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Byung-Gon Chun is the CEO and founder of FriendliAI. FriendliAI helps businesses innovate with generative AI models. He is also a professor at Seoul National University.
Despite the potential of generative AI, there are considerable barriers to its use for startup developers. Developers are thrown into the task of training and serving models, setting up the necessary resources and environments, and handling failures and performance issues. All of these steps are essential, but incredibly time consuming and expensive. This is where FriendliAI comes into play. It helps streamline the process by enabling startups to use the cloud to build and deliver generative AI models to meet requirements quickly and efficiently.
Building FriendliAI
With the release of GPT3 by OpenAI in 2020, I quickly found a great opportunity to apply my experience in a highly scalable machine learning system. As Professor of Computer Science and Engineering at Seoul National University and as his Principal Scientist at Microsoft, Distributed Computing With his 10 years of experience in his technology, I am keen to explore new opportunities in this area. was excited about Moreover, as the aggressive commercialization of generative AI has begun to flourish in various industries, it has become clear that advances in distributed AI computing technology are also needed.
Two years ago, I founded FriendliAI to give startups easy access to transformative generative AI. PeriFlow is a solution that easily trains and delivers generative AI models with amazing training and inference speed and minimal cost. Our ambition has taken us on an incredible journey. We are uniquely positioned within the market as a dedicated provider of generative AI training and service offerings. As a result, we are already partnering with multiple clients to develop and deliver state-of-the-art generative AI applications powered by PeriFlow.
A fast, convenient, and cost-effective way to serve and train generative AI models
PeriFlow is an automated platform that handles ML pipelines from training to AI model serving. Successfully reduced technical barriers and high costs associated with generative AI services. This is because it not only allows the training and inference process to run smoothly and cost-effectively, but also allows for automation in areas such as resolving faults and performance issues. Cumbersome manual monitoring. With PeriFlow, businesses, especially, can be confident that their AI workflows will run at peak efficiency in the cloud. Their generative AI inference can be up to tens of times faster than traditional inference.
FriendliAI is a prime example of how Azure can help startups grow and succeed. With Azure’s AI infrastructure and PeriFlow platform, you can easily migrate cloud services without sacrificing performance or reliability when scaling generative AI models from your laptop to the cloud. Countless organizations rely on the services Azure provides, proving its immense value within the Microsoft for Startups Founders Hub.
What’s more, PeriFlow helps users find the best combination of generated AI models and cloud resources in an easier way, allowing users to scale their models in a hassle-free way. These features allow startups to confidently leverage PeriFlow’s training and service capabilities while taking advantage of significantly higher request throughput at minimal cost.
Enable human-like communication at minimal cost
One of our customer success stories includes ScatterLab’s Luda Lee 2.0. It is an open domain conversational AI service that has garnered a lot of attention in the tech industry and has achieved the top spot on both Google Play and Apple App Store in South Korea. What makes Luda Lee 2.0 extraordinary is its impressive contextual prowess. The chatbot recognizes nuanced semantic differences, responds naturally to buzzwords and jokes, and even prompts philosophical responses such as “Everyone is precious regardless of race.” Thanks to the innovations of the ScatterLab team and the capabilities of her PeriFlow platform, the impressive chatbot is now serving models 17 times larger than her with amazing speed and minimal cost. ScatterLab has set a new gold standard for open domain conversational AI services in South Korea.
Choosing the best cloud environment for your AI platform
Cloud computing is driving innovation and transforming industries. With PeriFlow Platform leading generative AI innovation through the Azure cloud, users can maintain guaranteed performance, connectivity, and flexibility on a scalable basis. Below are some of the Azure services that PeriFlow leverages to deliver secure and reliable results.
- Azure virtual machine (VM): Azure supports GPU-enabled virtual machines for machine learning training and serving. ND and NC VMs are scalable for multi-GPU training and serve over high-speed interconnects using NVLink and Infiniband.
- Azure blob storage: Azure Blob Storage allows you to upload custom datasets. PeriFlow reads the dataset, trains the model, and creates checkpoints. Checkpoints are periodically sent to storage for future use by the PeriFlow serving service.
- Azure Kubernetes Service (AKS): AKS integrates with PeriFlow to deploy a service engine for flexible provisioning, cost control, and security.
With Azure best practices in operational excellence, cost optimization, and sustainability, Azure gives PeriFlow and its users the foundation they need for the streamlined experiences that make up the operational environment while maintaining efficiency and business continuity. Offers.
For startups starting AI
A new wave of AI services can pose a threat, especially for early-stage startups. A key to our early success was to focus on developing the best software for generative AI, start small, and work with our early generative AI customers to deliver and improve what we offer. This customer-centric perspective is critical to keeping us agile and focused. I am delighted to be a part of this wonderful journey and endeavour.
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