^rd generation business intelligence technologies.

Please join the session to hear about Associative Indexing (x) Augmented Intelligence = AI², the recent technology innovations leading exponentially more brainpower for users and where AI is making its way into business intelligence and what that might enable for businesses.

To follow soon…

In this talk, we will explore the applications of different facets of AI (machine learning, deep learning, NLP and computer vision) in online retail and e-commerce. We will walk through practical examples of how AI can be used to personalize customer experience and revolutionize your customer journey through personalized marketing campaigns, personalized recommendations, supply chain, CRM, reranked search and more. Kamelia will share her thoughts on building successful AI teams and an experiment-driven culture that will reshape your business by enhancing customer experience through AI.

• How are retailers using AI? A look at applications for delivery, payments, CRM, product content management.
• Using AI to deliver outstanding customer service and customer retention
• Customer recommendations

Recent Forrester research shows that the benefit of AI in testing is to augment tester’s intelligence to improve and speed up testing. Not to “automate” testers out of their job. On the other hand, AI infused applications made of automatic (traditional) sw and autonomous (models) sw can leverage consolidated testing practices and tools to support enterprises in automating testing for their AI Infused applications. But testing for the unknown is the hard bit. Featured speaker, Forrester Research VP and Principal Analyst Diego Lo Giudice will present his recent and ongoing research outcomes on both AI in testing and testing AI. In this presentation you will hear about:
1.       The Path To Autonomous Testing Goes Through Testers Augmentation
2.       AI Infused Applications (AIIA) need more and better testing, why ?
3.       How Can We Better Test AIIA ?
4.       Testing the unknown is largely unknown.

Enterprises across industries are using conversational AI strategies to improve customer service. Join Mitch Mason with the IBM Watson team, to learn how global brands are improving responsiveness, gaining operational efficiencies, and growing brand loyalty and conversion rates with Watson Assistant. Step through the three most common ways customers use assistants to add conversational AI to their customer and employee experiences

Recommendation systems are all around us. E-commerce companies like Amazon recommend products we are likely to buy based on our browsing behavior. Netflix suggests what shows we should watch based on our binging habits. Spotify builds a personalized playlist we would enjoy listening to, based on their understanding of what musical genre we are into.
In this talk, we will explore recent advances in the area of product recommendations in both research and practice. We will see how machine learning, design thinking, and solid data engineering principles are combined to create an engaging customer experience that positively impacts the bottom line.
We will look at how we use various deep learning architectures to obtain image and text embeddings that supplement user and product-based features to generate product recommendations that align closely with a consumer’s aesthetic preferences.

In recent years, professions like AI product management became popular because organizations from all industries are striving for AI leadership to enter the AI race and gain competitive advantage. However, does ML algorithm programming skills make these professions so valuable? The answer is no; technology has always been just the tool. What companies need is AI strategists who can bridge the business, product, and technology to reach sustainable profitability. In this presentation, I’ll share with you my experience from eBay and Yahoo AI initiatives and show how the product management profession changed in the AI era to add value to the business.