Oracle Generative AI Strategy Update

Summary

En el video, Greg Pavlik, vicepresidente senior de Oracle, comparte información sobre la estrategia de IA generativa de la empresa. Destaca cómo la IA generativa está transformando tareas que antes requerían de capital humano, y cómo Oracle se enfoca en construir una IA práctica para resolver problemas de negocio reales. Presenta ejemplos de cómo la IA generativa mejora la adquisición de talentos, aumenta la productividad de analistas y ofrece soluciones para servicios al cliente. Además, habla sobre la importancia de la seguridad de datos y la gestión de modelos personalizados. Se menciona el lanzamiento de OCI Generative AI Service, una solución que permite integrar modelos de lenguaje grande en aplicaciones y flujos de trabajo empresariales personalizados. Finalmente, se exploran las iniciativas futuras y cómo Oracle y Deloitte están trabajando juntos para apoyar a los clientes en su adopción de la IA generativa.

Takeaways

• 🚀 Oracle está enfocado en la generación de IA generativa para casos de uso empresariales reales, en lugar de solo para consumidores individuales.
• 📈 La IA generativa puede mejorar significativamente el proceso de adquisición de talentos automatizando la creación de anuncios de trabajo atractivos.
• 🤖 La integración de IA generativa con conjuntos de datos grandes y dinámicos permite a analistas obtener acceso instantáneo a información resumida y fácil de consumir.
• 💼 Oracle ofrece servicios de IA generativa que incluyen modelos de Cohere y Meta's llama 2, que son más eficientes y adaptables para ser personalizados.
• 🛡️ La personalización de modelos de lenguaje grandes a través de la técnica de afinación fina permite a los clientes mejorar la precisión en tareas críticas para su negocio.
• 🌐 Oracle ha integrado características e servicios de IA generativa en todas las capas de la pila de soluciones de Oracle, lo que permite una mejora continua de los modelos para el beneficio empresarial.
• 🔒 Oracle da prioridad a la gestión de datos, la seguridad de datos y la gobernanza de datos, ya sea en la nube o en entornos locales.
• 📅 Annuciaron la disponibilidad general del OCI Generative AI service el 23 de enero, un servicio totalmente administrado que permite integrar modelos de lenguaje grande en aplicaciones y flujos de trabajo personalizados.
• 📈 La IA generativa puede impulsar la innovación, mejorar procesos y ayudar a las empresas a realizar más tareas, pero requiere un enfoque adecuado para la entrega de la tecnología subyacente.
• 🤝 La colaboración entre Oracle y Deloitte ayuda a los clientes a abordar los desafíos de adopción de IA generativa, proporcionando servicios personalizados y asesoramiento en infraestructura de IA.
• 📈 Los casos de uso donde los clientes obtienen un valor real hoy en día incluyen la asistencia en la escritura y la summarización dentro de las aplicaciones de Fusion, mejorando la productividad y evitando la abandono de tareas.

Q & A

¿Qué es la inteligencia artificial generativa y cómo está impactando el mundo de los negocios?

La inteligencia artificial generativa es la capacidad de las máquinas para realizar tareas que anteriormente requerían de capital humano y esfuerzos para crear y perfeccionar. Está impactando el mundo de los negocios al ayudar a solucionar casos de uso empresariales reales, desde la atracción de talento hasta la productividad de los analistas.

¿Cómo está Oracle enfocado en la construcción de la IA generativa?

Oracle se ha enfocado en construir una IA práctica que ayude a los clientes a resolver sus problemas de negocio reales, automatizando procesos y mejorando la interacción con los candidatos en la contratación de talento, y proporcionando acceso instantáneo a información para analistas.

¿Cómo utiliza la IA generativa Oracle para mejorar la contratación de talento?

La IA generativa de Oracle puede mejorar la contratación de talento al automatizar la creación de anuncios de trabajo atractivos que transmiten claramente los requisitos y criterios de éxito de la posición.

¿Cómo puede la IA generativa ayudar a aumentar la productividad de un analista?

La IA generativa puede ayudar a aumentar la productividad de un analista proporcionándole acceso instantáneo a información de conjuntos de datos dinámicos y grandes, resumida según formatos predeterminados para una fácil consumición, lo que permite la creación de propuestas en pocos minutos.

¿Cómo ha utilizado Intermedia Cloud Communications la IA generativa para mejorar su servicio al cliente?

Intermedia Cloud Communications ha utilizado el servicio OCI Generative AI de Oracle para construir una nueva solución que mejore su departamento de servicios al cliente, automatizando la creación de resúmenes de las interacciones con los ingenieros de servicio y liberando tiempo para que estos se centren en la resolución de problemas de los clientes.

¿Qué enfoques tiene Oracle para entregar la mejor IA para las empresas?

Oracle se enfoca en tres temas: un enfoque único en modelos de alto rendimiento entrenados para escenarios de negocio reales, la integración de la IA generativa en toda la pila de soluciones de Oracle para una fácil adopción y entrega de valor para los clientes, y la priorización de la gestión de datos, seguridad y gobernanza de datos.

¿Cómo es que Oracle permite a los clientes personalizar modelos grandes de lenguaje a través de la técnica llamada afinación?

La afinación de modelos grandes de lenguaje permite a los clientes utilizar sus datos de negocios para proporcionar una mejor precisión en las tareas críticas que el modelo debe realizar para el negocio.

¿Qué es el servicio OCI Generative AI y cuáles son sus principales características?

El servicio OCI Generative AI de Oracle es un servicio totalmente administrado que permite integrar modelos de lenguaje grande en aplicaciones y flujos de trabajo personalizados. Proporciona a los clientes la flexibilidad de elegir entre modelos propietarios de Cohere o el modelo de código abierto Llama 2 de Meta, y ofrece la capacidad de afinación flexible para que las empresas se sientan seguras de que su IA funciona en su contexto de negocio específico.

¿Cómo es que el servicio de agentes de OCI Generative AI permite interactuar con los datos de una empresa?

El servicio de agentes de OCI Generative AI permite tener una conversación con los datos de una empresa. Una vez establecida la conexión con el almacén de datos, los usuarios pueden hacer preguntas sobre sus datos y recibir respuestas y referencias de estos.

¿Qué es la Generación Ampliada por Recuperación (RAG) y cómo beneficia a los profesionales de negocios?

La Generación Ampliada por Recuperación (RAG) combina el poder de los modelos de lenguaje grande con los conjuntos de datos empresariales para proporcionar resultados más precisos, confiables y contextualmente enraizados para los usuarios de negocios. En lugar de confiar únicamente en información no confiable recopilada de Internet, RAG permite que las empresas tengan conversaciones reales con sus propios datos.

¿Cómo está Oracle ayudando a las empresas a adoptar la IA generativa a través de su colaboración con Deloitte?

Oracle y Deloitte están trabajando juntos para abordar los desafíos de adopción de la IA generativa, como la elección de la arquitectura y la tecnología adecuada, la necesidad de modelos específicos para la industria y las preocupaciones de privacidad y seguridad. Ambas empresas ofrecen servicios personalizados, aprovechamiento de las funcionalidades de AI en las aplicaciones de Oracle y asesoramiento para clientes que deseen desarrollar su propia IA generativa.

¿Cuáles son algunos de los casos de uso en los que los clientes están obteniendo valor real de la IA generativa?

Los casos de uso en los que los clientes están obteniendo valor real de la IA generativa incluyen asistentes para compras en la industria de la atención médica y interfaces conversacionales para empleados en grandes cadenas de supermercados, que permiten preguntas y actualizaciones sobre nóminas, W-2s y información de talento y recursos humanos.

¿Por qué están los clientes tan ansiosos por adoptar la IA generativa en estos contextos industriales?

Los clientes están ansiosos por adoptar la IA generativa debido a su potencial para aumentar la eficiencia, mejorar la toma de decisiones a través del acceso a datos y tendencias, y ofrecer experiencias de cliente mejoradas.

¿Qué ventajas ofrece la integración de la IA generativa dentro de las aplicaciones de Oracle Fusion para los clientes?

La integración de la IA generativa en las aplicaciones de Oracle Fusion mejora la productividad para roles como reclutadores, agentes de servicio y gerentes, y ayuda a las empresas a obtener más valor de sus aplicaciones existentes, evitando la 'tiranía de la página en blanco' y facilitando la entrada de datos.

¿Cómo sugiere Miranda Nash que los clientes aborden la decisión de construir o comprar soluciones de IA generativa?

Miranda Nash sugiere que todos deberían probar la tecnología y, a medida que piensen en la ampliación a escala, es donde pueden ser desafiantes. En ese punto, pueden considerar recurrir a una solución de IA integrada, como la ofrecida por Fusion, donde Oracle se encarga del trabajo duro y proporciona una forma fácil de comenzar con la IA para las empresas.

¿Qué novedades están por venir en cuanto a la IA generativa en las aplicaciones de Oracle Fusion?

Las novedades incluyen aprovechar más características en la pila tecnológica, como los agentes de generación ampliada por recuperación y la integración de razonamiento. Esto permitirá a los clientes aprovechar más los datos que poseen, combinada con interacciones de lenguaje natural con los modelos de lenguaje grande.

Outlines

00:00

🚀 Introducción a la estrategia de IA generativa de Oracle

Greg Pavlik, vicepresidente senior de Oracle, presenta la actualización de la estrategia de IA generativa de la empresa. Destaca las recientes novedades y se enfoca en cómo Oracle está construyendo una IA práctica que resuelva problemas de negocio reales. Muestra ejemplos de cómo la IA generativa puede mejorar el reclutamiento de talentos y aumentar la productividad de los analistas, y comparte un caso de éxito con Intermedia Cloud Communications.

05:01

🤖 Generación de AI y su enfoque en el sector empresarial

Oracle se centra en la generación de modelos de IA de alto rendimiento, entrenados para escenarios de negocio real, y en la integración de la IA generativa en toda la pila de soluciones de Oracle para que sea fácil de adoptar y ofrecer valor a los clientes. Se aborda la importancia de la gestión de datos, la seguridad y la gobernanza, tanto en la nube como en entornos locales. Se menciona la OCI Generative AI Service y su capacidad de integración y personalización.

10:02

🌟 Anuncio de servicios de AI generativa y demostraciones

Se anuncia la disponibilidad general de la OCI Generative AI service y se destaca su integración con modelos de Cohere y Meta's llama 2. Se ofrece a los clientes la flexibilidad de elegir entre modelos propietarios o el modelo de código abierto Llama 2, y se resalta la capacidad de afinación fina para satisfacer las necesidades específicas de los negocios. Además, se presenta una demostración de cómo la OCI Generative AI agent service permite interactuar con datos empresariales.

15:03

📈 Soluciones de AI generativa para el sector empresarial

D'Arcy Mathias de Deloitte discute los desafíos que enfrentan las empresas al adoptar la IA generativa, incluyendo la elección de la arquitectura adecuada, la búsqueda de modelos específicos del negocio y las preocupaciones sobre privacidad y seguridad. Explica cómo la colaboración entre Oracle y Deloitte ayuda a los clientes a desarrollar microservicios personalizados, aprovechar las funcionalidades de IA de los productos de Oracle y asesorar en el desarrollo de IA generativa.

20:05

🛒 Generación de AI en aplicaciones de Oracle Fusion

Miranda Nash, vicepresidenta global de Fusion AI, comparte las novedades en la utilización de la IA generativa en las aplicaciones de Oracle Fusion, como la generación de descripciones de trabajo y artículos de conocimiento, y la asistencia en la redacción y resúmenes. Destaca cómo estas funciones mejoran la productividad y la eficacia en tareas y flujos de trabajo diarios, y cómo la infraestructura de Oracle Cloud y las aplicaciones de Fusion trabajan en conjunto para ofrecer una experiencia de IA generativa completa.

25:06

🔍 Próximos pasos y recursos para la IA generativa de Oracle

Greg Pavlik invita a los espectadores a explorar los servicios de IA generativa de Oracle en su sitio web y a leer la serie de blogs First Principles para entender mejor la tecnología detrás de la IA generativa. Resalta la estrategia de Oracle de apoyar a los clientes en su viaje de IA, independientemente de su punto de partida o necesidades específicas en cuanto a la IA.

Keywords

💡Generative AI

Generative AI es una rama de la inteligencia artificial que permite a las máquinas crear contenido original, como texto, imágenes o música, en lugar de simplemente analizar datos existentes. En el video, se destaca cómo Oracle se enfoca en el desarrollo de AI generativa práctica para resolver problemas de negocio reales, como la adquisición de talento y la productividad del analista.

💡Oracle

Oracle es una compañía de tecnología multinacional que ofrece una amplia gama de productos y servicios de software y hardware para empresas. En el contexto del video, Oracle está en el centro de la discusión sobre su estrategia de AI generativa y cómo está integrando y ofreciendo soluciones de AI a sus clientes empresariales.

💡Enterprise Use Cases

Los casos de uso empresarial se refieren a las aplicaciones específicas de la tecnología dentro de una organización para mejorar sus operaciones o resolver problemas específicos. En el video, se discute cómo la AI generativa de Oracle está diseñada para abordar casos de uso empresariales reales, como la automatización de publicaciones de trabajo y la mejora de la productividad del analista.

💡Talent Acquisition

La adquisición de talento es el proceso de atraer, seleccionar y emplear a los mejores candidatos para los puestos de trabajo dentro de una organización. En el video, se menciona que la AI generativa puede mejorar este proceso al automatizar la creación de publicaciones de trabajo atractivas y al establecer interacciones interactivas con los solicitantes.

💡Data Silos

Un silo de datos se refiere a una situación en la que los datos relevantes se aíslan dentro de diferentes departamentos o sistemas de una empresa, lo que dificulta la colaboración y la toma de decisiones informadas. En el video, se discute cómo la combinación de información de conjuntos de datos grandes con una solución de AI generativa puede ayudar a superar los silos de datos y mejorar la productividad del analista.

💡Customization

La personalización implica adaptar un producto o servicio para satisfacer las necesidades específicas de un cliente o usuario. En el video, se destaca la importancia de la personalización en los modelos de AI generativa, donde los clientes pueden usar sus propios datos empresariales para afinar y mejorar la precisión de las tareas críticas que el modelo debe realizar.

💡Data Security and Privacy

La seguridad y la privacidad de los datos son preocupaciones críticas para las empresas, especialmente cuando se utilizan soluciones de AI que manejan información confidencial. En el video, Oracle hace hincapié en la importancia de proteger los datos de sus clientes, asegurando que no se compartan con terceros y se mantengan controles estrictos sobre el uso y la retención de la información.

💡OCI Generative AI Service

OCI Generative AI Service es un servicio de inteligencia artificial ofrecido por Oracle Cloud Infrastructure que permite a las empresas integrar modelos de lenguaje grande en sus aplicaciones y flujos de trabajo personalizados. En el video, se anuncia la disponibilidad general de este servicio y se destaca su flexibilidad para permitir la afinación detallada de modelos de AI para necesidades específicas de negocio.

💡Retrieval Augmented Generation (RAG)

La Generación Ampliada por Recuperación (RAG) es una tecnología que combina el poder de los modelos de lenguaje grandes con los conjuntos de datos empresariales para proporcionar resultados más precisos y confiables para los usuarios de negocios. En el video, se menciona el lanzamiento beta de RAG para OCI Generative AI agents, lo que permite a los profesionales de negocios interactuar con sus conjuntos de datos de manera natural y contextualizada.

💡Oracle Fusion Applications

Oracle Fusion Applications son una suite de aplicaciones empresariales que ofrecen una amplia gama de soluciones para la gestión de negocios, desde recursos humanos hasta cadena de suministro. En el video, se discuten las nuevas funcionalidades de AI generativa que se integran en estas aplicaciones, mejorando la productividad y la eficacia en tareas y flujos de trabajo clave.

💡Data Management

La gestión de datos es el proceso de administrar la recopilación, almacenamiento, mantenimiento, retención y distribución de la información dentro de una organización. En el video, se resalta la importancia de la gestión de datos en la estrategia de AI generativa de Oracle, destacando cómo la infraestructura de OCI y la plataforma de datos moderna de Oracle facilitan la integración y el uso seguro de datos en soluciones de AI.

Highlights

Oracle's generative AI strategy focuses on solving real-world enterprise use cases.

Generative AI can automate the creation of engaging job postings and improve the talent acquisition process.

Oracle uses generative AI to build interactive engagement with applicants, making processes more efficient.

Generative AI solutions can provide instant access to summarized information, improving analyst productivity.

Intermedia Cloud Communications used Oracle's OCI Generative AI Service to enhance their customer services department.

Generative AI can save engineers' time by automating the logging of customer interactions.

Oracle focuses on delivering AI services that are efficient, customizable, and address enterprise needs.

OCI Generative AI Service supports models from Cohere and Meta's Llama 2 for cost-effective and customizable solutions.

Oracle embeds generative AI features across the entire Oracle solution stack for better enterprise refinement.

OCI Generative AI offers flexible fine-tuning, allowing enterprises to tailor AI to their specific business context.

Oracle's generative AI services are designed to integrate seamlessly into custom business applications and workflows.

Retrieval Augmented Generation (RAG) combines large language models with enterprise data for accurate and trustworthy results.

OCI Data Science AI Quick Actions is a no-code feature providing access to various open-source large-language models.

Oracle's collaboration with Deloitte helps customers adopt generative AI by addressing architecture, industry focus, and privacy/security concerns.

Deloitte and Oracle are developing custom microservices leveraging OCI GenAI services for industry-specific applications.

Healthcare and retail are the two industries where Deloitte has initially developed successful generative AI microservices.

Oracle's AI strategy includes a holistic approach, integrating AI offerings through every layer of the Oracle stack.

Oracle AI and Oracle modern data platform are designed to work together for efficient generative AI implementation using an organization's own data.

Oracle Fusion applications are gaining new generative AI capabilities to enhance productivity and effectiveness in core tasks and workflows.

Oracle's infrastructure investments, such as OCI Superclusters, are ideal for training generative AI models at scale.

Transcripts

[UPBEAT MUSIC]

GREG PAVLIK: Hello.

Thanks for joining us today for this update on Oracle's

generative AI strategy.

I'm Greg Pavlik, senior vice president

responsible for Oracle's AI services.

We've had some exciting announcements recently.

Today, I will talk about what we've been working on

and how these updates tie into our generative AI

strategy as a whole.

Before we dive in, a quick housekeeping note.

Make sure to use the comments feature

to ask any questions you may have

throughout our conversation.

We'll do our best to respond back to as many

of you as possible.

Let's get started.

Generative AI, it's showing the amazing ability for machines

to take on work that previously required human capital

and investment to create and to refine.

The challenge is that so many of the examples we see around us

are made for individual consumers

using internet services.

For businesses, successful generative AI

needs to focus on solving real-world enterprise use

cases.

So Oracle has been focused on building

practical AI that helps customers solve

their actual business problems.

Let's take a look at a few examples

of how this has been done.

Attracting top talent in a highly competitive industry

is expensive and often difficult to find

the best fit for a position.

But generative AI can vastly improve the talent acquisition

process.

It can help attract the best candidates

by automating the creation of engaging job postings

that distinctly convey the position's requirements

and success criteria.

We are also using generative AI to build interactive engagement

with applicants, which is much more efficient than older,

more manual processes.

Next, let's take a look at how I can help increase analyst

productivity.

A consulting firm, for example, sourcing necessary information

to complete projects can be difficult due to siloed data

and to siloed teams.

By combining information from dynamic and large data

sets with a generative AI solution

means that analysts can get instant access to information

that can be summarized according to predetermined

formats for easy consumption.

Draft proposals can be created in just minutes, improving

completion time and increasing competitiveness.

Next, I'd like to share some customer insights with you.

One of the biggest challenges we see customers face

is deciding how to make generative

AI useful for their enterprises, but it's not as hard

as you might think.

Intermedia Cloud Communications is

a leading provider for unified communications, voice over IP,

and identity and security services.

They used our OCI Generative AI Service

to build a new solution to further improve

their award-winning customer services department.

Their department has to run 24/7, 365 days a year

with thousands of chats and calls coming in

and hundreds of engineers working

to make their customers happy.

As you can imagine, an engineer's time

is best spent solving customer problems

rather than the task of logging interactions.

Intermedia story involves the steps

that follow an interaction with a customer service engineer.

Let's hear from Urvashi Sheth, chief customer

officer at Intermedia.

[VIDEO PLAYBACK]

- There's a summary that an agent or an engineer

has to prepare and send it as an email.

It takes another three or four minutes.

So what we decided that let's work with Oracle

and create a GenAI AI-based summary out

of the transcription of that chat.

So what does it do?

It saves about three to four minutes of that agent's time

or that engineer's time.

And that engineer can help us think about how do we

make the troubleshooting better, we

can use her expertise somewhere else

and get GenAI to summarize that call or that chat

and send the email very quickly.

Now, think about that three minutes

and multiply it with thousands of calls, how much time you're

saving using GenAI.

[END PLAYBACK]

GREG PAVLIK: Generative AI can drive innovation, improve

processes, and help companies accomplish more tasks,

but it requires the right approach

to delivering the underlying technology, the science,

and the solutions.

That's why Oracle focuses on delivering the best

AI available for enterprises.

We have been working on three themes.

First, a unique focus on high-performing models

trained for real business scenarios

to address generative AI requirements

for the enterprise.

Second, generative AI that we've embedded

across the entire Oracle stack for easy uptake and value

delivery for our customers.

And finally, we prioritize data management, data security,

and data governance, whether in the cloud or on-premise.

One of Oracle's key initiatives is

centered around providing enterprise-focused models that

are both efficient and customizable.

The OCI Generative AI Service supports models from Cohere

and Meta's llama 2.

Because these models are smaller in size

than some of the consumer-focused models,

they are more cost effective to run

and are more capable of being customized.

Customization of large language models

through a technique called fine-tuning,

allows customers to use their business data

to provide better accuracy on critical tasks

that the model must perform for the business.

We embed generative AI features and services

across every layer of the Oracle solution

stack, which means we're building AI where you need it.

By doing that, we can continue to refine the models to make

them better for enterprises.

Oracle's continued work across industries and cloud

applications enables us to get to customers

and help them to move quickly with generative AI solutions.

It allows us to continually refine

the models to make them more useful for your business.

Lastly, you want the right protections and controls

for your enterprise AI projects and data.

Oracle prioritizes data security and privacy.

We don't share your data or your custom models

with any third-party model providers.

[UPBEAT MUSIC]

After a very successful beta program,

we announced the general availability

of the OCI Generative AI service on January 23.

It's a fully managed service available to seamlessly

integrate large language models into your custom

business applications and your workflows.

OCI Generative AI provides customers

with the flexibility to choose between proprietary models

from Cohere or Meta's open-source model Llama 2.

As I noted, we selected these models from both providers

because they are efficient and adaptable,

so organizations can use their own data

to fine-tune the models to meet their specific business needs.

For our beta customers, you'll be

pleased to know we've enhanced the user

experience with improvements like LangChain

for easy integration, simplified endpoint management,

and even more content moderation.

Most importantly, OCI Generative AI offers flexible fine-tuning.

As a result, enterprises can feel confident

that their AI works for their specific business context.

And with that, we'd like to show you

what you can do with generative AI in the real world.

Let's take a look at a quick demo.

[UPBEAT MUSIC]

[VIDEO PLAYBACK]

- The OCI Generative AI agent service

allows you to have a conversation with your data.

All you need to do is direct the service

towards your data store.

In the beta release, we support OpenSearch as a data store.

Once the connection has been established,

you will be able to ask questions about your data

and receive answers, as well as references from your data.

For this demo, I've created an OpenSearch index

and called it 10-Ks, and loaded it

with 10-K filings for several large corporations.

A 10-K is a comprehensive report filed annually

by publicly traded companies about

their financial performance.

Using the agent service configuration pages,

I was able to connect my OpenSearch

index to the service.

Now that everything is ready, let's ask the agent

some questions about our data.

First, I'll start with a generic question about Oracle.

As you can see, the agent understood the question,

extracted the relevant information

from the data store, and summarized

it to construct a response.

The agent accomplished these tasks

while leveraging OCI's generative AI infrastructure.

For my next question, I'm going to ask

some more specific information about Oracle's cloud

as described in the 10-K. As you can see,

the agent responded not only with summarized information

from the data store, but also provided

a reference to the original document from which

the information was extracted.

Clicking the link in the reference

will take me to the original document.

The agent exposes an API endpoint,

which allows you to incorporate the agent

into your own applications.

[END PLAYBACK]

GREG PAVLIK: Now that we've seen generative AI in action,

let's talk more about what Oracle has available today.

We've also recently announced the beta release

of Retrieval Augmented Generation for OCI Generative

AI agents.

This new service harnesses AI to provide business professionals

with the ability to have natural language

interactions with large language models

that are grounded in their enterprise data sets.

Retrieval Augmented Generation, or RAG,

combines the power of large language models with enterprise

data, ensuring more accurate, trustworthy,

and contextually grounded results for business users.

Instead of only relying on unreliable, untrustworthy

information gathered from across the internet, in other words,

you can now have actual conversations

with your own data.

The initial beta release integrates

with OpenSearch and upcoming releases

will provide access to database capabilities in both Oracle

Database 23c and MySQL HeatWave.

For enterprises that want an easy way

to work with additional large-language models,

we also announced OCI Data Science AI Quick Actions.

This is a no-code feature of the OCI Data Science service that

enables access to a variety of open-source large-language

models, including options from Meta, Mistral AI, and more.

Once generally available, this feature

will support even more models that users

can fine-tune, evaluate, and deploy together

with their data.

We think this is the most compelling GenAI

offering for the enterprise, but don't just

take our word for it.

As you can see here, IDC's chief analyst Ritu Jyoti

says that, "With a common architecture for generative

AI that is being integrated across the Oracle ecosystem,

Oracle greatly simplifies the process for organizations

to deploy generative AI with their existing business

operations."

And as Futurum cloud analyst Ron Westfall said, "There's RAG

then there's RAG done right.

Oracle has delivered RAG the way the enterprise actually

want to consume it-- by prioritizing

data management, security, and governance to help

ensure enterprise-grade AI."

[UPBEAT MUSIC]

Joining me today from Deloitte is the company's global Oracle

offering and GenAI leader, D'Arcy Mathias.

Welcome, D'Arcy.

Every day we're hearing about new advances

in the world of generative AI, but we

know that there are challenges for enterprises.

So what are some of the challenges

that customers are facing when they're

trying to adopt generative AI?

D'ARCY MATHIAS: That's a great question, Greg.

And first of all, thanks for the opportunity

to be with you here today.

GenAI is absolutely a core aspect of our strategy,

as well as many of our clients.

And it seems like you can't get through a meeting

without somebody talking about GenAI and how it can help them.

However, it does come with certain barriers and challenges

that the vast majority of our clients are facing.

And there's really three key ones that come to mind.

The first challenge has to do with being

able to pick the right architecture

and technology that seamlessly integrates with what they've

already invested in with respect to an overall enterprise,

architecture, and their data structure.

So minimizing disruption from a tech perspective is number one.

Number two, what we're seeing is the first generation of GenAI

have typically been general purpose models,

and what clients are looking for is something more

specific to their business.

So an industry focus that really speaks

to their core objectives.

And the third one, which is probably the most relevant one

that comes up a lot has to do with an overarching concern

about privacy and security.

Understanding levels of access, how their data is being used,

and making sure they control the overall retention

of that data over the life of their GenAI investment.

Those are the three key areas where

we're seeing clients want to be very deliberate about planning

how they get on the GenAI journey,

but us Deloitte with Oracle are working hand

in hand to make sure that we address those three issues

with them to get them going.

GREG PAVLIK: One of the things that I

think would be great to get some insight into

is how does the Oracle/Deloitte collaboration really help

customers when it comes specifically to generative AI?

D'ARCY MATHIAS: It's a great question.

So Deloitte's global Oracle practice is broad in nature.

We cover basically everything that Oracle does,

and that feeds into our GenAI strategy, which

is very well aligned with Oracle strategy

and it falls into a three-pronged approach.

The first approach we have is to develop

custom microservices, Deloitte-led but leveraging

Oracle's OCI GenAI services, very industry-specific, very

targeted to how the clients want to achieve their outcomes using

GenAI.

The second area is around working with the Oracle product

roadmap and the AI functionality that's coming through the apps,

and working with our clients to make sure they take advantage

of those apps that are made available through the regular

updates from a SaaS perspective, and also making

sure that those AI capabilities are really

complementing the custom build in the first point.

And the third area, Greg, has to do

with advising our clients who want to do their own GenAI

development, and making sure they have the GenAI

infrastructure leveraging Oracle OCI and GenAI services.

And all three of those key pillars of our strategy

are very much aligned with what Oracle is doing, obviously,

and we go hand in hand with them to support our clients

across all three areas.

GREG PAVLIK: What are the use cases where you're seeing

customers get real value today?

What's being successful as you're going to market

and working with real clients?

D'ARCY MATHIAS: So what we did at the very beginning

of our GenAI journey was to take a real strong, industry-centric

approach to our conversation.

We met with a number of our global industry leaders,

as well as our key clients across basically any industry

to really understand what some of the use cases

were for them specifically to drive the benefit out of GenAI.

We started with that.

And then from there, we picked the top two industries

that would have the most immediate impact

from an investment around GenAI, and those

are health and retail.

On the health care side, the very first microservice

that we have created is a buyer's assistant.

It's very specific to health care

and it allows them to take advantage

of sourcing and procurement best practices to make sure

that as they're buying new product, that they're

able to take advantage of all the intelligence, all

the trends that are available to them.

For retail client industry, we have developed microservices

that are for our large grocery chain that

is a conversational interface for employees.

It allows them to ask questions about their payroll,

to view their W-2s.

They can also use this microservice

to make updates to their talent and HR information as well.

Those are the two initial industries

that we're starting to see a lot of traction, a lot of appetite

to be early adopters, but the other industries

are coming along quite quickly.

GREG PAVLIK: D'Arcy, can you elaborate

on why these customers are so eager to adopt generative AI

and apply them in these industry settings?

D'ARCY MATHIAS: It's really around the potential

for increased efficiency.

So efficiency was really the first one

that came up very consistently, looking for opportunities

to leverage AI and GenAI to help them do their business better.

The second one was better decision making really

around management decision making, access

to data and trends.

And the third one had to do with improved customer experiences.

Those are the three major reasons

that we've heard when we spoke to executives

across key industries.

I also want to mention that although we did build out

the first wave of microservices primarily for a grocery

chain, as well as health care, we've

architected those microservices to be easily ported

to other industries because we're talking about client

or customer engagement, as well as procurement and sourcing.

Those can easily apply to other industries.

And the next wave of industries that we're working on right now

include financial services, communications, and energy.

GREG PAVLIK: Thank you so much for your time, D'Arcy.

D'ARCY MATHIAS: Thanks, Greg.

I really appreciate the opportunity

to speak with you today.

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GREG PAVLIK: At Oracle, we're taking a holistic approach

to creating AI for the enterprise.

We're not just thinking about new managed services

for delivering generative AI, we're

thinking through the entire experience

and reimagining what's possible in a business context.

Built on our high-performing infrastructure,

we have integrated our AI offerings

through every layer of the Oracle stack

to create a complete generative AI experience for enterprises.

At Oracle, AI is designed to be a seamless experience,

not something you need to integrate and assemble

yourself.

Our infrastructure investments focus on OCI Superclusters

that provide ultra-fast clustering networking HPC

storage and efficient bare metal instances.

OCI Superclusters are ideal for training generative AI models

at scale.

A question we often hear is, how do I really

implement a solution that uses my own data as the basis

for its generative AI work?

Oracle AI and Oracle modern data platform

are the perfect pair for this scenario.

Organizations can now benefit from all the power of AI

directly embedded within their data management services,

including Oracle Autonomous Database,

and interact in natural language with their data securely.

Building applications using our generative AI services together

with Oracle's database offerings is simple

because they're engineered to work together.

You'll be able to use the data already stored in your Oracle

Database or in your MySQL database,

and leverage the vector database capabilities

that the latest releases of these two extremely popular

databases will soon offer.

OCI's generative AI also forms the basis

for generative AI capabilities embedded

across Oracle's suite of SaaS applications,

including Oracle Fusion applications, Oracle

NetSuite, and industry applications such as Oracle

Health.

These AI capabilities are placed directly

in the hands of your workforce via the software environments

that they use every day so they can achieve

higher levels of productivity and effectiveness

in their core tasks and workflows.

Later we will look at how Fusion Cloud applications are gaining

new generative AI capabilities.

This tight collaboration between infrastructure platform

services and applications enables a faster innovation

cycle for Oracle's customers worldwide.

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Now, my very last guest today is our Fusion AI global vice

president Miranda Nash.

Welcome, Miranda.

Thank you for joining us.

So the Fusion team had a lot of exciting announcements

at CloudWorld around using generative AI.

For those who weren't able to make CloudWorld,

can you bring us up to speed?

MIRANDA NASH: Sure.

We announced a whole series of new features embedded

right within the Fusion existing workflows.

So for example, generating a job description,

generating a knowledge article, generating item descriptions

in a supply chain context.

So they center around assisted authoring and summarization use

cases.

So another example is summarizing existing

performance feedback in the system

and using that as a starting point

for writing your annual review.

GREG PAVLIK: So for Fusion customers then,

what are the benefits for using generative

AI inside the applications?

MIRANDA NASH: They really center around productivity.

So we enhance productivity for all kinds of roles,

whether you're a recruiter, a service agent, a manager.

And it's not just individual productivity,

but helping businesses get more value out

of their applications.

So for example, we noticed that abandonment rates are pretty

high when people have to type and when they

have to write in the system.

So rather than having that, we avoid the tyranny

of the blank page, and that helps

all customers get more value from their existing Fusion

investment.

GREG PAVLIK: Great.

So then when customers are using Oracle Fusion apps,

it's running on top of the Oracle Cloud infrastructure,

what makes that important?

What's the value that comes from the combination of the two?

MIRANDA NASH: I think it's reflected by us sitting here

chatting today, as colleagues and as service provider

and internal customer.

This interaction between the applications and the tech stack

is the powerful feedback loop that

benefits all of our customers.

Again, whether that's we get the benefits

of really fast innovation on your side,

and then you get the benefits of really very real-world

enterprise use cases.

GREG PAVLIK: When customers see that this functionality is

available, it gives them options.

They could decide to build the solution themselves

using the OCI Generative AI Service,

or they could decide to consume generative AI

through Fusion apps.

How do you advise customers really

to approach this build versus buy decision point?

MIRANDA NASH: Well, we think everyone should try it.

Without a doubt, try it.

And then as you start to think about rolling out at scale,

that's where things can get challenging.

You need the expertise, you need evaluation,

you need guardrails.

And that's where companies could consider

turning to an embedded AI solution,

for example, as part of Fusion.

We take care of that hard work for them.

And that's a really easy way for companies

to get started with AI.

GREG PAVLIK: That makes a lot of sense,

and you can really see that we're bringing value

to the customer through Fusion applications

and allowing people to get an on-ramp to generative

AI that's easy and powerful.

What's coming next?

MIRANDA NASH: We're excited about taking

more advantage of features in the tech stack,

for example, retrieval augmented generation, agents,

and getting into reasoning as well.

So this just allows customers to take

more advantage of the data they have,

along with the natural language interactions with the LLM.

So as an example, in a supply chain context for a maintenance

product, we may want to read a manual, very complicated

technical manual and then have the AI suggest some steps

for a maintenance plan.

So that's an example of what we'll be seeing coming soon.

GREG PAVLIK: That's great context.

Thank you so much, Miranda.

MIRANDA NASH: Thanks, Greg.

GREG PAVLIK: And to all of you watching today,

thank you so much for tuning in.

Together the services I've just described

and many others make up the Oracle AI ecosystem

with offerings that span business apps, platform

services, data management, and AI infrastructure.

It's part of our AI strategy to ensure

that we're here to support you no matter

where you are in your AI journey and what kind of AI you need.

To get started with Oracle's generative AI services,

be sure to visit our website at Oracle.com/GenAI.

And lastly, check out the most recent post

in our First Principles blog series for a deep dive

into the technology behind our generative AI capabilities.

We're so glad you joined us today

to learn about the exciting innovations

that Oracle has to offer.

We'll see you next time.

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