Oracle Generative AI Strategy Update
Summary
TLDREn 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
🚀 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.
🤖 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.
🌟 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.
📈 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.
🛒 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.
🔍 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.
Mindmap
Keywords
💡Generative AI
💡Oracle
💡Enterprise Use Cases
💡Talent Acquisition
💡Data Silos
💡Customization
💡Data Security and Privacy
💡OCI Generative AI Service
💡Retrieval Augmented Generation (RAG)
💡Oracle Fusion Applications
💡Data Management
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.
[UPBEAT MUSIC]
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.
[UPBEAT MUSIC]
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.
[UPBEAT MUSIC]
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