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SAP Build Code adds generative AI tools, bridges to process data, Java, JavaScript

SAP launched SAP Build Code development tools that leverage generative AI and court Java and JavaScript developers as well as connect to data stores across the enterprise.

At SAP's TechEd 2023 conference, SAP outlined a series of tools that aim to enable developers to build applications and connect them to the SAP Business Technology Platform. These pro code tools, which build on last year's low code/no code rollout, feature the following:

  • Generative AI productivity tools to connect heterogenous systems.
  • Vector embedding capability in SAP HANA Cloud to handle unstructured data and provide context to models.
  • SAP AI Foundation, a developer repository to build AI-driven business apps.
  • Development tools that are optimized for Java and JavaScript and interoperate with ABAP Cloud development.
  • Code generation via SAP's generative AI assistant Joule.
  • Unification of design and run-time services to build interfaces using Java and Node.js.
  • The ability to work in Visual Studio cloud hosted environments.
  • Simplified API management so developers can connect to third party systems, link processes and keep business context.

SAP Build Code will be generally available in the first quarter.

The ERP giant's other big play was to connect its SAP Build Code developer base to its process optimization tools including SAP Build Process Automation, SAP Signavio, which will get a large language model specific to business processes or large process model, and SAP Integration Suite. By connecting development and process optimization, SAP is looking to keep data on its platform while extending into other third-party systems. To that end, SAP also said that models built in DataRobot can be hosted inside SAP AI Core and used in SAP Build applications and extensions.

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In addition, SAP Datasphere will get updates to import business context from SAP S/4HANA Cloud, SAP S/4HANA, SAP Business Warehouse and SAP BW/4HANA for data integration. Datasphere will also have simplified data sharing as well as prebuilt business content with a release planned for the fourth quarter.

Constellation Research's take

Holger Mueller, Constellation Research analyst, handicapped SAP's announcements. He said:

"SAP is doing right by its developer community with the launch of Build Code – which took a temporary back seat with all the attention the low code/no code offering had in the last 12 months. It is of strategic importance for both SAP customers and SAP alike that existing customers can move their ECC based customizations and extensions to the cloud future, where they need to upgrade to S/4HANA by 2027.

Given that most custom SAP code is in ABAP though, the SAP developer community wonders why the focus was Java/JavaScript. Certainly, a more en vogue platform today, but it is easier to move alike code / programming language – than re-writing. It would have been a big win if SAP could have delivered all pro-code tooling in 2023.

On the HANA side it is important that HANA gets the now 'standard' AI vector feature – what it will mean for in memory usage will have to be seen – but a key step to keep HANA and HANA data (where all of S/4 HANA data is) relevant in the AI age. What needs to be clarified is the basic working of SAP’s AI platform – that would have been a prime-time topic for TechEd. We may now have to wait till Sapphire."

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ServiceNow CEO McDermott talks business transformation, generative AI, processes

ServiceNow CEO Bill McDermott said workflow and process optimization are blending as enterprises shift away from siloed data and infrastructure to focus on transforming operations with new technologies such as generative AI.

McDermott, speaking during ServiceNow’s industry analyst day, closed out sessions with ServiceNow executives who outlined generative AI plans, strategy, target industries and returns on investment.

He said enterprises have created "a hornet's nest of complexity." "The number one reason that digital transformation hasn't delivered positive ROI to businesses is integration. And that's why 85% of the businesses that have gone on transformation didn't get a positive ROI, because nothing integrates," said McDermott.

ServiceNow reports strong Q3, ups outlook for 2023 

What's changed is an inflection point where enterprises have to cut costs, leverage new technologies and be agile enough to navigate a bevy of unknowns.  McDermott said IT budgets are likely to rise and "generative AI is the main cause of the increase." "I've tested this theory with CEOs that they're going to lean even more heavily on SG&A functions. They're not going to do what they've always done, which is upgrading older technology and 1,000 points of dim light point solutions. They're going to start stopping things in favor of investing in platforms that matter. There's about a half a dozen initiatives that matter and Gen AI is number one on the list," he said.

McDermott added that boosting efficiency requires a focus on processes and a move away from siloed operations.

"We're moving away from the siloed operation. Operations today have to be done in teams. It has to be done across silos. It has to be done in business processes, whether that sorts of pay cash and so forth. So, what you're seeing now is a complete renaissance in where the work needs to be done," he said. "We have to put a bit of an action layer above this mess. Straighten out the mess, go into the process, go into the end integration and then provide a UX that hides the complexity."

According to McDermott, C-level executives are pivoting to business transformation management "where you rethink the whole value chain."

Other key points from McDermott include:

Speed and time to ROI is critical. McDermott said CEOs have to rev innovation cycles even as they are navigating multiple concerns--geopolitical issues as well as economic concerns--and have to become more productive. "Leaders can't be focused on time consuming projects with high risks," said McDermott. "They have to get the job done. Customers need positive ROI. They need costs out and they need productivity up and keep an eye on growth."

He added that CEOs "really need to increase the clock speed of their companies."

Work is still complicated. "What I try to explain to CEOs in the context of what we do is companies still waste a lot of time," said McDermott. "The average worker today swivels between 13 disparate applications in the enterprise. And that's forfeiting more than 20% of their productivity. Some cases are a lot higher than that. That seems pretty ridiculous."

The intersection of data and AI. CEOs are starting to realize that to leverage generative AI they need to focus on their data. "The enlightened CEOs are getting the picture that they really need to focus on data," said McDermott, adding that AI is the next step. "If I can improve the productivity of my workers or my engineers by 30% to 40% combined with digital transformation, we're now moving into a whole different category--business transformation."

Generative AI's impact on employment. "I absolutely believe that this might be the great unlock in human productivity and enterprise productivity. And it actually might be a force multiplier for increasing the world's GDP. Because if I'm right on digital transformation, I would also be right that we're going to need more people in the workforce. They're going to do different things. They're going to be retrained. A lot of people forget we're in the tightest labor market that we've been in for two decades," said McDermott. "It's the biggest thing that we've come across in the enterprise, probably since the internet."

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Snowflake lays out AI managed service vision with Cortex

Snowflake consolidated its AI and machine learning efforts with Snowflake Cortex, a managed service that provides access to large language models (LLMs), AI models and vector search in one place and includes Snowflake Copilot, Document AI and Universal Search.

Cortex, announced at Snowflake's Snowday developer conference, is in private preview. Snowflake Cortex will include LLMs including Meta's Llama 2 model as well as task-specific models. For Snowflake, the move to Cortex highlights a vision that revolves around providing AI building blocks without expertise or GPU infrastructure management.

To go with Cortex, Snowflake expanded its Snowflake Horizon built-in governance platform. The company added data quality monitoring, data lineage UI, differential privacy policies, enhanced classification of data and an upcoming Trust Center that will streamline cross-cloud security and compliance modeling.

Snowflake also plans to provide a cost management interface so admins can manage costs in Snowflake.

RelatedSnowflake Q2 better than expected | Snowflake launches Snowpark Container Services, linchpin to generative AI strategy | Snowflake, Nvidia team up to enable custom enterprise generative AI apps

Although the announcements are notable for Snowflake customers, it's worth noting that many of these services are in private preview.

Doug Henschen, Constellation Research analyst, provided his take on Snowflake's barrage of announcements and private previews. He said:

"Snowflake is making lots of private preview announcements. Snowflake's general pattern is to make more "heads up it’s coming" announcements during Snowday and more "it's now public preview or GA" at Snowflake Summit in June, but I don't tend to get too get excited about private preview announcements that are six to 12 months from being available to customers.

Horizon and Cortex are, indeed, two of the higher-profile announcements. Horizon is really consolidating everything Snowflake already has and has planned in the way of metadata management, cataloging and governance. It’s partly a response to competitors, like Databricks and Google, that have put cataloging at the forefront with their Unity Catalog and Dataplex offerings, respectively. Snowflake already had a catalog and multiple governance capabilities, but they’re now pulling everything together under the Horizon umbrella and providing a clearer and more comprehensive vision of what’s ahead. Cortex is entirely in private preview but, here too, we're seeing the vision for how GenAI and more conventional AI/ML will be made available on the Snowflake platform."

Research: 

Instead, Henschen said Snowflake customers should focus on things that are closer to launch. Snowflake announced the following additions that are closer to prime time.

  • Snowpark ML Modeling API, which will be generally available soon, will give developers and data scientists tools to simplify model training faster.
  • Snowpark Model Registry, public preview soon, will have expanded support for models from Hugging Face.
  • Snowflake Native App Framework, generally available on AWS soon and in public preview soon on Microsoft Azure.
  • Snowflake Container Services, public preview in select AWS regions.
  • Support for Iceberg Tables, which will be in public preview soon.

Henschen said Snowflake customers need to focus on what's coming within weeks more than months. He added:

"The standouts for me are the things that are entering public preview or that will soon be generally available. Support for Iceberg Tables, for example, is now in public preview, and it promises interoperability of data managed in Snowflake for open access and usability of data for other workloads and applications. It’s a win for customers. Another example is the Snowpark ML Modeling API, which will enable the many customers using Snowpark to more easily tap into Snowflake data for model preprocessing and training.  Similarly, the Snowpark Model Registry, which is going into public preview, will improve support for ML OPS within Snowflake."

The biggest takeaway from Snowflake's Snowpark conference is that the company is consolidating its efforts to provide a unified platform. Snowflake's core themes at Snowpark were to simplify the data foundation, accelerate AI adoption and scale applications.

"It's a good set of announcements, but with so many elements being in private preview, my sense is that both Databricks and Google are ahead of them on having ML/AI and GenAI capabilities internally within the platform and in supporting customers who want to develop their own ML/AI and GenAI capabilities. I’d like to see either a shorter lag time between private preview and public preview stages or a shift by Snowflake towards only announcing capabilities that are nearly ready for public preview. There are capabilities, like Unistore, for example, that were announced at Snowflake Summit 2022 that still aren’t available. In my opinion it’s not a good idea to announce things unless they’ll definitely be available within six to eight months."

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AMD sees strong data center demand for Q4

AMD's third quarter financial results were better than expected, but the outlook for the fourth quarter was lighter than expected. AMD CEO Dr. Lisa Su said "our data center business is on a significant growth trajectory" due to its EPYC server processors and Instinct MI300 accelerator shipments.

The company reported third quarter earnings of $299 million, or 18 cents a share, on revenue of $5.8 billion, up 4% from a year ago. Non-GAAP earnings for the quarter were 70 cents a share.

Wall Street was expecting AMD to report third quarter earnings of 68 cents a share on revenue of $5.69 billion.

As for the outlook, AMD projected fourth quarter revenue of $6.1 billion, give or take $300 million. That outlook would equate to 9% revenue growth from the fourth quarter a year ago. Non-GAAP gross margin guidance of 51.5% was in line with expectations. That outlook is based on strong growth in AMD's data center unit and momentum in the client business with lower sales in gaming and embedded markets.

Like Intel, AMD saw stabilization in the PC business. Su said AMD saw record sales of its Ryzen 7000 series PC processors as well as server processors.

Key items from AMD's analyst conference call:

  • "Based on the rapid progress we are making with our AI road map execution and purchase commitments from cloud customers, we now expect Data Center GPU revenue to be approximately $400 million in the fourth quarter and exceed $2 billion in 2024 as revenue ramps throughout the year. This growth would make MI300 the fastest product to ramp to $1 billion in sales in AMD history. I look forward to sharing more details on our progress at our December AI event," said Su. 
  • "We've been planning the supply chain for the last year and we're always planning for success. So certainly, for the current forecast of greater than $2 billion, we have adequate supply. But we have also planned for a supply chain forecast that could be significantly higher than that, and we would continue to work with customers to build that out," said Su. 
  • "Looking at the next couple of quarters, we expect strong growth in our Data Center business, driven by both EPYC and Instinct processors. This growth will be partially offset by softening demand in our Embedded business and lower semi-custom revenue, given where we are in the console cycle," said Su. "As the PC market returns to seasonal patterns, we believe we are well positioned to gain profitable share in the premium and commercial portions of the market based on the strength of our product offerings."
  • Su said the fourth quarter revenue for its Instinct processors will initially be HPC, but then become mostly AI through 2024. "Within the AI space, we've had very good customer engagement across the board from hyperscalers to OEMs, enterprise customers and some of the new AI start-ups that are out there," she said. "From a workload standpoint, we would expect MI300 to be on both training and inference workloads. We're very pleased with the inference performance on MI300, so especially for large language model inference, given some of our memory bandwidth and memory capacity. We think that's going to be a significant workload for us. But I think we would see a broad set of workloads as well as broad customer adoption."

By the numbers for the third quarter:

  • Data center revenue was $1.6 billion, flat on a year ago. 4th generation AMD EPYC CPU sales were up 21% sequentially but offset by system-on-a-chip data center products. AMD said it added almost 100 new instances for its AMD EPYC processors across cloud hyperscalers.
  • AMD Instinct MI300A and MI300X GPUs are on track for volume production in the fourth quarter.
  • Client revenue was $1.5 billion, up 42% from a year ago. AMD Ryzen 7000 Series sales were up 46% from a year ago.
  • Gaming revenue was down 8% from a year ago to $1.5 billion in the quarter.
  • Embedded sales were $1.2 billion, down 5% from a year ago.
  • AMD acquired Nod.ai and Mipsology to build out its AI software offerings.

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Cloud customers still optimizing spend and should forever

While generative AI dominated the talking points among the big three cloud hyperscalers--Microsoft Azure, AWS and Google Cloud--there was a term that remained a close second: Optimization.

All three talked about cloud optimization as they have for the past year. CEOs are loathe to say things like cost cutting in the context of cloud, but there is certainly an ongoing tweaking of spending.

My handy conference call analytics--a word count of terms--puts optimization right in the mix as an ongoing theme. Here's what the big three are saying about customers optimizing their cloud spending through the September quarter.

Azure

Microsoft CFO Amy Hood said on the company's first quarter earnings call that "in Azure, as expected the optimization trends were similar to Q4. Higher-than-expected AI consumption contributed to revenue growth in Azure."

Makes you wonder when customers will start optimizing AI consumption too, eh?

For Microsoft's fiscal second half is assuming optimization and new workload trends will continue and Azure will see stable growth due to AI. Hood said:

"We've been very consistent that the optimization trends have been consistent for us through a couple of quarters now. Customers are going to continue to do that. It's an important part of running workloads that is not new. There obviously were some quarters where it was more accelerated, but that is a pattern that is and has been a fundamental part of having customers, both make new room for new workload adoption and continue to build new capabilities."

Optimization was mentioned 9 times on Microsoft's earnings call.

AWS

Amazon CEO Andy Jassy hit a similar theme with optimization on the company's third quarter earnings call. His message was similar to Microsoft's: Optimization is making room for new workloads. Jassy said:

"AWS' year-over-year growth rate continued to stabilize in Q3. And while we still saw elevated cost optimization relative to a year ago, it's continued to attenuate as more companies transition to deploying net new workloads."

According to Jassy, optimization remains a headwind, but the rate of cutting has slowed. He added that AWS is "encouraged by the strength of our customer pipeline."

Other optimization takeaways from Jassy include:

  • Customers aren't shutting down workloads en masse.
  • Many customers are shifting EC2 instances to Graviton processors over AMD and Intel to save money.
  • Customers are also moving from hourly on-demand rates to workloads with 1- to 3-year commitments to save money.
  • Optimization with help from AWS is a long-term customer win.

Jassy added:

"My perspective is that in 2024, I think a lot of the relatively low-hanging fruit on optimization has happened in 2023. It's not to say there won't be any more optimization. It's just that there's more low-hanging fruit when you have very large footprints and you've built a lot of applications on a platform."

Optimization was referenced 19 times on AWS' third quarter earnings call.

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Google Cloud

Although Google Cloud's revenue growth of 22% disappointed Wall Street, it's worth noting that the company's conference call featured the word optimization only 3 times and only one comment referred directly to Google Cloud.

Alphabet CEO Sundar Pichai said:

"We had definitely started seeing customers looking to optimize spend. We leaned into it to help customers given some of the challenges they were facing. And so that was a factor. But we are definitely seeing a lot of interest in AI. There are many, many projects underway now, just on Vertex alone, the number of projects grew over 7x. And so, we see signs of stabilization, and I'm optimistic about what's ahead."

What gives? Optimization is probably less of a theme for Google Cloud since it doesn't have the installed base that AWS and Azure enjoy.

My take

Frankly, I hope this cloud cost optimization theme remains forever. While optimization became a big theme a year ago, the reality is that enterprise buyers should always be optimizing.

With any luck enterprise buyers will be optimizing those pricey AI workloads real soon.

If enterprises don't optimize continually, they lose control of costs and more importantly can't hold cloud providers accountable. A continuous threat of optimization will keep both buyers and sellers of cloud compute on their collective toes.

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Ba da ba ba ba: McDonald's digital experience efforts paying off

McDonald's said its strong third quarter results were in part driven by digital sales and more than 57 million 90-day active members in its MyMcDonald's rewards program.

The restaurant chain, which handily topped expectations with its third quarter earnings report, highlights how digital customer experiences are building a moat around core franchises. For the third quarter ended Sept. 30, McDonald's reported revenue of $6.7 billion with net income of $2.3 billion, or $3.17 a share. Same store sales in the third quarter were up 8.8%.

In McDonald's top six markets, digital sales were more than 40% of system wide sales. That scale is creating a data flywheel that drives engagement,” said CFO Ian Borden, speaking on the company's earnings conference call. For comparison, Starbucks said August 1 that its 90-day active Starbucks Rewards customers grew to nearly 75 million with 31.4 million in the US. Domino's Pizza and a host of other quick service restaurants are trying to create their own data and digital experience flywheels. 

Borden said:

"We now have over 57 million 90-day active members across these top markets, and our relationship with them continues to grow. We're learning when they visit, how they visit, and what they buy, with more and more of our sales coming through identified channels than ever before."

Borden said that elevating McDonald's digit experience is improving loyalty and "driving those incremental visits that we believe would otherwise go uncaptured."

McDonald's has been deploying digital campaigns across social, streaming and content around core promotions such as Monopoly and big events like FIFA Women's World Cup. The company's plan revolves around providing value to core customers trying to navigate an uncertain economy.

Borden said it will continue to invest in its technology and digital footprint. "We've got a fully modernized estate. We've got a digital platform that's coming to life at a scale that's allowing us to really interact with our consumers on a much more individual basis," said Borden.

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Constellation Research's Connected Enterprise 2023: What we learned

This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly.

Constellation Research's Connected Enterprise 2023 has concluded, and this first-time attendee is somewhat fried. The brainpower at CCE is impressive, eclectic, and somewhat frenetic. I have to admit that it was fun being the dumbest person in the room by far.

As my brain recovers, I figured I'd outline some themes from CCE 2023.

What’s next?

There was a lot of talk about the future on multiple time frames. Naturally, Constellation Research Ray Wang figured it was time to look beyond generative AI and what’s next.

The post-AI business model will revolve around vast unique data sets and collectives that create value chains that monetize new services. The companies that are successful will lead in the future.

Speaking at Connected Enterprise 2023, Wang said: "We don't have enough data to make AI work. Billions of dollars will be wasted on AI implementation without a data strategy."

The issue is that enterprises will need more data to train models so you can trust AI. As a result, companies will start sharing data in collectives and create value chains.

What data will be needed to create this next generation enterprise called Data Inc.

Wang said there will be the following types of data to truly leverage AI:

  • Unique data sets.
  • Network and data.
  • Longitudinal data sets.
  • Derived Data advantage.
  • New classes of data.

Meanwhile, our merry band of analysts also laid out predictions for the years ahead. I stuck with the 18-month time frame. With all those caveats in mind, here are a few of the trends our gang sees ahead.

We also talked about automation, the future of work as well as sustainability.

Other stabs at the future you need to know:

Nuggets to know

  • HR professionals on a panel were concerned about developing young talent in remote and hybrid work environments. Physical presence is necessary for collaboration, but leadership styles should change for the next generation. In addition, the reason why people work has changed. "Young people today work for self-actualization. What they expect is that their experience at work is going to help them self-actualize. We must reimagine work," said Xapa CEO Christine Heckart.
  • Dion Hinchcliffe, Constellation Research analyst, said that there's a lot of pressure to push employees into the office. "Work from anywhere is becoming an endangered species," he said. There's a reason for that: One CXO in attendance said employees need to be in the office. "You can't raise your kids on Zoom. You can't groom the next generation of talent on Zoom either."

More from CCE 2023:

Business value

Ingram Micro's Chief Digital Officer Sanjib Sahoo said his company is approaching its transformation through a lens of DigiOps, which should prioritize business value and then looks to technologies to enable it.

This business value twist to digital transformation has to happen. Otherwise, attempts to reinvent businesses will fail because innovation and real returns will be disconnected.

Sahoo's talk covered a lot of ground, but here's the bottom line (like literally).

"Every single release or sprint we do has to create value for customers. Getting to DigiOps is about culture and developing real P&L responsibility. How much operating income am I generating? Am I growing margins? Is revenue growing? Technology is always focused on what's possible. Operational folks say 'that's OK, but here's how to do it.' Otherwise, you build the best technology with no adoption."

After more than a dozen CXO interviews at CCE with BT150 members and Supernova winners and finalists, I can confirm that business value is front and center. Value is also intertwined with business value.

The need to have a mind shift

While IT, transformation, technology and yes generative AI were key topics CCE, one thing that stuck out to me was the need to shift how you think. CxOs have talked about this a bit before, but it's becoming a chorus.

Sahoo talked about this shift in thinking when it comes to not only transforming operations and business value, but convincing employees to go along for the ride. Sahoo talked about compassion and mindsets about people, management and leading in general.

ServiceNow's Brian Solis, Head of Global Innovation, also talked about shifting mindsets. Solis' point was that technology change is accelerating and there's nothing normal about it. What's needed for the next phase of innovation? He said:

"This takes people coming together to actually believe that they do play a role in our future. The mind shift is to get yourself to believe you play a role in it."

Enterprises also need a mind shift to rethink how business runs beyond mere iteration and bolting technologies onto legacy systems. Companies need to look for ways to build for tomorrow. "The main shift I'm talking about is a path to sustainable innovation because right now we do sprints, we jump in, put something up there and we leave," said Solis. "If we do that organizations fail."

And speaking of mind shifts.

Jeremy Utley, Stanford Adjunct, Venture Investor, Co-Author of "Ideaflow: The Only Business Metric That Matters," said in a keynote that people need to think of ideas a natural occurring phenomenon that has a natural distribution. Ordinary ideas take up most of the curve and delightful and dopey ideas are at the ends.

Utley's big takeaway is that you need dopey ideas to get the delightful ones. "Dopey ideas are the price for delightful ones," said Utley. "We make mistakes as leaders when we just want delightful and ordinary ideas. When you chop off dopey you cut off delightful too."

Generative AI

Needless to say, generative AI was a key theme at CCE 2023, and we focused on multiple threads including threats, opportunities, governance and the outright scary. When it comes to generative AI, it's clear we're not there yet (especially on the enterprise side), but there's a lot to think about. Here are a few things that stuck out for me from a series of conversations.

The good...

Divya Chander, Chair of Neuroscience and Faculty in Medicine, Singularity Group, was upbeat about the generative AI and its ability to expand the pie for multiple groups. She said:

"Historically, it’s been very expensive to access these resources. But computing power is just getting cheaper and cheaper. And that's going to enable more people with good ideas to enter the marketplace, just like you can code using English now. The simple fact that we can fit more transistors onto a chip makes it so that anyone can use these things. It's really good for democratization."

Casey Santos, CIO of Asurion, said customer experiences will improve with generative AI and education can be personalized. Healthcare should also drive more value with AI. "This isn't something that will really open up faster diagnoses, faster treatments and better outcomes," she said.

Richie Etwaru, Principal Inventor Mobeus, outlined everything that's going to change. Language, trust, math, industry, learning, liability, labor, laws and even love. He's optimistic overall, but there's a lot of change ahead.

The bad...

Julia Glidden, Board Chair Pivotl, laid out the case why we all should be damn worried about generative AI. In short, think of the kids. She said:

"The risk is to humanity with the emphasis on human. The human ability to love, to touch, to feel. So, I'm going to ask everybody in this room, something I never did in 30 years of tech to join me in creating, informing, and enforcing a robust legal and regulatory framework for AI.

So, we don't sleepwalk into the next social media. And absolutely, and one of the things that we have to think about is the unintended consequences of the technology."

Glidden continued with the theme on a panel and said generative AI can be a crutch that kills critical thinking. "If we take away children's need to critically think, ingest data and analyze it for themselves it means you don't need to read and you don't need to write. You put in a few prompts in, and it happens. Attention in children's brains will atrophy."

Etwaru noted that this AI wave will go horribly wrong for some: "The Enron of AI is going to happen in the next five years."

The to-do list

Generative AI will require data governance, privacy issues to be solved as well as new models for business. Simply put, everything will be affected by generative AI.

It's about the data strategy not the AI

Boomi CEO Steve Lucas said generative AI is interesting, but noted we still haven't figured out how it will be used throughout an enterprise.

"I know AI will be here when I don't have to hit zero when I call a company," said Lucas, who said AI should be able to know when he's pissed.

Lucas said enterprise AI will be hampered due to data strategy. "Is your data meaningful?" asked Lucas. "We all need to think about what our inputs are in the organization, what's my model in the middle and what's my output."

If you fast forward 10 years there will be too many LLMs and co-pilots, said Lucas. The differentiator will be your stack and your data.

In short, we're not realizing AI's potential yet because companies are still struggling with their data. Lucas said:

"The reality is what information do you have, that coupled with an LLM will create a truly unique high horsepower scenario that will create competitive advantage?"

Software development

One of the primary use cases for generative AI is software development. Speaking at CCE 2023, Aaratee Rao, Managing Director at JP Morgan Chase, noted that cost efficiency always plays well. "How do we automate, automate, automate and use AI using machine learning, and to really make sure we save money," said Rao, who noted that cost optimization and quality improvements all boost customer experience.

Pauline Yang, a Partner at Altimeter Capital speaking on the same CCE panel, laid out the software development economics. Yang said:

"One of the big use cases that we've seen really take off is developer productivity. If you talk to CTOs, they have all these different metrics--how happy their developers are, how much more pull requests are they getting, or how more productive their senior engineers are. We believe that a lot of companies are becoming software companies, even if you're not selling software, and the costs of engineers right now are so high that 40% productivity gains with your engineers is massive and so is happiness of paid developers. All of those gains are economic value."

Infinite computing

Constellation Research analyst Holger Mueller's 2018 paper on infinite computing was a popular topic given the need to train models on-premises and in the cloud.

Mueller said:

"There's a race for building the supercomputers and building the AI infrastructure. There's a lot of investment going into the compute so larger instances that can do larger workloads."

Cloud providers are in an arms race to build this AI infrastructure and spending billions of dollars to get there.

Sustainability

I had a sustainability chat (that'll be on video soon) with Marie Merle Caekebeke, Sustainability Executive - Strategic Engagement at Baker Hughes. She's a Supernova 2023 winner in sustainability that leveraged C3 AI technology to process unstructured data for Baker Hughes' sustainability materiality reports.

Here are a few highlights from our chat.

Caekebeke was initially an AI skeptic but aimed to run a pilot to parse 3,500 stakeholder documents from a broad range of external stakeholders into more than 400,000 paragraphs.

  • By starting small, she was able to bring stakeholders together to identify trends and data that would find items that would impact materiality scores.
  • The goal was to enable humans to spend more time on strategic initiatives to improve ESG performance instead of manual tasks.
  • Baker Hughes' used natural language processing and machine learning pipelines to ensure consistent scoring and root out bias and find relevant information.

ESG was a topic on multiple panels. The big takeaway is that the bottom line is aligned with sustainability efforts.

I also connected with Nate Melby, CIO at Dairyland Power Cooperative, about edge computing and IoT use cases at utilities as well as sustainability. Simply put, the smart grid didn’t quite happen, but the evolution of the concept will be interesting to watch. Melby said in an interview:

“Sustainability is one of our largest goals. It intersects with technology when we talk about efficiency the data, we need to effectively manage the grid but then there's also this other layer, which is sustainability of our utility for the people that need us. We provide power in rural areas. Our whole mission is to provide that power at the lowest cost possible, but also as efficiently as we can now and into the future with diverse resources. We're seeing this energy transition happen.”

Leadership and Careers

Day 3 at CCE 2023 focused on leadership with topics such as employee engagement, managing hybrid workforces, career paths and serving on boards of directors. Some notable quotes include:

Colleen Jordan Hallihan, founder of Qii Consulting, outlined why authentic leadership is so important:

"If you are truly authentic, meaning that you understand what's really important to you, you know what is going to satisfy you. You are acting upon all of those things on a regular basis. That authenticity gives you results. You can wear many hats competently. It correlates with mental and emotional wellbeing."

The CXO market

Kathryn Ullrich, Managing Partner for Technology, Private Equity and Diversity at DHR Global, said the job market is looking up.

"The market started picking up this summer. I started seeing more searches come in. I've got a lot more leads that have come in. Typically, September, August, September are very slow months, but leads were coming in in October or August through October. I'm hoping that we get to a fourth quarter that's really good and more vibrant."

Yoko Senga, Partner and co-Head of the Product, Data & Technology Practice at True Search, said:

"We've seen a lot of growth in our CEO and CFO practices. That's the first change that a lot of companies make and as the year has gone on, we are now seeing other sea levels opening up."

Hybrid is dying...

Ullrich said most roles aren't hybrid.

"Hybrid is three days in the office, maybe four days in the office, especially if you're in front of teams. That is what we used to have. It's a full-time office job but you get to work from home on a Friday. I've stopped putting hybrid onto the job specs because they really are in the office."

Metaverse out of favor, but you'll need to invest

And you thought the metaverse was dead.

Raffaella Camera, Head of Brands at Epic Games Unreal Engine, said:

"It would be great not to talk about metaverse but more about 3D worlds in general. I think that the name has been confused too much with specific things like VR and AR. We try to come up with premium environments. Forget the world metaverse. Everyone recognizes we're moving from a 2D world to a 3D world to connect with consumers."

There's some metaverse play coming with the help of Apple. You just wait.

Perhaps, there's a new word needed for what we call metaverse today. "The word is not favorable anymore and the gets a bad rap," said Camera.

Alfred Tom, Executive Director of OMA3 Alliance and CEO of Wivity, said:

"The metaverse is what's going to get you to that next generation of consumer. Next-gen consumers are not watching TV and they're not even watching YouTube anymore. They're in Roblox and they're in Minecraft."

Color me skeptical about the idea that the metaverse winter will end anytime soon. "Stop calling it the metaverse and we'll be fine," said Camera.

 

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Reflecting on Constellation Connected Enterprise #CCE2023

Constellation Research hosted Constellation Connected Enterprise at Half Moon Bay, California, October 24-26.

Reflections

Of course, we all heard a lot about AI at #CCE2023. Every single Constellation Research client is looking at artificial intelligence — or is anxious that AI is looking at them! So, by design, this year’s event was structured around AI. Clients, vendors and Constellation’s analysts looked at AI from every angle, research theme and vertical.

Nevertheless, I feel CCE 2023 was actually all about data!

Maybe that’s just my bias (more on that later) or maybe it’s because the only thing any AI can do right now — especially large language models — is feed us information.

Here are some of the data-related learnings from another truly wondrous CCE.

Data quality and Data rights

On the Healthcare Industry Insights panel patient and biometric rights advocate Divya Chander unpacked privacy with Richie Etwaru. Divya said healthcare privacy is ”not a simple question of giving up data”. We need to look at who uses a patient’s data, why they use it, and how is it safeguarded.

On the Mastering Data to Decisions panel, Equifax’s Manish Limaye reminded us “do not forget fitness for purpose”. That's another one of the critical properties for progressive data protection; see my summing up below. 

Data Inc. companies, the future of post AI business

Ray Wang gave us a sneak peak at his major new research (and probably his next book) on “Data Inc. Companies”—new organisations that will master data in radical new ways, for precision decision making and closer connections between physical and digital worlds, delivering exponential advantage and trust.  

As always, Ray gave us a string of dizzying analyses and hot takes. My favorite: TopGolf is the “bowling alley of golf” with booths, fast food, beer and … data. Golf club maker Callaway acquired TopGolf for the enormous volumes of data on the ordinary golfers’ swing.

Among Ray’s latest pearls of wisdom, I especially love:

  • understand how to partner for data sources and signals
  • generate new derivatives, and
  • nourish networks.

Bias

Let’s remember that not all bias is terrible. In fact, no natural intelligence could work and survive in the real world if not for in-built bias. As the ruthless George Clooney character said in Up in the Air, “I stereotype. It’s faster”.

So bias is everywhere, both good and bad. It’s difficult to assess or even talk about bias partly because the word has negative and political connotations.

One of the liveliest recurring discussions at #CCE2023 was about AI versus human doctors. Statistics were flung around about medical error rates. But the way I look at it—see what I did there—the very idea of AI doctors is so new we should admit that we are all carry a preconceived picture of what AI healthcare is like.

AI as we know it now, dominated by Large Language Models, is barely one year old; as yet there can’t be any meaningful studies of healthcare outcomes.

So, all we have to go on is models of the impact AI might have in healthcare. All models are biased. The only model truly free of bias is the real world, and no one has the patience to watch how that one plays out.

The neatest insight about bias came from Kate Carruthers, the Chief Data & Insights Officer at the University of New South Wales. Indeed it was so neat, you might have missed it. On the Data To Decisions panel Kate told us that “Data is important because it fuels decisions. But data is not inert. Making the choice of which data to use means decisions have already been made.” That is, we are constantly making decisions, the basis of which is data that we might not have given any conscious thought. That’s bias!

MyPOV

To sum up, in the closing analysts’ Ask Me Anything panel I observed that traditional cybersecurity is too defensive for the digital age. Protecting the Confidentiality, Integrity and Availability (“C.I.A.”) of data is not wrong but it’s a limited worldview.

More progressive digital data protection looks at the factors that make data valuable — originality, permissions, AI auditability etc. — and optimises those factors.

More from CCE 2023:

 

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Software development becomes generative AI's flagship use case

Generative AI has its benchmark use case: Developer productivity. Why? Software engineers are pricey and the returns on multiple fronts--costs, developer engagement and overall value creation--are hard to ignore.

In recent days, the intersection of software development and generative AI has been noted repeatedly. Panels at Constellation Research's Connected Enterprise (CCE 2023) covered the topic multiple times on automation and AI panels. In addition, CEOs including Amazon's Andy Jassy, Microsoft's Satya Nadella and Alphabet's Sundar Pichai all noted developer productivity gains with generative AI and outlined where enterprises are headed.

Today, generative AI is taking manual and rote tasks away from developers and boosting productivity. Yes, generative AI means you may not have to add engineers as quickly, but it also allows them to move upstream. Lower-level engineers can be upskilled with generative AI. The math is also clear. ZipRecruiter estimates software engineer average salaries are about $140,000. Indeed puts a Bay Area software engineer working at Meta at about $167,000 on average. Salaries can also go way higher based on skills.

Speaking at CCE 2023, Aaratee Rao (pictured right below), Managing Director at JP Morgan Chase, noted that cost efficiency always plays well. "How do we automate, automate, automate and use AI using machine learning, and to really make sure we save money," said Rao, who noted that cost optimization and quality improvements all boost customer experience.

Pauline Yang (pictured left below), a Partner at Altimeter Capital speaking on the same CCE panel, laid out the software development economics. Yang said:

"One of the big use cases that we've seen really take off is developer productivity. If you talk to CTOs, they have all these different metrics--how happy their developers are, how much more pull requests are they getting, or how more productive their senior engineers are. We believe that a lot of companies are becoming software companies, even if you're not selling software, and the costs of engineers right now are so high that 40% productivity gains with your engineers is massive and so is happiness of paid developers. All of those gains are economic value."

Nadella said 40% productivity gains could be conservative. "With GitHub Copilot, we are increasing developer productivity by up to 55%, while helping them stay in the flow and bringing the joy back to coding," said Nadella on Microsoft's earnings call. He cited Shopify, Maersk and PwC as customers using GitHub Copilot to boost software developer productivity. 

Amazon CEO Andy Jassy, speaking on the company's third quarter earnings call, said that AWS' CodeWhisperer AI coding companion is gaining traction with its customization features. "The number one enterprise request for coding companions has been wanting these companions to be familiar with customers' proprietary code bases. It's not just having code companions trained in open-source code, companies want the equivalent of a long-time senior engineer who knows their code base well," said Jassy.

The major cloud players are playing some role in using generative AI to boost software developer productivity. Pichai, outlining Google Cloud's results during Alphabet's earnings, noted PayPal and Deutsche Bank were using Duet AI to boost developer productivity.

And as previously reported, Oracle's move to rewrite Cerner's code base is largely being automated with generative AI and "coming along very nicely."

Rao said copilots for technologists ae critical. "I lead a team of technologists and we're looking at copilots. How do we really do AI to see make sure that developers can be more productive when it comes to code reviews? We can get things done much faster, but you're going to see scrutiny. Is it safe to use?" she said.

Jassy noted that the potential is there for generative AI to know all forms of code well enough to improve quality along with productivity. "It's just a game changer if you can allow your engineers not to have to do the more repetitive work of cutting and pasting and building certain functions that really, if somebody knew your code base better, could do. And so, it's real -- it's a productivity game changer for developers," he said.

Other panelists throughout CCE noted that this generative AI copilot approach to software development can also develop entry level engineers faster because copilots would be a 24/7 code coach. Yang said:

"How do you help the engineers who only have a year of experience with a tool that's encoded with 30 years of experience and help them become better at their jobs much faster?"

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Intel's Q3 better than expected as PC business stabilizes

Intel handily topped third quarter expectations as the company's PC business stabilized.

The company reported third-quarter earnings of 7 cents a share on revenue of $14.2 billion, down 8% from a year ago. Non-GAAP earnings for the quarter were 41 cents a share. 

Wall Street expected Intel to report non-GAAP earnings of 22 cents a share on revenue of $13.6 billion.

While Intel isn't the juggernaut it once was, the company appears to be rebounding.

The company projected fourth quarter revenue of $14.6 billion to $15.6 billion with non-GAAP earnings of 44 cents a share.

CEO Pat Gelsinger said the company delivered "across-the-board progress" and is moving forward with its foundry business. By the numbers:

  • The PC business had revenue of $7.9 billion, down 3% from the third quarter a year ago.
  • Data Center and AI had revenue of $3.8 billion, down 10% from a year ago.
  • Network and Edge delivered third quarter revenue of $1.5 billion, down 32% from a year ago.
  • Foundry revenue was $311 million.

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