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Scale AI

Scale AI is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Scale AI rather than just read about it. In short: Scale AI, Inc. is an American artificial intelligence infrastructure and software company based in San Francisco, California. Originally focused on data annotation, the company also offers RLHF services, large language model (LLM) evaluation, and enterprise software suites to build and deploy AI applications.

Key takeaways

  • Scale AI belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Scale AI to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Scale AI from memory before moving on to harder problems.

Reference excerpt

Scale AI, Inc. is an American artificial intelligence infrastructure and software company based in San Francisco, California. Originally focused on data annotation, the company also offers RLHF services, large language model (LLM) evaluation, and enterprise software suites to build and deploy AI applications. The company’s research arm, the Safety, Evaluation and Alignment Lab, focuses on evaluating and aligning LLMs. It also co-created the benchmark Humanity's Last Exam. Scale AI outsources data labeling through its subsidiaries, Remotasks, which focuses on computer vision and autonomous vehicles, and Outlier, which focuses on annotating data for LLMs. Scale AI operates an LLM Red Team that conducts human adversarial testing to identify vulnerabilities, biases, and safety risks in AI models. The team has worked with OpenAI, Google DeepMind and national AI Safety Institutes to evaluate systems against complex threats, including cybersecurity vulnerabilities, jailbreaks, and agentic AI behaviors. Scale AI's customers in the commercial sector have included Google, Microsoft, Meta, General Motors, OpenAI, and Time. The company also directly works with world governments, including the United States on military-related projects, and with Qatar to improve the efficiency of its social programs. In June 2025, Meta Platforms spent more than $14 billion to acquire a 49% non-voting stake in Scale AI. CEO Alexandr Wang left Scale AI to join Meta and was replaced by Jason Droege.

History

Early years (2016–2019) Scale was founded in 2016 by Alexandr Wang and Lucy Guo through Y Combinator. The pair had worked together at Quora. Initial investors of Scale included Dragoneer Investment Group, Tiger Global Management and Index Ventures. Guo was fired in 2018. In August 2019, after Peter Thiel’s Founders Fund made a $100 million investment in Scale, the company's valuation exceeded $1 billion, and it acquired unicorn status.

Growth (2019–2025) Scale contracted with the United States Department of Defense in 2020. In May 2021, Michael Kratsios, Chief Technology Officer of the United States under the Trump administration, joined as Scale AI's managing director and head of strategy. By July 2021, Scale had reached a valuation of $7 billion, after a financing led by Greenoaks, Dragoneer Investment Group and Tiger Global Management. There was an increased demand for data labelling from clients in different industries. In January 2022, Scale AI won a $250 million contract to give American federal agencies access to its suite of tools. In February 2022, Scale AI developed its Automated Damage Identification Service in response to the Russian invasion of Ukraine. Satellite imagery was analyzed to measure the damage to buildings, which were then geotagged and reported to humanitarian groups. In November 2022, Scale AI was recognized by Time on it’s Best Inventions of 2022 list. The company also opened an office in St. Louis in that same year. In January 2023, Scale laid off 20% of its workforce. In May 2023, Scale AI signed a deal with the US Army’s XVIII Airborne Corps, becoming the first AI company to deploy its LLM (known as Donovan) on a classified network. In August 2023, Scale AI became OpenAI’s "preferred partner" to fine-tune GPT-3.5. The company's services were used to create ChatGPT. In that same month, Scale AI’s evaluation platform was used at DEF CON, a hacking convention, at its first generative AI red team event, testing models provided by various companies. In December 2023, Scale AI was among a list of companies that contributed to Meta’s Purple Llama initiative, a security framework for the purpose of development of open generative AI models. In February 2024, Scale AI was selected by the Department of Defense to test and evaluate its LLMs for military purposes under a one-year contract. In March 2024, Scale reached a valuation of almost $13 billion after Accel led another round of funding. In May 2024, Scale raised an additional $1 billion with new investors including Amazon and Meta Platforms. Its valuation reached $14 billion. In August 2024, Scale signed an agreement with the US AI Safety Institute, to collaborate on research, testing, and evaluation of the company’s AI models. The US AI Safety Institute is controlled by the Department of Commerce’s National Institute of Standards and Technology. In December 2024, Scale was sued by a former employee, alleging that the company was committing wage theft and misclassifying workers. The following month, a second employee filed a similar suit. In January 2025, several contractors sued Scale alleging psychological harm from being exposed to disturbing content. In January 2025, it was reported in The Conversation that Scale AI and Meta had previously teamed up to create and sell Defense Llama, an LLM product with military-style defense purposes. The company also took out a full-page ad in The Washington Post, appealing to American President Donald Trump to "win the AI war". Later in the month, Scale AI and the Center for AI Safety partnered to release Humanity's Last Exam, a benchmark test for AI systems. The company has assisted in the development of the benchmarks EnigmaEval, MultiChallenge, and MASK. In February 2025, Scale AI agreed to a five-year partnership with the Qatari government to improve government services via AI-based tools and training, including predictive analytics, automation, and advanced data analytics. The deal was signed at the Web Qatar 2025 Summit by Mohammed bin Ali bin Mohammed Al Mannai, the Qatari Minister of Communications and Information Technology. Also in February, the company became a third-party evaluator of AI models for the U.S. AI Safety Institute. In March 2025, Scale AI reached a multimillion-dollar deal with the United States Department of Defense to develop the Thunderforge project, a "major step in U.S. military automation". The project aims to use AI to “plan and help execute movements of ships, planes, and other assets”, with the goal of speeding up military decisions in both peace and wartime. The contract was awarded to Scale AI and other companies (such as Anduril Industries and Microsoft) by the Defense Innovation Unit, and is intended to first be used with the USINDOPACOM and EUCOM. In April 2025, Scale AI released Scale Evaluation, a platform for testing LLMs against benchmarks to pinpoint weaknesses and flag where additional training data would improve the model.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Scale AI

Start with the simplest possible case. Write down what Scale AI claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Scale AI before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Scale AI ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Scale AI

In research
Scale AI appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Scale AI in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Scale AI is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2016 establishments in California, 2016 in San Francisco, American companies established in 2016, so understanding it makes those chapters shorter.
In everyday life
Look for Scale AI outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Scale AI in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Scale AI means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Scale AI out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Scale AI in simple terms?

Scale AI, Inc. is an American artificial intelligence infrastructure and software company based in San Francisco, California. Originally focused on data annotation, the company also offers RLHF services, large language model (LLM) evaluation, and enterprise software suites to build and deploy AI ap…

Why does Scale AI matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Scale AI?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Scale AI.

Tags

  • 2016 establishments in California
  • 2016 in San Francisco
  • American companies established in 2016
  • Artificial intelligence associations
  • Artificial intelligence industry in the United States
  • Companies based in San Francisco
  • Technology companies based in California
  • Y Combinator companies

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