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Building end-to-end security for Messenger

Engineering at Meta

Our aim is to ensure that everyone’s personal messages on Messenger can only be accessed by the sender and the intended recipients, and that everyone can be sure the messages they receive are from an authentic sender. Third-party scrutiny E2EE implies confidentiality even if the provider wants to access the contents of a communication.

Building 144
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Building Trust in Public Sector AI Starts with Trusting Your Data

Cloudera

Launched in 2019, this strategy aims to position the US as a leader in AI research, development, and deployment. It focuses on five key pillars: investing in research and development; unleashing government AI resources; setting standards and policy; building the AI workforce; and advancing trust and security. million), among others.

Building 109
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Building Pinterest’s new wide column database using RocksDB

Pinterest Engineering

It is written in C++ and offers bindings for several programming languages, making it accessible for developers in different environments. In order to build a distributed and replicated service using RocksDB, we built a real time replicator library: Rocksplicator. RocksDB is a single node key value store.

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Going from Developer to CEO: Chronosphere

The Pragmatic Engineer

He’s solved interesting engineering challenges along the way, too – like building observability for Amazon’s EC2 offering, and being one of the first engineers on Uber’s observability platform. The focus seemed to shift to: invent something new → build a service for it → ship it.

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Is the “AI developer”a threat to jobs – or a marketing stunt?

The Pragmatic Engineer

Today, full subscribers got access to a comprehensive Senior-and-above tech compensation research. Devin has dominated tech news for the past few days, with major media outlets running sensational headlines, including the usually reserved Bloomberg’s, Gold-Medalist Coders Build an AI That Can Do Their Job for Them.

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Build AI-powered Recommendations with Confluent Cloud for Apache Flink® and Rockset

Rockset

Building a real-time, contextual and trustworthy knowledge base for AI applications revolves around RAG pipelines. What are the challenges building RAG pipelines? When you are building applications for consistent, real-time performance at scale you will want to use a streaming-first architecture.

Cloud 64
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Building A Community For Data Professionals at Data Council

Data Engineering Podcast

In order to stay current we need access to deeply technical presentations that aren’t burdened by extraneous marketing. What are some of the complexities or challenges in building one based on something as nebulous as data? In addition to your community building you are also an investor.

Building 100