TransformX Conference: Operationalizing AI at Scale

Use this time to make yourself familiar with the platform and network.

Greg Brockman, President and Co-Founder of OpenAI, will join Alexandr Wang, CEO and Founder of Scale, to discuss the role of foundation models like GPT-3 and DALL·E 2 in research and in the enterprise. Foundation models make it possible to replace task-specific models with those that are generalized in nature and can be used for different tasks with minimal fine-tuning.

In January 2021, OpenAI introduced DALL·E, a text-to-image generation program. One year later, it introduced DALL·E 2, which generates more realistic, accurate, lower-latency images with four times greater resolution than its predecessor. At the same time, it released InstructGPT, a large language model (LLM) explicitly designed to follow instructions. InstructGPT makes it practical to leverage the OpenAI API to revise existing content, such as rewriting a paragraph of text or refactoring code.

Before creating OpenAI, Brockman was the CTO of Stripe, which he helped build from four to 250 employees. Watch this talk to learn how foundation models can help businesses benefit from applications that they can create more quickly than with past generations of AI tools.

Thomas Kurian, the CEO of Google Cloud, will join Alexandr Wang, CEO and Founder of Scale, to discuss how AI helps businesses across various industries and use cases. Google Cloud is well-known for developer adoption, helping machine learning teams to create production-grade machine learning models. With platforms like Vertex AI and TensorFlow, Google boasts the most popular machine learning platforms adopted by over 3 million developers globally. Google also has succeeded with the widespread adoption of machine learning capabilities in its consumer and business products, including Gmail smart replies and predictive search.

Kurian will advise how to best roll out machine learning capabilities to many customers and ensure they are widely adopted. He will also discuss that, with the advent of foundation models, now is the time for all industries to more broadly adopt AI or risk falling behind the competition. He will detail practical use cases for retail, logistics, manufacturing, and healthcare. Kurian and Wang will also discuss the future of machine learning and what it will take to get there.

Before Google, Kurian spent 22 years at Oracle; his nearly 30 years of experience have given him a deep knowledge of engineering, enterprise relationships, and leadership of large organizations. Throughout his career, he has demonstrated a unique capability to align the latest technological developments, including machine learning, with real business problems to provide practical solutions to customers.

Leading organizations across every industry also need to be technology leaders, and today that means leveraging AI. Organizations applying AI don't necessarily have AI expertise, but they are prepared to leverage AI as a strategic asset for their innovation and product strategies. Many of these companies are looking for established use cases to supercharge their products, operations, and business lines. This is where pre-trained models create an opportunity for organizations without the resources and expertise build their own AI.

Alexandr Wang, Scale’s CEO and Co-Founder, will outline how Scale’s product investments are helping all types of organizations and teams apply and create their own AI.

Wang will also share how the latest advancements in AI allow next-generation models to be more versatile and attuned to specific business needs that weren’t possible before. He will explain why foundation models are the most exciting advancement happening in AI, and how Scale can help advance foundation models, especially as it applies to tuning these models to make them useful for specific tasks and industries including insurance, defense, logistics and many others.

Wang founded Scale while a 19-year-old student to help companies build long-term AI strategies with the right data and infrastructure. Under his leadership, Scale has grown to be valued as a $7 billion company serving hundreds of customers across industries from finance to e-commerce to U.S. government agencies.

Austin Russell, CEO and Founder of Luminar, will join Alexandr Wang, CEO and Founder of Scale for a fireside chat. The two will discuss the parallel missions of their respective companies with the purpose of training better models on high-quality, labeled data collected from the best 3D sensors available for autonomous systems.

Wang will ask Russell about his journey from Stanford dropout to his company’s 2020 NASDAQ IPO, product development, and how he thinks about building the machine learning infrastructure to train better models on 3D point cloud data. Russell will explain why he believes high-quality 3D sensors are essential for safe autonomy, and why simple 2D imagery doesn’t suffice.

Russell was a 2013 Thiel Fellow, which allowed him to drop out of his undergraduate studies and focus on Luminar full-time. He also became the world’s youngest billionaire as a result of his company’s IPO.

Modern medicine has provided effective tools to treat some of humanity’s most significant and burdensome diseases. At the same time, it is becoming consistently more challenging and more expensive to develop new therapeutics. The drug development process involves multiple steps, each of which requires a complex and protracted experiment that often fails. Insitro CEO and Founder Daphne Koller believes that, for many of these phases, machine learning models can help predict the outcome of the experiments and that those models, while inevitably imperfect, can outperform predictions based on traditional heuristics.

In this keynote, Koller will discuss how Insitro is bringing together high-quality data from human cohorts, while also developing cutting-edge methods in high-throughput biology and chemistry that can produce massive amounts of in vitro data relevant to human disease and therapeutic interventions.

Koller will also cover how the data are then used to train machine learning models that make predictions about novel targets, coherent patient segments, and the clinical effect of molecules. Insitro’s ultimate goal is to develop a new approach to drug development that uses high-quality data and ML models to design novel, safe, and effective therapies that help more people faster, and at a lower cost.

Koller also co-founded Engageli and has served as the co-CEO and President of Coursera. She received the MacArthur Foundation Fellowship in 2004 and the ACM Prize in Computing in 2008, and was elected a fellow of the American Association for Artificial Intelligence in 2004, in addition to receiving many other honors and awards.

Thanks to Dall-E, Stable Diffusion, Alexa, Siri, Google Assistant, and plenty of others, AI technologies are now more visible to the public than ever. But even though there have been numerous AI advancements and AI-infused products over the past decade, many organizations are still looking to understand how AI fits into their path to innovation. Eric Schmidt is an accomplished technologist, entrepreneur, and philanthropist and is well known for leading Google in its early days, from 2001 to 2011, and helping it to scale its infrastructure, diversify its product offerings, and maintain a strong culture of innovation. Today, he runs Schmidt Futures—a philanthropic venture—and advises governments and societies around the world on how to build a brighter future through technology.

Gerrit De Vynck, AI and algorithms reporter for The Washington Post, will moderate a fireside chat between Schmidt and Scale Founder and CEO Alexandr Wang, where they will talk about today’s advances in AI compared to 10 years ago. Schmidt and Wang will share their thoughts on what the next generation of AI companies will look like, what the proliferation of AI technology will mean for big tech, startups, and government, and how to push AI forward responsibly.

AI researchers have given the world a revolutionary new platform in the form of large models trained on internet data. And the game has changed dramatically with the recent release of advanced open source models.

Some people think that the model is the product. It is not. It is an enabling technology that allows new products to be built. The breakthrough products will be AI-native, built on these models from day one, by entrepreneurs who understand both what the models can do, and what people actually want to use.

While many AI technologies are still in their infancy, several are starting to emerge as practical for real-world applications. Many new AI-native products have grown explosively, reaching millions of users and creating huge businesses practically overnight. This is just the beginning.

Nat Friedman was the CEO of GitHub from 2018 to 2022, led Microsoft’s $7.5 billion acquisition of GitHub, and founded two startups. Friedman is joined by Alexandr Wang, Founder and CEO of Scale, to explore this new AI-native future and what it will take to succeed.

Dr. Craig Martell recently transitioned from an industry job as Head of Machine Learning at Lyft to becoming the new Chief Digital and AI Officer at the U.S Chief Digital and Artificial Intelligence Office (CDAO). Drawn by the mission, Dr. Martell brings a wealth of AI and business experience that he hopes will help increase the pace of technology adoption.

Dr. Martell will join Alexandr Wang, CEO and Founder of Scale, to discuss his charter to help the DoD increase its speed and agility for developing and fielding advances in AI, data analytics, and machine-learning technology. Dr. Martell will discuss how he plans to align incentives to take advantage of existing private-sector technology while streamlining procurement processes.

He will cover how his team will organize the immense quantities of data the department processes to make it more AI-ready to improve the department's capabilities overall.

Dr. Martell will also identify the advanced AI capabilities he plans to implement across the CDAO and how some of the latest advancements in large models factor into his plans. Finally, he will describe how his group communicates complex technical topics to non-technical leaders in the government and how the industry can best support the government with AI initiatives.

Deputy CTO of Microsoft and former CEO of Wikipedia, Lila Tretikov, joins John Maeda, CTO of Everbridge, to discuss how AI impacts humanity and how to best leverage this technology to grow. They will discuss the evolution of art and artists' role in the age of AI. Lila will discuss how Large Language Models (LLMs) are redefining how we interact with machines today and how advances in this technology will enable non-developers to build applications and immersive experiences with simply a prompt. Lila and John will explore AR/VR/XR, practical applications for headsets like Microsoft's hololens, and how this technology will evolve in the future. Lila and John also draw on their vast experience to outline the most impactful business applications of machine learning technology today.

They also discuss how AI mirrors humanity and the importance of being intentional about what data we use to train our models to enhance ourselves best. We think of AI as learning from us. But in its growing capacity to extend beyond any person's memory, computing, or even historical lifetime, it enables us to explore the sum of all human knowledge and to further simulate the possibilities of our future.

Neda Cvijetic, Senior Vice President of Autonomous Driving at Stellantis, will join Russell Kaplan, Scale’s Director of Engineering, for a fireside chat. The two will discuss the role of data diversity in building safer autonomy, and Cvijetic will share highlights from her career building autonomous vehicles at Tesla, NVIDIA, and now Stellantis, the parent company of Dodge, Fiat, and Chrysler.

Cvijetic will explain the opportunities that arise while building an entirely new infrastructure for training models for autonomous vehicles at a large automotive OEM, without the hindrance of having to support legacy systems. She will also discuss how she plans to achieve Stellantis’s publicly shared goals around Level 3 autonomy in 2024. The Stellantis portfolio includes Jeep, meaning its systems will also handle off-road scenarios. Kaplan and Cvijetic will also cover core paradigms in autonomous vehicles, from mapping to deploying to a million-vehicle fleet, to large language models, with more than a few surprising real-world anecdotes.

Prior to Stellantis and NVIDIA, Cvijetic worked on autopilot and infotainment systems at Tesla, served on the adjunct faculty of Columbia University, and held senior research positions at NEC Labs America. She holds more than 20 U.S. patents.

Stable Diffusion disrupted the deep learning scene when it was released in August, advancing the field of text-to-image models because of its ability to generate photo-realistic images given any text input. And unlike other models, Stable Diffusion makes its source code available, further advancing the democratization of AI. Stable Diffusion was created by Stability AI, in collaboration with EleutherAI and LAION. Stability AI is on a mission to design and implement solutions using collective intelligence and augmented technology and has developer communities with over 20,000 members who are building AI for the future. In this fireside chat, Emad Mostaque, CEO of Stability AI, will discuss emerging trends for open source AI infrastructure, the importance of data for real-world applications of AI, and predictions on the development of “text-to-everything” in artificial intelligence.