Speakers | Kisaco Research

Speakers

Enterprise Generative AI Summit
23-24 January, 2024
Florida, USA
  • Author:

    Donald Thompson

    Distinguished Engineer
    LinkedIn

    Donald is currently a Distinguished Engineer at LinkedIn, primarily overseeing the company's generative AI strategy, architecture, and technology. He has more than 35 years of hands-on experience as a technical architect and CTO, with an extensive background in designing and delivering innovative software and services on a large scale. In 2013, Donald co-founded Maana, which pioneered computational knowledge graphs and visual no-code/low-code authoring environments to address complex AI-based digital transformation challenges in Fortune 50 companies. During his 15 years at Microsoft, Donald started the Knowledge and Reasoning group within Microsoft's Bing division, where he innovated "Satori", an internet-scale knowledge graph constructed automatically from the web crawl. He co-founded a semantic computing incubation funded directly by Bill Gates, portions of which shipped as the SQL Server Semantic Engine. Additionally, he created Microsoft's first internet display ad delivery system and led numerous AI/ML initiatives in Microsoft Research across embedded systems, robotics, wearable computing, and privacy-preserving personal data services.

    Donald Thompson

    Distinguished Engineer
    LinkedIn

    Donald is currently a Distinguished Engineer at LinkedIn, primarily overseeing the company's generative AI strategy, architecture, and technology. He has more than 35 years of hands-on experience as a technical architect and CTO, with an extensive background in designing and delivering innovative software and services on a large scale. In 2013, Donald co-founded Maana, which pioneered computational knowledge graphs and visual no-code/low-code authoring environments to address complex AI-based digital transformation challenges in Fortune 50 companies. During his 15 years at Microsoft, Donald started the Knowledge and Reasoning group within Microsoft's Bing division, where he innovated "Satori", an internet-scale knowledge graph constructed automatically from the web crawl. He co-founded a semantic computing incubation funded directly by Bill Gates, portions of which shipped as the SQL Server Semantic Engine. Additionally, he created Microsoft's first internet display ad delivery system and led numerous AI/ML initiatives in Microsoft Research across embedded systems, robotics, wearable computing, and privacy-preserving personal data services.

  • Author:

    Sol Rashidi

    Former CDO/CAO of Estee Lauder, Merck Pharmaceuticals, Sony Music, and RCCL
    Estée Lauder

    Sol Rashidi

    Former CDO/CAO of Estee Lauder, Merck Pharmaceuticals, Sony Music, and RCCL
    Estée Lauder
  • Author:

    Donna Schut

    Head of Technical Solutions Management, Generative AI & Large Scale ML
    Google Cloud

    Donna Schut

    Head of Technical Solutions Management, Generative AI & Large Scale ML
    Google Cloud
  • Author:

    Shreesha Jagadeesh

    Associate Director of Applied Machine Learning
    BestBuy

    Shreesha Jagadeesh is an Associate Director of Machine Learning at Best Buy. He leads a multi-national team of ML Scientists and Engineers building models that power the online customer journey through personalized recommendations and ads. He leverages his expertise in Multi-Stage Recommender Systems, LLMs, Embeddings, Multi-Arm Bandits, Offline Policy Evaluation and A/B testing to help digital teams to personalize the experiences deepening customer relationship & driving ecommerce revenue for Best Buy.

     

    Prior to Best Buy, he has worked in a variety of corporate and consulting roles including at Amazon, EY and Cisco building Data Science models in a diverse set of domains spanning HR, Tax, Legal and Supply Chain. Outside of his day job, he advises early-stage startup, reviews pre-publication books/courses and has also published 2 online Data Science courses. He lives in Boston with his wife and enjoys travelling to exotic locations with an Antarctica expedition coming up in December 2024.

    Shreesha Jagadeesh

    Associate Director of Applied Machine Learning
    BestBuy

    Shreesha Jagadeesh is an Associate Director of Machine Learning at Best Buy. He leads a multi-national team of ML Scientists and Engineers building models that power the online customer journey through personalized recommendations and ads. He leverages his expertise in Multi-Stage Recommender Systems, LLMs, Embeddings, Multi-Arm Bandits, Offline Policy Evaluation and A/B testing to help digital teams to personalize the experiences deepening customer relationship & driving ecommerce revenue for Best Buy.

     

    Prior to Best Buy, he has worked in a variety of corporate and consulting roles including at Amazon, EY and Cisco building Data Science models in a diverse set of domains spanning HR, Tax, Legal and Supply Chain. Outside of his day job, he advises early-stage startup, reviews pre-publication books/courses and has also published 2 online Data Science courses. He lives in Boston with his wife and enjoys travelling to exotic locations with an Antarctica expedition coming up in December 2024.

  • Author:

    Stavros Zervoudakis

    Vice President of Artificial Intelligence
    Mutual Financial

    Stavros Zervoudakis

    Vice President of Artificial Intelligence
    Mutual Financial
  • Author:

    Sherry Marcus

    Director, Applied Science, Generative AI Services
    AWS

    Sherry Marcus

    Director, Applied Science, Generative AI Services
    AWS
  • Author:

    Hemant Jain

    Senior Software Engineer, Inference
    Cohere

    Hemant works on efficiently fine-tuning and serving LLMs as a part of the Platform team at Cohere. Prior to this, he spent 3 years at NVIDIA developing Triton Inference Server, an open-source solution used to deploy machine learning models into production. He has a Masters in Data Science from the University of Washington.

    Hemant Jain

    Senior Software Engineer, Inference
    Cohere

    Hemant works on efficiently fine-tuning and serving LLMs as a part of the Platform team at Cohere. Prior to this, he spent 3 years at NVIDIA developing Triton Inference Server, an open-source solution used to deploy machine learning models into production. He has a Masters in Data Science from the University of Washington.

  • Author:

    Melissa Harup

    SVP and Chief Counsel
    Mondelez International

    Melissa Harup

    SVP and Chief Counsel
    Mondelez International
  • Author:

    Jack Qiao

    Senior Manager Data Science & AI
    Lowe's Companies Inc.

    Jack Qiao

    Senior Manager Data Science & AI
    Lowe's Companies Inc.
  • Author:

    Julius Lo

    Director
    NEUCHIPS

    Julius is a Director of NEUCHIPS, an AI ASIC startup for recommendation inferencing. Julius leads NEUCHIPS software team, covering server integration to on-board firmware. Before NEUCHIPS, Julius worked for Global Unchip Corp., hTC and Mediatek, devoting himself to RTL circuit design, Linux device drivers and performance optimization with power balancing in 20+ chips. He is an author of 6+ international patents in the areas of scheduling and data compression.

    Julius Lo

    Director
    NEUCHIPS

    Julius is a Director of NEUCHIPS, an AI ASIC startup for recommendation inferencing. Julius leads NEUCHIPS software team, covering server integration to on-board firmware. Before NEUCHIPS, Julius worked for Global Unchip Corp., hTC and Mediatek, devoting himself to RTL circuit design, Linux device drivers and performance optimization with power balancing in 20+ chips. He is an author of 6+ international patents in the areas of scheduling and data compression.

  • Author:

    Peter Clark

    Head of Computational Science & Engineering
    Janssen R&D

    Peter Clark, PhD is the Head of Computational Science & Engineering within the Therapeutics Discovery (TD) organization of Janssen R&D, where he leads a dynamic, interdisciplinary team of scientists focused on accelerating the research and development of protein based therapeutics through the design and implementation of disruptive computational approaches and platforms. Prior to joining Johnson & Johnson, Peter served as the Director of Bioinformatics at the University of Pennsylvania, Perelman School of Medicine, where he worked closely with academic and commercial collaborators on the design, optimization, and evaluation of various gene therapy platform technologies from early research and development through commercially partnered IND enabling clinical studies. Peter is also a clinically trained molecular pathologist (The Children’s Hospital of Philadelphia) with extensive experience in the design, validation, and implementation of diagnostic and prognostic next generation sequencing (NGS) assays within a clinical, CAP/CLIA certified laboratory setting. During his clinical molecular pathology fellowship at CHOP, Peter co-developed and commercialized the first to market, high resolution, next generation sequencing based HLA genotyping assay and was subsequently awarded the Scholar of the Year award by the American Society for Histocompatibility and Immunogenetics (ASHI) in 2015 for his contributions to the field of solid organ and bone marrow transplantation. Peter earned his B.Sc. and Ph.D. from Drexel University, School of Biomedical Engineering prior to completing a postdoctoral fellowship at The Center for Computational Medicine at Thomas Jefferson University.  Peter’s diverse expertise in computational science, engineering, clinical molecular genetics, computational biology, and translational research has led to the publication of over 30 peer-reviewed scientific publications as well as two book chapters, several issued patents and three biotechnology spin-off companies.

    Peter Clark

    Head of Computational Science & Engineering
    Janssen R&D

    Peter Clark, PhD is the Head of Computational Science & Engineering within the Therapeutics Discovery (TD) organization of Janssen R&D, where he leads a dynamic, interdisciplinary team of scientists focused on accelerating the research and development of protein based therapeutics through the design and implementation of disruptive computational approaches and platforms. Prior to joining Johnson & Johnson, Peter served as the Director of Bioinformatics at the University of Pennsylvania, Perelman School of Medicine, where he worked closely with academic and commercial collaborators on the design, optimization, and evaluation of various gene therapy platform technologies from early research and development through commercially partnered IND enabling clinical studies. Peter is also a clinically trained molecular pathologist (The Children’s Hospital of Philadelphia) with extensive experience in the design, validation, and implementation of diagnostic and prognostic next generation sequencing (NGS) assays within a clinical, CAP/CLIA certified laboratory setting. During his clinical molecular pathology fellowship at CHOP, Peter co-developed and commercialized the first to market, high resolution, next generation sequencing based HLA genotyping assay and was subsequently awarded the Scholar of the Year award by the American Society for Histocompatibility and Immunogenetics (ASHI) in 2015 for his contributions to the field of solid organ and bone marrow transplantation. Peter earned his B.Sc. and Ph.D. from Drexel University, School of Biomedical Engineering prior to completing a postdoctoral fellowship at The Center for Computational Medicine at Thomas Jefferson University.  Peter’s diverse expertise in computational science, engineering, clinical molecular genetics, computational biology, and translational research has led to the publication of over 30 peer-reviewed scientific publications as well as two book chapters, several issued patents and three biotechnology spin-off companies.

  • Author:

    Kevin Tsai

    Head of Technical Solution Architecture, Generative AI & ML Infrastructure
    Google Cloud

    Kevin currently leads a team of Solution Architects with focus on Generative AI and large-scale, accelerated infrastructure. Kevin has also led teams in Data Analytics, Data Management, and ML at Google, and has more than 20 years of experience in the technology industry

    Kevin Tsai

    Head of Technical Solution Architecture, Generative AI & ML Infrastructure
    Google Cloud

    Kevin currently leads a team of Solution Architects with focus on Generative AI and large-scale, accelerated infrastructure. Kevin has also led teams in Data Analytics, Data Management, and ML at Google, and has more than 20 years of experience in the technology industry

  • Author:

    Marc Paradis

    Vice President of Data Strategy
    Northwell Holdings

    Marc Paradis

    Vice President of Data Strategy
    Northwell Holdings
  • Author:

    Linus Liang

    Founder and Managing Partner
    Kyber Knight Capital

    Linus is the Founder and Managing Partner of Kyber Knight Capital. He brings over twenty-five years of experience in venture capital and entrepreneurship to his leadership role. Before starting Kyber Knight Capital, Linus spent a decade at Signia Ventures, where he continues as a Partner. His entrepreneurial pursuits include co-founding Embrace, the company behind the world’s most affordable infant incubator. To date, Embrace has impacted the lives of over 500,000 infants worldwide in over a dozen countries.

    Before Embrace, Linus founded several software companies focusing on mobile technology and social networking. He is well known for joining Zynga’s founding team, following the acquisition of his start-up, where he served as the tenth employee.

    Linus’s career also encompasses roles at major corporations, including Program Manager at Microsoft, database researcher at IBM, and a member of the investment team at Andreessen Horowitz.

    Linus is a holder of a B.A. in Computer Science from U.C. Berkeley, as well as an M.S. in Computer Science, an M.A. in Education, and an MBA from Stanford University. He is a co-instructor for Stanford’s Frontier Technologies course and has previously taught a Big Data class at Stanford’s Business School.

    Linus Liang

    Founder and Managing Partner
    Kyber Knight Capital

    Linus is the Founder and Managing Partner of Kyber Knight Capital. He brings over twenty-five years of experience in venture capital and entrepreneurship to his leadership role. Before starting Kyber Knight Capital, Linus spent a decade at Signia Ventures, where he continues as a Partner. His entrepreneurial pursuits include co-founding Embrace, the company behind the world’s most affordable infant incubator. To date, Embrace has impacted the lives of over 500,000 infants worldwide in over a dozen countries.

    Before Embrace, Linus founded several software companies focusing on mobile technology and social networking. He is well known for joining Zynga’s founding team, following the acquisition of his start-up, where he served as the tenth employee.

    Linus’s career also encompasses roles at major corporations, including Program Manager at Microsoft, database researcher at IBM, and a member of the investment team at Andreessen Horowitz.

    Linus is a holder of a B.A. in Computer Science from U.C. Berkeley, as well as an M.S. in Computer Science, an M.A. in Education, and an MBA from Stanford University. He is a co-instructor for Stanford’s Frontier Technologies course and has previously taught a Big Data class at Stanford’s Business School.

  • Author:

    Jeff Winter

    Senior Director of Industry Strategy, Manufacturing
    Hitachi Solutions America

    Jeff Winter

    Senior Director of Industry Strategy, Manufacturing
    Hitachi Solutions America
  • Author:

    Viswanatha Allugunti

    UX UI Mobility Manager
    Johnson and Johnson

    Viswanatha Allugunti

    UX UI Mobility Manager
    Johnson and Johnson
  • Author:

    Gautam Hotti

    Director of Generative AI
    Novartis

    Highly experienced and visionary Director and Head of Enterprise Architecture with over 20 years of experience in leading cross-functional teams to design, build and implement complex software systems and platforms. Proven track record of developing architecture services and processes, rolling out governance best practices, leading distributed systems architecture and development. Currently driving adoption of Generative AI in Novartis.

    Gautam Hotti

    Director of Generative AI
    Novartis

    Highly experienced and visionary Director and Head of Enterprise Architecture with over 20 years of experience in leading cross-functional teams to design, build and implement complex software systems and platforms. Proven track record of developing architecture services and processes, rolling out governance best practices, leading distributed systems architecture and development. Currently driving adoption of Generative AI in Novartis.

  • Author:

    Alon Bochman

    Head of AI
    Factset

    Alon Bochman

    Head of AI
    Factset
  • Author:

    Rashmi Gopinath

    General Partner
    B Capital

    Rashmi Gopinath is a General Partner at B Capital Group where she leads the fund’s enterprise software practice in cloud infrastructure, cybersecurity, devops, and AI/ML sectors. She brings over two decades of experience investing and operating in cutting-edge enterprise technologies. She led B Capital’s investments in over 24 companies such as DataRobot, FalconX, Clari, Phenom People, Synack, Innovaccer, Labelbox, Fabric, 6Sense, Highspot, Pendo, Starburst, OwnBackup, Figment, Perimeter81, Zesty, among others.

    Rashmi was previously a Managing Director at M12, Microsoft’s venture fund, where she led investments globally in enterprise software and sat on several boards including Synack, Innovaccer, Contrast Security, Frame, UnravelData, Incorta, among others.

    Prior to M12, Rashmi was an Investment Director with Intel Capital where she was involved in the firm’s investments in startups including MongoDB (Nasdaq: MDB), ForeScout (Nasdaq: FSCT), Maginatics (acq. by EMC), BlueData (acq. by HPE), among others. Rashmi held operating roles at high-growth startups such as BlueData (acq. by HPE) and Couchbase (Nasdaq: BASE) where she led global business development, product and marketing roles. She began her career in engineering and product roles at Oracle and GE Healthcare. She earned an M.B.A. from Northwestern University, and a B.S. in Electrical Engineering from University of Mumbai in India.

    Rashmi Gopinath

    General Partner
    B Capital

    Rashmi Gopinath is a General Partner at B Capital Group where she leads the fund’s enterprise software practice in cloud infrastructure, cybersecurity, devops, and AI/ML sectors. She brings over two decades of experience investing and operating in cutting-edge enterprise technologies. She led B Capital’s investments in over 24 companies such as DataRobot, FalconX, Clari, Phenom People, Synack, Innovaccer, Labelbox, Fabric, 6Sense, Highspot, Pendo, Starburst, OwnBackup, Figment, Perimeter81, Zesty, among others.

    Rashmi was previously a Managing Director at M12, Microsoft’s venture fund, where she led investments globally in enterprise software and sat on several boards including Synack, Innovaccer, Contrast Security, Frame, UnravelData, Incorta, among others.

    Prior to M12, Rashmi was an Investment Director with Intel Capital where she was involved in the firm’s investments in startups including MongoDB (Nasdaq: MDB), ForeScout (Nasdaq: FSCT), Maginatics (acq. by EMC), BlueData (acq. by HPE), among others. Rashmi held operating roles at high-growth startups such as BlueData (acq. by HPE) and Couchbase (Nasdaq: BASE) where she led global business development, product and marketing roles. She began her career in engineering and product roles at Oracle and GE Healthcare. She earned an M.B.A. from Northwestern University, and a B.S. in Electrical Engineering from University of Mumbai in India.

  • Author:

    Daniel Wu

    Head of AI & ML, Commercial Banking
    JP Morgan Chase

    Daniel Wu is a technical leader who brings more than 20 years of expertise in software engineering, AI/ML, and high-impact team development. He is the Head of Commercial Banking AI and Machine Learning at JPMorgan Chase where he drives financial service transformation through AI innovation. His diverse professional background also includes building point of care expert systems for physicians to improve quality of care, co-founding an online personal finance marketplace, and building an online real estate brokerage platform.

    Daniel is passionate about the democratization of technology and the ethical use of AI - a philosophy he shares in the computer science and AI/ML education programs he has contributed to over the years.

    Daniel Wu

    Head of AI & ML, Commercial Banking
    JP Morgan Chase

    Daniel Wu is a technical leader who brings more than 20 years of expertise in software engineering, AI/ML, and high-impact team development. He is the Head of Commercial Banking AI and Machine Learning at JPMorgan Chase where he drives financial service transformation through AI innovation. His diverse professional background also includes building point of care expert systems for physicians to improve quality of care, co-founding an online personal finance marketplace, and building an online real estate brokerage platform.

    Daniel is passionate about the democratization of technology and the ethical use of AI - a philosophy he shares in the computer science and AI/ML education programs he has contributed to over the years.

  • Author:

    Das Dasgupta

    Former CDO
    Saatchi and Saatchi

    Former CDAIO, Saatchi & Saatchi; Adjunct Professor of Data Science & Operations (DSO) at USC Marshall School of Business.

    Dr. Das Dasgupta was most recently the Chief Data Officer at Saatchi & Saatchi (S&S), an advertising agency owned by the $11B Publicis Groupe. His prior leadership roles include Global SVP of Data Science and Digital Transformation at Viacom, L8 Director at Amazon with four L8 reports, and Partner at McKinsey and EY.

    Das is an expert in utilizing data and artificial intelligence to grow revenues and cut business costs. He structures this through three lenses - product leadership, operational excellence, and customer intimacy. This includes building top-tier data strategy teams and systems with the right AI and machine learning technologies so that companies can make informed data-driven decisions related to marketing & advertising, operations/supply chain, and back-office automation with proven ROI.

    A few examples include building an AI/ML powered system for S&S that helped increase return on ad spend for their clients by an average of 40%, automating the order-to-cash, procure-to-pay, and records-to-reports systems for Viacom’s back office (saving $30M over two years), and also developing Amazon’s process of taking a picture of a delivered package and sending it to the customer which significantly improved the customer experience and saved $100M+ in costs for Amazon. Across the companies Dr. Dasgupta has been involved with, his work has contributed to over $500M in cost savings and revenue growth.

     

    Das Dasgupta

    Former CDO
    Saatchi and Saatchi

    Former CDAIO, Saatchi & Saatchi; Adjunct Professor of Data Science & Operations (DSO) at USC Marshall School of Business.

    Dr. Das Dasgupta was most recently the Chief Data Officer at Saatchi & Saatchi (S&S), an advertising agency owned by the $11B Publicis Groupe. His prior leadership roles include Global SVP of Data Science and Digital Transformation at Viacom, L8 Director at Amazon with four L8 reports, and Partner at McKinsey and EY.

    Das is an expert in utilizing data and artificial intelligence to grow revenues and cut business costs. He structures this through three lenses - product leadership, operational excellence, and customer intimacy. This includes building top-tier data strategy teams and systems with the right AI and machine learning technologies so that companies can make informed data-driven decisions related to marketing & advertising, operations/supply chain, and back-office automation with proven ROI.

    A few examples include building an AI/ML powered system for S&S that helped increase return on ad spend for their clients by an average of 40%, automating the order-to-cash, procure-to-pay, and records-to-reports systems for Viacom’s back office (saving $30M over two years), and also developing Amazon’s process of taking a picture of a delivered package and sending it to the customer which significantly improved the customer experience and saved $100M+ in costs for Amazon. Across the companies Dr. Dasgupta has been involved with, his work has contributed to over $500M in cost savings and revenue growth.

     

  • Author:

    Jeff Herbst

    Founding Managing Partner
    GFT Ventures

    Jeff Herbst is Co-Founding Managing Partner of GFT Ventures, an early stage AI-focused venture capital fund with approximate $140M in assets under management.  He brings to the fund over three decades of venture capital, operational, business development and M&A experience. Prior to launching GFT, Jeff spent 20 years as NVIDIA's Vice President of Business Development where he built an ecosystem of accelerated computing applications spanning the domains of AI, Data Science, Autonomous Machines, and Graphics and Visualization. During his tenure at the company, among other things he created the Nvidia GPU Ventures program, overseeing more than 40 global investments and 20 acquisitions valued over $8B. He also led the Nvidia Inception global startup accelerator, now comprised of more than 10,000 AI, Data Science and High Performance computing companies.

    Jeff Herbst

    Founding Managing Partner
    GFT Ventures

    Jeff Herbst is Co-Founding Managing Partner of GFT Ventures, an early stage AI-focused venture capital fund with approximate $140M in assets under management.  He brings to the fund over three decades of venture capital, operational, business development and M&A experience. Prior to launching GFT, Jeff spent 20 years as NVIDIA's Vice President of Business Development where he built an ecosystem of accelerated computing applications spanning the domains of AI, Data Science, Autonomous Machines, and Graphics and Visualization. During his tenure at the company, among other things he created the Nvidia GPU Ventures program, overseeing more than 40 global investments and 20 acquisitions valued over $8B. He also led the Nvidia Inception global startup accelerator, now comprised of more than 10,000 AI, Data Science and High Performance computing companies.

  • Author:

    Mike Shirazi

    General Partner
    Pursuit Ventures

    Mike Shirazi

    General Partner
    Pursuit Ventures
  • Author:

    John Almasan

    Senior Managing Director, Head of AI & Emerging Tech
    TIAA

    Dr. John Almasan is an accomplished technology executive with over 20 years of experience leading global tech teams and building large-scale data, AI, and cloud platforms for prominent companies such as TIAA, McKinsey & Co., American Express, Bank of America, and Nationwide Insurance. With deep expertise in multi-cloud big data engineering, machine learning, and data science, John is a hands-on practitioner and passionate about enabling the acceleration of AI adoption.

    As an adjunct professor at various universities and a member of Arizona State University's Executive Board of Advisors, John is committed to preparing the next generation to meet the future's skillset needs and demands. He focuses on employee cross-training and actively engages in teaching and mentoring students in the field.

    John holds two master's degrees in Engineering and Statistics, a Doctor of Business Administration, and has over 20+ patents credited to his name. He has received several awards throughout his career for his contributions to the technology industry.

    John Almasan

    Senior Managing Director, Head of AI & Emerging Tech
    TIAA

    Dr. John Almasan is an accomplished technology executive with over 20 years of experience leading global tech teams and building large-scale data, AI, and cloud platforms for prominent companies such as TIAA, McKinsey & Co., American Express, Bank of America, and Nationwide Insurance. With deep expertise in multi-cloud big data engineering, machine learning, and data science, John is a hands-on practitioner and passionate about enabling the acceleration of AI adoption.

    As an adjunct professor at various universities and a member of Arizona State University's Executive Board of Advisors, John is committed to preparing the next generation to meet the future's skillset needs and demands. He focuses on employee cross-training and actively engages in teaching and mentoring students in the field.

    John holds two master's degrees in Engineering and Statistics, a Doctor of Business Administration, and has over 20+ patents credited to his name. He has received several awards throughout his career for his contributions to the technology industry.

  • Author:

    Nick Nystrom

    Chief Technology Officer
    Peptilogics

    Nick Nystrom

    Chief Technology Officer
    Peptilogics
  • Author:

    Jürgen Weichenberger

    Head of AI - New Value Streams
    Schneider Electric

    Jürgen Weichenberger

    Head of AI - New Value Streams
    Schneider Electric
  • Author:

    Jon Bennion

    Machine Learning Engineer and LLMOps
    FOX

    Jon Bennion

    Machine Learning Engineer and LLMOps
    FOX
  • Author:

    Aayush Mudgal

    Senior Machine Learning Engineer
    Pinterest

    Aayush Mudgal

    Senior Machine Learning Engineer
    Pinterest

Other events you might be interested in:

Efficient Generative AI Summit