Data Science – Noise

Real-time data quality monitoring: Kafka stream contracts with syntactic and semantic test

Grab Tech — Wed, 26 Nov 2025 00:00:10 +0000

Introduction In today’s data-driven landscape, monitoring data quality has become a critical need for ensuring reliable and efficient data usage across domains. High-quality data is the backbone of AI innovation, driving efficiency and unlocking new o...

What should be included in a data science curriculum for schools?

Jan Ander — Thu, 30 Oct 2025 11:24:44 +0000

Current artificial intelligence (AI) methods, especially machine learning (ML), rely heavily on data. To complement our work on AI literacy, we have been investigating what data science teaching resources and education research are currently available. Our goal is to work out what data science concepts should be taught in a data science curriculum for schools.…

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Machine-learning predictive autoscaling for Flink

Grab Tech — Thu, 30 Oct 2025 00:00:10 +0000

Introduction As Grab transitions to derive more valuable insights from our wealth of operational data, we are witnessing a steep increase in stream-processing applications. Over the past year, the number of Flink applications grew 2.5 times, driven by...

Modernising Grab’s model serving platform with NVIDIA Triton Inference Server

Grab Tech — Tue, 21 Oct 2025 00:00:10 +0000

Introduction Catwalk is Grab’s machine learning (ML) model serving platform, designed to enable data scientists and engineers in deploying production-ready inference APIs. Currently, Catwalk powers hundreds of ML models and online deployments. To acco...

Bringing data science to life for K–12 students with the ‘API Can Code’ curriculum

Diana Kirby — Thu, 12 Jun 2025 11:23:57 +0000

As data and data-driven technologies become a bigger part of everyday life, it’s more important than ever to make sure that young people are given the chance to learn data science concepts and skills. In our April research seminar, David Weintrop, Rotem Israel-Fishelson, and Peter Moon from the University of Maryland introduced API Can Code,…

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Join our free data science education workshop for teachers

Jan Ander — Mon, 09 Jun 2025 10:32:50 +0000

Are you a teacher who is interested in data science education for key stage 5 (age 16 to 18)? Then we invite you to join our free, in-person workshop exploring the topic, taking place in Cambridge, UK on 10 July 2025. You will be among the very first educators to see some of our first…

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Streamlining RiskOps with the SOP agent framework

Grab Tech — Thu, 08 May 2025 00:00:10 +0000

Introduction In the blog our previous introduction to the SOP-driven LLM Agent Framework, we the potential of LLM agent framework to revolutionise business operations was discussed. Now, we’re excited to explore a compelling use case: automating Accou...

Introducing the SOP-driven LLM agent frameworks

Grab Tech — Fri, 25 Apr 2025 00:00:10 +0000

Introduction We’re excited to introduce an innovative Large Language Model (LLM) agent framework that reimagines how enterprises can harness the power of AI to streamline operations and boost productivity. At its core, this framework leverages Standar...

Grab AI Gateway: Connecting Grabbers to Multiple GenAI Providers

Grab Tech — Mon, 17 Feb 2025 00:00:10 +0000

The transformative world of Generative AI (GenAI), which refers to artificial intelligence systems capable of creating new content such as text, images, or music that is similar to human-generated content, has become integral to innovation, powering th...

Teaching about AI in K–12 education: Thoughts from the USA

Katharine Childs — Thu, 13 Feb 2025 11:55:09 +0000

As artificial intelligence continues to shape our world, understanding how to teach about AI has never been more important. Our new research seminar series brings together educators and researchers to explore approaches to AI and data science education. In the first seminar, we welcomed Shuchi Grover, Director of AI and Education Research at Looking Glass…

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How can we teach students about AI and data science? Join our 2025 seminar series to learn more about the topic

Jane Waite — Thu, 12 Dec 2024 09:54:06 +0000

AI, machine learning (ML), and data science infuse our daily lives, from the recommendation functionality on music apps to technologies that influence our healthcare, transport, education, defence, and more. What jobs will be affected by AL, ML, and data science remains to be seen, but it is increasingly clear that students will need to learn…

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How we seamlessly migrated high volume real-time streaming traffic from one service to another with zero data loss and duplication

Grab Tech — Thu, 05 Dec 2024 00:00:10 +0000

At Grab, we continuously enhance our systems to improve scalability, reliability and cost-efficiency. Recently, we undertook a project to split the read and write functionalities of one of our backend services into separate services. This was motivated...

Supercharging LLM Application Development with LLM-Kit

Grab Tech — Fri, 29 Nov 2024 00:00:10 +0000

Introduction At Grab, we are committed to leveraging the power of technology to deliver the best services to our users and partners. As part of this commitment, we have developed the LLM-Kit, a comprehensive framework designed to supercharge the setup...

Metasense V2: Enhancing, improving and productionisation of LLM powered data governance

Grab Tech — Thu, 14 Nov 2024 00:00:10 +0000

Introduction In the initial article, LLM Powered Data Classification, we addressed how we integrated Large Language Models (LLM) to automate governance-related metadata generation. The LLM integration enabled us to resolve challenges in Gemini, such a...

LLM-assisted vector similarity search

Grab Tech — Wed, 23 Oct 2024 00:00:10 +0000

Introduction As the complexity of data retrieval requirements continue to grow, traditional search methods often struggle to provide relevant and accurate results, especially for nuanced or conceptual queries. Vector similarity search has emerged as a...

Leveraging RAG-powered LLMs for Analytical Tasks

Grab Tech — Wed, 09 Oct 2024 00:00:10 +0000

Introduction Retrieval-Augmented Generation (RAG) is a powerful process that is designed to integrate direct function calling to answer queries more efficiently by retrieving relevant information from a broad database. In the rapidly evolving business...

Evolution of Catwalk: Model serving platform at Grab

Grab Tech — Tue, 01 Oct 2024 00:00:50 +0000

Introduction As Southeast Asia’s leading super app, Grab serves millions of users across multiple countries every day. Our services range from ride-hailing and food delivery to digital payments and much more. The backbone of our operations? Machine Le...

Improve Your Next Experiment by Learning Better Proxy Metrics From Past Experiments

Netflix Technology Blog — Mon, 26 Aug 2024 15:46:24 +0000

By Aurélien Bibaut, Winston Chou, Simon Ejdemyr, and Nathan KallusWe are excited to share our work on how to learn good proxy metrics from historical experiments at KDD 2024. This work addresses a fundamental question for technology companies and acade...

A Recap of the Data Engineering Open Forum at Netflix

Netflix Technology Blog — Thu, 20 Jun 2024 15:01:27 +0000

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024The Data Engineering Open Forum at Netflix on April 18th, 2024.At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role...

Round 2: A Survey of Causal Inference Applications at Netflix

Netflix Technology Blog — Thu, 06 Jun 2024 20:10:54 +0000

At Netflix, we want to ensure that every current and future member finds content that thrills them today and excites them to come back for more. Causal inference is an essential part of the value that Data Science and Engineering adds towards this miss...