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Robust & Responsible AI Newsletter - Issue #3

Every quarter we send out a roundup of the hottest MLOps and Data-Centric AI news including industry highlights, what’s brewing at WhyLabs, and more.

ISSUE: September 2022

🕚  TL;DR

Trying to keep up with MLOps, but only have 10 minutes? Here is your shortlist:

Read: Monitoring data the simple way. WhyLabs’ new monitoring system makes alerts more helpful and manageable so users can focus on improving their models instead of worrying about them in production.

Run: The wait is over! After spending years iterating on different architectures and features, BentoML has officially released v1.0.0, calling it the standard model serving architecture of the future!

Attend: Data-Centric AI Summit. Want to learn how to put data-centric AI into practice in the real world? Register for Bernease Herman’s talk on adapting experimental data-centric AI principles for production ML systems at this event brought to you by AIIA and the Data-Centric AI Community!

💡 Open Source Spotlight

There's a lot going on in the world of open source tooling! Here is what's new:

Finding new homes. After developing one of the world’s most popular open-source annotation tools, learn why Intel is moving CVAT development under the OpenCV umbrella. Also, PyTorch, one of the primary platforms for AI research, announced its move to the Linux Foundation!

Who doesn’t enjoy a unified interface? released UnionML for seamless creation of web-native machine learning applications. Learn more about the new unified interface for ML and data tools!

Let your imagination run wild! Craiyon (formerly Dalle-E mini), is a free, open-source AI that produces amazing images from text inputs. Read about Craiyon’s AI model or try it for yourself - but watch out, it’s addictive!

Craiyon Generated Image

📚 What MLOps experts are reading

Keeping up with the latest on MLOps can be a full-time job. Here are the highlights:

Navigating the AI/Infrastructure tool maze. The first annual AI Infrastructure Ecosystem report is out, providing a comprehensive and clear overview of the entire AI/ML infrastructure landscape.

What’s trending in data, code, and infrastructure? This free AWS white paper examines the evolution of MLOps through the lens of three of the industry's prominent venture capital investors and leading startups in the space.

A lively debate on the merits of platform architectures. Stitchfix shares their initial design considerations for the platform they built, presents the API data scientists use to interact with it, and details its capabilities.

☕️ What’s brewing at WhyLabs

At WhyLabs, we are focused on making AI observability as easy and intuitive as your coffee machine. Here are our latest releases:

The end of ad-hoc monitoring. A Fortune 500 fintech company is leveraging WhyLabs to avoid millions of dollars of lost revenue by monitoring their 380 models in production. Read the case study!

Images can be tricky. We break down how to monitor image data, the types of problems that slow down the adoption of computer vision systems, and a solution for these challenges in our blog.

whylogs Apache Airflow provider. To help you make the most of whylogs within your existing Airflow pipelines, we created the whylogs Airflow provider to make your workflow more responsible, scalable, and efficient. Learn more in our blog!

🎟️ Robust & Responsible AI, at an event near you

If you're looking for high quality events, we've got you covered. As a perk, you will always have a friend, because somebody from WhyLabs is either speaking or attending!

Intro to Observability Workshop | Sept 21 | Virtual

Get your hands dirty with AI observability. Sage Elliott is hosting a hands-on workshop on how to use validation and monitoring techniques to implement your own AI observability solution from start to finish. And you’ll receive a certificate for completing the workshop!

ODSC West | Nov 1 - 3 | San Francisco, CA

The largest applied data science conference. Register now to get 40% off your ticket and message us on Slack to connect while you’re there!

AWS re:Invent | Nov 28 - Dec 2  | Las Vegas, NV

The most transformative event in tech. Register today to attend the learning conference hosted by AWS and connect with the WhyLabs team on Slack if you’ll be there!

NeurIPS | Nov 28 - Dec 3 | New Orleans, LA

One of the most prestigious and competitive international conferences in ML and computational neuroscience. Join the WhyLabs team in NOLA to meet with researchers in ML, neuroscience, statistics, optimization, computer vision, natural language processing, and more!

Join the Community

Join the Robust & Responsible AI (Rsqrd) Community on Slack to connect with other practitioners, share ideas, and learn about exciting new techniques. Attend the community live chats or check out YouTube to see all the recordings.

If you want to help support whylogs, the open-source standard for data logging, check out our GitHub and give us a star.

📬  Subscribe to the Robust & Responsible AI newsletter to get the latest Data-Centric AI and MLOps news delivered quarterly to your inbox!

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Model Monitoring for Financial Fraud Classification

Model monitoring is helping the financial services industry avoid huge losses caused by performance degradation in their fraud transaction models.

Data and ML Monitoring is Easier with whylogs v1.1

The release of whylogs v1.1 brings many features to the whylogs data logging API, making it even easier to monitor your data and ML models!

Data Quality Monitoring in Apache Airflow with whylogs

To make the most of whylogs within your existing Apache Airflow pipelines, we’ve created the whylogs Airflow provider. Using an example, we’ll show how you can use whylogs and Airflow to make your workflow more responsible, scalable, and efficient.

Data Logging with whylogs: Profiling for Efficiency and Speed

Rather than sampling data, whylogs captures snapshots of the data making it fast and efficient for data logging, even if your datasets scale to larger sizes.

Data Quality Monitoring for Kafka, Beyond Schema Validation

Data quality mapped to a schema registry or data type validation is a good start, but there are a few things most data application owners don’t think about. We explore error scenarios beyond schema validation and how to mitigate them.

Data + Model Monitoring with WhyLabs: simple, customizable, actionable

The new monitoring system maximizes the helpfulness of alerts and minimizes alert fatigue, so users can focus on improving their models instead of worrying about them in production...

A Solution for Monitoring Image Data

A breakdown of how to monitor unstructured data such as images, the types of problems that threaten computer vision systems, and a solution for these challenges.

How to Validate Data Quality for ML Monitoring

Data quality is one of the most important considerations for machine learning applications—and it's one of the most frequently overlooked. We explore why it’s an essential step in the MLOps process and how to check your data quality with whylogs.

Small Changes for Big SQLite Performance Increases

A behind-the-scenes look at how the WhyLabs engineering team improved SQLite performance to make monitoring data and machine learning models faster and easier for whylogs users.
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