Scale AI | LinkedIn (original) (raw)
Software Development
San Francisco, California 185,323 followers
The Data Engine that powers the most advanced AI models.
About us
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.
Industry
Software Development
Company size
501-1,000 employees
Headquarters
San Francisco, California
Type
Privately Held
Founded
2016
Specialties
Computer Vision, Data Annotation, Sensor Fusion, Machine Learning, Autonomous Driving, APIs, Ground Truth Data, Training Data, Deep Learning, Robotics, Drones, NLP, and Document Processing
Locations
Employees at Scale AI
Updates
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185,323 followers
6mo Edited
Today, we’re announcing Scale has closed 1Boffinancingata1B of financing at a 1Boffinancingata13.8B valuation, led by existing investor Accel. For 8 years, Scale has been the leading AI data foundry helping fuel the most exciting advancements in AI, including autonomous vehicles, defense applications, and generative AI. With today’s funding, we’re moving into the next phase of our journey: accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI). “Our vision is one of data abundance, where we have the means of production to continue scaling frontier LLMs many more orders of magnitude. We should not be data-constrained in getting to GPT-10.” - Alexandr Wang, CEO and founder of Scale AI. This new funding also enables Scale to build upon our prior model evaluation work with enterprise customers, the U.S. Department of Defense, and collaboration with the White House to deepen our capabilities and offerings for both public and private evaluations. There’s a lot left to do. If this challenge excites you, join us: https://scale.com/careersRead the full announcement: https://lnkd.in/gVBhaPZ5
Scale’s Series F: Expanding the Data Foundry for AI scale.com -
185,323 followers
5d Edited
"Many organizations have access to AI tools but lack the skilled personnel needed for effective integration. This underscores the importance of partnerships to help bridge this knowledge gap and facilitate smoother transitions to AI-driven solutions." Read more from our CFO Dennis Cinelli in the Algorithms vs Applications report from Economist Impact. The report examines the factors influencing investment decisions in today's AI ecosystem. 👉 https://lnkd.in/grG5jtCZ - “As we reflect on the value of service at the heart of Veterans Day, perhaps the most impactful way to celebrate is by dedicating ourselves to pursuing more opportunities for service in our personal and professional lives and remembering that service can take many forms.” We thank all veterans for their service and are proud to highlight the contributions made by Scaliens who have served. Bryan Lee reflects on rekindling a sense of mission and purpose after military service in today’s blog. Read the full story here → https://lnkd.in/gb-5agAN
- Contrary to prior work, new research from Scale finds that LLMs continue to learn new knowledge during post-training following a power law similar to well known pre-training scaling laws. Let’s dive in 👇 The Superficial Alignment Hypothesis suggests that most of a language model's knowledge and skills come from its initial training. Post-training a model is about giving it the right style and format. However, our research team found that when evaluated appropriately on reasoning benchmarks LLMs continue to learn and apply new information to better tackle complex questions. Specifically, they found that just like pre-training scaling laws, post-training performance scales as a power law against the number of fine-tuning examples. What this implies is the Superficial Alignment Hypothesis is an oversimplification of how models learn. Relying on just human preference votes alone can be misleading, especially for complex reasoning tasks. Evaluating models using both human preference and objective reasoning benchmarks provides a more holistic picture of a model's true capabilities. Read the full paper here from authors Mohit Raghavendra, Vaskar Nath, and Sean Hendryx: https://lnkd.in/gXNzCgvD
- We are proud to announce Defense Llama, the LLM built on Meta's Llama 3 to support American national security missions. Defense Llama empowers our service members and national security professionals to apply generative AI to defense-related questions and scenarios, such as planning operations and understanding adversary vulnerabilities. We collaborated with Meta and defense experts to use fine-tuned data to configure the parameters of Defense Llama. Defense Llama is available now, exclusively in controlled U.S. government environments within Scale Donovan. Learn more: https://lnkd.in/gwuxeYrj
- Scale AI reposted this
Long before most enterprises saw AI’s potential, Alexandr Wang had a vision. As a kid growing up in Los Alamos, New Mexico, Alex was surrounded by science and technology. After enrolling at MIT, he began experimenting with AI by tackling small, everyday problems. What started as a personal side project — trying to track when his fridge needed restocking — sparked a realization: data was the key to unlocking AI’s future. In 2016, he founded Scale AI to help companies harness the power of high-quality data. Today, Scale provides the data infrastructure that powers AI models for some of the world’s largest AI enterprises, helping them build customized AI agents using their proprietary data. Index Ventures partner Mike Volpi caught up with Alex at Scale’s new San Francisco office. They discussed the evolution of AI, the challenges of moving projects from prototype to production, the geopolitical dynamics shaping the future of AI, and more.https://lnkd.in/gPw4-YU6 -
185,323 followers
2w Edited
We are excited to announce Xiaote Z. as the first General Manager of Outlier, which is part of the Scale family of products and services dedicated to advancing GenAI through specialized human expertise. Xiaote will drive the next phase of Outlier growth–actively addressing feedback and keeping an eye on the future. She will focus on three key pillars: 1️⃣ Best-In-Class Platform: leading with contributor experience 2️⃣ Reliability and Transparency: improving pay transparency and contributor support 3️⃣ More Opportunity and Flexibility: increasing contributor choice and testing Expert Match, a feature that enables customers to select their expert team. As we take this next step, we're committed to our mission to advance AI through expert-driven, high-quality data, ensuring that both AI and its development process benefit humanity. Hear from Xiaote on this exciting next step for Outlier: https://lnkd.in/g8vp5Ad2 - Hosted by Scale CEO Alexandr Wang and entrepreneur and investor, Nat Friedman, the AI Leadership Summit brought together the world’s foremost AI leaders and industry executives to explore the blueprint to develop and implement AI. Attendees discussed frontier AI's role in enterprise, advances in LLM capabilities and evaluation, U.S.-China strategic dynamics, and what’s on the horizon for the industry. Special thanks to partners Amazon Web Services (AWS), Coatue, and NFDG.
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- Scale AI reposted this
3,523 followers
1mo Edited
🔥We just heard from keynote speaker Michael Kratsios, Managing Director at Scale AI and former Chief Technology Officer of the United States, in a fireside chat moderated by Keegan McBride (Oxford Internet Institute, University of Oxford). Michael gave an enlightening talk on the geopolitical dimensions of AI, how to balance regulation with innovation, trends in AI policy, and the importance of sector-specific regulation.
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