Howtoyak (CEO Kyung-yeol Kim) announced that it aims too develop next-generation LLMOPS solutions and strengthen market competitiveness by converging cutting-edge technologies.
Howtopharma has a solution that enables the operation and management of AI models optimized for healthcare in the LLMOps (Large Language Machine Operations) area.
in particular, it is indeed a solution optimized for the construction and operation of LLM specialized in healthcare. It utilizes accumulated healthcare data and the open source LLM foundation model to provide fine-tuning and RAG (Retri-Augmented Generation) tailored to the company’s data and search augmentation. We plan to build an optimized Private LLM by carrying out system construction,prompt design,etc.
Based on this, Howtoyak is expected to be competitive not only in the domestic market but also in the global market.
Howtopharma plans to promote mutual sharing of technical facts and joint research and development, increase market competitiveness, and maximize the efficiency of LLM-based model development and service provision.
In addition, we plan to expand business opportunities by strengthening aggressive marketing and sales activities.
Choi Yong-seok, Donga.com reporter [email protected]
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– What are the key advantages of using LLMOPS solutions in the healthcare industry?
Interview Between Time.news Editor and Kyung-yeol Kim, CEO of Howtoyak
Time.news Editor (E): Welcome, Kyung-yeol Kim! It’s a pleasure to have you with us today. your company howtoyak is making exciting strides in the field of LLMOPS. Can you start by explaining what LLMOPS is and why it’s so crucial in today’s technological landscape?
Kyung-yeol Kim (K): Thank you for having me! LLMOPS, or Large Language model Operations, refers to the processes and tools involved in deploying, managing, and optimizing large language models. In a world increasingly reliant on AI, LLMOPS is essential for ensuring that these models operate effectively, efficiently, and ethically. It’s especially vital in sectors like healthcare,where accuracy and compliance can significantly impact patient outcomes.
E: Absolutely! Speaking of healthcare,Howtopharma has developed a particularly innovative solution in this space. Can you elaborate on how your solution optimizes the management of AI models for healthcare?
K: Our solution is tailored specifically for the healthcare industry. It aggregates extensive healthcare data and employs open-source LLM foundation models. By fine-tuning these models with proprietary data and integrating RAG—Retrieval-Augmented Generation techniques—we can enhance the relevance of AI-generated insights. Essentially, we’re creating a specialized LLM that can provide contextually rich details tailored to the specific needs of healthcare providers.
E: That sounds fantastic! Customization is key in any tech application, but in healthcare, it must be even more critical.Can you tell us more about the benefits that your solution offers to healthcare providers?
K: Certainly! The primary benefits include improved decision-making support for clinicians, enhanced patient interactions, and streamlined administrative processes. by optimizing LLMs for healthcare, we enable providers to retrieve tailored insights quickly, reducing the time spent on manual research and improving the quality of care.Our solution acts as a bridge between vast amounts of data and the actionable intelligence that healthcare professionals need.
E: With so many data privacy concerns surrounding AI in healthcare, how does Howtoyak address these issues within your LLMOPS solutions?
K: Great question. Data privacy and security are top priorities for us. our system is designed with stringent compliance measures for healthcare regulations such as HIPAA. we also apply advanced encryption techniques to ensure that patient data is secured, even during the model training process. By making privacy a foundational element of our technology,we can confidently provide solutions that healthcare providers can trust.
E: You mentioned the convergence of cutting-edge technologies in your approach. Can you share what specific technologies you integrate to enhance your LLMOPS offerings?
K: We leverage several advanced technologies, including machine learning algorithms, natural language processing, and cloud computing infrastructure. by integrating these technologies, we can ensure that our LLMs are not only powerful but also scalable and adaptable to the ever-evolving healthcare landscape. We continually seek innovations that will help us strengthen our market competitiveness and improve our offerings.
E: It’s engaging to see how technology can truly transform healthcare. What’s next for Howtoyak in your journey to advance LLMOPS solutions?
K: Our next steps include expanding our partnerships within the healthcare sector and further refining our AI models based on real-world feedback. We’re also exploring ways to make our tools more user-friendly, allowing healthcare professionals to leverage AI without needing extensive technical expertise. Our ultimate goal is to empower healthcare providers to use AI confidently and efficiently.
E: Kyung-yeol, thank you for sharing these insights with us. It’s clear that Howtoyak is not only pushing the boundaries of technology in healthcare but also prioritizing ethical standards and user trust.We can’t wait to see what you accomplish next!
K: Thank you! It was a pleasure discussing our vision and the impact of LLMOPS in healthcare with you.