Uber Expands AI Solutions Business, Offering Global Data Services and New AI Foundry

Uber Expands AI Solutions Business, Sets Up New Foundry

Uber also said it is launching a new foundry to train large AI models. Uber Technologies (UBER) said Friday it is expanding its AI data services business, opening up operations to support AI labs and enterprises globally as well as setting up a new foundry. The ride-hailing giant said it would expand Uber AI Solutions to offer "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." "We're bringing together Uber's platform, people, and AI systems to help other organizations build smarter AI more quickly," Uber AI Solutions head Megha Yethadka said. Uber also said it is launching a new foundry using "custom-collected datasets -- including audio, video, image, and text" to train large AI models. Uber shares rose about 1.5% at the opening bell Friday. They are up roughly 40% this year.

Uber AI Solutions Expands Resources for Training AI Models and Agents | PYMNTS.com

Uber AI Solutions offers other businesses solutions that Uber has developed over the past decade while using data and AI in its own operations, the company said in a Friday (June 20) press release. "We're bringing together Uber's platform, people and AI systems to help other organizations build smarter AI more quickly," Megha Yethadka, general manager and head of Uber AI Solutions, said in the release. "With today's updates, we're scaling our platform globally to meet the growing demand for reliable, real-world AI data." One solution offered by Uber AI Solutions is a platform that connects enterprises to global talent who can provide annotation, translation and editing for multilingual and multimodal content, according to the release. The available talent includes experts in coding, finance, law, science and linguistics. The company also offers datasets to train large AI models for generative AI, mapping, speech recognition and other use cases; task flows, annotations, simulations and multilingual support to help train AI agents; and its own internal platforms for managing large-scale annotation projects and validating AI outputs, per the release. "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," the release said. The AI industry has faced a shortage of high-quality data for training AI models, PYMNTS reported in July. While the internet generates enormous amounts of data daily, quantity doesn't necessarily translate to quality when it comes to training AI models. Researchers need diverse, unbiased and accurately labeled data, and that combination is becoming increasingly scarce. In another, separate development in this space, SandboxAQ said Wednesday (June 18) that it launched a dataset designed to help researchers advance AI models in drug discovery. Generated with the use of SandboxAQ's AI large quantitative model capabilities and Nvidia's development platform for AI training and fine-tuning, the dataset enables researchers to train AI models to accurately predict protein-ligand binding affinities at least 1,000 times faster than traditional physics-based methods.

Uber Expands Ai Data Platform to Power Next-Gen Enterprise and Ai Lab Needs

Uber Technologies, Inc. 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. Uber 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 foundry: A 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. Uber 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 builders: Uber 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. 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.