Jivi MedX ranks number 1 in the world on Open Medical LLM Leaderboard; leaves behind GPT-4 and Med-PaLM2
· Jivi aims to launch its AI healthcare product later this year
Chandigarh, May 31, 2024: A purpose-built medical Large Language Model (LLM) developed by Jivi, an Indian healthcare AI startup co-founded by former BharatPe Chief Product Officer Ankur Jain and GV Sanjay Reddy, Chairman, Reddy Ventures, has ranked number 1 on the Open Medical LLM Leaderboard. Jivi’s LLM, Jivi MedX, has beaten established LLMs, including OpenAI’s GPT-4 and Google’s Med-PaLM 2 with an average score of 91.65 across the leaderboard’s nine benchmark categories.
Hosted by leading AI platform Hugging Face, the University of Edinburgh, and Open Life Science AI, the leaderboard ranks medical-specific LLMs based on their performance in answering medical questions from exams and research. The evaluation covers medical exams such as Indian medical entrance exams (AIIMS and NEET), US Medical License Exams (USMLE), and detailed assessments in clinical knowledge, medical genetics, and professional medicine, among others.
“Jivi is revolutionizing primary healthcare through generative AI, making top-quality care accessible 24/7 at a fraction of the cost. Our mission at Jivi is to harness artificial intelligence to enhance patient care. Our platform accelerates diagnostics and ensures higher accuracy, enabling timely and precise treatment for all,” said Ankur Jain, Co-founder and CEO, JIVI.
Jivi currently operates with a lean, 20-member team of physicians, surgeons, AI engineers, and data scientists. It is developing technology to transform accessibility, affordability, and quality of healthcare globally.
“This is a monumental achievement for an Indian company. At Jivi, our mission is to make top-of-the-line healthcare available to everyone globally. Our LLM being the best worldwide gives us immense pride and confidence as we prepare to bring Jivi to over a billion people,” said GV Sanjay Reddy, Co-founder and Chairman, Jivi.
Jivi uses its large proprietary medical dataset consisting of millions of medical research papers, journals, clinical notes, and other sources to train its Jivi MedX LLM. This dataset is among the largest in the world. Jivi MedX was trained using an instruction fine-tuning algorithm called Odds Ratio Preference Optimisation (ORPO).
Disclaimer
The information contained in this website is for general information purposes only. The information is provided by TodayIndia.news and while we endeavour to keep the information up to date and correct, we make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability or availability with respect to the website or the information, products, services, or related graphics contained on the website for any purpose. Any reliance you place on such information is therefore strictly at your own risk.
In no event will we be liable for any loss or damage including without limitation, indirect or consequential loss or damage, or any loss or damage whatsoever arising from loss of data or profits arising out of, or in connection with, the use of this website.
Through this website you are able to link to other websites which are not under the control of TodayIndia.news We have no control over the nature, content and availability of those sites. The inclusion of any links does not necessarily imply a recommendation or endorse the views expressed within them.
Every effort is made to keep the website up and running smoothly. However, TodayIndia.news takes no responsibility for, and will not be liable for, the website being temporarily unavailable due to technical issues beyond our control.
For any legal details or query please visit original source link given with news or click on Go to Source.
Our translation service aims to offer the most accurate translation possible and we rarely experience any issues with news post. However, as the translation is carried out by third part tool there is a possibility for error to cause the occasional inaccuracy. We therefore require you to accept this disclaimer before confirming any translation news with us.
If you are not willing to accept this disclaimer then we recommend reading news post in its original language.
