LIVE | Microsoft CEO Satya Nadella's Keynote Address On The Potential Of Next-generation AI | N18L

CNBC-TV18
7 Feb 202432:40

Summary

TLDREl script aborda la revolución en la tecnología de la información y la gestión, con la introducción de un nuevo motor de razonamiento neural. Se enfatiza la importancia de la adopción de productos como los co-pilotos y la necesidad de integrar tecnologías AI en todos los sectores de la economía para impulsar el crecimiento. Se destaca la misión de Microsoft de empoderar a cada persona y organización en India, así como la iniciativa de capacitación en habilidades de AI para más de 2 millones de personas. Además, se mencionan ejemplos inspiradores de cómo la AI está transformando la vida en India, desde el sector tecnológico hasta la agricultura y la movilidad social.

Takeaways

  • 🌐 La nueva capacidad de razonamiento neural permite una mejor comprensión del mundo digital y revoluciona la pila tecnológica.
  • 📈 La inversión en tecnologías como la inteligencia artificial tiene un impacto directo en el PIB y el crecimiento económico de un país.
  • 🚀 Las empresas Microsoft se centran en empoderar a personas y organizaciones en India para participar plenamente en la era de la inteligencia artificial.
  • 🛠️ La adopción de productos como los co-pilotos de IA es fundamental para mejorar la productividad y romper los silos de especialización.
  • 🔄 La transformación digital a través de la nube y la IA es la misma, y es la manera en que Microsoft se comunica con sus clientes y optimiza sus procesos empresariales.
  • 💡 La implementación de IA en empresas como Axis Bank y HCL Tech muestra cómo se están adaptando sus flujos de trabajo y mejorando la eficiencia.
  • 🌟 La infraestructura de Microsoft, desde el nivel de la infraestructura hasta los modelos de aprendizaje automático, está diseñada para apoyar la creación de productos de IA por parte de sus clientes.
  • 🔧 Microsoft expone su pila tecnológica a los usuarios para que puedan construir sus propios productos de IA, aprovechando los servicios de Azure y otros recursos.
  • 🔐 La seguridad y la confianza son fundamentales en la era de la IA, y Microsoft ofrece soluciones para proteger los datos y garantizar la conformidad con marcos éticos de IA responsables.
  • 📚 La capacitación en habilidades de IA es esencial para el éxito en la nueva era tecnológica, y Microsoft tiene la iniciativa de capacitar a más de 2 millones de personas en India.
  • 🌍 La capacidad de resolver problemas en India demuestra el potencial global de las soluciones de IA, ya que si se puede hacer en India, se puede hacer en el mundo.

Q & A

  • ¿Qué implica la nueva capacidad de razonamiento neural para el mundo digital actual?

    -La nueva capacidad de razonamiento neural representa una herramienta avanzada para interpretar y dar sentido al mundo digital, permitiendo una comprensión más profunda y efectiva de los datos digitizados, lo que a su vez puede revolucionar la estructura tecnológica existente y tener un impacto significativo en el PIB de una economía.

  • ¿Cómo se relaciona la inversión en tecnologías generales de propósito con el crecimiento económico de un país?

    -La inversión intensa y cross-sectoral en nuevas tecnologías generales de propósito, como es el caso de la inteligencia artificial, puede marcar una diferencia significativa en las perspectivas económicas futuras de un país. Un ejemplo histórico es la inversión del 10% del PIB del Reino Unido en el sistema de ferrocarril durante la Revolución Industrial, lo que sentó las bases para su crecimiento futuro.

  • ¿Cuál es la misión de Microsoft en la India en el contexto de la inteligencia artificial?

    -La misión de Microsoft en la India es empoderar a cada persona y organización para que pueda participar plenamente en la era de la inteligencia artificial, fomentando el crecimiento económico y la innovación en todos los sectores y regiones de la economía india.

  • ¿Qué es un co-piloto en el contexto de la inteligencia artificial y cómo puede afectar la productividad?

    -Un co-piloto es una herramienta de inteligencia artificial diseñada para complementar las capacidades humanas, facilitando la obtención de experticia a un simple clic y mejorando la productividad en tareas variadas. Su adopción puede cambiar drásticamente la forma en que se realizan las tareas, rompiendo los silos de experticia y acelerando el progreso en áreas como la cadena de suministro, ventas, derecho y más.

  • ¿Qué implicaciones tiene la implementación de co-pilotos en diferentes sectores de la economía india?

    -La implementación de co-pilotos en diversos sectores de la economía india puede aumentar la velocidad y la eficiencia en la toma de decisiones y en la ejecución de tareas, permitiendo una mayor producción y una mejora en la calidad de la salida de todos los sectores involucrados.

  • ¿Cómo están las empresas en la India adoptando la inteligencia artificial en sus operaciones?

    -Las empresas en la India están adoptando la inteligencia artificial de manera rápida y amplia, integrándola en sus procesos comerciales, de gestión de proyectos, análisis de datos y más. Empresas como Axis Bank, HCL Tech y M tree están adoptando co-pilotos y adaptándolos a sus flujos de trabajo específicos, lo que demuestra un alto grado de compromiso con la innovación y la mejora continua.

  • ¿Qué es la iniciativa de habilidades en AI que anunció Microsoft para la India y cómo beneficia a la población local?

    -La iniciativa de habilidades en AI de Microsoft tiene como objetivo capacitar a más de 2 millones de personas en India con habilidades en inteligencia artificial. Esto ayudará a la fuerza laboral local a prepararse y prosperar en la nueva era de la tecnología, creando nuevas oportunidades de empleo y fomentando el crecimiento económico a través de la educación y la capacitación en tecnologías emergentes.

  • ¿Qué es la plataforma kara y cómo está contribuyendo al desarrollo económico en rural India?

    -Kara es una organización que se basa en la inteligencia artificial para crear soluciones que ayudan a comunidades en el campo de la India. Ofrece trabajos bien remunerados en la etiquetaje de tareas AI a personas en zonas rurales, lo que no solo mejora sus ingresos sino que también contribuye a la creación de oportunidades económicas en áreas que de otro modo podrían estar desatendidas.

  • ¿Qué es la plataforma Jogle Bundi Studio y cómo está siendo utilizada para el empoderamiento social?

    -Jogle Bundi Studio es una herramienta de codificación de bajo nivel que permite a las personas crear aplicaciones de inteligencia artificial personalizadas. Está siendo utilizada por organizaciones benéficas y sociales para brindar información y servicios a grupos como los trabajadores migrantes, mejorando su acceso a servicios y oportunidades en nuevas localidades y empoderándolos a tomar decisiones informadas.

  • ¿Qué medidas están tomando para garantizar la seguridad y la confianza en la inteligencia artificial?

    -Para asegurar la seguridad y confianza en la inteligencia artificial, se están implementando medidas como entornos de confianza cero, salvaguardias para proteger los datos y la propiedad intelectual, y un marco de inteligencia artificial responsable que incluye principios, estándares y procesos de auditoría para garantizar que la IA se desarrolle y utilice de manera ética y segura.

  • ¿Cómo están las empresas en la India aprovechando la inteligencia artificial para transformar la experiencia del cliente?

    -Las empresas en la India están utilizando la inteligencia artificial para crear agentes virtuales que pueden interactuar con los clientes, proporcionándoles asistencia personalizada y procesando transacciones de manera eficiente. Esto mejora significativamente la experiencia del cliente, facilitando la interacción y la planificación de viajes, por ejemplo, en el caso de Air India.

  • ¿Qué es la plataforma de datos y cómo está ayudando a las empresas a mejorar sus operaciones con inteligencia artificial?

    -La plataforma de datos es una solución que integra el almacenamiento de datos y el cálculo de inteligencia artificial, permitiendo a las empresas acceder a todos sus datos y aplicar el procesamiento de IA en tiempo real. Esto ayuda a las empresas a tomar decisiones más informadas y agilizar sus procesos operativos, mejorando la eficiencia y la toma de decisiones.

Outlines

00:00

🌐 Revolución Tecnológica y su Impacto en el PIB

Este párrafo aborda la evolución hacia la digitalización y cómo la introducción de un nuevo motor de razonamiento neural transforma completamente la pila tecnológica, impactando potencialmente en el PIB. Se destaca la importancia de la inversión intensiva en tecnologías generales y su implementación transversal en la economía para el progreso de un país. Utiliza el ejemplo histórico del Reino Unido invirtiendo en su sistema ferroviario durante la Revolución Industrial para ilustrar cómo la inversión en tecnología impulsa el crecimiento económico. El papel de la inteligencia artificial (IA) en este contexto se resalta como un factor clave para el futuro crecimiento económico, especialmente en mercados de alto crecimiento como India.

05:02

🚀 Transformación Impulsada por la IA y Adopción de Copilotos

El segundo párrafo se enfoca en la transformación empresarial impulsada por la IA, específicamente en la adopción de 'copilotos' de IA para mejorar la productividad en diversas áreas como la cadena de suministro, ventas, y desarrollo legal. Argumenta que la adopción de estas herramientas es crucial para romper silos dentro de las organizaciones, cambiando fundamentalmente la manera en que se procesa el conocimiento y se realizan las tareas. Ejemplos de empresas indias adoptando estas tecnologías muestran cómo la IA está siendo integrada en los flujos de trabajo para optimizar procesos y fomentar la innovación.

10:03

🌍 Infraestructura y Modelos para la Innovación en IA

Este párrafo detalla los esfuerzos de inversión en infraestructura y desarrollo de modelos de IA como fundamentos para la innovación tecnológica. Se menciona la expansión de la infraestructura de computación para soportar la IA a gran escala, incluyendo la formación de modelos y la inferencia en tiempo real. Destaca la importancia de la diversidad en el hardware de silicona y cómo los avances en la IA están redefiniendo la arquitectura de los sistemas centrales, prometiendo una reducción continua en los costos gracias a la ley de Moore. Además, se hace énfasis en el desarrollo de modelos de lenguaje de última generación y modelos de IA más eficientes y accesibles.

15:05

🔬 IA y la Revolución Científica

Se discute cómo la IA puede acelerar significativamente el progreso científico, especialmente en campos como la química, la ciencia de materiales y la biología. La IA se presenta como una herramienta capaz de emular procesos y reducir el espacio de búsqueda para el descubrimiento de nuevos materiales o fármacos, citando el ejemplo de un desarrollo que redujo el contenido de litio en las baterías en un 70%. Este párrafo enfatiza el potencial transformador de la IA para condensar siglos de avance científico en décadas, facilitando así transiciones energéticas críticas y avances en diversos campos de la ciencia.

20:07

🏆 Aplicaciones Prácticas y Empoderamiento mediante la IA

Este segmento explora diversas aplicaciones prácticas de la IA en empresas y en el sector público, mostrando cómo estas herramientas están siendo utilizadas para optimizar procesos y mejorar la toma de decisiones. Ejemplos incluyen el uso de agentes de IA en Air India para asistencia al cliente, el desarrollo de bots para agricultores por ITC, y la adopción de IA en el sector legal para analizar contratos. Se destaca el impacto positivo de estas aplicaciones en la eficiencia operativa y la capacidad para romper barreras de conocimiento, mejorando la calidad del trabajo y la toma de decisiones en diversas industrias.

25:09

🛡️ Seguridad, Privacidad y IA Responsable

El último párrafo aborda la importancia de la seguridad, la privacidad de los datos y el desarrollo responsable de la IA. Se discuten las medidas de seguridad implementadas para proteger la infraestructura de IA y los datos de los usuarios, asegurando que la propiedad y la privacidad sean respetadas. También se menciona el compromiso con la indemnización por derechos de autor y el marco de IA responsable de la empresa, destacando la necesidad de procesos auditables y principios éticos en el desarrollo de tecnologías de IA. La sección subraya el compromiso con la construcción de un entorno de IA seguro y confiable.

30:10

🌟 Empoderamiento Social a través de la IA

Este párrafo se centra en la iniciativa de una empresa social que utiliza soluciones basadas en IA para promover la movilidad social en la India rural. A través de la grabación de datos en lenguas maternas y la creación de conjuntos de datos valiosos, esta empresa está mejorando significativamente los ingresos de las comunidades rurales. Se destaca el uso de servicios de IA y la infraestructura de Azure para validar y enriquecer estos conjuntos de datos, subrayando el potencial de la tecnología para resolver problemas a gran escala y mejorar la calidad de vida de las personas en regiones desatendidas.

Mindmap

Keywords

💡Inteligencia artificial (AI)

La inteligencia artificial es una tecnología avanzada que permite a las máquinas realizar tareas que normalmente requieren inteligencia humana, como el aprendizaje, el razonamiento y la toma de decisiones. En el video, se discute cómo la AI está transformando la economía y la productividad en India, y se menciona su aplicación en diversos sectores como la tecnología de la información, la cadena de suministro y la venta.

💡Transformación digital

La transformación digital se refiere al proceso de convertir y adaptar un negocio o una industria a las tecnologías digitales. En el contexto del video, se destaca la importancia de la transformación digital en la mejora de los procesos empresariales, la optimización de los recursos y la creación de nuevas oportunidades económicas.

💡Economía de India

La economía de India es uno de los mayores mercados de crecimiento en el mundo, con un potencial económico significativo y ambiciones gubernamentales para su desarrollo futuro. En el video, se discute cómo la AI está desempeñándose como un factor clave en el impulso del PIB de India y la transformación de la economía en su conjunto.

💡Co-piloto (Co-pilot)

El co-piloto es una herramienta de inteligencia artificial desarrollada por Microsoft que ayuda a los desarrolladores de software a escribir código de manera más eficiente y precisa. En el video, se destaca la importancia de la adopción de co-pilotos como un paso crítico para mejorar la productividad y la toma de decisiones en las empresas.

💡Infraestructura de tecnología (Tech stack)

La infraestructura de tecnología se refiere a la conjunto de herramientas, servicios y plataformas que una empresa utiliza para sus operaciones tecnológicas. En el video, se discute cómo Microsoft está reformando su infraestructura de tecnología para incluir la inteligencia artificial y cómo esto está impactando positivamente a los usuarios y la economía en India.

💡Gobierno de India

El gobierno de India es el órgano ejecutivo de la República de la India, encargado de la administración pública y la toma de decisiones en el país. En el video, se hace referencia a las ambiciones del gobierno de India en relación con el desarrollo económico y la adopción de tecnologías emergentes como la inteligencia artificial.

💡Nube

La nube se refiere a la infraestructura de tecnología que permite a los usuarios acceder a servicios de computación y almacenamiento a través de Internet. En el video, se discute cómo la nube es un medio esencial para la transformación digital y la adopción de la inteligencia artificial en India.

💡Innovación

La innovación se refiere al proceso de crear o introducir nuevos productos, procesos o ideas en el mercado. En el contexto del video, la innovación es un tema central, ya que se discute cómo la inteligencia artificial está impulsando la creación de soluciones tecnológicas únicas y la mejora de los resultados empresariales en India.

💡Seguridad cero (Zero trust)

El concepto de seguridad cero es un enfoque de seguridad informática que假定 que no hay ninguna red confiable y que todos los usuarios, dispositivos y datos deben ser verificados continuamente. En el video, se resalta la importancia de la seguridad cero en la protección de la infraestructura de AI y la necesidad de implementar medidas de seguridad sólidas para proteger los datos y la información.

💡Responsabilidad AI (Responsible AI)

La responsabilidad AI se refiere al conjunto de prácticas y principios éticos que guían el desarrollo y la implementación de sistemas de inteligencia artificial. En el video, se discute cómo Microsoft está adoptando un marco de responsabilidad AI para garantizar que sus tecnologías AI se utilicen de manera segura, justa y transparente.

💡Habilidades en AI

Habilidades en AI se refiere a la competencia y el conocimiento en el campo de la inteligencia artificial, incluyendo el desarrollo de algoritmos, la análisis de datos y la comprensión de cómo se aplican estas tecnologías en diversos contextos. En el video, se anuncia un nuevo initiative de Microsoft para capacitar a más de 2 millones de personas en India con habilidades en AI, lo que demuestra su compromiso con la educación y el desarrollo del talento en esta área.

Highlights

The new capability of a neural reasoning engine is revolutionizing the tech stack by making sense of the digitized world.

AI has the potential to significantly impact GDP growth, as seen in India's high-growth market.

Investment in new general purpose technologies like AI can greatly influence a country's future prospects.

Microsoft's mission is to empower every person and organization in India through the adoption of AI technologies.

AI products from Microsoft are integrated into every aspect of the tech stack, not limited to one specific product.

The AI age is bringing expertise to one's fingertips, breaking down silos of knowledge.

Adopting AI co-pilots is critical for increasing productivity and transforming business processes.

AI transformation is not just about the technology but the tangible business outcomes it enables.

Three imperatives for driving business outcomes with AI include adopting AI products, utilizing Azure services, and focusing on responsible AI practices.

Azure's tech stack, from infrastructure to models, is available for businesses to build their own AI solutions.

Moore's law is very much alive in the context of AI, with costs continuing to decrease.

AI has the potential to greatly accelerate scientific research and development.

Microsoft is building the best toolchain for developers to create applications and democratize technology.

The data platform is crucial for AI applications, linking data with the reasoning engine for real-time insights.

Air India and ITC are examples of organizations leveraging AI to transform their operations and customer experiences.

AI can enhance human agency by providing access to information and enabling action in rural India.

Trust, security, and responsible AI practices are fundamental to the successful adoption of AI technologies.

Microsoft's initiative to skill over 2 million people in India with AI skills aims to empower the workforce for the future.

Organizations like Kara are using AI to create economic opportunities in rural India by bringing AI tasks to local communities.

Transcripts

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category it's called Information

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Management which is you every day you

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get up you digitize a little more and

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you make sense of the digitized world

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now we have a new

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capability uh of making sense of that

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digitized world a new reasoning engine

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uh which is a neural reasoning engine

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which we can apply to an increasingly

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digitized world and so these two things

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a new user experience and a new

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reasoning engine pretty much completely

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revolutionize the entire Tech stack um

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this ultimately is going to have an

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impact on GDP right because at the end

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of the day you can only talk about tech

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uh as a real thing if it is going to

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have a real impact in the overall growth

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of an economy and in the in India's case

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uh as Punit was saying definitely today

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this is one of the highest growth

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markets uh you see it the buoyancy of it

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uh the government and all of you have

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high Ambitions of what's going to happen

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even by 2025 uh and what percentage of

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that GDP growth is going to actually be

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driven by AI are all I think going to be

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very interesting numbers for us to track

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in fact I was recently came across a

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fascinating statistic in in the United

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Kingdom during the height of the

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Industrial Revolution they spent as much

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as 10% of their GDP on the railroad

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system and then the rest obviously is

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history but I think that's another

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understanding which is when you have a

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new general purpose technology how

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intensely you invest and deploy it

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cross- sectorally inside an economy I

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think makes difference uh to a country's

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prospects going forward and that's why

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that's exciting that we are at the early

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stages of this adoption cycle but

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rapidly scaling it um that's what we are

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focused on at Microsoft our mission is

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to empower every person and every

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organization in India to be able to

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participate fully uh to me that's what

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you know gives me a lot of satisfaction

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is to see new technology but applied in

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unique intense ways uh across small and

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large businesses across public and

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private sector across every part of

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Indian economy across every region of

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India that's what's uh really our

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mission that's why we have built this

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into the entirety of tech stack people

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say what is an AI product from Microsoft

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it's called everything from Microsoft

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there is not one product quite frankly

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uh because we've gone plumbed it all the

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way from the core infrastructure it's

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fascinating the more I look at it you

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know I get up in the morning and I'm

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reviewing some data center plan uh the

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everything from what we do on the

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concrete to the hwx system to the

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infrastructure are all being defined by

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the power draw of AI systems I mean it's

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not about like any one product but the

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entirety of what we do has been is being

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shaped um and the opportunity of

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ultimately though you can even you know

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we us to talk about digital

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transformation all through Cloud that's

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effectively the same thing which is the

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way we engage our customers uh the way

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we engage you know the experience

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experience of our employees the business

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processes and how they're optimized uh

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and the space of just raw innovation in

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any Enterprise all of these are the

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ultimate outcomes that we will measure

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ourselves by right so it's not about

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tech for tech sake but it's a tech

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applied for these business outcomes that

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I think more so than I would say even in

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the cloud era I feel that the ability to

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tangibly say what is the change in the

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business outcome I think we're able to

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go to grock that uh much faster so it's

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exciting time for AI

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transformation um and AI driven

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transformation um so in that context for

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us I would say there are three

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imperatives if I had to sort of even

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look across what's happening around the

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world uh what we ourselves quite frankly

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are seeing inside the company there are

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three imperatives of how you all can get

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ahead um on uh driving those business

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outcomes the first one is to just adopt

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some of these products like co-pilots

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Fast uh it reminds me quite frankly of

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uh the first paradigm shift I was part

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of which is the PCS uh you know even

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it's interesting by the way PCS are an

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interesting thing because if you even

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take some of these critiques of uh the

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impact of it in economic growth like

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Robert Gordon uh the one thing that he

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gives credit to is PCS in the late late

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90s when they became standard issue and

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part of uh work uh they changed

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productivity in fact he will claim that

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that was the last time it actually had a

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direct relationship uh to productivity

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stats um and obviously I take a lot of

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pride in it but I feel this AI age is

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very similar that is it's diffusing

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right if you think about what PCS did

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they brought information at your

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fingertips this age of AI is really

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really expertise at your fingertips

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think you know what happened to

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forecasting before PCS right before

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email and spreadsheets how did we do

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forecasting uh and then how did the

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business process of forecasting change

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same thing is happening now whether it

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is supply chain whether it's sales

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whether it's legal or what have you when

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you can summon the expertise it's the

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greatest Silo breaker and so that's why

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I think adoption of co-pilots becomes

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critical and we seeing all kinds uh of

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productivity stats uh here but all of it

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stems from this fundamental notion that

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knowledge turns inside an organization

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are changing right and you can come at

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it horizontally whether it's Frontline

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work or knowledge work or you can come

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at it from business process sales

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service software development security

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operations so the tangible way you can

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in fact my biggest encouragement for you

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is to go deploy these tools create a a

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cohort measure it yourself that's it uh

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because you got to build your own

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confidence that you can sense it see it

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uh and that way you can drive it uh and

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so that's what I think is very much

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possible and you see all of these

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statistics uh and in fact in in in India

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uh that's what been most exciting for me

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you know I've been sort of learning

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about all of these uh use cases IT

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services at some level you could say

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it's existential for any one of us right

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I was talking to Jensen the other day

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he's got all of everybody

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uh in Nvidia is deployed copile it makes

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sense because he's his thing is like you

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know like we will all be found out in

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fact the firm level differences will

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start showing up uh especially in Tech

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uh in short order if you're not an early

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adopter and so obviously that you see

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even with the IT services in in this

play06:49

country uh all going uh Fast and Furious

play06:52

on it but it's just not that and in fact

play06:54

I think Punit had these uh slides where

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there is adoption across the board

play06:58

across every sector of the Indian

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economy and it's exciting to see just to

play07:02

give you a flavor for it I was just

play07:05

reading up about what axis Bank did this

play07:08

is one of the the thing that I sort of

play07:10

describe as the standard issue right

play07:12

just like at some point everyone all of

play07:13

us sort of said hey PCS a standard issue

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co-pilot as a standard issue that's what

play07:18

they're doing so they're basically

play07:20

saying let's take the most horizontal

play07:22

approach of having everybody equipped

play07:25

with a co-pilot so that every piece of

play07:27

knowledge work can be done fast somebody

play07:29

described this to me as lean for

play07:32

knowledge work I think that's a good way

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to even think about it right which is

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you're increasing the speed and the sort

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of alignment across organizations so

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that you can get things done with the

play07:44

least amount of time and effort right

play07:47

that's essentially the mindset uh so

play07:49

that's kind of what axis is trying to do

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um both um HCL Tech and um M tree are

play07:56

also adopting this but they're also

play07:59

adding their own workflows into it right

play08:01

so it's not just the horizontal tools

play08:03

that are baked in but in the case of HCL

play08:06

a lot of their project management and

play08:08

Bug triage is integrated into the

play08:11

co-pilot in the case of mine tree even

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the insights into how they drive their

play08:16

Staffing for various projects is plugged

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into it so in some sense it's not just

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the one workflow that we have but you

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can steer it to the workflows that

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matter inside your Enterprise and wire

play08:28

it all into the co-pilot so copilot's

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understanding is not just what was

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prefabricated it is what your Enterprise

play08:35

is and that's exciting and in the case

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of infosis the the this is probably one

play08:40

of the bigger use cases of GitHub

play08:42

co-pilot uh GitHub Co in fact if I go

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back into my own belief in this entire

play08:47

regime of AI if you will uh all came

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about when I first saw gbd3 uh inside or

play08:54

what became gbd3 inside of GitHub uh

play08:58

co-pilot um and it's the most proven use

play09:01

case it's the place where the

play09:02

productivity stats are most robust I

play09:04

mean it went from I mean remember

play09:05

software developers are pretty skeptical

play09:07

people right it went from this won't

play09:09

work to oh my God I can't live without

play09:10

it uh in the shortest amount of time uh

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and it's exciting to see now this is now

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being broadly deployed uh even across

play09:19

organizations like infosis now the um

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the next imperative of course is adopt

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so the first thing is don't reinvent the

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wheel get the co-pilots that have been

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prefabricated whether it's sort of for

play09:32

specific business processes like

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software development or security or the

play09:36

horizontal ones add your own data add

play09:39

your own workflow so that's if that's

play09:41

number one the number two is we are

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exposing all of the tech stack we use to

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build our co-pilots to you as first

play09:50

class Azure services so that means

play09:52

there's nothing magic about what we did

play09:55

because you can take that same thing and

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apply it to any anything you want to

play10:00

build duvo as far as your own AI

play10:03

products uh and so that's the second

play10:05

imperative this co-pilot stack uh from

play10:07

the bottom to the top is available to

play10:09

you uh so for our investments here

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obviously start with the raw

play10:14

infrastructure itself right we have more

play10:16

regions than any other hyperscaler

play10:18

around the world in in India itself uh

play10:21

we have uh three regions already fourth

play10:24

coming on line we have the two regions

play10:27

with Geo so we are definitely investing

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to make sure that compute with low

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latency at scale including all the AI is

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available for all of you to be able to

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take advantage we're investing a lot as

play10:40

I said in making sure in fact when I

play10:42

think back having started uh in our

play10:45

Cloud group you know what now 15 years

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ago um I I sometimes sort of wake up and

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sort of can't recognize even the core

play10:53

system architecture it's so rapidly

play10:56

changing so we are investing a lot part

play10:59

in making sure that the AI

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infrastructure whether it's for large

play11:03

model training or small batch training

play11:05

or inferencing uh how do we make sure we

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have the best performance on end uh so

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that's something that we're doing across

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multip and and having diversity of

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silicon uh as well so we are very very

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excited about the progress and some of

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the Benchmark data uh that we have seen

play11:21

uh is very very because here's the thing

play11:23

right people talk about the death of

play11:25

Mo's law let me tell you Moors law is

play11:27

very much alive when it comes to to AI

play11:29

right what used to be uh you know the

play11:32

cost curves of AI are only going to come

play11:34

down so that means a set of tokens in

play11:36

and out today are going to follow the

play11:38

mors law so that means when you're even

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thinking about your AI project uh I I

play11:43

tell my teams don't worry about cogs we

play11:45

can know we can optimize cogs um and so

play11:48

if you want to be the most ambitious

play11:50

about being able to use this to create

play11:53

the most value for your customers

play11:54

partners and for the business and then

play11:56

know that there is no other raw material

play11:59

in the world that just drops in price

play12:01

using Mor's law like this and so that's

play12:03

if you talk about business leverage this

play12:05

is business leverage um the next thing

play12:08

is we have the raw infrastructure but

play12:11

then we have these models right so these

play12:13

are like the foundaries of this world

play12:15

right so therefore you have the lot we

play12:17

have the the best uh model today even

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right with all the sort of hoopla you

play12:22

know one year after uh still GPD 4 on

play12:25

nlu take your benchmark and anyone still

play12:28

is better uh we're waiting for the

play12:31

competition to arrive it'll arrive I'm

play12:32

sure but the fact is uh that we have the

play12:35

most leading uh llm uh out there uh we

play12:39

have all the open source models so it's

play12:41

not about like even co-pilot is not

play12:42

about just uh open AI models uh in fact

play12:45

we use a combination of models uh in any

play12:48

of our products which is what all of you

play12:50

will use so we have in Azure the best of

play12:53

Open Source models the best of Frontier

play12:55

models uh we also are innovating in what

play12:58

is is called the small language models

play13:00

in fact one of the best if you go to

play13:01

hugging phase today uh you'll find that

play13:04

fi is the leading small language model

play13:08

uh and it's a pretty cool research uh

play13:11

finding right which is you can take a

play13:12

slightly different approach uh to

play13:15

learning as opposed to thinking of all

play13:17

tokens as equal if you took a cognitive

play13:20

approach to like for example the

play13:22

original book or the original paper on

play13:25

uh Transformers was attention is all you

play13:27

need uh the paper we wrote uh was

play13:30

textbooks is all you need uh and it's

play13:33

intuitive right when you're learning

play13:34

something uh you would rather go to a

play13:36

textbook and learn versus saying let me

play13:38

run from all the text that was ever

play13:40

written about a subject so that

play13:42

intuition is what's leading to these

play13:44

small models actually performing on par

play13:47

with some of the largest models so we're

play13:48

very very excited uh about the slms

play13:51

these are the things that can run on on

play13:53

your phones and on your PCS as well as

play13:55

obviously in the cloud at scale and you

play13:57

can cost stop optimized going back again

play13:59

to that morw point so you can think

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about llms and slms all playing a role

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in how you build out your products the

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perhaps when I look at the thing that

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I'm most excited about uh is uh what I

play14:14

think all of this can do for Science and

play14:16

the acceleration of science clearly I

play14:19

think knowledge work Frontline work um

play14:22

like whether it's software development

play14:24

whether it's the everyday uh knowledge

play14:26

work will be revolutionized

play14:29

but if I think about one of the pressing

play14:31

challenges we as a society have is we

play14:33

have to take whatever the 250 years of

play14:36

science right they take energy

play14:37

transition we're not going to make it to

play14:39

the other side um if we don't compress

play14:43

maybe 250 years of development of

play14:45

chemistry into perhaps the next 25 years

play14:48

uh so we need some new way to even

play14:51

change the scientific process and its

play14:54

curve uh and that's where I think AI can

play14:57

help um AI ENT the way we think about it

play14:59

is like if you want to simulate in

play15:02

silico uh that's where high performance

play15:05

Computing is used right if you want to

play15:06

even simulate a single molecule or

play15:08

molecular Dynamic cells and then all way

play15:11

the complex systems of course the real

play15:13

breakthrough there will be Quantum but

play15:15

the interesting thing AI does is AI is

play15:18

kind of like an emulator that or it

play15:20

reduces the search space so that you can

play15:23

for example if you want to build a new

play15:25

material uh you can discover that new

play15:28

material or generate in fact generative

play15:30

diffusion models like matter genen that

play15:33

we developed are allowing us to build

play15:35

new materials and in fact we round

play15:37

tripped one such example recently we

play15:39

worked with one of the National Labs in

play15:40

the United States and essentially

play15:42

generated a new material which reduce

play15:45

the lithium content in a battery by 70%

play15:48

right I and I really wanted my team to

play15:50

show me this that this is a complete

play15:52

roundtrip so it's not just oh we

play15:54

generated something in silico but can

play15:56

you fabricate it and put it back back

play15:58

into a battery of course we're not a

play16:00

battery company but think about this in

play16:01

the hands of somebody who is in the

play16:03

battery business right so you're not

play16:06

just building batteries you're able to

play16:08

kind fundamentally change the frontier

play16:10

of science uh that helps you build the

play16:13

next generation of batteries this is

play16:15

happening in chemistry it's happening in

play16:17

material science uh it is going to start

play16:20

happening in biology it's obviously drug

play16:22

discover you know drug being able to

play16:24

generate new molecules for drug

play16:25

Discovery are you know is easy it's the

play16:27

drug discovery process which is going to

play16:29

be the more complex one but nevertheless

play16:31

we're definitely uh very excited about

play16:34

what AI for science means so we're now

play16:36

imp thinking of this as first class just

play16:38

like as you thought about Microsoft 365

play16:41

for knowledge work you will sort of come

play16:43

to and we'll do this through partnership

play16:44

so that's why I think it's very exciting

play16:46

in a country like India where there is

play16:48

so much investment and so much Capital

play16:50

going into the core basic science uh

play16:53

driven Industries to be able to really

play16:56

come help India leap froggy even some of

play16:59

the Scientific Revolution would be very

play17:01

very exciting um to harness all this

play17:05

we're building the best tool chain in

play17:07

some sense one of the things that I take

play17:09

great satisfaction from is we are a

play17:11

tools company that's how we got started

play17:12

in 1975 and here we are in 2024 and we

play17:16

get a real kick out of building the best

play17:19

tools for developers uh whether it's

play17:21

GitHub whether it's vs code whether it's

play17:24

the low code no code tools and Power

play17:26

Platform uh all of these things coming

play17:29

together and the power of all of this

play17:31

technology has to be democratized so

play17:34

that people can build applications at

play17:35

the end of the day uh and that's what

play17:37

our goal is uh with the entire tool

play17:40

chain the other very very important part

play17:43

of the teex stack is the data platform

play17:46

right so if you think about a reasoning

play17:48

engine if you want to build an

play17:50

application it's about taking the data

play17:53

you have and using this reasoning engine

play17:55

on top of the data and so we are

play17:57

bringing essentially AI compute to all

play18:00

of the data in its all its forms whether

play18:02

it's operational stores whether it's

play18:04

analytical stores linking these two

play18:06

things in real time uh in fact one of

play18:08

the things that I'm very sort of excited

play18:11

about is a product called fabric uh and

play18:14

what we did is I I think of it as the

play18:16

product built for the AI age because it

play18:19

separates out uh the core storage from

play18:25

compute and with even the business model

play18:28

so that means I can build a application

play18:32

which is using all the data in one Lake

play18:36

and I can have different types of comput

play18:38

sometimes it's SQL sometimes it's spark

play18:41

sometimes it's Azure open AI there are

play18:43

three different types of compute jobs

play18:45

that can all be brought in on the same

play18:47

data or different data uh joints if you

play18:50

will and so that to me is a very

play18:52

breakthrough uh way to think about your

play18:55

data uh in the context of AI so this is

play18:58

this is a one of the a lot of people

play18:59

talk about their AI projects the first

play19:01

thing is you got to get your data house

play19:04

in order in order to be able to get uh

play19:06

the best value out and that's why you

play19:08

see the adoption Cycles even in India

play19:11

even though the cloud adoption in India

play19:12

was a lot slower than what what happened

play19:14

in the rest of the world but the fact

play19:16

that it has happened is what's helping

play19:18

anyone today take AI without any of that

play19:21

diffusion uh impedance or delay if you

play19:24

will because you're already in the cloud

play19:26

your data is already in the cloud and

play19:27

you're able to rapidly they turn it

play19:28

around and adopt something like a new

play19:31

reasoning engine on top of that same

play19:32

data uh lots of interesting um uh

play19:36

customer use cases um uh here and I

play19:40

think Punit had many uh of these

play19:42

examples and I had a chance this morning

play19:44

to visit with a few of these folks and

play19:47

really learn about how they are going

play19:48

about building things and they're really

play19:50

inspirational right uh uh take Air India

play19:54

uh if what Chandra was telling me is how

play19:57

he's really inst instructed the team

play19:59

there to accelerate everything that

play20:02

they're doing right essentially from

play20:04

lack of um he was telling me you know

play20:07

they're just putting in all of the

play20:09

systems uh that had like a lot of

play20:11

deficit but rapidly getting into uh you

play20:14

know place where they're leading in fact

play20:17

going from not having systems to Leading

play20:19

with some of those experiences so the

play20:21

thing that they built for example was an

play20:22

agent an AI agent for the customer it's

play20:25

one of the leading uh uh products uh out

play20:29

there so if you go to the Air India home

play20:31

you know homepage on the web you can

play20:33

speak to this uh AI agent complete your

play20:36

entire transaction and travel planning

play20:38

and they have like high ambition on it

play20:41

uh and they have on the back end of it

play20:43

as well they're also creating a bunch of

play20:45

agents to streamline the business

play20:47

process not just on the front end to the

play20:48

consumers I had a chance to meet with

play20:50

the ITC team that they're building this

play20:53

um uh essentially a bot for the farmers

play20:57

uh to be able to then get all the

play20:59

knowledge they need uh because in some

play21:01

sense in a vernacular language to be

play21:04

able to access all of the information

play21:06

and to be able to even take action uh

play21:09

right this is the other very interesting

play21:11

site or rather interesting Dimension to

play21:13

this which is it reduces the expertise

play21:17

required to use Computing and the

play21:21

knowledge that is accessible right so

play21:23

that is why I think in India the most

play21:26

exciting thing is for the quality of all

play21:28

Indian output to go up because it sort

play21:31

of helps reduce the barrier I think that

play21:33

that's going to probably be uh an

play21:35

example in in farming um arnd uh they're

play21:39

you know this is a fascinating use case

play21:40

so they obviously uh have been in

play21:43

business for 100 plus years and here

play21:45

they are using AI to for example for

play21:47

their legal department to say let's make

play21:49

sense of contracts faster let's

play21:51

understand risk uh and what have you

play21:54

very obvious use case after all any

play21:55

lawyer or anyone in the legal department

play21:57

who spent a a lot of time uh trying to

play21:59

assess uh risk On Any Given contract the

play22:02

easiest use case is to just be able to

play22:04

use gen to think you know make sense of

play22:07

it but the interesting thing is for

play22:09

their commercial teams to effectively

play22:11

summon the legal expertise right right

play22:15

at the point when the contract or the

play22:17

RFP is even being issued that's the real

play22:20

transformation the real transformation

play22:22

is when the expertise silos are broken

play22:25

right so you don't have to wait for

play22:27

finance to at the end of the quarter

play22:29

tell you all the mistakes you made or

play22:31

for legal to tell you all the risks you

play22:34

took without knowing right so it's the

play22:36

ability to bridge that expertise Gap

play22:39

just in time that's why I kind of think

play22:40

of this as lean for knowledge work uh

play22:43

that's what they're doing um and then

play22:45

the last example was very inspirational

play22:47

like last time I was here I saw the the

play22:50

the demo of jugal bandi and I spoke

play22:53

about it many many times because it was

play22:54

just a drop you know it's like drop the

play22:56

mic moment for me to see how this

play22:59

digital public good and Bash combined

play23:02

with jugal bandi was being used to

play23:04

transform lives of people in rural India

play23:07

speaking in vernacular languages uh and

play23:09

being able to not only get access to

play23:11

information and knowledge but to take

play23:13

action right that I mean talk about

play23:14

human agency in the age of AI being

play23:17

enhanced that was an example and now the

play23:19

team has even built a fantastic thing

play23:21

called jugle Bundy Studio which is a no

play23:23

code lood Tool uh for people to be able

play23:26

to build these BS and make them

play23:28

available to all of the uh social

play23:31

entrepreneurs the nonprofits who are

play23:34

doing things um and so I had a chance to

play23:36

meet uh the folks uh from uh one of the

play23:39

nonprofits or social Enterprise called

play23:41

aami and they built a thing for uh

play23:44

migrant laborers coming in uh and for

play23:47

them to be able to access uh this

play23:50

information uh it's called bundu Uh so

play23:53

therefore somebody who comes in from say

play23:55

Rural and prades into Bangalore is the

play23:57

example they showed and sort of in

play23:59

speaking in telu perhaps getting access

play24:02

uh to information on how they can get

play24:04

housing how should they go about getting

play24:06

the right terms all of the things then

play24:08

think about the sort of you know

play24:10

reducing the um i' would say the stress

play24:14

of being able to get to Services when

play24:17

you come into a new place across uh the

play24:21

the you know across India is fantastic

play24:23

to watch the empowerment it gives to the

play24:25

end the end citizen here but also the

play24:28

empowerment to all of the social

play24:30

Enterprises to be able to use something

play24:32

like this to make a real difference is

play24:33

fantastic to watch um so those are some

play24:37

some of the f i that the ability for you

play24:41

all to build your own AI applications is

play24:44

never been easier never be and and I see

play24:46

it at scale in India so that brings me

play24:48

to the last imperative which is

play24:51

ultimately trust uh because in some

play24:53

sense as we talk about AI we got to talk

play24:56

about safety and Trust as first class CL

play24:58

part of it um it it has a couple of

play25:00

different dimensions the first one is

play25:02

the dimensional security right because

play25:03

again just like how data is important

play25:06

securing your entire AI estate is

play25:09

important whether it's the end points

play25:11

whether it is the identity uh whether

play25:13

it's infrastructure or your applications

play25:15

this is where the zero trust environment

play25:18

uh that we have sort of evangelized and

play25:20

built the product suite for uh becomes

play25:22

very very important because you can't

play25:24

talk about security you've got to

play25:26

operationally operate it right or you

play25:28

have to have operational security

play25:29

posture that matches your rhetoric

play25:32

around security and uh this is everyday

play25:34

exercise uh as somebody said to me you

play25:37

can't get fit by watching others go to

play25:39

the gym you got to go to the gym and

play25:40

this is uh a place where you got to

play25:42

practice that um the second uh piece is

play25:47

uh the safeguards that we have put in

play25:50

place because one of the questions

play25:51

people ask is look in this age of AI

play25:54

who's who what what's happening with my

play25:57

data is my data my data it's absolutely

play25:59

your data will always be your data uh

play26:01

your data is not used to enrich anybody

play26:04

else's models um uh your AI model so if

play26:08

you build let's say a fine-tune model

play26:10

and you deploy it it's protected by

play26:12

using the same security boundaries that

play26:14

we talked about uh and also our

play26:16

commitment to copyright uh

play26:18

indemnification because at the end of

play26:20

the day uh this is all going to be you

play26:22

know a societal decision effectively

play26:24

what is fair use what's the

play26:26

transformative use of data

play26:28

uh very important by the way it's

play26:29

fascinating to watch countries like

play26:31

Japan and others take very enlightened

play26:33

stances around copyright uh because they

play26:36

have sort of seen what has happened um

play26:39

you know in other Paradigm shifts where

play26:42

perhaps they over regulated uh so I

play26:44

think this is something that I think

play26:45

each diff each country will choose its

play26:47

regime the global Norms will emerge but

play26:50

copyright is something that we are are

play26:51

very much on the Forefront of and making

play26:53

sure that there's indemnification

play26:55

directly from us um and then then the

play26:57

last thing is of course the responsible

play26:59

AI framework and even here the you have

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what we have done is we have the

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principles we have taken those

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principles and translated them into a

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set of standards and those standards are

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implemented uh as a set of processes

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starting at the engineering so these are

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not just things that we talk about but

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they're core part of the Engineering

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Process and we have an audit function

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right because it's not just about saying

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things that you literally have to have

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an audit function where you go in and

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say are you managing the process the way

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you said you are and so this is how we

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approaching it all of this is available

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as effectively a set of services for you

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so whenever you are thinking about

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building your own AI applications you

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can go ahead and Implement effectively a

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robust responsible AI framework uh

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around your own AI development so uh so

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that's really uh the three imperatives

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that I at least wanted to share with you

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um I want to wrap up where I started our

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mission at the end of the day is to

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Empower every person and every

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organization in India uh to be able to

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achieve more in this age of AI and in

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that context I'm very excited today to

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even announce a new initiative around

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Skilling uh we are going to C 2 million

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plus uh people in India with AI skills

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uh we think that obviously at the end of

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the day uh really taking uh the the

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workforce and making sure that they have

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the skills in order to be able to thrive

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in this new ages the most important

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thing that any of us can be doing and we

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are you know happy to play our role in

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it but it's not just the skills but it's

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even the jobs that get created and in

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this context I was very inspired when I

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had a chance to meet uh with the folks

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behind Kara in fact it was uh the

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founder of Kara was telling me about how

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a lot of the research that you know was

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the the foundation of it came from

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Microsoft India Microsoft research in

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India it's fantastic that it's now

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translated into this thriving uh

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organization that is taking essentially

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what is AI tasks of labeling uh and

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bringing those jobs very you know wellp

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paying jobs to rural India um and being

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able to really create Economic

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Opportunity uh that is pretty unique and

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it's fantastic to see not only people in

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you know who are software developers

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participating which we know GitHub for

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example in India has more AI Engineers

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or the AI engineering community is

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second to the United States in India uh

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but you even see that R in rural India

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people are participating uh in the AI

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economy uh thanks to the work uh of

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organizations like Kara is fantastic uh

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to see and so let me I think we'll roll

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the video and you'll get to chance to

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meet some of the folks uh who are part

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of

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this India has 22 official languages and

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morati is actually a language that is

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spoken by millions and millions of

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people but unfortunately many Indian

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languages are under resource we cannot

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let language be the thing that does not

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allow you to use technology AI is a

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transformative technology people deserve

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to have access to these amazing

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Technologies in their language Cara

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exists to accelerate social mobility in

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rural India by building AI based

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solutions to help communities our

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workers record sentences in their mother

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tongue on their smartphones and for the

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simple task we pay them nearly 20 times

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the Indian minimum w and that leads to a

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data set so they keep on making

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royalties every single time those data

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sets are resold I think it is imperative

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that if we are changing someone's income

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structure in this way that we also need

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to help them understand financial

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literacy

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K's platform is hosted on Azure we use

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Azure cognitive services for our own AI

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based validation work and we also using

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a your open

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AI if you can solve it for India you can

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solve it for the

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world

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uh anyone may have we have mic's flowing

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around just raise your hand and a

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question yeah go

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ahead

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all

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Related Tags
Tecnología IACrecimiento económicoIndia digitalInfraestructura de cloudAdopción de co-pilotosDesarrollo científicoEmpleo ruralEducación financieraKara AIAzure Cognitive Services
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