AI Technologists | Kisaco Research

AI Technologists

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In this keynote, we'll explore the potential of Large Language Models (LLMs) in unlocking legacy systems and rethinking the connective tissue between legacy datasets and systems with new experiences. Traditionally, enterprises have relied on costly and time-consuming solutions to abstract legacy technology or modernize legacy systems. However, LLMs offer us the change to reimagine this enterprise architecture. By leveraging an LLMs ability to understand APIs, systems, and call tools, LLMs can generate the required structured output to interact with dozens of legacy systems. In this talk, we will discuss the ways LLMs can augment and replace enterprise gateways, reducing the need for custom software development and middleware solutions. We'll also examine the critical role of inference speed in enabling the deployment of LLMs in new and unique ways and explore the potential for LLMs to become a core tool in the enterprise.

C-Suite
Business Leader
AI Implementation
AI Technologists
Digital Change
Infrastructure Procurement

Author:

Austin Vance

CEO
Focused Labs

Austin Vance, the co-founder and CEO of Focused Labs, brings a dynamic blend of technical prowess and leadership to the forefront of the software industry. With a career spanning 24 years in software development, he has a rich history of leading high-performing engineering teams at organizations such as Pivotal and PayPal. This extensive experience has not only honed his expertise in the field but also deepened his commitment to delivering exceptional customer service through innovative software solutions. Under his guidance, Focused Labs excels in providing customers with custom software solutions that drive growth, enhance efficiency, and foster innovation, solidifying its position as a trusted partner in the tech ecosystem.

Austin Vance

CEO
Focused Labs

Austin Vance, the co-founder and CEO of Focused Labs, brings a dynamic blend of technical prowess and leadership to the forefront of the software industry. With a career spanning 24 years in software development, he has a rich history of leading high-performing engineering teams at organizations such as Pivotal and PayPal. This extensive experience has not only honed his expertise in the field but also deepened his commitment to delivering exceptional customer service through innovative software solutions. Under his guidance, Focused Labs excels in providing customers with custom software solutions that drive growth, enhance efficiency, and foster innovation, solidifying its position as a trusted partner in the tech ecosystem.

With GenAI (Generative AI) leading the way, in today’s rapidly evolving digital landscape, the integration of Conventional and Generative AI in enterprises and businesses offers a transformative potential that can redefine how they operate, innovate, and deliver value to their customers.

Being at the forefront of this paradigm disruption, Hexaware has been empowering industry leaders to make smarter choices, radically accelerate productivity, secure organizations, maximize data potential, and revolutionize customer experiences by strategically aligning GenAI capabilities with specific business goals through a structured approach driven by feasibility, relevance, and ROI.

Join us for an insightful fireside chat which aims to demystify the complexities of implementing GenAI and AI at scale, offering a roadmap for organizations looking to leverage these technologies for competitive advantage.

 

C-Suite
Business Leader
AI Implementation
AI Technologists
Digital Change
Infrastructure Procurement

Author:

Arun ‘Rak’ Ramchandran

President & Global Head – Consulting & GenAI Practice, Hi-Tech & Professional Services
Hexaware

Rak stands at the forefront of cutting-edge technology and business transformation as the President and Global Head of GenAI Consulting and Practice at Hexaware. Since joining the organization in 2017, Rak has been instrumental in leading the Hi-Tech, Platforms, and Professional Services (HTPS) vertical BU as well, driving significant growth and innovation.

Under Rak's visionary leadership, Hexaware launched its GenAI Consulting and Practice Unit, marking a pivotal shift towards becoming an AI-first company. As the head of consulting, Rak orchestrates Hexaware’s comprehensive enterprise architecture and technology consulting services, encompassing a broad spectrum of service lines and digital transformation capabilities tailored for diverse industry segments. Rak’s prior experience with Capgemini & Infosys provides him with the perspective and insights into successful technology service organizations, and his base in Silicon Valley gives him the network and vantage point in interpreting and getting ahead of emerging technology trends.

Arun ‘Rak’ Ramchandran

President & Global Head – Consulting & GenAI Practice, Hi-Tech & Professional Services
Hexaware

Rak stands at the forefront of cutting-edge technology and business transformation as the President and Global Head of GenAI Consulting and Practice at Hexaware. Since joining the organization in 2017, Rak has been instrumental in leading the Hi-Tech, Platforms, and Professional Services (HTPS) vertical BU as well, driving significant growth and innovation.

Under Rak's visionary leadership, Hexaware launched its GenAI Consulting and Practice Unit, marking a pivotal shift towards becoming an AI-first company. As the head of consulting, Rak orchestrates Hexaware’s comprehensive enterprise architecture and technology consulting services, encompassing a broad spectrum of service lines and digital transformation capabilities tailored for diverse industry segments. Rak’s prior experience with Capgemini & Infosys provides him with the perspective and insights into successful technology service organizations, and his base in Silicon Valley gives him the network and vantage point in interpreting and getting ahead of emerging technology trends.

Author:

Shivani Govil

Product Leader, Chief Product Officer, AI leader, Investor
Google

Shivani Govil

Product Leader, Chief Product Officer, AI leader, Investor
Google

In the ever-evolving generative AI landscape, GPUs have remained the dominant architecture for running large AI models. However, GPUs rely on brute force and are incredibly inefficient, not to mention increasingly unavailable. It’s clearly time for a change. It’s time for the comeback of the CPU.

You may be surprised to learn that running AI models on CPUs can bring about significant performance enhancements and incredible flexibility. By taking advantage of the rapidly evolving CPU architecture and mapping our unique neuroscience-based optimizations to it, Numenta is bringing this technological revolution to the generative AI field today. 

This presentation will explore:

  1. The benefits of embracing CPU-based AI, from reducing the cost and complexities associated with GPUs to increasing flexibility and scalability. 
  2. The latest advancements in Numenta’s neuroscience-based AI platform, NuPIC, the Numenta Platform for Intelligent Computing.
  3. Practical applications of CPU-based generative AI through a customer success story
C-Suite
AI Technologists
Business Leader
Digital Change
Infrastructure Procurement
AI Implementation

Author:

Subutai Ahmad

CEO
Numenta

Subutai is passionate about neuroscience, deep learning, and building intelligent systems. An accomplished technologist, he has been instrumental in driving Numenta’s research, technology and business since 2005. He previously served as VP Engineering at YesVideo where he helped grow the company from a three-person start-up to a leader in automated digital media authoring. In 1997, Subutai co-founded ePlanet Interactive which developed the IntelPlay Me2Cam, the first computer vision product developed for consumers. Subutai holds a B.S. in Computer Science from Cornell University, and a Ph.D in Computer Science from the University of Illinois at Urbana-Champaign.

Subutai Ahmad

CEO
Numenta

Subutai is passionate about neuroscience, deep learning, and building intelligent systems. An accomplished technologist, he has been instrumental in driving Numenta’s research, technology and business since 2005. He previously served as VP Engineering at YesVideo where he helped grow the company from a three-person start-up to a leader in automated digital media authoring. In 1997, Subutai co-founded ePlanet Interactive which developed the IntelPlay Me2Cam, the first computer vision product developed for consumers. Subutai holds a B.S. in Computer Science from Cornell University, and a Ph.D in Computer Science from the University of Illinois at Urbana-Champaign.

Artificial intelligence (AI) stands at the forefront of enterprise innovation, offering unparalleled opportunities for growth, efficiency, and competitive advantage. However, the journey toward AI optimization is fraught with challenges, from legacy infrastructures to strategic alignment and workforce readiness. This keynote speech will navigate the complex landscape of AI integration, presenting a comprehensive roadmap tailored for Fortune 500 companies ready to harness the power of generative AI.

Technologist Deep-Dive (Gen AI & Data Science) Track
Retail
Business Leader
Data Science
AI Technologists

Author:

Dr. Astha Purohit

Director - Product (Tech) Ops
Walmart

Astha is a global leader in Retail with extensive expertise in artificial intelligence and generative AI. She has advised Fortune 500 companies and senior C-suite leaders on driving innovation and growth in Retail to deliver amazing customer experiences.

She is a former McKinsey consultant and an MBA graduate from MIT Sloan. Currently she is a Director at Walmart spearheading AI and ML model development and deployment across the Walmart product eco-system.

Dr. Astha Purohit

Director - Product (Tech) Ops
Walmart

Astha is a global leader in Retail with extensive expertise in artificial intelligence and generative AI. She has advised Fortune 500 companies and senior C-suite leaders on driving innovation and growth in Retail to deliver amazing customer experiences.

She is a former McKinsey consultant and an MBA graduate from MIT Sloan. Currently she is a Director at Walmart spearheading AI and ML model development and deployment across the Walmart product eco-system.

Technologist Deep-Dive (Gen AI & Data Science) Track
AI Safety
AI Technologists
Data Science
C-Suite
Moderator

Author:

Sarah Luger

Co-Chair, Data Sets Working Group
MLCommons

Sarah Luger host of the AI Artifacts podcast (www.aiartifacts.net) and the Co-Chair of the Data Sets Working Group for AI benchmarking organization, MLCommons. Data Sets Working Group continues the research initiated with the Rigorous Evaluation of AI Systems workshop series at AAAI Human Computation and AAAI conferences. The goal is to develop robust schemas and infrastructure supporting the Open Source hosting of benchmark evaluation data sets. The group aims to provide free storage for researchers who have human-generated data (spoken word data is the current focus) of generally high quality.

Sarah is a Contributing Member of the MLCommons AI Safety Stakeholder Engagement, Benchmarks and Tests, and Platform Technology working groups. This nonprofit engineering consortium guides the ML industry by developing benchmarks, public datasets, and best practice.

Her current AI Safety work focuses on building LLM Safety Test Sets, Creating Scoring System, and Running Benchmarks. Sarah is leading the subsequent work automating the translation of safety test prompts into in low-resource languages.

Sarah Luger

Co-Chair, Data Sets Working Group
MLCommons

Sarah Luger host of the AI Artifacts podcast (www.aiartifacts.net) and the Co-Chair of the Data Sets Working Group for AI benchmarking organization, MLCommons. Data Sets Working Group continues the research initiated with the Rigorous Evaluation of AI Systems workshop series at AAAI Human Computation and AAAI conferences. The goal is to develop robust schemas and infrastructure supporting the Open Source hosting of benchmark evaluation data sets. The group aims to provide free storage for researchers who have human-generated data (spoken word data is the current focus) of generally high quality.

Sarah is a Contributing Member of the MLCommons AI Safety Stakeholder Engagement, Benchmarks and Tests, and Platform Technology working groups. This nonprofit engineering consortium guides the ML industry by developing benchmarks, public datasets, and best practice.

Her current AI Safety work focuses on building LLM Safety Test Sets, Creating Scoring System, and Running Benchmarks. Sarah is leading the subsequent work automating the translation of safety test prompts into in low-resource languages.

Panelists

Author:

Jonathan Bennion

AI Engineer
Rackspace

Jonathan Bennion

AI Engineer
Rackspace

Author:

Sergey Davidovich

Co-Founder & Chairman
SparkBeyond

Sergey is an entrepreneur, technological visionary and machine intelligence enthusiast, who continually strives to bridge the gap between human and machine reasoning and interaction. He’s passionate about computational knowledge representation, acquisition, storage, reasoning, and processing.
 

Sergey has served in a range of executive technological positions in disruptive startup companies. Prior to co-founding SparkBeyond, Sergey served as GM and SVP of R&D for NewBrandAnalytics, a social business intelligence pioneer. He’s also served as VP R&D of SemantiNet, a semantic reasoning engine, and co-founded Delver, a social search engine that was acquired by Sears, where he served as CTO. Prior to founding Delver, Sergey was the architect of a large-scale award-winning predictive maintenance system.

Sergey Davidovich

Co-Founder & Chairman
SparkBeyond

Sergey is an entrepreneur, technological visionary and machine intelligence enthusiast, who continually strives to bridge the gap between human and machine reasoning and interaction. He’s passionate about computational knowledge representation, acquisition, storage, reasoning, and processing.
 

Sergey has served in a range of executive technological positions in disruptive startup companies. Prior to co-founding SparkBeyond, Sergey served as GM and SVP of R&D for NewBrandAnalytics, a social business intelligence pioneer. He’s also served as VP R&D of SemantiNet, a semantic reasoning engine, and co-founded Delver, a social search engine that was acquired by Sears, where he served as CTO. Prior to founding Delver, Sergey was the architect of a large-scale award-winning predictive maintenance system.

Author:

Vipul Raheja

Applied Research Scientist
Grammarly

Vipul Raheja is an Applied Research Scientist at Grammarly. He works on developing robust and scalable approaches centered around improving the quality of written communication, leveraging Natural Language Processing and Deep Learning. His research interests lie at the intersection of large language models and controllable text generation. He has published several papers at top-tier Machine Learning and Natural Language Processing conferences and is also an organizer of the workshops on Intelligent and Interactive Writing Assistants held at ACL and CHI conferences. He obtained an MS in Computer Science from Columbia University.

Vipul Raheja

Applied Research Scientist
Grammarly

Vipul Raheja is an Applied Research Scientist at Grammarly. He works on developing robust and scalable approaches centered around improving the quality of written communication, leveraging Natural Language Processing and Deep Learning. His research interests lie at the intersection of large language models and controllable text generation. He has published several papers at top-tier Machine Learning and Natural Language Processing conferences and is also an organizer of the workshops on Intelligent and Interactive Writing Assistants held at ACL and CHI conferences. He obtained an MS in Computer Science from Columbia University.

Technologist Deep-Dive (Gen AI & Data Science) Track
AI Technologists
Data Science
Digital Infrastructure
MLOps

Author:

Aayush Mudgal

Senior Machine Learning Engineer
Pinterest

Aayush Mudgal is a Senior Machine Learning Engineer at Pinterest, currently leading the efforts around Privacy Aware Conversion Modeling. He has a successful track record of starting and executing 0 to 1 projects, including conversion optimization, video ads ranking, landing page optimization, and evolving the ads ranking from GBDT to DNN stack. His expertise is in large-scale recommendation systems, personalization, and ads marketplaces. Before entering the industry, Aayush conducted research on intelligent tutoring systems, developing data-driven feedback to aid students in learning computer programming. He holds a Master's in Computer Science from Columbia University and a Bachelor of Technology in Computer Science from Indian Institute of Technology Kanpur. 

Aayush Mudgal

Senior Machine Learning Engineer
Pinterest

Aayush Mudgal is a Senior Machine Learning Engineer at Pinterest, currently leading the efforts around Privacy Aware Conversion Modeling. He has a successful track record of starting and executing 0 to 1 projects, including conversion optimization, video ads ranking, landing page optimization, and evolving the ads ranking from GBDT to DNN stack. His expertise is in large-scale recommendation systems, personalization, and ads marketplaces. Before entering the industry, Aayush conducted research on intelligent tutoring systems, developing data-driven feedback to aid students in learning computer programming. He holds a Master's in Computer Science from Columbia University and a Bachelor of Technology in Computer Science from Indian Institute of Technology Kanpur. 

Technologist Deep-Dive (Gen AI & Data Science) Track
AI Technologists
Data Science
Hallucination Prevention
AI Optimizations

Author:

Dat Ngo

Machine Learning Engineer
Arize AI

Dat Ngo is a data scientist and machine learning engineer who works directly with Arize AI users to evaluate and troubleshoot generative AI applications. Before Arize, Ngo led strategic data science efforts at PointPredictive, alliantgroup, and Wood Mackenzie. Ngo has a Master of Science in Applied Statistics from Texas A&M University.

Dat Ngo

Machine Learning Engineer
Arize AI

Dat Ngo is a data scientist and machine learning engineer who works directly with Arize AI users to evaluate and troubleshoot generative AI applications. Before Arize, Ngo led strategic data science efforts at PointPredictive, alliantgroup, and Wood Mackenzie. Ngo has a Master of Science in Applied Statistics from Texas A&M University.

In an era where artificial intelligence is not just an asset but a necessity, understanding the intricacies of Large Language Models (LLMs) has become paramount for enterprises. This session, 'Understanding and Mitigating Hallucinations in Large Language Models', offers a deep dive into the phenomenon of LLM hallucinations – a critical challenge in the deployment of AI technologies in business environments.


We will explore the mechanics behind LLM hallucinations, shedding light on how these AI models, despite their sophistication, can generate inaccurate or misleading information. From the subtlety of input-conflicting hallucinations to the complexity of context and fact-conflicting errors, we will dissect various types of hallucinations with real-world examples, including notable instances from prominent LLMs.

This talk will not only focus on the identification and detection of such hallucinations but will also present effective strategies for mitigation. We will discuss the role of data quality, model fine-tuning, and advanced techniques like Reinforcement Learning with Human Feedback (RLHF) in reducing the risks of inaccuracies. Furthermore, the session will highlight the importance of balancing the creative potential of LLM hallucinations with the need for factual accuracy, especially in high-stakes business decisions.

Attendees will leave with a comprehensive understanding of the challenges and opportunities presented by LLM hallucinations. This knowledge is crucial for enterprises looking to leverage AI responsibly and effectively, ensuring that their use of these powerful tools aligns with the highest standards of accuracy and reliability in the business world.

Technologist Deep-Dive (Gen AI & Data Science) Track
Retail
Business Leader
Data Science
AI Technologists

Author:

Ved Upadhyay

Senior Data Scientist
Walmart Global Tech

Ved Upadhyay is a seasoned professional in the realm of data science and artificial intelligence (AI). With a focus on addressing complex challenges in data science on an enterprise scale, he boasts over 7 years of hands-on experience in crafting AI-powered solutions for businesses. Ved’s expertise spans diverse industries, including retail, e-commerce, pharmaceuticals, agrotech, and socio-tech, where he has successfully productized multiple machine learning pipelines. Currently serving as a Senior Data Scientist at Walmart, Ved spearheads multiple data science initiatives centered around customer propensity and responsible AI solutions at enterprise scale. Prior to venturing into the industry, Ved earned his master’s degree in Data Science from the University of Illinois at Urbana-Champaign and contributed as a Deep Learning researcher at IIIT Hyderabad. His research contributions are reflected in multiple publications in the field of applied AI. 

Ved Upadhyay

Senior Data Scientist
Walmart Global Tech

Ved Upadhyay is a seasoned professional in the realm of data science and artificial intelligence (AI). With a focus on addressing complex challenges in data science on an enterprise scale, he boasts over 7 years of hands-on experience in crafting AI-powered solutions for businesses. Ved’s expertise spans diverse industries, including retail, e-commerce, pharmaceuticals, agrotech, and socio-tech, where he has successfully productized multiple machine learning pipelines. Currently serving as a Senior Data Scientist at Walmart, Ved spearheads multiple data science initiatives centered around customer propensity and responsible AI solutions at enterprise scale. Prior to venturing into the industry, Ved earned his master’s degree in Data Science from the University of Illinois at Urbana-Champaign and contributed as a Deep Learning researcher at IIIT Hyderabad. His research contributions are reflected in multiple publications in the field of applied AI. 

This presentation explores the integration of generative AI in healthcare and pharmacology, highlighting advancements in prompt engineering and its impact on decision-making. The session will examine the complexities and variability of AI responses and the difficulties in establishing a reliable ground truth, emphasizing the need for structured and reproducible outputs to support clinical and business processes efficiently.

Application & Gen AI Integration (Business Leaders) Track
Healthcare
Pharma
Data Science
AI Technologists

Author:

Zoran Krunic

Principal Product Manager
Amgen

Since joining Amgen R&D in 2018, Zoran Krunic has been at the forefront of applying Machine Learning to enhance patient outcomes and streamline clinical trial enrollment processes, utilizing comprehensive Electronic Health Records and clinical datasets. His pioneering work in the Quantum Machine Learning space, in collaboration with IBM's Quantum team, has been instrumental in integrating machine learning with quantum computing through IBM’s Qiskit platform.

Prior to his tenure at Amgen, Zoran developed Machine Learning algorithms at Optum to predict hardware and software failures within complex enterprise architectures. He has a strong background in data engineering and systems development, having contributed significantly to large-scale projects at renowned organizations such as Capital Group and ARCO Petroleum.

In his current full and part-time endeavors, Zoran is leading the efforts in embracing generative AI technologies, with a particular focus on OpenAI's GPT and Anthropic's Claude-2 models. His work is focused on prompt engineering and its application to code generation, advanced document analysis, and process management, with a commitment to ethical AI practices and data privacy.

A recognized voice in quantum computing circles, Zoran is a regular presenter at industry conferences and has served on numerous panels discussing the integration of quantum computing and generative AI within the Health Sciences sector.

With a Master of Science in Electrical Engineering & Computer Science, Zoran continues to explore and contribute to the evolving relationship between quantum computing and artificial intelligence, fostering groundbreaking advancements in healthcare technology.

Zoran Krunic

Principal Product Manager
Amgen

Since joining Amgen R&D in 2018, Zoran Krunic has been at the forefront of applying Machine Learning to enhance patient outcomes and streamline clinical trial enrollment processes, utilizing comprehensive Electronic Health Records and clinical datasets. His pioneering work in the Quantum Machine Learning space, in collaboration with IBM's Quantum team, has been instrumental in integrating machine learning with quantum computing through IBM’s Qiskit platform.

Prior to his tenure at Amgen, Zoran developed Machine Learning algorithms at Optum to predict hardware and software failures within complex enterprise architectures. He has a strong background in data engineering and systems development, having contributed significantly to large-scale projects at renowned organizations such as Capital Group and ARCO Petroleum.

In his current full and part-time endeavors, Zoran is leading the efforts in embracing generative AI technologies, with a particular focus on OpenAI's GPT and Anthropic's Claude-2 models. His work is focused on prompt engineering and its application to code generation, advanced document analysis, and process management, with a commitment to ethical AI practices and data privacy.

A recognized voice in quantum computing circles, Zoran is a regular presenter at industry conferences and has served on numerous panels discussing the integration of quantum computing and generative AI within the Health Sciences sector.

With a Master of Science in Electrical Engineering & Computer Science, Zoran continues to explore and contribute to the evolving relationship between quantum computing and artificial intelligence, fostering groundbreaking advancements in healthcare technology.