How Thomson Reuters developed Open Arena, an enterprise-grade large language model playground, in under 6 weeks

“Unleashing the Power of Open Arena: Thomson Reuters’ Incredible Journey to Creating an Enterprise-Grade Language Model Playground in Just 6 Weeks!”

Introduction:

Thomson Reuters, a global content and technology-driven company, has been at the forefront of utilizing artificial intelligence (AI) and machine learning (ML) in its products. With the introduction of generative AI, Thomson Reuters aims to further advance how professionals work, helping them automate workflows and draw valuable insights. To achieve this, Thomson Reuters Labs created Open Arena, an enterprise-wide platform developed in collaboration with AWS. Open Arena serves as a playground for Thomson Reuters teams to experiment with generative AI and discover unique use cases by merging LLM capabilities with company data. With the support of AWS services like SageMaker and Lambda, Open Arena provides a safe and controlled environment for company-wide experimentation.

Full Article: “Unleashing the Power of Open Arena: Thomson Reuters’ Incredible Journey to Creating an Enterprise-Grade Language Model Playground in Just 6 Weeks!”

Thomson Reuters: Harnessing the Power of Generative AI for Innovation

Thomson Reuters, a global content and technology-driven company, has been at the forefront of using artificial intelligence (AI) and machine learning (ML) in its professional information products. With a dedicated innovation team called Thomson Reuters Labs, the company has been pioneering the use of AI and natural language processing (NLP) for years.

A major milestone for Thomson Reuters was the introduction of Westlaw Is Natural (WIN) in 1992. WIN was one of the first technologies of its kind, utilizing NLP to revolutionize legal research. Fast forward to 2023, and Thomson Reuters continues to push the boundaries of innovation and technology.

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Generative AI Opens New Doors for Thomson Reuters

The introduction of generative AI offers an exciting opportunity for Thomson Reuters to once again revolutionize how professionals work. By utilizing generative AI, Thomson Reuters can help professionals draw insights, automate workflows, and focus their time where it matters most.

While Thomson Reuters explores the potential of generative AI and other technologies for its customers, it is also using these technologies internally. The company is committed to driving awareness and understanding of AI among its colleagues. They have implemented a company-wide AI awareness program, including webinars, training materials, and panel discussions, to help their teams understand and embrace AI.

Enter Open Arena: Thomson Reuters’s Enterprise-Wide Playground

Thomson Reuters Labs has created Open Arena, an enterprise-wide large language model (LLM) playground in collaboration with AWS. Open Arena is a web-based platform that allows Thomson Reuters employees to experiment with a variety of tools powered by LLMs. The platform is designed to be user-friendly and accessible to employees without coding backgrounds.

Open Arena enables quick and efficient access to several sets of corpora, making it a valuable resource for customer support agents, website information retrieval, document summarization, and more. As Thomson Reuters employees explore the capabilities of Open Arena, new ideas and trends emerge, leading to continuous growth and innovation.

Envisioning the Open Arena

Thomson Reuters set out to build a safe and user-friendly platform for its employees—an “open arena” where they could freely interact with LLMs. The platform aimed to merge the capabilities of LLMs with Thomson Reuters’s extensive company data, allowing teams to generate innovative solutions and improve products and services for clients.

Building the Open Arena with AWS

Building the Open Arena was a complex and multi-faceted process. Thomson Reuters leveraged the capabilities of AWS’s serverless and ML services to create a comprehensive and intuitive platform. The architecture of Open Arena was designed to ensure scalability, manageability, and cost-effectiveness.

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SageMaker served as the backbone of Open Arena, facilitating model deployment and providing a robust environment for fine-tuning models. The Hugging Face on SageMaker DLC offered by AWS enhanced the deployment process, while Lambda functions handled API management.

To deliver a seamless user experience, Open Arena utilized Amazon API Gateway, Amazon S3, Amazon CloudFront, and the company’s single sign-on mechanism. The platform was designed to integrate seamlessly with multiple LLMs through REST APIs, allowing for quick adaptation to new models and advancements in generative AI.

The Heart of Open Arena: Diverse Assortment of LLMs

At the core of Open Arena are various LLMs, both open-source and in-house developed models. These LLMs have been fine-tuned to provide specific responses based on user prompts. Thomson Reuters has experimented with different LLMs for different use cases, optimizing their performance and efficiency.

Thomson Reuters considered various aspects when selecting a model for each use case, including its performance on relevant NLP tasks and engineering considerations. The company prioritizes efficiency, secure customization, and flexibility in integrating and deploying state-of-the-art LLMs.

The Future of Innovation at Thomson Reuters

Thomson Reuters continues to innovate and leverage the power of AI and ML to redefine how professionals work. With Open Arena, the company has created a platform that fosters experimentation, creativity, and collaboration across its global teams. As new models and techniques emerge in the field of generative AI, Thomson Reuters is well-equipped to drive innovation and deliver cutting-edge solutions to its clients.

Summary: “Unleashing the Power of Open Arena: Thomson Reuters’ Incredible Journey to Creating an Enterprise-Grade Language Model Playground in Just 6 Weeks!”

Thomson Reuters, a leading global content and technology company, has been using artificial intelligence (AI) and machine learning (ML) in its professional information products for years. The company’s innovation team, Thomson Reuters Labs, has been instrumental in their AI endeavors. To further advance their AI capabilities, Thomson Reuters Labs created Open Arena, an enterprise-wide playground for generative AI. Developed in collaboration with AWS, Open Arena allows Thomson Reuters employees to experiment with language models and explore unique use cases using Thomson Reuters’ extensive data. The platform leverages AWS services such as SageMaker, Lambda, DynamoDB, and Hugging Face Deep Learning Containers to enable seamless deployment and integration of models.

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Thomson Reuters Open Arena FAQs


Frequently Asked Questions – Thomson Reuters Open Arena

How Thomson Reuters developed Open Arena, an enterprise-grade large language model playground, in under 6 weeks?

Thomson Reuters successfully developed Open Arena, an enterprise-grade large language model playground, in under 6 weeks by employing a streamlined development process and leveraging deep expertise in natural language processing.

Here’s a high-level overview of the development process:

1. Project Planning and Preparation

Prior to the 6-week development sprint, Thomson Reuters executed thorough project planning and requirements gathering. This phase involved defining the goals, functionalities, and target audience of Open Arena.

2. Resource Allocation

Thomson Reuters dedicated a skilled and cross-functional team to work on Open Arena during the 6-week period. The team consisted of developers, data scientists, UX/UI designers, and quality assurance specialists.

3. Agile Development Methodology

The development process followed an agile methodology, allowing for iterative improvements and quick feedback loops. This approach facilitated rapid prototyping, testing, and refinement.

4. Leveraging Existing Technologies

Thomson Reuters made smart use of pre-existing technologies and frameworks, saving time and effort in the development process. They leveraged their extensive knowledge of natural language processing and machine learning to accelerate the creation of Open Arena.

5. Continuous Communication and Collaboration

Constant communication and collaboration among the development team members ensured efficient problem-solving and prevented any potential roadblocks. This proactive approach further accelerated the development timeline.

6. Quality Assurance and Testing

A dedicated quality assurance team rigorously tested Open Arena at every stage of development to identify and address any issues or bugs. This ensured a reliable and stable product by the end of the 6-week period.

Through these strategic steps and efficient execution, Thomson Reuters successfully developed Open Arena, meeting the timeline requirements without compromising on quality or user experience.

Other Questions about Open Arena:

Q: What are the main features of Open Arena?
Open Arena offers various features, including:
  • Large language model playground
  • Enterprise-grade functionality
  • Advanced natural language processing capabilities
  • Deep learning and machine learning integration
  • Customizable and extensible framework
  • Integration with data sources and APIs
Q: Is Open Arena suitable for research purposes?
Absolutely! Open Arena provides researchers with a powerful platform to experiment with large language models, conduct deep learning research, and explore advanced natural language processing techniques.
Q: Can Open Arena handle multilingual content?
Yes, Open Arena supports multiple languages and can handle various multilingual use cases, making it a versatile tool for global enterprises.
Q: How secure is the information processed in Open Arena?
Thomson Reuters prioritizes data security and privacy. Open Arena implements robust security measures to protect user data and ensure compliance with industry regulations.


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