ScaleAI, which provides data labeling services to companies that want to train machine learning models, has raised a $1 billion Series F round from big-name institutional and corporate investors, including Amazon and Meta.
Fundraising is a mix of primary and secondary funding, and is the latest in a major investment in AI. Amazon recently closed a $4 billion investment in OpenAI rival Anthropic, and the likes of Mistral AI and Perplexity are also in the process of raising more billion-dollar rounds at higher valuations.
Prior to this round, Scale AI had raised about $600 million in its eight-year history, including a $325 million Series E in 2021 that valued it at about $7 billion — double the value of its Series D in 2020. Is. Three years later, and despite headwinds that caused it to lay off 20% of its staff last year, Scale AI is now valued at $13.8 billion — a sign of the times, as investors head into the AI gold rush. Struggling for
The Series F was led by Accel, which also led the company's Series A and participated in subsequent venture rounds.
In addition to Amazon and Meta, Scale AI has attracted a variety of new investors: the venture arms of Cisco, Intel, AMD and ServiceNow participated, as did DFJ Growth, WCM and investor Elad Gil. . Many of its existing investors also returned: Nvidia, Coatue, Y Combinator (YC), Index Ventures, Founders Fund, Tiger Global Management, Thrive Capital, Spark Capital, Greenoaks, Wellington Management, and former GitHub CEO, Nat Friedman. .
Banking on the growing importance of data
Data is the lifeblood of artificial intelligence, which is why companies specializing in data management and processing are doing well right now. Just last week, Wicca said it raised $140 million in a $1.6 billion post-money valuation to help companies build data pipelines for their AI applications.
Founded in 2016, Scale AI meshes machine learning with 'human-in-the-loop' supervision to manage and interpret large amounts of data to train AI systems in industries such as autonomous vehicles. It is necessary for
But most data is unstructured, and AI systems have a hard time using such data right off the bat. This requires labeling, which is a resource-intensive effort, especially with large data sets. Scale AI provides companies with data that has been properly interpreted and primed to train models. It also specializes in different industries with different needs — a self-driving car company will likely need labeled data from cameras and lidar, while natural language processing (NLP) use cases interpret interpreted text. will be needed.
The company's customers include Microsoft, Toyota, GM, Meta, the US Department of Defense and, until last August, ChatGPT maker OpenAI, which allows companies to fix their GPT-3.5 text-generating models. Tapping Scale AI for
Scale AI says it will use the new cash to “help accelerate the abundance of frontier data that will pave our way to artificial general intelligence.”
“Data abundance is not a default — it's a choice,” said Alexander Wang, CEO and founder of ScaleAI, in a press release. “This requires bringing together the best minds in engineering, operations, and AI. Our vision is one of data abundance, where we have the production means to continue scaling the frontier LLM that is many orders of magnitude we should not be limited to the data in reaching GPT-10.