- “Chase now investing more than $11 billion each year on the technology side of its business.
- Last year, Chase inked a five-year deal with Persado, a platform that leverages AI to personalize marketing messages, with Chase chief marketing officer Kristin Lemkau saying at the time that ‘machine learning is the path to more humanity in marketing.’”
“A key tenet of our personalization model is that the more information clients share, the better we are able to personalize their recommendations. We are usually able to adapt the model based on feedback from our clients; however, rules-based systems aren’t generally adaptive. We need the system to learn from client feedback on the outfits it recommends. We’re receiving immensely helpful feedback, from how clients engage with the outfit recommendations and also from a custom-built internal QA system.
Style Profile: When a client signs up for Stitch Fix, we receive 90 different data points — from style to price point to size.
Feedback at checkout: 85% of our clients tell us why they are keeping or returning an item. This is incredibly rich data, including details on fit and style — no other retailer gets this level of feedback.
Style Shuffle: an interactive feature within our app and on our website where clients can “thumbs up” or “thumbs down” an image of an item or an outfit. They can do this at any time — so not just when they receive a Fix. So far, we’ve received an incredible 4 billion item ratings from clients.
Personalized request notes to Stylists: Clients give their Stylists specific requests, such as if they are looking for an outfit for an event, or if they’ve seen an item that they really like.”
- “The number of Zoom meetings jumped from a pre-Covid 10 million daily-meeting participants in 2019 to a whopping 300 million in April 2020.
- As of April 21, U.S. and Canadian e-commerce orders have grown by 129% year-over-year, while global online retail orders have achieved an impressive 146% growth.
- According to a Coresight Research report and pre-Covid-19 projections from Statista, the reality-technology market, which includes augmented reality and virtual reality, is forecast to reach $18.8 billion in 2020.”
“Everything you wanted to know about artificial intelligence (AI) but were afraid to ask! AI, inspired by our understanding of how the human brain learns and processes information, has given rise to powerful techniques known as neural networks and deep learning. This workshop will provide a high-level overview of these and other artificial intelligence techniques. Through pre-built hands-on exercises, we will discuss how current AI platforms compare with how the brain works, how systems actually “learn,” and how to build and apply neural networks. We will also discuss the societal and ethical issues surrounding the real-world applications of neural networks. By the end of the course, students will understand how AI techniques work so they can: (1) converse with neural network practitioners and companies; (2) critically evaluate AI news stories and technologies; and (3) consider what the future of AI can hold and what barriers need to be overcome with current neural network models. This workshop is ideal for product managers who interact with data scientists, software engineers who wish for more AI exposure, and anyone in the general public who wants to know how current AI works.
Ronjon Nag, Interdisciplinary Fellow, Stanford Distinguished Careers Institute; Fellow, Stanford Center for the Study of Language and Information; Founder and Managing Partner, R42 Group
Ronjon Nag has invented and deployed artificial intelligence systems for over three decades. He received a PhD in engineering from Cambridge, an MS from MIT, and the IET Mountbatten Medal, and he was a Harkness Fellow at Stanford. Companies he has co-founded or advised have been sold to Motorola, BlackBerry, and Apple.”
“Digitization as a necessary first step for many AI projects
At first glance, it may seem that digitization has nothing to do with AI. However, digitization is a necessary first step to extracting value from data that is locked in non-digital assets or human-based processes. By first digitizing and then digitalizing processes and documents, greater value can be applied to business organizations letting them tackle increasingly harder business problems of increasingly more strategic value. Without the foundational layer of digitization, organizations can’t apply higher level technology such as AI and ML to extract additional value. After all, data is the foundational layer upon which information, understanding, and insights can be gathered.”