Thu.Feb 13, 2025

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10 Lessons from 10 Years of Innovation and Engineering at Picnic

Picnic Engineering

A decade ago, Picnic set out to reinvent grocery shopping with a tech-first, customer-centric approach. What began as a bold experiment quickly grew into a high-scale operation, powered by continuous innovation and a willingness to challenge conventions. Along the way, weve learned invaluable lessons about scaling technology, fostering culture, and driving innovation.

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Looking back at our Bug Bounty program in 2024

Engineering at Meta

In 2024, our bug bounty program awarded more than $2.3 million in bounties, bringing our total bounties since the creation of our program in 2011 to over $20 million. As part of our defense-in-depth strategy , we continued to collaborate with the security research community in the areas of GenAI, AR/VR, ads tools, and more. We also celebrated the security research done by our bug bounty community as part of our annual bug bounty summit and many other industry events.

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Snowflake’s Fully Managed Service: Beyond Serverless

Snowflake

As analytics steps into the era of enterprise AI, customers requirements for a robust platform that is easy to use, connected and trusted for their current and future data needs remain unchanged. "Serverless computing" has enabled customers to use cloud capabilities without provisioning, deploying and managing either hardware or software resources.

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Introducing SAP Databricks

databricks

Today we are announcing a deep partnership with SAP which we think can be game changing for our industry. In short, it is.

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A Guide to Debugging Apache Airflow® DAGs

In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

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What is Few-Shot Learning? Unlocking Insights with Limited Data

Edureka

Few-shot learning (FSL) is changing data science by allowing models to make correct predictions using very little labeled data. Unlike traditional guided learning, which needs a lot of data, Few-Shot Learning (FSL) is about learning from just a few examples. This makes FSL perfect for situations where data is limited or difficult to get. In this blog, we’ll explore Few-shot learning, its main ideas, and how it differs from traditional learning methods.

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How to Scale Sklearn with Dask

KDnuggets

Here's how Dask applies the building blocks of sklearn to bring ML modeling workflows to the next level of scalability via high-performance parallel computing

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Bridging the Gap: Democratizing AI for All

KDnuggets

Lets explore how democratizing AI can level the playing field and create opportunities for all, no matter the background or resources.

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Using Apache Flink® for Model Inference: A Guide for Real-Time AI Applications

Confluent

How Flink enables developers to connect real-time data to external models through remote inference, enabling seamless coordination between data processing and AI/ML workflows.

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Snowflakeのフルマネージドサービスは単なるサーバーレスではない

Snowflake

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Know Before You Go: Gartner Data & Analytics Summit 2025 in London

Monte Carlo

The Gartner Data & Analytics Summit 2025 in London is approaching quickly! Gartner gathers industry leaders, data and AI practitioners, and technology enthusiasts alike to discuss strategies, solutions, use cases, and more. The Monte Carlo team will be attending, so be sure to look for us there! Stay tuned for more info to come. If youll be attending as well, its always a best practice to get ahead of the game and plan your experience to get the most out of the conference.

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

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Snowflake、ケープタウンでの展開をまもなく開始

Snowflake

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How Real-Time Data Streaming with GenAI Accelerates Singapore’s Smart Nation Vision

Confluent

Using data streaming and GenAI to enhance citizen servicesConfluent helps Singapores public and private sectors modernize through IMDAs Tech Acceleration Lab.

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Tied the Knot: Mapping the Married

ArcGIS

Valentines Day is often seen as a celebration of couples and with Esri Demographics we can map where potential celebrants of this holiday live.

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New Snowflake Deployment: Cape Town Coming Soon

Snowflake

Snowflake is excited to announce a brand-new chapter in its AI Data Cloud infrastructure story in Africa by committing to support AWS in Cape Town by July 2025. Supporting customers compliance with regional data residency The Global Innovation Index ranks South Africa number one in innovation in Africa, with South Africa hosting the continents leading financial hub and a growing technology hub.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.