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US Foods Builds Digital-First Ecommerce Platform with Data Streaming

Confluent

Learn how US Foods built a digital-first ecommerce platform—using data streaming to future-proof its infrastructure and implement data mesh principles.

Food 69
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Creating an IoT-Based, Data-Driven Food Value Chain with Confluent Cloud

Confluent

You have food processors. Worldwide food processing machinery manufacturer BAADER sees all these necessary handoffs as opportunities to make the food value chain more efficient. We have all the tools we need to collect, process and distribute high-value events to create a true event-driven food value chain.

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Snowflake Startup Challenge 2024: Announcing the 10 Semi-Finalists

Snowflake

In 2020, Snowflake announced a new global competition to recognize the work of early-stage startups building their apps — and their businesses — on Snowflake, offering up to $250,000 in investment as the top prize. This year’s entries presented an impressively diverse set of use cases. SignalFlare.ai

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Building Your Data Product Machine: Less Tech, More Strategy

The Modern Data Company

With this in mind, let’s explore how to demystify the process of building your data-driven strategy, making it accessible and actionable. Design and Build Plan : Planning the production line with an eye for both current needs and future adaptability reflects the strategic approach needed for data architecture and processes.

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Building a Media Understanding Platform for ML Innovations

Netflix Tech

We build creator tooling to enable these colleagues to focus their time and energy on creativity. For instance, let’s say that an editor has found a visually stunning shot of a plate of food from Chef’s Table , and she’s interested in finding similar shots across the entire show. Thus, we didn’t build all the modules completely.

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Container Runtime: GPU Training & Inference with Snowflake Notebooks

Snowflake

Build cost-effective, scalable and flexible ML models in Snowflake Many enterprises are already using Container Runtime to cost-effectively build advanced ML use cases with the easy access to GPUs. CHG builds and productionizes its end-to-end ML models in Snowflake ML. With over $5.5 See this quickstart to learn more.

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Lifecycle of a Successful ML Product: Reducing Dasher Wait Times

DoorDash Engineering

Building an ML-powered delivery platform like DoorDash is a complex undertaking. Once we identify an opportunity, we usually start small by testing the ML hypothesis using a heuristic before deciding to invest into building out the ML models. If the initial heuristic works, we build out and replace the heuristic with the ML models.

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