Blog
Company Updates & Technology Articles
March 7, 2024
Introducing WMDP: Measuring and Mitigating Catastrophic Risk Potential from LLMs
As the capabilities of AI systems rapidly increase, it is clear that AI holds a great deal of promise for transforming our world for the better. At the same time, similar to many scientific advancements before it, AI also harbors the potential for malicious use. That is why in 2023, Scale published our vision for model test & evaluation, followed by our new frontier research effort, the Safety, Evaluations and Alignment Lab (SEAL).
February 13, 2024
Accelerate Generative AI Across Your Enterprise with Scale GenAI Platform
2023 ushered in a wave of excitement about Large Language Models (LLMs) and became the year of the Generative AI proof-of-concept. Enterprises experimented with Generative AI and explored how it may impact their business. According to BCG, Generative AI solutions can deliver up to 50% efficiency and effectiveness gains. However, only 10% of enterprises actually have Generative AI models in production.
February 8, 2024
Scale AI Joins U.S. Artificial Intelligence Safety Institute Consortium
Scale AI is proud to announce a new collaboration with the National Institute of Standards and Technology (NIST) in the Artificial Intelligence Safety Institute Consortium (AISIC) to develop science-based and empirically backed guidelines and standards for AI measurement and policy, laying the foundation for AI safety across the world.
December 12, 2023
Efficient and Effective Fine-Tuning Using Mixture-of-Experts PEFT
At Scale, we have always believed that building custom LLMs through fine-tuning is key to unlocking greater performance for any given organization’s specific use case. We work with enterprise customers to implement cutting-edge enterprise Generative AI solutions, combining the best large language models with the latest research techniques and balancing our solutions for both effectiveness with efficiency to optimize model performance.
December 6, 2023
We Fine-Tuned GPT-4 to Beat the Industry Standard for Text2SQL
Our machine learning team at Scale has recently fine-tuned GPT-4 to achieve state-of-the-art performance (84% accuracy) for generalized text-to-SQL translation on one of the most popular benchmark datasets, the SpiderDev Set. In this blog post, we will discuss why text2sql is an important use case, why it is hard in practice, where fine-tuning can help, how we implemented a real-world solution, and finally, what our results were.
December 5, 2023
Introducing Scale’s Automotive Foundation Model
Autonomous vehicle development requires iterative improvements in perception models through a data engine. These data engines currently rely on a set of task-specific models based around a fixed taxonomy of objects and scenarios to identify. However, there are two critical limitations to existing data engines: