Engineering at Meta

SEPTEMBER 7, 2023

Earlier this year, a small team of engineers at Meta started working on an idea for a new app. It would have all the features people expect from a text-based conversations app, but with one very key, distinctive goal – being an app that would allow people to share their content across multiple platforms. We wanted to build a decentralized (or federated) app that would enable people to post content that is viewable by anyone on other social apps, and vice versa.

Media 142

Media Engineering Coding Python 142

Snowflake

SEPTEMBER 7, 2023

Snowpark is the set of libraries and runtimes that enables data engineers, data scientists and developers to build data engineering pipelines, ML workflows, and data applications in Python, Java, and Scala. Functions or procedures written by users in these languages are executed inside of Snowpark’s secure sandbox environment , which runs on the warehouse.

Amazon Web Services 119

Amazon Web Services AWS Government Python 119

KDnuggets

SEPTEMBER 7, 2023

As LLMs continue to evolve, integrating multiple models or switching between them has become increasingly challenging. This article suggests a Microservice approach to separate model integration from business applications and simplify the process.

Building 100

Building Process 100

Engineering at Meta

SEPTEMBER 7, 2023

Meta presents Chakra execution traces , an open graph-based representation of AI/ML workload execution, laying the foundation for benchmarking and network performance optimization. Chakra execution traces represent key operations, such as compute, memory, and communication, data and control dependencies, timing, and resource constraints. In collaboration with MLCommons , we are seeking industry-wide adoption for benchmarking.

Metadata 101

Metadata Utilities Systems Designing 101

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

Data

databricks

SEPTEMBER 7, 2023

Check out our Solution Accelerator for RFM Segmentation for more details and to download the notebooks. For retail brands, effective customer engagement depends.

Retail 97

Retail 97

Confluent

SEPTEMBER 7, 2023

Kafka-on-Windows tutorials are everywhere, but most run Kafka directly on Windows.

Kafka 113

Kafka 113

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But in highly regulated industries where these technologies may be prohibited, the focus is less on off the shelf generative AI, and more on the relationship between their data and how AI can transform their business.

Insurance 78

Insurance Finance Portfolio Government 78

KDnuggets

SEPTEMBER 7, 2023

Learn the basic Python package visualization for your work.

Python 100

Python Data Science Data 100

Engineering at Meta

SEPTEMBER 7, 2023

We’re introducing Arcadia, Meta’s unified system that simulates the compute, memory, and network performance of AI training clusters. Extracting maximum performance from an AI cluster and increasing overall efficiency warrants a multi-input system that accounts for various hardware and software parameters across compute, storage, and network collectively.

Systems 101

Systems Architecture Utilities Designing 101

LinkedIn Engineering

SEPTEMBER 7, 2023

Espresso is the database that we designed to power our member profiles, feed, recommendations, and hundreds of other Linkedin applications that handle large amounts of data and need both high performance and reliability. As Espresso continued to expand in support of our 950M+ member base, the number of network connections that it needed began to drive scalability and resiliency challenges.

Bytes 88

Bytes Transportation Utilities Java 88

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Database

Snowflake

SEPTEMBER 7, 2023

Higher education institutions have a lot of plates to spin, and the University of Birmingham is no exception. Following a tough pandemic, the need to digitally transform had never been more pressing. The university needed to modernize its data capabilities to better serve staff, students and researchers—and it used the Snowflake Data Cloud to do it.

Education 89

Education Business Intelligence Professional Services Cloud 89

Precisely

SEPTEMBER 7, 2023

Advanced data analytics enable insurance carriers to evaluate risk at a far more granular level than ever before, but big data can only deliver real business value when carriers ensure data integrity. For P&C insurance, that starts with having accurate and precise information as to the location of an insured property. Data quality is critical, but data integrity goes much further than accuracy, completeness, and consistency.

Insurance 52

Insurance Data Integration Data Government 52