Arcee AI Transitions from AWS to Together AI for Enhanced Flexibility and Performance
The post Arcee AI Transitions from AWS to Together AI for Enhanced Flexibility and Performance appeared on BitcoinEthereumNews.com. Peter Zhang May 05, 2025 22:08 Arcee AI migrates from AWS to Together Dedicated Endpoints, optimizing costs and performance for their specialized small language models, enhancing operational agility and efficiency. Arcee AI, a company focused on simplifying AI adoption, has made a strategic move by transitioning its specialized small language models (SLMs) from Amazon Web Services (AWS) to Together Dedicated Endpoints. This migration, according to together.ai, has brought significant improvements in cost efficiency, performance, and operational agility for Arcee AI. Optimizing Small Language Models At the heart of Arcee AI’s strategy is the development of specialized small language models optimized for specific tasks, typically under 72 billion parameters. The company leverages proprietary techniques for model training, merging, and distillation to produce high-performing models that excel in tasks like coding, text generation, and high-speed inference. With the migration to Together AI, seven of these models are now accessible via Together AI’s serverless endpoints. These models include Arcee AI Virtuoso-Large, Arcee AI Virtuoso-Medium, Arcee AI Maestro, Arcee AI Coder-Large, Arcee AI Caller, Arcee AI Spotlight, and Arcee AI Blitz, each designed for various complex tasks ranging from coding to visual tasks. Software Enhancements: Arcee Conductor & Arcee Orchestra Additionally, Arcee AI has developed two software products, Arcee Conductor and Arcee Orchestra, to enhance their AI offerings. Conductor serves as an intelligent inference routing system, efficiently directing queries to the most suitable model based on task requirements. This system not only reduces costs but also improves performance benchmarks by utilizing the best model for each task. Arcee Orchestra focuses on building agentic workflows, enabling enterprises to automate tasks through seamless integration with third-party services. The no-code interface allows users to create automated workflows effortlessly, powered by AI-driven capabilities. Challenges with AWS and the Move to Together AI Initially, Arcee AI deployed its models…
The post Arcee AI Transitions from AWS to Together AI for Enhanced Flexibility and Performance appeared on BitcoinEthereumNews.com.
Peter Zhang May 05, 2025 22:08 Arcee AI migrates from AWS to Together Dedicated Endpoints, optimizing costs and performance for their specialized small language models, enhancing operational agility and efficiency. Arcee AI, a company focused on simplifying AI adoption, has made a strategic move by transitioning its specialized small language models (SLMs) from Amazon Web Services (AWS) to Together Dedicated Endpoints. This migration, according to together.ai, has brought significant improvements in cost efficiency, performance, and operational agility for Arcee AI. Optimizing Small Language Models At the heart of Arcee AI’s strategy is the development of specialized small language models optimized for specific tasks, typically under 72 billion parameters. The company leverages proprietary techniques for model training, merging, and distillation to produce high-performing models that excel in tasks like coding, text generation, and high-speed inference. With the migration to Together AI, seven of these models are now accessible via Together AI’s serverless endpoints. These models include Arcee AI Virtuoso-Large, Arcee AI Virtuoso-Medium, Arcee AI Maestro, Arcee AI Coder-Large, Arcee AI Caller, Arcee AI Spotlight, and Arcee AI Blitz, each designed for various complex tasks ranging from coding to visual tasks. Software Enhancements: Arcee Conductor & Arcee Orchestra Additionally, Arcee AI has developed two software products, Arcee Conductor and Arcee Orchestra, to enhance their AI offerings. Conductor serves as an intelligent inference routing system, efficiently directing queries to the most suitable model based on task requirements. This system not only reduces costs but also improves performance benchmarks by utilizing the best model for each task. Arcee Orchestra focuses on building agentic workflows, enabling enterprises to automate tasks through seamless integration with third-party services. The no-code interface allows users to create automated workflows effortlessly, powered by AI-driven capabilities. Challenges with AWS and the Move to Together AI Initially, Arcee AI deployed its models…
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