Messages
9/15/2022
12 : 4
🗜🗜Edge#226: DeepSpeed Compression, a new library for extreme compression of deep learning models
It combines compression and system optimization techniques for building smaller and more efficient deep learning architectures
9/15/2022
0 : 54
🎙Or Itzary/Superwise About Model Observability and Streamlining Large ML Projects
Getting to know the experience gained by researchers, engineers, and entrepreneurs doing real ML work is an excellent source of insight and inspiration. Share this interview if you like it. No
9/13/2022
11 : 14
😶🌫️ Edge#225: Understanding Latent Diffusion Models
In this issue: we explain latent diffusion models; we discuss the original latent diffusion paper; we explore Hugging Face Diffusers, a library for state-of-the-art diffusion models. Enjoy the learning
9/11/2022
11 : 14
↕️↔️TensorFlow 2.10 is Here
Weekly news digest curated by the industry insiders
9/9/2022
11 : 34
📌 Event: Learn strategies to scale your ML models using Kubernetes - SEP 14
Running distributed workloads is key to the future of AI. As models become more complex and advanced, distributed workloads will be the only way forward. Get ahead of the curve, and learn practical
9/8/2022
12 : 14
🤘Edge#224: AlexaTM 20B is Amazon’s New Language Super Model Also Capable of Few-Shot Learning
The model is the largest seq2seq architecture capable of few-shot-learning
9/7/2022
11 : 54
🗺 ❓What is the current ML value chain landscape? Help us shape it!
Today we have a very special project for you –>
9/6/2022
11 : 14
🍵☕️ Edge#223: Different Types of Diffusion
+OpenAI's GLIDE; +the Hugging Face text-to-image catalog
9/4/2022
11 : 14
🤖➕👨💻Human-AI Collaborative Writing
Weekly news digest curated by the industry insiders
9/2/2022
12 : 4
📝 Guest post: How to Write Better Annotation Guidelines for Human Labelers: 4 Top Tips*
In this guest post, Superb AI discusses the importance of manual annotation or the direct involvement of human labelers and shares 4 great tips on how to write better annotation guidelines for human
9/1/2022
12 : 4
📺 Edge#222: Inside Axion, The Feature Store Architecture Powering ML Pipelines at Netflix
The feature store is a key component of Netflix's ML Platform
8/31/2022
11 : 54
🎙Fabio Buso about How Hopsworks Feature Store Became Fully Serverless
Getting to know the experience gained by researchers, engineers, and entrepreneurs doing real ML work is an excellent source of insight and inspiration. Share this interview if you like it. No
8/30/2022
11 : 24
🧪🧪 Edge#221: What are Diffusion Models
+ Google's Imagen; +MindsEye
8/28/2022
11 : 14
🤖➕🙎🏽AGI and Human Alignment
Weekly news digest curated by the industry insiders
8/26/2022
11 : 54
📌 Event: Data Validation for Enterprise ML using Great Expectations and Hopsworks Feature Store/ Aug 31
Defining expectation suites and reusing existing ones Have you ever worked really hard on training an awesome model just to have everything break in production because of a change in ETL logic in a
8/25/2022
12 : 14
🐙 Edge#220: Dive into Meta AI’s Make-A-Scene, which pushes the boundaries of AI art synthesis
The new model uses text-to-image and image-to-image generation to produce astonishing artistic outputs.
8/24/2022
12 : 4
📝 Guest post: Your Fitbit for data and model health*
In this article, our partner WhyLabs describes the importance of monitoring data health and how they are helping organizations track vitals along ML and data pipelines to proactively detect data
8/23/2022
11 : 34
📄➡️🖼 Edge#219: A New Series About Text-to-Image Models
In this issue: we start the new series about text-to-image models; we discuss CLIP, a neural network that can learn image representations while being trained using natural language datasets; we explore
8/22/2022
3 : 9
🍱 The Text-to-Image Synthesis Revolution
Weekly news digest curated by the industry insiders
8/19/2022
11 : 24
📝 Guest post: "ML Data": The past, present and future*
In this article, co-founder and CTO of Galileo Atindriyo Sanyal gives a fascinating overview of 'ML data intelligence' evolution and shares a few insights on why the organizations that obsess