Category: Engineering

As part of MLflow 2’s support for LLMOps, we are excited to introduce the latest updates to support prompt engineering in MLflow 2.7.  Assess LLM project viability with an interactive prompt interfacePrompt engineering is a great way to quickly assess if a use case can be solved with a large language model (LLM). With the […]

Artificial Intelligence (AI) has evolved and improved dramatically over the past 18 months, and the technology has myriad applications and amazing potential for the future of ecommerce. But with such lightning-quick advancements, it’s vital that we in the technology industry, especially companies like eBay with the size, scope, and personnel to guide the future of […]

We’ve been hard at work on the next version of a new, magical listing experience, which uses AI to analyze, research, and extrapolate information from a small amount of data provided by the seller — greatly simplifying the process of listing an item on eBay. In the first version, a seller could add in a […]

We are thrilled to announce that you can run even more workloads on Databricks’ highly efficient multi-user clusters thanks to new security and governance features in Unity Catalog Data teams can now develop and run SQL, Python and Scala workloads securely on shared compute resources. With that, Databricks is the only platform in the industry […]

We are thrilled to announce great enhancements to onboard more workloads to Unity Catalog clusters in shared access mode, Databricks’ highly efficient, secure multi-user clusters. Data teams can now develop and run SQL, Python and Scala workloads securely on shared compute resources. With that, Databricks is the only platform in the industry offering fine-grained access […]

With the rapid advancement of neural network-based techniques and Large Language Model (LLM) research, businesses are increasingly interested in AI applications for value generation. They employ various machine learning approaches, both generative and non-generative, to address text-related challenges such as classification, summarization, sequence-to-sequence tasks, and controlled text generation. Organizations can opt for third-party APIs, but […]

Introduction Southeast Asia (SEA) is a dynamic market, very different from other parts of the world. When travelling on the road, you may experience fast-changing road restrictions, new roads appearing overnight, and high traffic congestion. To address these challenges, GrabMaps has adapted to the SEA market by leveraging big data solutions. One of the solutions […]

To build customer support bots, internal knowledge graphs, or Q&A systems, customers often use Retrieval Augmented Generation (RAG) applications which leverage pre-trained models together with their proprietary data. However, the lack of guardrails for secure credential management and abuse prevention prohibits customers from democratizing access and development of these applications. We recently announced the MLflow […]

Launched in 2019, Segmentation Platform has been Grab’s one-stop platform for user segmentation and audience creation across all business verticals. User segmentation is the process of dividing passengers, driver-partners, or merchant-partners (users) into sub-groups (segments) based on certain attributes. Segmentation Platform empowers Grab’s teams to create segments using attributes available within our data ecosystem and […]

One of the key challenges that organizations face when adopting the open data lakehouse is selecting the optimal format for their data. Among the available options, Linux Foundation Delta Lake, Apache Iceberg, and Apache Hudi are all excellent storage formats that enable data democratization and interoperability. Any of these formats is better than putting your […]