MosaicML StreamingDataset: Fast, Accurate Streaming of Training Data from Cloud Storage
Loading your training data becomes an escalating challenge as datasets grow bigger in size and the number of nodes scales. We built StreamingDataset...
Databricks Expands Brickbuilder Solutions for Migrations in EMEA
Today, we're excited to announce that Databricks has expanded Brickbuilder Solutions by collaborating with key partners in Europe, the Middle East, and Africa...
Getting started with NLP using Hugging Face transformers pipelines
Advances in Natural Language Processing (NLP) have unlocked unprecedented opportunities for businesses to get value out of their text data. Natural Language Processing...
Announcing Multi-Cloud support for Security Analysis Tool (SAT)
Last November, we announced the availability of the Security Analysis Tool (SAT) for AWS on our blog . Today we are excited to...
Blazingly Fast LLM Evaluation for In-Context Learning
With MosaicML you can now evaluate LLMs on in-context learning tasks (LAMBADA, HellaSwag, PIQA, and more) hundreds of times faster than other evaluation...
Creating Health Plan Price Transparency in Coverage With the Lakehouse
Check out our Price Transparency Solution Accelerator for more details, and to download the notebooks. Don't miss our Price Transparency On-Demand Webinar and...
Five Challenges CIOs Need to Overcome in the New Year
As IT leaders kick off the new year during one of the most tumultuous times in recent history, CIOs are being forced to...
Design Patterns for Batch Processing in Financial Services
Introduction Financial services institutions (FSIs) around the world are facing unprecedented challenges ranging from market volatility and political uncertainty to changing legislation and...
Using Abandoned Cropland for Carbon Sequestration: a Data-driven Approach
This is a collaborative post from Databricks and MIT. We thank Cesar Terrer, Assistant Professor at MIT, Civil and Environmental Engineering Department (CEE)...
Announcing Support for Enhanced Fan-Out for Kinesis on Databricks
Historically, conventional wisdom held that stream processing is the domain of strictly low latency, operational use cases like sub-second inventory updates on an...