Latest news with #UberAI
Yahoo
11 hours ago
- Business
- Yahoo
Uber Expands AI Data Platform to Power Next-Gen Enterprise and AI Lab Needs
SAN FRANCISCO, June 20, 2025--(BUSINESS WIRE)--Uber Technologies, Inc. (NYSE: UBER) today announced a major expansion of its AI data services business, Uber AI Solutions, making its technology platform available to support AI labs and enterprises around the world. The new offerings include customized data solutions for building smarter AI models and agents, global digital task networks, and tools to help companies build and test AI models more efficiently. Over the past decade, Uber has developed deep expertise in collecting, labeling, testing, and localizing data for its own global operations, including optimizing the search of places or menu items, training self-driving car systems, building Gen AI agents for customer support, and translating content in more than 100 languages. Now that same expertise is being made available to other businesses through Uber AI Solutions, the company's dedicated team focused on powering the next generation of artificial intelligence. "We're bringing together Uber's platform, people, and AI systems to help other organizations build smarter AI more quickly," said Megha Yethadka, GM and Head of Uber AI Solutions. "With today's updates, we're scaling our platform globally to meet the growing demand for reliable, real-world AI data." What's New Global digital task platformUber AI Solutions is now available in 30 countries with a platform that connects enterprises to global talent, including experts in coding, finance, law, science, and linguistics. These tasks include annotation, translation, and editing for multi-lingual and multi-modal content. Powered by Uber's foundational platforms for identity, verification, payments and more, this expands Uber's gig work model into the world of AI. A new data foundryA new service that provides ready-to-use and custom-collected datasets—including audio, video, image, and text—to train large AI models. Built with data collected by individuals around the world using Uber technology, the data foundry supports use cases on generative AI, mapping, speech recognition, and others, with built-in privacy and compliance. Agentic AI supportUber AI Solutions is offering the tools and data to help train smart AI agents, including realistic task flows, high-quality annotations, simulations and multilingual support, helping AI agents understand and navigate real-world business processes. Shared infrastructure for AI buildersUber is making its internal platforms available to enterprise clients. These are the same platforms Uber uses to manage large-scale annotation projects and validate AI outputs, and includes AI-powered smart onboarding, quality checks, smart task decomposition and routing, and feedback loops to ensure accuracy and efficiency. Building the human intelligence layer for AI With these advancements, Uber AI Solutions is poised to become the human intelligence layer for AI development worldwide—combining software, operational expertise, and its massive global scale. Looking ahead, Uber is building an AI-powered interface that will allow clients to simply describe their data needs in plain language, letting the platform handle setup, task assignment, workflow optimization, and quality management for scalable AI training. About Uber Uber's mission is to create opportunity through movement. We started in 2010 to solve a simple problem: how do you get access to a ride at the touch of a button? More than 61 billion trips later, we're building products to get people closer to where they want to be. By changing how people, food, and things move through cities, Uber is a platform that opens up the world to new possibilities. View source version on Contacts Uber Press Contact: press@
Forbes
13 hours ago
- Business
- Forbes
Uber Is Making A Push In Data Labeling After Scale AI's Deal With Meta
Uber is making a push in data labeling. Last week, Scale AI's bombshell deal for Meta to take a 49% stake in the company sent shockwaves throughout the industry: In its wake, prominent clients like OpenAI have pulled back on working with Scale, which the ChatGPT maker had already been doing for months. Google is also planning its split. And a host of data-labeling rivals has been emboldened to step in to fill the void. Among them is a little-known unit from a familiar giant: Uber. Since last November, the ride-hailing behemoth has operated Uber AI Solutions, a data-labeling platform focused on training AI models for enterprise clients. Now as Scale's deal has carved a new opening in the market, Uber is making its pitch to new customers. 'For Uber, our core has always been being the platform of choice for flexible on-demand work,' Megha Yethadka, general manager of the unit and a 10-year veteran of the company, told Forbes. Uber drivers, of course, are contractors that shuttle around passengers and deliveries all across the globe. 'That extends itself really well to this business of digital tasks now.' On Friday, Uber told Forbes it's making a push to expand the service. Among the updates: a new service that provides ready-to-use datasets, including audio, video, images and text, to customers training their own models. The company will also license out the platforms it uses internally for managing data labeling projects and accessing its network of contracted clickworkers, making them available for clients to use. Beyond just training models, Uber is now also offering clients tools to develop AI agents, which can take specific actions for users, like helping with customer support. Another change: Launched as Uber Scaled Solutions, the company recently swapped out the 'scaled' in its name for 'AI.' Yethadka said the rebrand had nothing to do with avoiding confusion with its similarly-named rival, but wanting to more simply convey the AI of the unit. Going forward, Uber wants to separate itself from its data-labeling rivals by automating more of the process to set up clickwork projects. The company is developing a software interface that allows clients 'to simply describe their data needs in plain language,' while the platform automatically handles assigning tasks, setting up workflows and maintaining quality control. The idea is to hand over the project to human clickworkers more quickly, instead of doing manual work to onboard workers. 'We do see an opportunity to build this into a meaningful business line for Uber.' The company said Uber AI Solutions is now available in more than 30 countries, an expansion from its five initial launch markets last November, which included the U.S., Canada and India. Since the start of this year, Yethadka said Uber has doubled the number of clickworkers on its platform. She declined to disclose how many taskers are in the company's network overall, but said there are 'tens of thousands' of people working on each topic area of tasks, including STEM, coding and law. The most engaged clickworkers spend about 3 to 4 hours a day performing tasks, which can range from $20 to $200 per hour, depending on the complexity of the work, Yethadka said. The unit has more than 50 corporate customers, including the autonomous vehicle company Aurora and Niantic, the creator of Pokemon Go that recently ditched the games business to pivot to enterprise AI. The expansion comes as Scale's tie-up with Meta has thrown the data labeling industry into a frenzy. As part of the deal, Scale CEO and founder Alex Wang is heading to Meta to lead the tech giant's newly-formed Superintelligence Lab, an effort to compete with other deep-pocketed frontier labs including those from OpenAI, Anthropic and Google. Now, 'a number of companies are, of course, looking to revisit their partner strategy for data,' said Yethadka, aiming to find vendors that are 'neutral and impartial." In the aftermath, smaller rivals, including unicorns Mercor and Turing and startup Invisible Technologies, are clamoring to pounce. But Uber stands out among the competition because of its sheer size and resources, Yethadka argues. 'A lot of companies in this space are a lot smaller, VC-funding dependent,' she said. Meanwhile Uber, which is worth $175 billion and tallied $43.9 billion in revenue last year, is a more reliable long-term bet, Yethadka said. (She declined to break out the data-labeling unit's revenue.) While other companies in the space more resemble service providers, Uber has a long history of shipping products, which brings a different perspective when the company collaborates with customers, she said. 'We have been a product company and an operations company, and have done this for a living ourselves,' said Yethadka. 'We do see an opportunity to build this into a meaningful business line for Uber.' Even Scale had taken notice of Uber before the Meta deal. 'This space is full of opportunities. I think more people are seeing the value of the work we're doing here, which is why even a business like Uber will want to try their hand at the same space,' Xiaote Zhu, GM of Scale's Outlier platform for generative AI clickwork, told Forbes earlier this year. Still, it's not a foregone conclusion that Uber will come out on top, competitors say. The spoils will go to the company that compiles the best pool of clickworkers. 'Data annotation is transitioning towards higher and higher-skilled work,' Brendan Foody, CEO of $2 billion-valued Mercor, told Forbes. 'Uber's success will depend on how effectively they build this high-skilled talent network.' What's more, Uber has its own baggage. For years, the company limped through controversies around regulation and the treatment of its contract drivers. Yethadka said customers have not minded, and that Uber has committed to 'do the right thing' when it comes to data confidentiality and security controls. 'And that continues to be applied to this new line of business as well,' she said.
