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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.

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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.

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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.

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.

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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.

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.

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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
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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.

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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.

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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.

In today's dynamic financial landscape, the ability to leverage cutting-edge technologies is paramount for banks seeking to thrive and excel. This presentation delves into the transformative potential of artificial intelligence (AI) and provides a comprehensive roadmap to harness its power to revolutionize banking operations and customer experiences:

  1. Discover the essential considerations for responsibly building classical AI and Generative AI models in the financial sector
  2. Uncover the common pitfalls to avoid, preventing project failures and ensuring successful AI implementation
  3. Understand the prerequisites for crafting an AI strategy tailored to multi organization and company's unique needs
  4. Learn how to craft a step-by-step AI Strategy for transforming banking operations and customer experiences
  5. Reap the transformative power of AI capabilities and position cross-functional organizations for success in an evolving financial landscape.
Application & Gen AI Integration (Business Leaders) Track
Business Leader
AI Implementation
C-Suite
Finance
Banking
BFSI

Author:

Pratik Gautam

Lead Product Manager and VP
Citigroup

Pratik is a lead Product Manager and VP at Citigroup. He is an accomplished product leader with 15 years of experience in digital, advanced analytics, automation, and artificial intelligence, with a series of successes in innovation transformations. He has diverse experience in AI within the customer support domain, including call record indexing, document management, RPA automation, and chatbots for global banks such as JPMorgan Chase and Citigroup. Pratik has also applied AI technology such as computer vision, NLP, and OCR for middle and back-office functions and is currently exploring LLM innovations with prompt engineering, AI workflows, and chatbots, leveraging the latest generative AI-based innovations for Citigroup. 

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Pratik Gautam

Lead Product Manager and VP
Citigroup

Pratik is a lead Product Manager and VP at Citigroup. He is an accomplished product leader with 15 years of experience in digital, advanced analytics, automation, and artificial intelligence, with a series of successes in innovation transformations. He has diverse experience in AI within the customer support domain, including call record indexing, document management, RPA automation, and chatbots for global banks such as JPMorgan Chase and Citigroup. Pratik has also applied AI technology such as computer vision, NLP, and OCR for middle and back-office functions and is currently exploring LLM innovations with prompt engineering, AI workflows, and chatbots, leveraging the latest generative AI-based innovations for Citigroup. 

At the turn of the millennium, in their seminal book 'Discipline of Market Leaders, the authors Michael Treacy and Fred Wiersema posited that Excellence could be grouped into three dimensions - product leadership, operational excellence, and customer intimacy. Two decades later, we revisit these dimensions in light of the perfect storm of AI and present use cases that help companies transform through a step-change in their market leadership by thoughtfully and deliberately implementing AI in their functions to gain a step-change in performance improvement along with revenue, costs, and overall profitability. 

Application & Gen AI Integration (Business Leaders) Track
Advertising
Business Leader
C-Suite
Customer Experience

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.

 

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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.

 

Application & Gen AI Integration (Business Leaders) Track
Data Privacy
Ethical AI
C-Suite
Healthcare
Finance
Manufacturing
Moderator

Author:

Hira Dangol

Vice President, AI/ML & Automation
Bank Of America

Industry experience in AI/ML, engineering, architecture and executive roles in leading technology companies, service providers and Silicon Valley leading organizations. Currently focusing on innovation, disruption, and cutting-edge technologies through startups and technology-driven corporation in solving the pressing problems of industry and world.

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Hira Dangol

Vice President, AI/ML & Automation
Bank Of America

Industry experience in AI/ML, engineering, architecture and executive roles in leading technology companies, service providers and Silicon Valley leading organizations. Currently focusing on innovation, disruption, and cutting-edge technologies through startups and technology-driven corporation in solving the pressing problems of industry and world.

Author:

Zafer Sahinoglo, Ph.D.

VP of Business Innovation
Mitsubishi Electric Innovation Center

Dr. Zafer Sahinoglu received his M.B.A. degree from Massachusetts Institute of Technology in 2013, and Ph.D. degree in Electrical Engineering and M.Sc. degree in Biomedical Engineering from New Jersey Institute of Technology, Newark, NJ, in years 2002 and 1998, respectively.

He was a senior principal research scientist in MERL between 2001 and 2016. His technical expertise includes stochastic signal processing, space-time adaptive processing, ultra-wideband and OFDMA wireless communications, and indoor localization and tracking, biomedical signal processing, Li-ion battery modeling.

He worked in Japan for 6 months in 2014 to promote new software and service based business models in various business divisions. He formed a Vision 2020 Business Innovation group in Mitsubishi Electric US in 2016, where his team developed several SaaS platforms. He has been leading and managing product design and agile product development, building business models, developing technology strategies, and bundling these steps into customized processes with continuous innovation.

He is an inventor on more than 80 patents, has co-authored more than 100 international journal and conference papers, made more than 50 contributions to international standards including ZigBee, IEEE 802.15.4a UWB PHY and MAC, IEEE 802.15.4e MAC, and MPEG 21. He has written two books on wireless communication and localization systems published by Cambridge University Press. He also earned Docent Dr. (Associate Prof.) title in Turkey in 2012 in Electrical Engineering.

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Zafer Sahinoglo, Ph.D.

VP of Business Innovation
Mitsubishi Electric Innovation Center

Dr. Zafer Sahinoglu received his M.B.A. degree from Massachusetts Institute of Technology in 2013, and Ph.D. degree in Electrical Engineering and M.Sc. degree in Biomedical Engineering from New Jersey Institute of Technology, Newark, NJ, in years 2002 and 1998, respectively.

He was a senior principal research scientist in MERL between 2001 and 2016. His technical expertise includes stochastic signal processing, space-time adaptive processing, ultra-wideband and OFDMA wireless communications, and indoor localization and tracking, biomedical signal processing, Li-ion battery modeling.

He worked in Japan for 6 months in 2014 to promote new software and service based business models in various business divisions. He formed a Vision 2020 Business Innovation group in Mitsubishi Electric US in 2016, where his team developed several SaaS platforms. He has been leading and managing product design and agile product development, building business models, developing technology strategies, and bundling these steps into customized processes with continuous innovation.

He is an inventor on more than 80 patents, has co-authored more than 100 international journal and conference papers, made more than 50 contributions to international standards including ZigBee, IEEE 802.15.4a UWB PHY and MAC, IEEE 802.15.4e MAC, and MPEG 21. He has written two books on wireless communication and localization systems published by Cambridge University Press. He also earned Docent Dr. (Associate Prof.) title in Turkey in 2012 in Electrical Engineering.

Author:

Andy Lofgreen

AVP, Data Science Practice
DataRobot
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Andy Lofgreen

AVP, Data Science Practice
DataRobot

GAI has driven a huge revolution in how AI platforms are designed, architected, and scaled for training, fine tuning, evaluation, inferencing and GAI application engineering needs using RAG, embeddings and distributed multi-agents frameworks. In this session we will deep dive into the (re)evolution of AI platforms and various technologies to scale this for next generation GAI needs.

AI Agents
C-Suite
Business Leader
AI Implementation

Author:

Animesh Singh

Executive Director, AI & Machine Learning
LinkedIn

Executive Director, AI and ML Platform at LinkedIn | Ex IBM Senior Director and Distinguished Engineer, Watson AI and Data | Founder at Kubeflow | Ex LFAI Trusted AI NA Chair

Animesh is the Executive Director leading the next generation AI and ML Platform at LinkedIn, enabling creation of AI Foundation Models Platform, serving the needs of 930+ Million members of LinkedIn. Building Distributed Training Platform, Machine Learning Pipelines, Feature Pipelines, Metadata engine etc. Leading the creation of LinkedIn GAI platform for fine tuning, experimentation and inference needs. Animesh has more than 20 patents, and 50+ publications. 

Past IBM Watson AI and Data Open Tech CTO, Senior Director and Distinguished Engineer, with 20+ years experience in Software industry, and 15+ years in AI, Data and Cloud Platform. Led globally dispersed teams, managed globally distributed projects, and served as a trusted adviser to Fortune 500 firms. Played a leadership role in creating, designing and implementing Data and AI engines for AI and ML platforms, led Trusted AI efforts, drove the strategy and execution for Kubeflow, OpenDataHub and execution in products like Watson OpenScale and Watson Machines Learning.

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Animesh Singh

Executive Director, AI & Machine Learning
LinkedIn

Executive Director, AI and ML Platform at LinkedIn | Ex IBM Senior Director and Distinguished Engineer, Watson AI and Data | Founder at Kubeflow | Ex LFAI Trusted AI NA Chair

Animesh is the Executive Director leading the next generation AI and ML Platform at LinkedIn, enabling creation of AI Foundation Models Platform, serving the needs of 930+ Million members of LinkedIn. Building Distributed Training Platform, Machine Learning Pipelines, Feature Pipelines, Metadata engine etc. Leading the creation of LinkedIn GAI platform for fine tuning, experimentation and inference needs. Animesh has more than 20 patents, and 50+ publications. 

Past IBM Watson AI and Data Open Tech CTO, Senior Director and Distinguished Engineer, with 20+ years experience in Software industry, and 15+ years in AI, Data and Cloud Platform. Led globally dispersed teams, managed globally distributed projects, and served as a trusted adviser to Fortune 500 firms. Played a leadership role in creating, designing and implementing Data and AI engines for AI and ML platforms, led Trusted AI efforts, drove the strategy and execution for Kubeflow, OpenDataHub and execution in products like Watson OpenScale and Watson Machines Learning.