Scale AI provides an end-to-end solution to manage the entire ML lifecycle, focusing on improving AI applications through better data.

Anna Matalon

Alexandr Wang

Sagi Reichberg

Leonardo Martinez

Gabrielle Gutierrez

Scale AI

DeepNatural provides advanced solutions for constructing high-quality language data and deploying no-code applications powered by fine-tuned and quantized large language models (LLMs). Self-described.

DeepNatural

Exa connects AI to the world's knowledge, enabling it to return accurate and up-to-date information through advanced search capabilities.

Inner Eye provides solutions that fuse human intelligence with artificial intelligence to optimize decision making.

Amir Geva

Leon Deouell

Inner Eye

At Scale, our mission is to accelerate the development of AI applications. We believe that to make the best models, you need the best data. 

The Scale Generative AI Platform leverages your enterprise data to customize powerful base generative models to safely unlock the value of AI. The Scale Data Engine consists of all the tools and features you need to collect, curate and annotate high-quality data, in addition to robust tools to evaluate and optimize your models. Scale powers the most advanced LLMs and generative models in the world through world-class RLHF, data generation, model evaluation, safety, and alignment.

Scale is trusted by leading technology companies like Microsoft and Meta, enterprises like Fox and Accenture, Generative AI companies like Open AI and Cohere, U.S. Government Agencies like the U.S. Army and the U.S. Airforce, and Startups like Brex and OpenSea. 

AIspace Ventures

Tiger Global Management

Greenoaks

Human Capital

Index Ventures

Coatue

Wellington Management

Y Combinator

Dragoneer Investment Group

Durable Capital Partners

Founders Fund

Our latest research has been featured by TIME. Our team developed a novel and state of the art unlearning method: 'CUT' - which removes hazardous model capabilities while retaining general capabilities. This is groundbreaking research, and shows that we can effectively remove knowledge from a model, with limited consequences. The method can aid in preventing 'jailbreaks', which has plagued the field. 

You can read our blogpost on the paper here: https://lnkd.in/g2aqNmK7

And you can read the article here: https://lnkd.in/gUGwEwEy

Many thanks to our co-authors and partners such as Scale AI

“‘Our hope is this becomes adopted as one of the primary benchmarks that all open source developers benchmark their models against,’ [Scale CEO Alexandr Wang] says. ‘Which will give a good framework to minimize safety issues.’”

Will Henshall from TIME covered the development and impact of the WMDP benchmark released by Scale’s Safety and Evaluation Lab (SEAL) and the Center for AI Safety (CAIS) today, including:

⏩ How the benchmark was designed

⏩ The novel unlearning technique pioneered by the team, which removes hazardous material from LLMs without degrading performance

⏩ Why it’s important that this benchmark and unlearning technique become standard practice to minimize LLM safety risks

Read the full article here: https://lnkd.in/gUGwEwEy 

📣 Today we are announcing the release of the WMDP LLM benchmark, designed by Scale’s Safety, Evaluations, and Analysis Lab (SEAL) in partnership with the Center for AI Safety (CAIS).

WMDP covers knowledge across biosecurity, chemical security, and cybersecurity. It serves as an open source proxy measurement for hazardous knowledge contained by LLMs within these domains.

The benchmark is an open source collection of 4K+ multiple-choice questions written by subject matter experts.

Our goal is to help researchers and model builders mitigate these risks and reduce the potential for malicious use of LLMs.

Learn more about WMDP here: https://lnkd.in/g6ybF8Gw

Read the paper here: https://lnkd.in/gEK7Q7PE

Scale GenAI Platform is now available on the Microsoft Azure Marketplace! Accelerate Generative AI across your enterprise with Scale GP. 💪

With Scale GP on Azure, enterprises can make more cost-effective investments and more easily build, test, and deploy customized Generative AI applications. Azure customers can purchase Scale GP through the Azure Marketplace, leveraging their existing Microsoft Azure Consumption Commitment (MACC).

“With this next generation of AI, we have an extraordinary opportunity to help organizations build customized Generative AI applications to transform every part of their business. Our integration with Scale AI will help Microsoft Azure customers unlock a new wave of AI-powered innovation.” - Zia Mansoor, Corporate Vice President, Data and AI, Microsoft.

👉 To learn more about Scale GP, visit scale.com/genai-platform or visit the Azure Marketplace: https://lnkd.in/gN4KM8ax

Metric
Company Name	Scale AI	DeepNatural	Exa	Inner Eye
Symbol
MSH ID	COM:SCALE	AI:DEEPNATURAL	AI:EXA	AI:INNEREYE
Market	PRIVATE	PRIVATE	PRIVATE	PRIVATE
Sector	Technology	Technology	Technology	Technology
Industry	Artificial Intelligence (AI) and Machine Learning (ML)	Artificial Intelligence	Software & IT Services	Artificial Intelligence
Country	US	US	US	US
Stage	Series F	Seed
Employee Count	2.58K			21
Website	scale.com	deepnatural.ai	exa.ai	innereye.ai
LinkedIn	scaleai	deepnatural
Founders

Metric
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Enterprise Value
Monthly Web Traffic	395.38K	4.85K	84
Web Traffic Growth	0.11	-0.30	-0.76
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Raised Capital	1B	438.81K

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COM:SCALE

Scale AI

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