Mosaic ML

Mosaic ML

Open-source platform for generative AI models

About Mosaic ML

Simplify's Rating
Why Mosaic ML is rated
B
Rated C on Competitive Edge
Rated A on Growth Potential
Rated B on Rating Differentiation

Industries

Data & Analytics

Cybersecurity

AI & Machine Learning

Company Size

51-200

Company Stage

Acquired

Total Funding

$1.4B

Headquarters

San Francisco, California

Founded

2021

Overview

Mosaic ML focuses on training and deploying generative AI models for businesses that need AI solutions for tasks like code generation and data analysis. Their platform allows clients to easily integrate Large Language Models (LLMs) into their applications, making the deployment of AI models quick and efficient. Unlike many competitors, Mosaic ML offers an open-source platform that is secure and cost-effective, promising up to 15 times cost savings while allowing clients to maintain full control of their data. The platform is designed to work seamlessly with existing data pipelines and is cloud-agnostic, providing flexibility for businesses. The goal of Mosaic ML is to help companies leverage AI technologies effectively while managing the complexities of model training and deployment.

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Simplify's Take

What believers are saying

  • Partnership with Oracle enhances scalability and efficiency of AI model training services.
  • MosaicML's MPT-7B-8K model showcases innovation in large language model development.
  • Acquisition by Databricks provides additional resources and market reach opportunities.

What critics are saying

  • Increased competition from open-source models like OLMo could challenge MosaicML's market position.
  • Potential AI bubble burst may reduce investment and interest in AI startups.
  • Dependency on major cloud providers like Oracle could affect cost structure and service delivery.

What makes Mosaic ML unique

  • MosaicML offers a user-friendly open-source platform for integrating large language models.
  • The platform promises up to 15x cost savings, enhancing its appeal to businesses.
  • MosaicML's cloud-agnostic design ensures seamless integration with existing data pipelines.

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Funding

Total Funding

$1364M

Above

Industry Average

Funded Over

2 Rounds

Acquisition funding comparison data is currently unavailable. We're working to provide this information soon!
Acquisition Funding Comparison
Coming Soon

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

3%

2 year growth

10%
Plants Need CO2
Mar 27th, 2025
The TAO of data: How Databricks is optimizing AI LLM fine-tuning without data labels

The Mosaic research team at Databricks developed the new TAO method.

Forbes
Feb 5th, 2024
How Olmo From Ai2 Redefines Llm Innovation

OLMo LLM AI2The Allen Institute for AI created the Open Language Model, or OLMo, which is an open-source large language model with the aim of advancing the science of language models through open research. It marks a major milestone in the evolution of large language models.Unlike current open large language models like Llama and Mistral, which might limit access to their training data, architectures, or evaluation methodologies, OLMo stands out by providing full access to its pre-training data, training code, model weights, and evaluation suite. This openness is aimed at empowering academics and researchers to collectively study and advance the field of language modeling.OLMo represents a collaborative effort to advance the science of language models. The developers behind the LLM have a mission to empower academics and researchers by providing access to training code, models, and evaluation code necessary for open research.OLMo's architecture is built on AI2’s Dolma dataset, which features a three trillion-token open corpus. It includes full model weights for four model variants at the 7B scale, each trained to at least 2T tokens. OLMo's innovative aspects include its training approaches, size, and the diversity of data it was trained on

Analytics India Magazine
Jan 2nd, 2024
MosaicML Announces Beyond Chinchilla-Optimal for LLM Scaling Laws in Inference

MosaicML has unveiled its latest research, titled "Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws."

LangLabs
Nov 6th, 2023
Exciting Updates from the AI Industry: British Startups, Accessible AI, and Cutting-Edge Innovations

Weights & Biases has partnered with @MosaicML to provide a FREE course covering LLM Evaluation, Dataset Curation, Distributed Training, and Practical Tips from industry experts.

Blocks and Files
Oct 25th, 2023
Storage news ticker - October 25

Arcion's software will be integrated into MosaicML's GenAI software.

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