{"id":72751,"date":"2024-03-19T00:05:07","date_gmt":"2024-03-19T00:05:07","guid":{"rendered":"https:\/\/pakistaninewspaperlist.com\/news\/hippocratic-ai-announces-collaboration-with-nvidia-to-develop-super-low-latency-empathy-inference-for-one-of-the-worlds-first-generative-ai-powered-healthcare-agents\/"},"modified":"2024-03-19T00:05:07","modified_gmt":"2024-03-19T00:05:07","slug":"hippocratic-ai-announces-collaboration-with-nvidia-to-develop-super-low-latency-empathy-inference-for-one-of-the-worlds-first-generative-ai-powered-healthcare-agents","status":"publish","type":"post","link":"https:\/\/pakistaninewspaperlist.com\/news\/hippocratic-ai-announces-collaboration-with-nvidia-to-develop-super-low-latency-empathy-inference-for-one-of-the-worlds-first-generative-ai-powered-healthcare-agents\/","title":{"rendered":"Hippocratic AI Announces Collaboration with NVIDIA to Develop Super-Low-Latency \u201cEmpathy Inference\u201d for One of the World\u2019s First Generative AI-Powered Healthcare Agents"},"content":{"rendered":"<div id=\"main-body-container\" itemprop=\"articleBody\">\n<p align=\"left\">PALO ALTO, Calif., March  18, 2024  (GLOBE NEWSWIRE) &#8212; Today, <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=t2KzraNkXNFqxmNDNFGkc7X2qZrarD1ZYwPX8fFf5Pw-CYONiZfWYM9O9bVyU9sQ6DlS69N7A5z2jHnvb9Vw_3C3pJej1FOS8um9amPKQqg=\" rel=\"nofollow noopener\" target=\"_blank\" title=\"\"><u>Hippocratic AI<\/u><\/a> announced a collaboration with <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=BSXiOcf18dlR7t13fJ-lfSNRCnEo8xFeZwtyNJlkoQNN6PqlmjQHQpq0p0wwvODiuXKP6iG7CT22GFMRcHMbYg==\" rel=\"nofollow noopener\" target=\"_blank\" title=\"\"><u>NVIDIA<\/u><\/a> to develop empathetic AI healthcare agents \u2014 powered by the NVIDIA AI platform \u2013 enabling super-low-latency conversational interactions. User tests repeatedly show that super low latency voice interaction is required for patients to build an emotional connection naturally. Since LLMs run on inference engines, Hippocratic AI has termed this low latency inference: \u201cEmpathy Inference.\u201d The AI healthcare agents are built on Hippocratic\u2019s safety-focused large language model (LLM), the first designed specifically for healthcare. Health systems, payors, digital health companies, and pharma deploy Hippocratic AI\u2019s healthcare agents to augment their human staff and complete low risk, non-diagnostic, patient facing tasks over the phone.<\/p>\n<p>\u201cWith generative AI, patient interactions can be seamless, personalized, and conversational\u2014but in order to have the desired impact, the speed of inference has to be incredibly fast. With the latest advances in LLM inference, speech synthesis and voice recognition software, NVIDIA\u2019s technology stack is critical to achieving this speed and fluidity,\u201d said Munjal Shah, co-founder and CEO of Hippocratic AI. \u201cWe\u2019re working with NVIDIA to continue refining our technology and amplify the impact of our work of mitigating staffing shortages while enhancing access, equity, and patient outcomes.\u201d<\/p>\n<p>\u201cVoice-based digital agents powered by generative AI can usher in an age of abundance in healthcare, but only if the technology responds to patients as a human would,\u201d said Kimberly Powell, vice president of Healthcare at NVIDIA. \u201cThis type of engagement will require continued innovation and close collaboration with companies, such as Hippocratic AI, developing cutting-edge solutions.\u201d<\/p>\n<p>At NVIDIA GTC, a global AI developer conference, Hippocratic AI and NVIDIA showcased the solution with the NVIDIA Avatar Cloud Engine suite of technologies, which brings digital humans to life with generative AI.<\/p>\n<p>Hippocratic AI is working with NVIDIA to develop a super-low-latency inference platform to power real-time use cases. According to research conducted by Hippocratic AI, every half second of improvement in inference speed increases the ability for patients to emotionally connect with AI healthcare agents by 5-10% or more. For instance when asked, \u201cDid you feel this AI cared about you?\u201d over 1002 licensed US nurses acting as patients said yes 84.3% of the time when the inference was over 3 seconds but 88.2% yes when inference was 2.2 seconds. When asked, \u201cDo you feel comfortable confiding in this AI?\u201d respondents said yes 80.1% when the end-to-end inference time was over 3 seconds but 88.9% when it was 2.2 seconds.<\/p>\n<p>As part of the collaboration, Hippocratic AI will continue to build upon NVIDIA\u2019s low-latency inference stack and enhance conversational AI capabilities using NVIDIA Riva models for automatic speech recognition and text-to-speech translation. The companies will also customize the models for the medical domain. Hippocratic AI will leverage <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=BSXiOcf18dlR7t13fJ-lfZBz1m9NYeQolUevJZsmFP-7czf2Cg2CXl0kfKeaJGu7HsBp2xoigR_5VDlYFdPlkAhr8xFRTC6FlnOEM9uQag4=\" rel=\"nofollow noopener\" target=\"_blank\" title=\"NVIDIA NIM\">NVIDIA NIM<\/a> microservices for deployment of these new AI models capabilities to optimize performance and accelerate the pace of innovation.<\/p>\n<p>In addition, Hippocratic AI uses NVIDIA H100 Tensor Core GPUs to support the development and delivery of its LLM and patient-facing solutions. The company today announced that its generative AI healthcare agents out performed GPT-4 and LLaMA2 70B Chat on a bevy of safety benchmarks.<\/p>\n<table style=\"border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; border-collapse: collapse; width:100%; border-collapse:collapse ;\">\n<tr>\n<td style=\"max-width:40%; width:40%; min-width:40%;;border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; vertical-align: top ; vertical-align: middle ; \">\u00a0<\/td>\n<td style=\"max-width:15%; width:15%; min-width:15%;;border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; text-align: center ;  vertical-align: middle; vertical-align: top ; \">Hippocratic AI <br \/>Constellation<\/td>\n<td style=\"max-width:15%; width:15%; min-width:15%;;border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; text-align: center ;  vertical-align: middle; vertical-align: top ; \">LLaMA 2 70B <br \/>Chat<\/td>\n<td style=\"max-width:15%; width:15%; min-width:15%;;border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; text-align: center ;  vertical-align: middle; vertical-align: top ; \">Open AI GPT-<br \/>4<\/td>\n<td style=\"max-width:15%; width:15%; min-width:15%;;border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; text-align: center ;  vertical-align: middle; vertical-align: top ; \">Human nurses<\/td>\n<\/tr>\n<tr>\n<td style=\"border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; vertical-align: top ; vertical-align: middle ; \">Identify medication impact on lab values (only MoA)<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \"><strong>79.61<\/strong><strong>%<\/strong><\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">0.00%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">74.22%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">63.40%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; vertical-align: top ; vertical-align: middle ; \">Identify condition-specific disallowed OTCs<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \"><strong>88.73<\/strong><strong>%<\/strong><\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">30.66%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">55.54%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">45.92%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; vertical-align: top ; vertical-align: middle ; \">Correctly compare lab value to reference range<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \"><strong>96.43<\/strong><strong>%<\/strong><\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">48.24%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">77.89%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">93.74%<\/td>\n<\/tr>\n<tr>\n<td style=\"border-top: solid black 1pt ; border-right: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; vertical-align: top ; vertical-align: middle ; \">Detect toxic OTC dosages<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \"><strong>81.50<\/strong><strong>%<\/strong><\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">9.11%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">38.06%<\/td>\n<td style=\"border-top: solid black 1pt ; border-bottom: solid black 1pt ; border-left: solid black 1pt ; padding-right: 0 ; text-align: center ;  vertical-align: middle; vertical-align: top ; vertical-align: middle ; \">57.64%<\/td>\n<\/tr>\n<\/table>\n<p>These successful benchmarks are the result of Hippocratic AI\u2019s unique three-part approach to safety, comprised of: (1) a 70B-100B primary model trained using evidence-based content; (2) a novel constellation architecture with multiple models totaling over one trillion parameters, in which the primary LLM is supervised by multiple specialist support models to improve medical accuracy and substantially reduce hallucinations (more on this architecture in Hippocratic\u2019s paper); (3) built-in guardrails that bring in a human supervisor when necessary.<\/p>\n<p>Hippocratic has engaged more than <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=n6yrA_okszCSr30bSBl6FKweem0Y32fiHQFUmqqZI7-L6M0VkMYa1Micqwq-oDiI7HvFnS95sJy2SNGaULlC93CtgvFyWk6sCcMBC56ok9ULTLfjQM9IbAlnwGZsOXXvsAyQx_JRAxvN95GsD0V1oKcuNpumALaiFhjeKo2yA1Y8NhwkGT_ay9W5iSDhomk7OPxLnf80wkH3FQ1bp8uKpeG1vLGlYdKa2kBqeOck27afPwGSGhSjzpmhmU2WX5_PwwFhUQTPnHM_jpCJ8mUpc60WAyMJSMvYWqaXMhzFrHT89QIyzKl6kNIe0snnN3GUBb9xPbnjv9uSmtQeIijcQhgQd8qb56WQlVXeB92z7bY=\" rel=\"nofollow noopener\" target=\"_blank\" title=\"\"><u>40 beta partners<\/u><\/a> to conduct rigorous internal tests of its initial AI healthcare agents, which focus on chronic care management, wellness coaching, health risk assessments, social determinants of health surveys, pre-operative outreach, and post-discharge follow-up.<\/p>\n<p>To learn more about Hippocratic AI, visit <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=ubl3Bs85z2GHQCFh-tcL_UMz20AayrvRnc7eeVZp8gblibP32kg7LPygGK3wRkUj0LxbSlieN1k9PXobHg7xG3ykMpLnv4-hgerBue5XBkA=\" rel=\"nofollow noopener\" target=\"_blank\" title=\"\"><u>www.HippocraticAI.com<\/u><\/a> or tune into Munjal Shah\u2019s upcoming session at NVIDIA GTC on Wednesday, March 20 at 10:30 a.m. PT. Register now at <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=GCJijZR1Yv-9p1OABz3r5GgdQhhULNzGtzhhD7O8cveQ3o8RMeVNDxZsoCqROauFriPwhDlBhBoh4uObwnJXCFIQdw2j9ceV2dtN3eqGXrs=\" rel=\"nofollow noopener\" target=\"_blank\" title=\"\"><u>https:\/\/www.nvidia.com\/gtc<\/u><\/a>.<\/p>\n<p><strong>About Hippocratic AI<\/strong><br \/>Hippocratic AI\u2019s mission is to develop the first safest focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health. The company was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, and NVIDIA. Hippocratic AI has received a total of $120M in funding and is backed by leading investors including General Catalyst, Andreessen Horowitz, Premji Invest and SV Angel. For more information on Hippocratic AI go to <a href=\"https:\/\/www.globenewswire.com\/Tracker?data=ubl3Bs85z2GHQCFh-tcL_UMz20AayrvRnc7eeVZp8ga6K48Y-Q-n3pgnvqJYSXGXMCEDvuN58fs5TmzmmZM9jp7CTI5bN3XLSDicnY6lsV4=\" rel=\"nofollow noopener\" target=\"_blank\" title=\"\"><u>www.HippocraticAI.com<\/u><\/a>.<\/p>\n<p><strong>Press Contact<\/strong><br \/>LaunchSquad for Hippocratic AI <br \/>hippocraticai@launchsquad.com<\/p>\n<p>\n            <\/div>\n","protected":false},"excerpt":{"rendered":"<p>PALO ALTO, Calif., March 18, 2024 (GLOBE NEWSWIRE) &#8212; Today, Hippocratic AI announced a collaboration with NVIDIA to develop empathetic AI healthcare agents \u2014 powered by the NVIDIA AI platform \u2013 enabling super-low-latency conversational interactions. User tests repeatedly show that super low latency voice interaction is required for patients to build an emotional connection naturally. [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":72752,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"fifu_image_url":"https:\/\/ml.globenewswire.com\/Resource\/Download\/36432e6f-6efd-461d-819b-e22ea59319be","fifu_image_alt":"","footnotes":""},"categories":[208],"tags":[],"class_list":["post-72751","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-globenewswire"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.10 - aioseo.com -->\n\t<meta name=\"description\" content=\"PALO ALTO, Calif., March 18, 2024 (GLOBE NEWSWIRE) -- Today, Hippocratic AI announced a collaboration with NVIDIA to develop empathetic AI healthcare agents \u2014 powered by the NVIDIA AI platform \u2013 enabling super-low-latency conversational interactions. 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