Top 5 Key Areas: Deep Learning in Retail & Advertising

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Recent advances in deep learning have enabled research and industry to master many challenges in computer vision and natural language processing that were out of reach until just a few years ago. Yet these challenges represent only the tip of the iceberg of what is possible.

And the rapid uptake of artificially intelligent software across industries like finance, manufacturing and retail is only getting quicker. Gartner predicts that 85% of customer interactions will be managed autonomously by 2020, with cross-channel bots that are able to recognize the voices and faces of customers as soon as 2018. Many retailers have already deployed product recommendation software that allows computers to make better predictions and offer smart choices in real time, ensuring happy customers and further sales.

It's easy to see how this kind of technology will be valuable, as customers are overwhelmed by an ever-growing online market, when introducing recommender-style artificial intelligence can cut the time and effort involved in browsing products. But the widespread impact of AI in retail and advertising won't be limited to recommendations in the near future - in fact, it's set to change and improve every corner of the industry.

At the inaugural Deep Learning in Retail & Advertising Summit, taking place in London on 1-2 June, we’ll explore how AI is revolutionising retail worldwide, through inventory forecasting and stock level optimisation, natural language processing (NLP) for personalised shopping experiences, computer vision for sizing efficiency, smart algorithms for fraud detection, and more. 

Through bringing together key influencers to share cutting-edge research and real-world retail applications, we can explore how to successfully apply artificially intelligent software to enhance and grow the retail and advertising industries.

We’ve rounded up the top 5 topics not to be missed at the summit:

Computer Vision For E-commerce

The fashion industry is a visual world, with millions of images displayed everyday by e-commerce sites to serve consumers the latest trends and products. However, automatically categorizing and searching through large collections of images according with many detailed attributes still remains a challenge. 

At the summit, Susana Zoghbi, Postdoctoral Researcher at KU Leuven, will share expertise on deep learning techniques such as computer vision and pattern recognition to automatically identify fine-grained attributes in both images and text in the presence of incomplete and noisy data. This technology will be increasingly paramount for large online stores to continue an upward trajectory in this new era of AI.

Next Generation Consumer Analytics

Due to the increasing volumes of personal data being generated about each individual consumer, companies are introducing a new generation of AI-enhanced personal data analysis, which is is set to revolutionise retail analytics. By integrating sensors and automatic feature learning, it is now possible to gather a detailed trace of your life activities and experiences, and scientists are utilising these advancements to improve customer lifetime value (CLTV). Accuracy in CLTV allows retailers to better allocate marketing spend, identify and nurture high value customers, minimise exposure to unprofitable customers and attribute value to indirect marketing such as content production.

We'll explore this further with customer analytics experts Ben Chamberlain, Senior Data Scientist at ASOS, and Cathal Gurrin, Senior Lecturer at Dublin City University, on 1-2 June, delving further into customer "lifelogs" and big data, and how to leverage these new technologies for better customer understanding.

Micro-Moment Shopping & NLP

Apps and the low-cost wide availability of mobile devices has revolutionised the industry by allowing instant access to brand research and price comparison online. Over an incredibly short amount of time, the usual methods of purchasing goods has been completely overhauled, fracturing the consumer journey into hundreds of real-time informed decisions - which have become known as  micro-moments.

Understanding these micro-moments is now paramount to retailers everywhere, and AI offers novel solutions to keep up in a rapidly advancing technological world. Kumar Ujjwal, Senior Product Manager in Big Data & Machine Learning at Kohl's Department Stores, will explore deep learning in the micro-moment of shopping, with details of how a retailer can leverage NLP to aid their customers in making smart decisions in their shopping experience.

Intelligent Stock Management
At Zalando, they're applying deep neural networks for sizing solutions in online retail, customer engagement and recommendation systems. The company attributes many of their great user experiences to the addition of machine learning, such as precise predictions of future interests of consumers, based on deep analysis of previous engagements.

Calvin Seward, Research Scientist at Zalando's Research Lab, will join us to share how they use AI for intelligent management of warehouse stock, as well as tips and tricks of the trade for running GPU enabled neural networks with minimal technical overhead.

Human-Computer Interaction & Cooperation
While historical milestones in AI have been frequently associated with computers matching or outperforming humans in difficult cognitive tasks, less attention has been given to the development of AIs that have more cooperative relationships with humans. You've probably heard of human-computer interaction (HCI), which focuses on interfaces and communication between people and computers; human-machine cooperation (HMC) is the next step: fusing the strengths of both human creativity and common sense, which can be difficult to program in AI, with the powerful cognition of machines.

Despite a large number of recent advances in computer vision,  these do not always work for industry-specific image recognition needs and a collaboration between machines and people is needed to successfully build datasets that fuel specialised image recognition solutions. Augustin Marty, Co-Founder & CEO at Deepomatic, will join us to share how machine-human cooperation techniques can be leveraged to build datasets that fuel specialised image recognition solutions.

Don’t miss out; join the summit to learn more

The Deep Learning in Retail & Advertising Summit is a unique opportunity to interact with the influential technologists, data scientists, CTOs, founders and software engineers leading a new era of retail. Confirmed attendees include Amazon, Tesco, Trivago, Kohl's, Zalando, ASOS and Staples, as well as leading academic institutions and exciting new startups.

Join the event to learn from and connect with over 200 prominent innovators sharing best practices for a positive impact in this sector. For more information and to register, visit the event website here.

Tickets are limited for this summit! Previous events have sold out, so please book early to avoid disappointment. 

Suggest a speaker for the event here.

 Read more about how AI is impacting retail and advertising
View all upcoming RE•WORK summits here.

Neural Networks Machine Learning Deep Learning Algorithms Deep Learning Computer Vision A I Retail Finance Stock Level Optimisation Personalised Shopping Targeted Marketing Fraud Detection Retail Deep Learning in Retail & Advertising Summit Adtech

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