JENNY BROWN: With over 300 sessions at Next 2023,
it's understandable that you couldn't get to them all.
So if you didn't see Enterprise Readiness for Generative AI,
then stay tuned because here's the Rewind.
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Generative AI is poised to usher in a new wave of innovation.
And with any new innovation, there
are inherent questions around risks like safety, security,
and privacy.
It's an exciting prospect.
But without getting answers to core questions,
it could be overwhelming.
And with that in mind, the four key enterprise readiness
questions that customers are asking
are, my data is my differentiator,
but how can I protect my IP while customizing foundation
models?
I want to be an AI-everywhere organization.
But how do I deploy AI to every employee
and in every location, while keeping everything
secure and compliant?
I want to scale up to meet the moment.
But how can I scale up with Gen-AI-specific infrastructure
cost effectively, resiliently, and sustainably?
I need to be effective, responsible, and safe.
But how do I make Gen AI work for every end user
while mitigating harms?
So how does Google Cloud address those concerns?
Enterprise readiness is at the core of our approach
to generative AI with our data governance
and privacy, security and compliance
support, infrastructure reliability and sustainability,
and responsible AI.
So let's take a quick look at each of those questions
and how they relate to those core principles.
Question one was, my data is my differentiator,
but how can I protect my IP while customizing foundation
models?
With our data governance and privacy.
You are in full control of your data, not Google.
In fact, your data is only processed
according to your instructions.
Your data is also secure, as we have extensive data governance
and security controls.
And we stand by our commitments to transparency and compliance
with regulations and privacy best practices.
While Gen AI is new, our commitment
to Cloud security and privacy are
inherent because it's built on our Cloud platform.
And privacy by design and default
is built into our entire stack.
We also have adapter layers that allow
you to customize foundation models for your own use cases
while keeping your data private.
Question two was, how do I deploy AI
to every employee in every location
while keeping everything secure and compliant?
With Google Cloud, we have security by design,
by default, and in deployment, including
world-class compliance offerings with multiple levels
of encryption, physical security, and ongoing security
testing, cryptographically secured
identities with a zero-trust model and default
encryption at rest, and suspicious activity monitoring,
malware identification, and encryption
at rest and in transit.
And for generative AI specifically, we
have VPC security controls, customer-managed encryption
keys, and access transparency.
Question three was, how can I scale up with Gen-AI-specific
infrastructure cost effectively, resiliently, and sustainably?
With Google Cloud's infrastructure reliability
and sustainability.
Our infrastructure is resilient and scalable by design,
with 38 regions, 112 availability zones, 187 network
edge locations, and thousands of edge nodes.
We have purpose-built infrastructure
for generative AI with various hardware, speed, scaling,
and price performance options to meet your needs,
built with an open-source software
ecosystem, all of that on the greenest cloud in the industry.
And, finally, question four, how do
I make Gen AI work for every end user while mitigating harms?
With responsible AI.
We were one of the first companies
to articulate AI principles.
These principles put beneficial use, users, safety,
and avoidance of harms as essential business
considerations.
Google Cloud's approach to responsible AI
includes not only how we develop our AI products
but how we enable our customers to innovate
and build responsibly with product and data governance
processes to align our products with our AI principles
in a consistent, repeatable way.
We provide tooling and support to our customers
across the product life cycle, from technical safeguards
and safety filters to citation checks.
We also develop and share research, education,
and best practices for the industry, our customers,
and our partners.
In summary, adopt a platform, not a model.
Whether first party, third party, or open source,
Google Cloud gives you the tools, services,
and infrastructure to make every model enterprise ready.
If you'd like to see the full talk,
check out the link in the description.
And don't forget to subscribe to our YouTube channel
for more great Next Rewind content.
Thanks for watching.
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