Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Oracle's infrastructure as a service business gained momentum in the fourth quarter courtesy of generative AI workloads, according to CTO Larry Ellison. The company's cloud business also showed strong sales with the addition of Cerner.

The database, cloud and ERP company reported fourth quarter earnings of $1.19 a share on revenue of $13.8 billion, up 17% from a year ago. Non-GAAP earnings for the fourth quarter were $1.67 a share. Cerner contributed $1.5 billion in revenue in the fourth quarter. Wall Street was expecting Oracle to report non-GAAP earnings of $1.58 a share on revenue of $13.73 billion.

For fiscal 2023, Oracle reported net income of $8.5 billion, or $3.07 a share, on revenue of $50 billion, up 18% from a year ago. Non-GAAP fiscal 2023 earnings were $5.12 a share.

In a statement, Ellison said Oracle's IaaS landed more than $2 billion in deals for its Oracle Gen2 Cloud. Ellison said Nvidia is using its clusters as are LLM developers such as Mosaic ML, Adept AI and Cohere. "Our GPU clusters are built using the highest-bandwidth and lowest-latency RDMA network—and scale up to 32,000 GPUs," said Ellison.

CEO Safra Catz said infrastructure growth is accelerating with fourth quarter sales up 77% from a year ago. 

On a conference call, Catz said organic revenue growth is accelerating and the cloud has transformed Oracle's business and culture. "Consumption of our Gen-2 cloud is 7x larger. Our cloud infrastructure growth rate has doubled from last year," she said. "We're at the middle of the beginning."

"Our exploding AI demand leaves us with significant upside," she said. "Customers are choosing to run on Oracle infrastructure."

AWS, Microsoft Azure, Google Cloud themes: Optimization, generative AI and the long game

On applications, Catz said the combination of Fusion ERP and NetSuite means Oracle can support customers of all sizes. Catz said cloud database workloads will also fuel growth in the future as on-premise databases migrate to the cloud. Overall, she said gross margins in the cloud business will improve even as Oracle builds out its infrastructure.

Even though Oracle's IaaS business remains smaller than the big three--Amazon Web Services, Microsoft Azure and Google Cloud--its growth rates are higher in comparison. For context, Oracle's annual IaaS revenue run rate exiting the fourth quarter is $5.6 billion. Comparisons across the cloud providers are tricky since few break out only IaaS sales.

On a conference call, Ellison said Oracle Cloud Infrastructure's Gen2 architecture, hardware and software can deliver higher performance for AI workloads. "In the cloud where you pay by the minute if you run twice as fast you pay half as much," said Ellison.

He said generative AI demand will drive returns for both applications and its cloud business as well as internally. "The biggest strategic difference is that we use our infrastructure and build enterprise scale applications with it. We have a continuous feedback loop and improvements in productivity," said Ellison. "By being in applications and infrastructure we make both better."

That feedback loop between cloud, hardware and applications means Oracle's cloud unit is suited well for generative AI training, said Ellison. He touted a partnership with Nvidia to scale AI workloads. He added that Oracle is launching a generative AI service designed to protect enterprise training data while implementing large language models. Salesforce is also targeting the same use case via an abstraction layer to protect corporate data when training LLMs.

Ellison said specialized LLMs will be instrumental to industries such as healthcare. Oracle Cloud is working with Cohere to train specialized models.

By the numbers for the fourth quarter:

• IaaS cloud revenue in the fourth quarter was $1.4 billion, up 76% from year.
• Cloud revenue in the fourth quarter was $4.4 billion, up 54%. Excluding Cerner, cloud revenue for fourth quarter was up 33%.
• Cloud application revenue was $3 billion, up 45%.
• Fusion Cloud ERP revenue was $700 million, up 26%
• NetSuite Cloud ERP revenue was $700 million, up 22%. It's worth noting that Oracle's core cloud ERP suite now has the same revenue as NetSuite.
• R&D was 17% of revenue for the year ending May 31.

For fiscal 2023, Oracle reported total cloud services and licenses support revenue of $35.3 billion.

Oracle said it added Children’s National Hospital, Daiwa Securities Group, DHL Supply Chain, Emerson, GitLab, Mayo Clinic, Skecher as customers in the fourth quarter.

As for the outlook, Catz said Oracle Cloud Infrastructure will have another strong year. Cloud capital spending in fiscal 2024 will be on par with fiscal 2023. For the first quarter, Catz said total revenue will grow from 7% to 9% with added upside depending on capacity. Cloud revenue will grow 28% to 30%. Non-GAAP earnings will be between $1.12 a share to $1.16 a share.

For fiscal 2024, Catz said Oracle is seeing strong demand for AI workloads. Cloud revenue including Cerner will grow at similar rates in 2024 compared to 2023.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Salesforce launched AI Cloud, which aims to be the layer that keeps corporate data private and secure as enterprises roll out generative AI and large language models.

As previously reported, enterprises are focused on generative AI, LLMs and the productivity and cost savings those technologies provide but are wary about keeping corporate data private. The aim for many enterprises is to take foundational models from multiple providers and add their corporate data to it for competitive advantage.

Salesforce, which already houses enterprise data via CRM and its Data Cloud, is aiming to be that abstraction layer between foundational models and enterprise data. Indeed, a Salesforce survey found that 73% of employees believe generative AI will introduce security risks.

AI Cloud includes the Einstein Trust Layer to preserve data privacy and security as foundational models are used in the enterprise. Einstein Trust Layer prevents LLMs from retaining sensitive customer data. AI Cloud also includes Salesforce's existing AI technologies across its portfolio (Tableau, Salesforce, Flow and MuleSoft) including Einstein and its recent Commerce GPT and Marketing GPT. 

As for pricing, Salesforce is offering an AI Cloud Starter Pack for $360,000 annually with an annual contract. The AI Cloud Starter Pack includes Data Cloud, MuleSoft automation, Tableau Analytics, Slack, CRM and an AI readiness assessment from Salesforce services.

• Salesforce launches Marketing GPT, Commerce GPT, aims to connect generative AI to ROI
• Salesforce Q1 better than expected, margins improve
• Slack GPT plans to integrate language models, summarize conversations, offer writing tips
• Tableau Pulse aims to bring analytics, insights to business users

The AI Cloud Starter Pack includes:

• CRM: 50 Unlimted Edition Licenses.
• Slack: 50 Enterprise Licenses.
• Tableau: 50 Explorer Licenses. 
• Einstein: Usage.
• MuleSoft: Usage.
• Data Cloud: Usage.
• Salesforce Services: AI Coach for Readiness.

The price depending on the size of the company will vary. Services can be delivered by integrators such as Accenture, Deloitte and PwC. Large enterprises will also have more licenses beyond the starter pack and change management will also need to be considered.

The biggest takeaway from Salesforce's AI Cloud is that it can host LLMs from Amazon Web Services, Anthropic, Cohere and others within Salesforce infrastructure. Salesforce also has a partnership with OpenAI to keep data retained inside of Salesforce.

Other key points about AI Cloud include:

• Customers of AI Cloud can use Salesforce LLMs for code generation and business process automation. Salesforce LLMs include CodeGen, CodeT5+ and CodeTF.
• Users can bring their own models and can connect Amazon SageMaker and Google Vertex AI directly to AI Cloud via Einstein GPT Trust Layer.
• Generative AI will be embedded into Salesforce's portfolio.
• AI prompts will be optimized and be context-rich across sales, service, marketing and IT teams.
• Einstein GPT Trust Layer will be generally available this month with Service GPT. Sales GPT is in pilot with general availability in July.

Benioff: Trusted AI is critical

At an event in New York City, Salesforce CEO Marc Benioff said the company has been working with select customers on generative AI for the last year and a half.

For instance, Vasilis Dimitropoulos, VP Global Gucci 9 and Product Care at Gucci, said his company was "business case zero in AI." Dimitropoulos said Gucci took LLMs from Salesforce, complemented them with internal data and ultimately looked to "Gucci-fy" generative AI so it could help multiple functions.

AAA was a customer trying to balance security, hype and innovation. Generative AI at AAA is initially focused on customer service, support and DevOps. 

F1 was also cited as a Salesforce customer that was connecting to data sources via MuleSoft, harmonizing data in Data Cloud and then providing a unified view of a customer that can be used for generative AI personalized marketing campaigns.

Benioff said generative AI can take data from the call center, enable customer service reps as well as sales, commerce and marketing. "One of the great promises of generative AI to augment humans," said Benioff.

The caveat with generative AI is that it can also lead to data issues. "The onus is on us to give enterprises the next generation of AI," said Benioff.

He added that trust is critical. In 1999, Salesforce had to create a sharing model where customers could block off data. In 2016, Salesforce enabled private prediction training with anonymous predictions across the platform. For 2023, Salesforce is offering private generative training. "Customers have the ability to use generative AI without sacrificing data privacy and security," said Benioff. "It's not just about trusted AI. It's also about responsibility. We're all on a societal AI journey. We've all seen where this could go. Responsible AI use is so critical."

Benioff said:

"When we look at these new models, there's a big AI trust gap over privacy, hallucinations, data control, bias and toxicity. These are technical terms that's actually happening inside of these models."

A look at the trust model

Salesforce executives walked through the AI Cloud and how it is architected to preserve corporate data. Key items:

• LLMs don't have control over recall. Salesforce will be able to show customers the lineage of data and where it's stored.
• The Einstein GPT Trust layer includes inter and intra enterprise trust, anonymized zero retention generation and an open model approach.
• AI Cloud will leverage Customer 360 data from CRM, Slack and engagement events.
• AI will be able to be used for workflows across departments, outcomes and generative AI tools.

Salesforce's Patrick Stokes, EVP and general manager of platform at Salesforce, walked through how generative AI prompts can include instructions based on logic instruction and details from within a corporate data sets. "Consider all of the data that Salesforce has as well as the context. This is all data that we can add to the prompt for better generation on the other side," said Stokes.

Stokes added that the Einstein GPT Trust Layer can securely retrieve data, mask data for PIAA so it can't be used and erase the prompt completely. "We can delete the prompt so it is never learned by the LLM," said Stokes.

Here's a look at the architecture behind AI Cloud including the trust layer as well as models involved.

Ultimately, there will be multiple models. Enterprises will pick models based on costs as well as efficiency. There will be models focused on use cases and tethered to business outcomes, said Srini Tallapragada, President and Chief Engineering Officer at Salesforce. "We don't want to pick models for you," he said. "Right LLM for the right task is important."

That theme about right model for the right job has been popping up repeatedly among CIOs. For instance, Goldman Sachs CIO Marco Argenti said that his company is likely to use a broad range of smaller models. See: Goldman Sachs CIO Marco Argenti on AI, data, mental models for disruption

Tallapragada said enterprises will be able to build their own generative AI models. Demos were focused on personalization, code building using generative AI for developers and multiple use cases. 

How enterprises are approaching generative AI

Enterprises CIOs and CXOs have said that generative AI is promising, but security and data privacy are critical. There's also the need for data architecture to support AI. Salesforce's plan is to argue that its AI Cloud and the combination of LLMs and human feedback will better deliver business outcomes specific to tasks and industries. 

Here's a look at what CXOs are saying about generative AI. 

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Commercial PCs are going to become more powerful and more expensive as enterprises configure them for data science, analytics and model training. As a result, you can expect your work laptop to resemble workstations in terms of specifications.

Enter the PC for the "data center stack" and AI model training. Just like generative AI is reshaping data center spending, the PC may have premium configurations in the future.hether PC demand has bottomed remains an open question. PC executives note that the devices acquired in 2021 will be replaced in the years ahead and the overall market is larger than it was before the COVID-19 pandemic. PC shipments in the first quarter were down 29% from a year ago, according to IDC.

PC executives, however, are hopeful demand will start to improve in part because enterprises will need devices capable of handling generative AI models, data science, analytics and collaboration workloads.

• How Generative AI Has Supercharged the Future of Work

Speaking at a recent investment conference, HP CFO Marie Myers said that the PC is going to evolve. Myers said:

"First of all, I'd say the data science stack. There's no doubt, the data scientists need a rich configuration. We feel we're well positioned in terms of driving and delivering on that opportunity. Right now, we're really building out a stack for data scientists that I'm really excited about. And that configuration, I think, is going to be available on the market. The second piece is just the PC itself. If you're going to use things like Microsoft Co-pilot, you're going to need a richer configuration inside your laptop to drive that and enable that ability.

Finally, we see an opportunity that's probably differentiated around the fact that people are going to tend to work on the edge. A lot of what we've done has been cloud. But as data moves closer and people are really worried about privacy and security, you don't want to necessarily, build a model and have all of that data exposed in the cloud. So, there is an interesting opportunity that certainly we're starting to explore around working on the edge and what that laptop configuration would look like in that area is quite unique and different."

Sam Burd, President of Dell Technologies' Client Solutions Group, had a similar take. Speaking at an investor conference, Burd said:

"We're seeing today AI models running on workstations where you can run 5 million to 500 million parameter models. And we see this trend in business spaces or an approach where businesses are going to want to do AI in their environment, on their data, on devices that they have.

Think about that workstation environment coming to more mainstream PCs, where we see the advent of offload engines and NPUs or VPUs that add AI processing capability on CPUs that will be available on the architecture in the future."

Lenovo CEO Yang Yuanqing said on Lenovo's recent earnings conference call that "PCs are still the essential productivity tool in this digital era" and demand will pick up in the second half into 2024.

Yuanqing said hybrid work and digitization will spur PC upgrades. In addition, the definition of productivity will change.

Here's where the PC is headed.

• PCs will handle select AI workloads.
• Co-pilot-powered applications will need richer configurations.
• GPUs will take on more importance.
• Collaboration including Microsoft Teams and Zoom will use more PC power.
• CIOs see PCs as critical to increasing productivity but will look for subscription models to smooth out spending.
• Role based configurations on PCs for AI and data science will become the norm.

Also see: Dell Technologies Q1 better than expected, but sales fell 20% from a year ago

HP: AI can change the role of PCs

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Adobe is scaling its Firefly Generative AI across enterprise content workflows and embedding it into Adobe Express. The upshot is that enterprises will be able to safely scale on-brand images, video and text using generative AI.

The news, announced at Adobe Summit EMEA 2023, is the next step in scaling Firefly by embedding it in Adobe's portfolio of apps and Creative Cloud for enterprises. Adobe is looking to expand its market from creative pros, marketing and communications to knowledge workers including regional field marketing, sales, product, customer success and other roles. The idea is that content creation can be democratized within the enterprise. 

Here's what you need to know:

Adobe Firefly and Express

• Adobe Firefly Generative AI is now integrated into Adobe Express, Adobe's all-in-one content creation app that has a new version in beta.
• Adobe Express brings together photo, design, video, document and generative AI tools into one editor.
• Adobe Express is integrated into Creative Cloud and Experience Manager.
• Firefly content is trained on Adobe stock and publicly available images and tagged with Content Credentials, which provides transparency into the origin of content.
• Adobe and Google will partner to bring Firefly and Express to Google's Bard AI service. Creators will be able to describe their vision in bard to create Firefly generated images directly in Bard and then modify in Express.
• The new Adobe Express adds a bevy of new features including PDF support, collaboration tools and animations to name a few.
• Adobe Express is available today in beta for the desktop version with a mobile version on deck. 

Adobe Firefly and Adobe Express go enterprise

• Firefly for Enterprise makes the generative AI technology available companywide for content creation and editing in Express, Experience Manager or Creative Cloud.
• Firefly for Enterprise will be available via the standalone Firefly application as well as Express and Creative Cloud.
• Firefly will leverage Adobe's collection of templates, fonts, stock images, videos and music and can combine with a company's branded assets via API.
• Enterprises "have the opportunity to obtain an IP indemnity from Adobe for content generated by certain Firefly-powered workflows."

The big picture

Since Adobe launched Firefly content creators have been busy generating new images. Since March, Firefly beta users have generated more than 200 images. Photoshop users have generated more than 150 million images in two weeks using the Generative Fill feature.

Given Adobe can provide enterprises IP indemnity it's likely that businesses will quickly look to automate and scale content creation. Indeed, Adobe said companies such as IBM, Dentsu and Mattel are experimenting with Firefly to "drive efficiencies, reduce costs and accelerate their content supply chains."

ChatGPT: Hype or the Future of Customer Experience

This acceleration of content supply chains blends together well with Salesforce's efforts with Marketing GPT and Commerce GPT. Adobe is infusing generative AI across its portfolio at a rapid clip. For instance, Adobe also added Adobe Sensei GenAI, a co-pilot for marketers and customer experience teams, to Adobe Experience Cloud applications.

Constellation Research analyst Liz Miller said:

"Generative AI and the creative power of Adobe Firefly opens up a whole new age of creativity. Coupled with the features of Adobe Express we are inviting a whole new team to the creative table...literally anyone who wants to create. Adobe made a promise a couple years back to democratize creativity. These announcements bring that into an easy to use, accessible to all formats. Express in an enterprise environment means assets created for social to assets created in customer service now all reside within the enterprise for use. That...and Firefly and Express are just fun to use."

What remains to be seen is whether these generative AI efforts will create branded content sprawl and how enterprises will manage it. On an analyst briefing, Adobe's Matthew Purdon, Sr. Product Director, Digital Media B2B, said that enterprises will develop policies about how and when generative AI can be used for their brand content. "There will be controls around this as well. It is early days," said Purdon, who added that "there will be best practices for review and approval."

More: 

• Goldman Sachs CIO Marco Argenti on AI, data, mental models for disruption

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Google Cloud is ramping up its generative AI partnerships and customers as its Generative AI support on Vertex AI is generally available.

The company followed up on its Google I/O announcements revolving around Google Cloud models and generative AI with partnerships with the likes of SAP, Salesforce, Twilio and collaborations with Mayo Clinic. Customer announcements included Priceline, GA Telesis, and PhotoRoom.

Google Cloud's barrage of announcements highlight how vendors are moving quickly to embed generative AI into platforms. Salesforce also announced Marketing GPT and Commerce GPT and will hook up its Data Cloud with Google Cloud models.

For enterprise customers, these generative AI partnerships mean they will be able to use foundations models and build on top of them with first party data. For instance, Google Cloud's Model Garden on Vertex AI will provide models that can be tuned in its Generative AI Studio. Google Cloud is also adding Enterprise Search on Generative AI App Builder so companies can create custom chatbots and search engines.

Tech buyers should spend their time thinking through strategy and the best use cases for generative AI, said CIOs and data leaders at a recent conference. In the meantime, CXOs will have to keep pace with the rapid fire generative AI offerings from their strategic vendors.

Here's what you need to know about Google Cloud's latest enterprise generative AI efforts:

• Google Cloud is eyeing industry use cases for its generative AI efforts. The company said that it will collaborate with Mayo Clinic to improve workflows, surface research and improve patient outcomes with Enterprise Search in Generative AI App Builder, which is HIPAA compliant. Google Cloud has been a Mayo Clinic partner.
• Google Cloud added GA Telesis, PhotoRoom and Priceline to its customer roster for generative AI applications.
• SAP and Google Cloud expanded their partnership. Specifically, Google Cloud will integrate its data cloud into SAP Datasphere. The general idea is to combine SAP data within Datasphere with non-SAP data on Google Cloud. See: Business process automation platform debate about to heat up
• Twilio and Google Cloud expanded a partnership to bring Google Cloud generative AI to Twilio's customer engagement products. The two companies will natively integrate Google Cloud Contact Center AI with Twilio Flex.  

Related:

• Goldman Sachs CIO Marco Argenti on AI, data, mental models for disruption

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Cisco rolled out a series of portfolio additions designed to simplify networking and security as well as lay the groundwork for AI and ML workloads.

At Cisco Live in Las Vegas, the company outlined its Cisco Networking Cloud vision, which will unify the company's portfolio with a single platform to manage networking. The general idea is to proactively manage networks, automate and assure performance across Internet of things, Wi-Fi, 5G, AI and security deployments.

Cisco Networking Cloud will feature a nimbler Cisco Catalyst switch stack as well as tools to monitor data center power and energy consumption. Cisco Catalyst products will also have a flexible subscription model as well as simplified licensing. 

Cisco also added AI data center blueprints to improve performance.

The first step to Cisco Networking Cloud is enhancements to the company's portfolio including single sign-on, API key exchange/repository, cross platform navigation and a common user interface.

According to Cisco, its ThousandEyes software will expand visibility across any network, deliver insights and provide workflows tied into Cisco Networking Cloud. 

Among other items from Cisco Live:

• Cisco Secure Access, a security edge system that offers access across locations, devices and applications. Other security enhancements include Secure Firewall 4200.
• Cloud native application security tools being added to Panoptica to secure the multicloud application lifecycle from code to development to production.
• Cisco Full-Stack Observability (FSO) is now generally available. FSO also has integration between AppDynamics and ThousandEyes for monitoring.
• Webex by Cisco will add generative AI summaries of meetings. Cisco also launched Room Bar Pro, which can be deployed into workspaces.