Outerbounds, a cutting-edge machine learning infrastructure startup, has just unveiled exciting new product capabilities designed to help enterprises embrace and utilize generative AI models like ChatGPT.
Founded by former Netflix data scientists and led by CEO Ville Tuulos and CTO Savin Goyal, Outerbounds aims to establish itself as a leading provider of ML infrastructure. With the growing demand for large language models (LLMs), businesses are seeking innovative solutions to leverage this technology.
The latest additions to the Outerbounds platform include GPU compute for generative AI use cases, bank-grade security and compliance, and workstation support for data scientists. These features are designed to empower customers to accelerate the delivery of their data, ML, and AI projects while maintaining control over their valuable data and models.
Tuulos recently discussed the rationale behind these new features in an interview with NeuralNation, emphasizing the importance of thoughtful implementation. He stated, “The adoption of generative AI and LLMs should not be a quick fix or a gimmick. It should be tailored to enhance a company’s products in meaningful ways.”
“While AI may be new and exciting, it should not be an excuse for delivering subpar product experiences,” Tuulos added. “The most successful companies will learn how to adapt and customize AI techniques to support their products in specific ways, rather than simply adding it as an easy chat feature.”
Building on Netflix Roots
Since its launch in 2021, Outerbounds has played a pivotal role in the success of various businesses, including Trade Republic, Convoy, and Wadhwani AI. Notably, Trade Republic implemented a new ML-powered feature in just six weeks, resulting in significant improvements in product metrics, thanks to Outerbounds.
Outerbounds is built on Metaflow, an open-source framework developed by the founders at Netflix in 2019. Metaflow is currently utilized by numerous leading ML and data science organizations across industries, including Netflix, Zillow, 23andMe, CNN Media Group, and Dyson.
Tuulos highlighted Outerbounds’ unique approach to MLOps and ML lifecycle management, focusing on user experience rather than solely technical capabilities.
“From the very beginning, we have prioritized user experience,” Tuulos explained. “While many other solutions have primarily focused on technical capabilities, treating user experience as an afterthought, we firmly believe that technology will mature. Ultimately, it is the best user experience that prevails.”
Seamless Integration and Bank-Grade Security
Despite the complexities of AI and ML, Outerbounds has successfully navigated the immature and chaotic landscape, drawing on its expertise. “Establishing a solid foundation for any AI project is crucial,” Tuulos emphasized, underscoring the importance of data, compute, orchestration, and versioning in AI initiatives.
Outerbounds’ CTO, Savin Goyal, echoed Tuulos’ sentiments regarding the need for robust AI infrastructure. He stated, “ML and AI should adhere to the same security standards as any other infrastructure, if not higher.”
“We follow a cloud-prem deployment model,” Goyal added. “Everything runs on the customer’s cloud account, adhering to their security policies and governance. We seamlessly integrate with Snowflake, Databricks, and open-source solutions.”
Goyal also emphasized that Outerbounds assists customers in addressing challenges related to model governance, transparency, and bias when deploying generative AI models.
“We believe that there should not be a single entity dictating what bias means or what is acceptable in the realm of gen AI,” Goyal explained. “Each company should take responsibility for these choices based on their understanding of the market, similar to how companies are accountable for their behavior today, even without gen AI. We provide companies with tools to customize and fine-tune gen AI according to their specific needs.”
A Human-Centric Approach to ML Operations
Outerbounds distinguishes itself in a crowded market by adopting a unique approach to ML operations. “We are developing a human-centric infrastructure that maximizes the productivity of data scientists and data developers,” Tuulos stated.
With the latest feature update, Outerbounds aims to address the challenge of data access, which Goyal identifies as a “fundamental bottleneck.” He explained, “How much time does it take for an individual to iterate through various iterations and hypotheses? If accessing the necessary data consumes 20 minutes of your time, it disrupts your flow state.”
The newly released features align Outerbounds with its mission to facilitate the adoption of ML and AI across different aspects of businesses. The company envisions a future where AI and ML can be applied ubiquitously, and these enhancements represent a significant step towards realizing this vision.
As the field of AI continues to evolve, businesses grapple with the complexities of implementation and governance. Outerbounds, with its new features, positions itself at the forefront of this transformation, offering solutions that are not only technologically advanced but also considerate of user experience and governance concerns. With its latest offerings, Outerbounds paves the way for broader and more effective utilization of AI and ML in the enterprise.
Netflix’s AI legacy continues to inspire sectors far and wide with its pioneering approach to the use of AI technology. The streaming giant, which has made waves with its personalized recommendations, sophisticated algorithms, and automated workflows, is now providing a similar playbook for the enterprise world.
Outerbounds, a new AI company, is leveraging the lessons learned from Netflix to make it easier for large companies to harness AI technology. By focusing on ease of use and incorporating real-world experience, Outerbounds is aiming to help companies overcome the traditional challenges of AI implementations.
Outerbounds is aiming to empower companies by giving them access to the same best-in-class data engineering, machine learning, and AI challenges that Netflix has perfected over the years. This includes solutions for data wrangling, anomaly detection, rationalization, and more. Outerbounds also provides its own unique solutions to existing data challenges, such as its AI-enabled search engine.
The company believes that the key to effective AI implementations is the ability to move quickly and efficiently while ensuring accuracy and precision. By focusing on how to deploy AI solutions rapidly and accurately, Outerbounds plans to bridge the gap between the pace of business and the complexity of implementing AI solutions.
Outerbounds is also helping to increase access to the AI tools and expertise needed to successfully deploy AI. This is facilitated by the company’s platform, which provides access to a wide range of AI tools via simple APIs. This allows companies to increase the speed and accuracy of their AI deployments.
The Netflix success story is proving to be a significant turning point in the history of AI implementation across the business world. Outerbounds is playing a major role in the legacy of Netflix, providing an innovative approach to allowing companies to access and take advantage of the same advanced AI tools and successes that Netflix has pioneered. As Outerbounds continues to refine and develop its technology, enterprise AI is sure to become an increasingly important part of the Netflix story.
