Companies understand the importance of artificial intelligence and machine learning, especially since it’s become an increasingly important competitive differentiator, and are eager to jump in. But as always, the question stands: Once you’ve identified the potential of AI for your business, do you buy, or do you build?
That’s one of the big questions we’ll be tackling at this year’s Transform: Accelerating Your Business With AI. Spoiler alert: Lyft, Uber, Airbnb, and LinkedIn, featuring prominent speakers at this year’s event, have come down firmly on the side of building their own AI solutions. And they’ve ended up with some dramatically successful — and very cool — results.
Of course, it’s fine for tech companies in Silicon Valley with a ton of resources to build their own solutions. For the rest of us, that sounds utopian, and Transform will have plenty to share from more traditional companies — manufacturing companies from the midwest you may not have heard of, for example, or mainstays like Raytheon, Schneider Electric, Otis, Johnson & Johnson, and more. We’ll also have how-to AI product workshops on things like deep learning and edge computing
But as far as the tech trend-setters are concerned, here’s a preview of conversations in store at this year’s Transform 2019, and a look at just a few of the things our featured guests have accomplished with their in-house tools.
The soul of Lyft, and the company’s driving force, is its focus on AI experimentation and innovation. Cross-departmental collaboration, with teams consisting of a marketer, a data scientist, an engineer, and a product manager, work to keep roughly 10 million customers happy and requesting more rides.
That means consistent, seamless experiences every time, delivered efficiently and personalized enough to ensure a customer’s loyalty. Currently that includes the chat-like experience powered by AI and machine learning bots in the Lyft app, which anticipates customer questions and analyzes driver and passenger data to offer the most effective resolutions, and continues to learn, grow, and get more effective as use cases are added and teams continue to iterate, experiment, and learn themselves.
You’ll hear more about how Lyft is breaking down silos and implementing AI across the company from featured speaker Gil Arditi, Head of Product, Machine Learning at Lyft.
At “Implementing AI architecture across your company stage,” you’ll learn how Lyft is scaling an AI-first organization for 2020 and beyond. And in his talk, “Recent advancements in AI algorithms and systems,” Arditi will be talking about significant advances made in AI over the past year, all of which have implications for technology strategies for any ambitious company.
Is Uber “the first AI company“? If making machine learning and neural networks the foundation of all their business processes and the central driver of their competition in the market qualifies, we’re looking at a yes.
The company uses AI in every business case, both internally and externally, to make data-driven decisions at scale. It optimizes marketing spend and placement across channels according to market dynamics, and sets financial goals for the company against the bigger picture. It forecasts user supply and demand to boost the effectiveness of their service and the return for their drivers — as well as route optimization and onboarding. It plans for hardware capacity to ensure service is always up and cost-effective, handles risk assessment, is on top of fraud detection, and can probably solve the Kobayashi Maru scenario.
For more on Uber’s all-in on AI, and how their results can inform your own strategy, check out the panel that Franziska Bell, Director of Data Science at Uber, will be heading up at Transform, “Implementing AI architecture across your company.” You’ll learn about the AI platform that allows Uber to forecast across the organization, best-practice approaches to implementing an AI strategy, and more.
To disrupt an entire industry, you need to find new ways to answer old questions — or start asking better questions. Airbnb turned the hospitality and travel industry on its head from the start with the way it tackled its central mission, connecting guests with the right vacation experience. On the host side, its priority is helping hosts maximize revenue by building new AI and machine learning approaches to tackle everything from personalized real-time search ranking and dynamic pricing to paid growth and online experimentation with machine learning and artificial intelligence.
It fuels all their products, inside and out. Their sophisticated neural network, which mimics how neurons fire in the human brain, boosts the relevance of search results on its website and mobile app. AI-powered search, discoverability, and personalization helped the company go from 500 Experiences in 12 cities, to more than 20,000 active Experiences in two years. With conversational AI technologies and a machine learning framework, guest messages can be classified and intent identified to shorten the time a guest has to wait for a response and to reduce the overall workload required for hosts. The in-house AI system can turn design sketches into product source code, and its machine learning-powered language system can translate listing reviews into guests’ native languages.
To learn more about the Airbnb team’s approaches to solving everything the market throws at them, don’t miss Jeff Feng, data product lead at Airbnb. In his session, “How to implement AI at massive scale,” he’ll talk about how scaled AI platforms help developers become more productive across their organizations. And catch the talk by Airbnb’s Andrew Hoh, Product Manager, Applied Machine Learning, “Standardizing and scaling AI in your organization,” where he’ll dive into how smart organizations can standardize processes for machine learning and AI projects, and scale training and deployment without having to reinvent the wheel each time.
At LinkedIn, AI is like oxygen, says Deepak Agarwal, head of artificial intelligence. It infuses every experience, from the personalization of a member’s feed to models that automate the process of building the AI systems themselves, and they continue to explore new use cases, per-member models as part of their continued work to expand the use of generalized linear mixed models (GLMix), member-to-topic interest graphs, creator-side optimization for members who create high-quality content on LinkedIn over time, and more.
Because the demand for artificial intelligence and machine learning has dramatically increased for products across the company, LinkedIn is taking the build-it approach one step further. Rather than continually hiring expensive data scientists to integrate into existing departments, the company has launched an AI academy to equip employees in areas like engineering, product management, and more with the knowledge they need to integrate AI into their current projects and dive into more intelligent products and technology and continue to innovate.
To learn more about how the company is integrating AI into every feature, and the results of their AI Academy initiative, don’t miss Agarwal Transform this year, when he, too, joins the session “Implementing AI architecture across your company stage.”
At Transform 2019, we’re showcasing the best of AI business applications, and debating advances in all AI business areas, including sessions on computer vision, robotic process automation, AI at the edge, and more. Register now to see top AI innovators from Lyft, Uber, Airbnb, and LinkedIn go in deep about their AI experiences, plus executives from companies like Google, Amazon, Microsoft, Facebook and Salesforce squaring off not only about the future of it all, but how businesses should be applying it right now.