Alexander Wang, at age 27, has become one of the world’s youngest billionaires. He succeeded in doing so by having more than 100,000 employees on contracts who help him power the modern AI. His startup named Scale AI has hired workers from all over the world and these workers wrote and summarized texts as well as label images for AI to better understand human patterns. This is known as data labeling and the employees summarize news articles or write stories in Hindi to Mandarin.
This data labeling business has become so in demand by Gen AI companies that Scale AI’s revenue jumped to triple last year and now has a value of $14 billion. Wang says that his company’s importance is all due to the computing chip they are using which is developed by Nvidia. Scale AI’s office is located in San Francisco and the company hires individuals through advertising on LinkedIn and Reddit. The work is remote and most of the workers do not know that they are working for Scale AI in their initial days. The employees do their tasks on two websites known as Outlier and Remotasks on which no affiliation with Scale AI is mentioned. Projects are also given code names so the employees do not know what clients they are working for.
Many remote employees get frustrated with their jobs and quit. Sometimes they get delayed payments or hourly wages as low as $8. Some also do not produce quality content and some cheat to increase their productivity. Wang also doesn't like the way his company is working right now. He calls this work mundane and boring and has said that his company is trying to develop new software and AI products.
Scale AI has also worked for Meta and has given the company code word “Flamingo”. Last year, Meta had asked the company to create 27,000 questions and answers so they can train their AI models. When Meta received the data, it turned out that contractors had used ChatGPT to write all the responses. Upon contact with the company, Wang tried to save the project and asked its employees to rewrite everything and send it to Meta. Wang also discovered that many of the badly written data had come from Kenyans so Wang restricted all their projects to the USA and English speaking countries. But it wasn't very useful because many USA accounts were being sold to people from other countries on Facebook and WhatsApp.
Alexander Wang grew up in New Mexico and has Chinese immigrant scientist parents. He started to think of a new business start up as soon as he got in the ninth grade. In 2015, he went to MIT and chose five graduate computer science courses but he soon dropped out. He soon accepted a job offered by Eric Wu, CEO of Opendoor. Soon after, he enrolled in an AI training program by Sam Altman, now CEO of OpenAI. After a while, he started his own startup known as Scale AI.
Since Scale AI also labeled images, many car companies needed an AI company who could help them with labeling images for their car’s automated systems. They turned to Scale AI. Soon, Scale AI signed up Cruise and Tesla. Scale AI then chooses the contractors and gives them projects. The hiring process at Scale AI is simple. You get hired by applying for the job advertised by the company. The worker is then given written assignments that the model can use to learn how humans think. The writing samples are then given to clients so they can train their AI models. The worker is soon paid for his work.
Image: alexanddeer/Insta
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This data labeling business has become so in demand by Gen AI companies that Scale AI’s revenue jumped to triple last year and now has a value of $14 billion. Wang says that his company’s importance is all due to the computing chip they are using which is developed by Nvidia. Scale AI’s office is located in San Francisco and the company hires individuals through advertising on LinkedIn and Reddit. The work is remote and most of the workers do not know that they are working for Scale AI in their initial days. The employees do their tasks on two websites known as Outlier and Remotasks on which no affiliation with Scale AI is mentioned. Projects are also given code names so the employees do not know what clients they are working for.
Many remote employees get frustrated with their jobs and quit. Sometimes they get delayed payments or hourly wages as low as $8. Some also do not produce quality content and some cheat to increase their productivity. Wang also doesn't like the way his company is working right now. He calls this work mundane and boring and has said that his company is trying to develop new software and AI products.
Scale AI has also worked for Meta and has given the company code word “Flamingo”. Last year, Meta had asked the company to create 27,000 questions and answers so they can train their AI models. When Meta received the data, it turned out that contractors had used ChatGPT to write all the responses. Upon contact with the company, Wang tried to save the project and asked its employees to rewrite everything and send it to Meta. Wang also discovered that many of the badly written data had come from Kenyans so Wang restricted all their projects to the USA and English speaking countries. But it wasn't very useful because many USA accounts were being sold to people from other countries on Facebook and WhatsApp.
Alexander Wang grew up in New Mexico and has Chinese immigrant scientist parents. He started to think of a new business start up as soon as he got in the ninth grade. In 2015, he went to MIT and chose five graduate computer science courses but he soon dropped out. He soon accepted a job offered by Eric Wu, CEO of Opendoor. Soon after, he enrolled in an AI training program by Sam Altman, now CEO of OpenAI. After a while, he started his own startup known as Scale AI.
Since Scale AI also labeled images, many car companies needed an AI company who could help them with labeling images for their car’s automated systems. They turned to Scale AI. Soon, Scale AI signed up Cruise and Tesla. Scale AI then chooses the contractors and gives them projects. The hiring process at Scale AI is simple. You get hired by applying for the job advertised by the company. The worker is then given written assignments that the model can use to learn how humans think. The writing samples are then given to clients so they can train their AI models. The worker is soon paid for his work.
Read next: New Survey Shows What Companies Think of AI Adoption and the Challenges They Are Facing
