TransformX Conference: Operationalizing AI at Scale

Mike Schroepfer, Meta’s first Senior Fellow, has been a driving force behind transformative technologies, from his time leading groundbreaking work in computer vision, natural language processing, and the metaverse to his focus today on combating climate change with technology. Schroepfer will sit down with Scale Founder and CEO Alexandr Wang to share lessons from Facebook’s transition from being web-focused to becoming mobile-focused and, ultimately, an AI-centric company. He will explain the developer pain that motivated an industry-standard framework like React Native, as well as the motivations behind keeping PyTorch as a community-focused tool, built for researchers.

He will discuss large language models and how more carefully curated, differentiated, and high-quality data will drive significant advancements in capabilities in the near term. He will also cover the future of augmented and virtual reality, including real-time machine translation with closed-captioning, contextual recognition of real-world objects to create more helpful applications, and more efficient hardware with native AI.

At Meta, Schroepfer focuses on supporting the company’s strategic technology priorities including its investments in AI and development of technical talent. From 2013 to 2022, he served as Meta’s Chief Technology Officer, where he led the development of the technology and teams that enabled the company to scale to billions of people around the world and make breakthroughs in fields like AI and virtual reality.

Pieter Abbeel wears many hats: Professor at UC Berkeley, Director of the Berkeley Robot Learning Lab, Founder of three companies, podcast host, and investor. The common thread is that Professor Abbeel is passionate about AI and robotics. In this keynote presentation, he will explore the possibility of training a large neural network to enable faster learning in robotics. Professor Abbeel will discuss his lab’s approach to solving this problem and will cover how video prediction is an excellent proxy for generalizable robots, the relevant models and datasets useful for pre-training, how unsupervised learning can help robots learn from themselves; and the usefulness of a human-in-the-loop. He will describe a four-step framework that might be able to lead, ultimately, to generalized robotics. Professor Abbeel is co-director of the Berkeley Artificial Intelligence (BAIR) Lab and founded Gradescope, which provides AI to help instructors with grading homework and exams, and Covariant, which provides AI for robotic automation of warehouses and factories. He is also a founding partner at AIX Ventures, a venture capital firm focused on AI start-ups, and is the host of The Robot Brains podcast, which explores what AI and robotics can do today and where they are headed.

Few organizations have had a greater number of AI breakthroughs than Koray Kavukcuoglu’s team at DeepMind, a subsidiary of Alphabet. DeepMind’s research has changed multiple industries—from games with AlphaGo, to text-to-speech systems with WaveNet, and more recently biology with its AlphaFold protein-folding technology.

In July 2022, DeepMind announced that over 200 million predicted protein structures, representing virtually all known proteins, would be released on the AlphaFold database. AlphaFold can accurately predict 3D models of protein structures and has the potential to accelerate research in every field of biology.

Koray Kavukcuoglu is Vice President of Research at DeepMind. In this fireside chat with Alexandr Wang, Scale CEO, learn how his DeepMind researchers consistently bridge industry, science, and AI domains to create the world’s most meaningful AI advancements. Kavukcuoglu will discuss how AlphaFold evolved from research to having measurable real-world impact, the principles for managing incredibly large breakthrough projects and scopes, and how to plan for the next big scientific discovery.

John List is a Professor at the University of Chicago and the Chief Economist at Walmart; he formerly served as Chief Economist at Lyft and Uber. Economists look at machine learning through a different lens. They identify causal effects, detect heterogeneity, and generally want to improve the bottom line and make the world better. List will take you through his experiences with machine learning and share the economics of apologies at Uber, the value of time at Lyft, and how the voltage effect impacts machine learning at scale. The Voltage Effect: How to Make Good Ideas Great and Great Ideas Scale is List’s latest best-selling book. To obtain data for the field experiments he pioneered in the 1990s, List has used several different markets, including charitable fundraising activities, the sports trading card industry, the ride-share industry, and the education sector, to highlight a few. This collective research has led to collaborative work with several schools, charities, and businesses, including Humana, United Airlines, Sears, General Motors, and many others. List’s research includes over 200 peer-reviewed journal articles and several published textbooks. He co-authored the international best seller, The Why Axis, in 2013. He is a current editor of The Journal of Political Economy.

Bradley Horowitz, industry veteran and Google product leader, will talk with Scale founder and CEO Alexandr Wang about the transformative experiences that have helped him in his current role as lead for products with billions of users, which over the past decade have included Gmail, Calendar, Google Docs, Hangouts, Google News, Blogger, Reader, and Google Photos. He will discuss how he learned to build what users really need, and not what academics believe they need. He will discuss the potential of AI-enable features and applications being explored further and the need to solve the simple problems before being able to convince customers to try more sophisticated features.

When it comes to billion-user systems like Gmail, he will explain how he has helped tackle issues with data-driven product development, a good sense of triage, and relentless experimentation. He also will cover the lessons he learned from Flickr, which he helped Yahoo acquire, and how it’s best to let computers and humans do what they each do best.

Before joining Google, Horowitz helped lead video-analysis startup Virage to an IPO and served as VP of advanced development at Yahoo. Bradley is also an angel investor in Slack, Upstart, Grab, Miro, Coda, Sana and over 100 other high-impact startups.

Jeff Wilke is chairman and co-founder of Re-Build Manufacturing, a private company helping to bolster America’s industrial competitiveness. Before taking on this role, Wilke spent more than 21 years at Amazon, most recently as CEO of Worldwide Consumer, where he grew the business from $1 billion to a mind-boggling $386 billion a year. He spent his first seven years at Amazon building global operations. Wilke brings a wealth of knowledge across areas including supply chain, retail, and operations. Wilke will speak with Scale CEO Alexandr Wang to discuss his journey at Amazon and will cover how focusing on data and building models can help power eCommerce marketplaces. Learn how Wilke applied AI across the entire eCommerce stack and created an authoritative and comprehensive product catalog with more than 12 million listings. He will also share his predictions about the future of AI and sustainability. Wilke is an active philanthropist and mentor of startup founders who identify as female and/or People of Color. He is Vice Chairman of Code.org and Chairman of the U.S. Government’s Advisory Committee on Supply Chain Competitiveness.

Pinterest’s team knows that people want to feel included. When platforms lack representation, it tells people that the way someone may look or where they come from isn't the ‘norm.’ It’s more important than ever before to design inclusive systems that remove historical biases. Nadia Fawaz is the senior staff applied research scientist and technical lead of inclusive AI at Pinterest, which hosts over 400 million users who speak over 35 languages across 8 billion boards. In this keynote, Fawaz will explain how ML learns implicit bias and algorithmic fairness, how to design inclusive systems with cross-functional teams, how Pinterest learned from errors and made its models also learn from errors, and how Pinterest has built inclusive features, especially regarding skin tone and hair patterns, to create a more engaging platform. Fawaz will discuss how it is possible to change technology with intent. Fawaz’ research and engineering interests include machine learning for personalization, AI fairness and data privacy; her work aims at bridging theory and practice. Before joining Pinterest, she was a Staff Software Engineer in Machine Learning at LinkedIn, a Principal Research Scientist at Technicolor Research lab, and a Postdoctoral Researcher at the Massachusetts Institute of Technology’s Research Laboratory of Electronics.

Mike Fisher, Chief Technology Officer of Etsy, will join Scale CEO Alexandr Wang for a fireside chat. Etsy’s systems process over 6 billion events each day. Etsy’s platform was originally created to link creators of unique items with people wanting to buy these one-of-a-kind pieces. In this fireside chat, Fisher will discuss scaling the Etsy platform to support over 100 million buyers and 5 million sellers using machine learning. Fisher also discusses how the company has rebuilt many of its search engine capabilities with more intelligent algorithms to provide more accurate recommendations.

Learn how Etsy addresses long-term product and content issues and how the company built a strong DevOps and engineering culture that encourages experimentation. Before joining Etsy, Fisher served as a captain and pilot in the U.S. Army, was a Vice President at PayPal, and had several technology leadership roles at GE.

Faire is an online marketplace that connects the world’s “best independent brands” with local retailers. There are over 85,000 brands and over 600,000 retailers using the platform across Europe and North America. Daniele Perito, Co-Founder and Chief Data Officer of Faire, will discuss how the marketplace is using machine learning to grow sales for both their small business customers and ultimately their consumers as well. Retailers on Faire can buy inventory and pay 60 days later, giving them the ability to return products that don’t sell, without disrupting their cash flow. Brands on Faire benefit from analytics and marketing tools that allow them to grow their customer base and their business. Offering these value propositions and acting as a matchmaker between brands and retailers requires dozens of models that span the gamut of machine learning and data techniques, from information retrieval to entity resolution to anti-fraud to default risk assessment with binary classifiers to operations research and econometrics.

Learn how Faire built and curated tools and infrastructure to be able to run thousands of trials simultaneously and experiment at scale. Prior to Faire, Perito was Director of Security, Risk for Square Cash, where he worked on building secure, fast, and easy-to-use products.

During his 13-year tenure, Nick Beighton, former CEO of ASOS, grew the online apparel company from 200 million to 4 billion GBP in revenue by investing in data. Beighton will be joined by Jules de Boinville, Head of Scale’s UK deployments, to discuss how his team improved catalog data at ASOS and the key measurements they used to understand the business impact of their digital initiatives.

Beighton will also cover the core business values he helped create and best practices to effectively use customer and product data in eCommerce to deliver higher conversion rates. Beighton will describe how ASOS started by working on optimizing discovery tools, delivering product recommendations, and correctly tagging product attributes, four years before they invested in digital marketing. Underlying it all was a spirit of experimentation, which Beighton will explain in more depth. Before joining ASOS, Beighton worked for KPMG, specializing in business transformation, and held finance-related positions in other online retailers.

The digital shelf has grown to include everything from hotels and vacation rentals to toothpaste, prescription drugs, corner shops, taco trucks, and even your neighbor's used couch. Over the past couple of years, eCommerce and retail companies have evolved the digital shelf and digitized commerce to meet consumers’ changing needs. Aatish Nayak, Head of Catalog at Scale, joins Saad Ahmed, Managing Director, Regional Head of Commercial at Grab, and Rong Yan, Chief Technology Officer at Verishop, to discuss the most pressing advancements. This expert panel will explore how platforms have evolved to digitize online retail, the importance of data-centric AI, and will share their predictions on the future of eCommerce.

Jordan Fisher, CEO of Standard AI, is passionate about changing the real-world retail experience by unlocking better shopping experiences with computer vision. Fisher will discuss applying computer vision models to the physical world to create human-centric applications; augmenting retail staff with better inventory tools and store layout analytics; and creating better shopper experiences with autonomous checkout. Even given the challenges in today’s retail environment—the labor shortage, inflation, the supply chain crunch, and difficulties competing against tech giants—shoppers expect more options and a better experience. Fisher’s vision is to allow customers to come in, shop, skip the checkout line, and get a receipt within minutes after they leave. At a shop at San Jose State University, traffic increased by 20%, average total receipts increased by almost 23%, and there was a decrease in wait time by over 50%. Further, store employees get analytics about which items are out of stock or misplaced, as well as traffic patterns about individual shoppers that do not collect PII. Fisher has spent his career focusing on both fundamental research and product development. He has worked in computational fluid dynamics, securities regulations, video games, machine learning, and retail, and seeks out areas where innovative products can be forged by tackling difficult research initiatives.