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Nvidia highlights algorithmic research as it moves to FP4

Nvidia highlights algorithmic research as it moves to FP4

Nvidia has developed a system that preserved large language model (LLM) accuracy with less precision. The system, which will be outlined at the Hot Chips conference, highlights how Nvidia's AI game is becoming more about software and optimization as much as it is hardware.

In a briefing, Dave Salvator, Director of Accelerated Computing Products at Nvidia, outlined the Nvidia Quasar Quantization System and Research.

He outlined how Nvidia new Blackwell GPUs move to FP4--four bits of floating-point precision per operation. In a nutshell the shorter the floating-point string, the faster the execution. Moving to FP4 and reduced precision means faster compute, lower power and reduced data movement. The trick is preserving accuracy.

Salvator said Nvidia has been doing a lot of algorithmic work to preserve accuracy as it goes to FP4. "It's one thing to claim you have FP4 support in your chip. It is another thing entirely to actually make it work in real AI applications," said Salvator. "The amount of algorithmic work we have been doing to ensure that we preserve accuracy as we as we go to that reduced precision has been a substantial amount of work, and it's ongoing work."

Here's a look at the system and the output of an FP4 bunny. Click to enlarge the first slide.

Salvator explained the importance of the FP4 generated bunny picture.

"What you see on the left-hand side is an AI generated image from Stable Diffusion where we use first FP16, and then we ask with the same prompt to generate that same image using FP4. Now you may notice there are some slight differences in the image, not so much around image quality, but for instance, how the bunny is posed. That's actually an artifact of doing AI generated imagery. If you run the same prompt through most text to image generators, what you'll see is that from run to run, the image generated will be slightly different. In other words, the image that gets generated is not entirely deterministic. It's not going to be the exact same image every time. What's more important to focus on is the image quality? And what you can see is that we've preserved a huge amount of the quality. In fact, nearly all of it when you look at that image that was generated using FP4."

Salvator noted that Nvidia's algorithmic research will land in developer libraries for software developers. The upshot from Nvidia's talk at the Hot Chips conference is that the company's Blackwell efforts revolve around a complete platform including switches, racks and cooling to go along with GPUs.

Other talks from Nvidia at the Hot Chips conference include:

  • A tutorial on liquid cooling systems with Blackwell including warm water direct-to-chip approaches.
  • A talk on how Nvidia uses generative AI to build its processors. 
  • And a deep dive into Blackwell architecture including shots of Blackwell-based systems and core components in the lab.

Nvidia is an AI player at Hot Chips, but rivals are also at the conference. Qualcomm, IBM, Intel and AMD are also giving talks.

Data to Decisions Tech Optimization Innovation & Product-led Growth Future of Work Next-Generation Customer Experience Digital Safety, Privacy & Cybersecurity nvidia AI GenerativeAI ML Machine Learning LLMs Agentic AI Analytics Automation Disruptive Technology Chief Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Workday Q2 solid, announces Equifax partnership

Workday Q2 solid, announces Equifax partnership

Workday’s second quarter was better than expected as revenue posted growth of 16.7%. The company also moved to build out its Workday Payroll services.

The cloud HR and finance firm, reported second-quarter earnings of 49 cents a share on revenue of $2.085 billion, up 16.7% from a year ago. Non-GAAP earnings were $1.75 a share.

Wall Street was expecting Workday to report earnings of $1.65 a share on revenue of $2.07 billion.

Workday CFO Zane Rowe said the company is “focused on balancing targeted investments across our growth areas along with driving efficiencies across the company as we leverage the power of the platform.”

Rowe added that the macroeconomic backdrop in the second quarter was on par with the previous quarter. Workday reiterated its previous outlook for fiscal year 2025 subscription revenue and raised its non-GAAP operating margin. Workday projected fiscal 2025 subscription revenue of $7.7 billion to $7.725 billion, up 17%. Non-GAAP operating margin will be 25.25%.

Insights:

For the third quarter, Workday projected subscription revenue of $1.955 billion, up 16% from a year ago.

Constellation Research analyst Holger Mueller said:

"Workday delivers solid results, but stays on a constant pace of around 15% growth. The question for the second half is this: Will there be an AI acceleration for Workday, and will it propel its growth in the 20% range? If Workday delivers to forecast where is growth missing that is being compensated by AI growth? Or – hard to believe – is the growth not coming from AI? With the platform readiness on the Extend side for AI powered Next Generation Applications – we will know soon."

Ahead of earnings, Workday and Equifax forged a partnership to provide employment and income verification through the HR and finance platform. Workday said it will integrate Workday Payroll and The Work Number employment and income verification from Equifax. Workday's new opt-in Employment Verification Connector For Equifax integration is expected to be available to all U.S. Payroll customers in 2025.

Workday launched Global Payroll Connect, which integrates with payroll providers, so customers can integrate payroll with Workday’s platform. Workday said the pre-built API integrations in Global Payroll Connect cut implementation costs by up to 50%. Workday also outlined Workday Payroll provided by Strada to HCM customers.

Research:

On a conference call with analysts, Carl Eschenbach, CEO of Workday, said enterprises "are focusing their investments on the areas that will help them increase productivity and improve their operations."

Eschenbach said Workday is winning more full suite deals. He also said that Workday Financial now has more than 2,000 customers. 

Other notable items from the conference call:

  • Workday Rising will feature a heavy dose of the company's AI vision and a show case of innovations across applications, platform and user experience. 
  • The partner ecosystem has been driving ACV. Partner-driven ACV more than doubled in the second quarter sequentially.
  • The Equifax partnership is an example of Workday's alliance strategy. Eschenbach also touted the recently announced strategic alliance with Salesforce
Data to Decisions Future of Work Tech Optimization workday AI Analytics Automation CX EX Employee Experience HCM Machine Learning ML SaaS PaaS Cloud Digital Transformation Enterprise Software Enterprise IT Leadership HR Chief Information Officer Chief Customer Officer Chief People Officer Chief Human Resources Officer

Zoom Contact Center shows traction in Q2

Zoom Contact Center shows traction in Q2

Zoom's revenue growth remains anemic, but the company is increasingly winning platform deals and displacing legacy players in the contact center.

The company reported second-quarter earnings of $219 million, or 70 cents a share, on revenue of $1.16 billion, up 2.1% from a year ago. Non-GAAP earnings of $1.39 a share handily topped estimates. For the third quarter, Zoom is expecting revenue of $1.16 billion to $1.165 billion with non-GAAP earnings of $1.29 a share to $1.31 a share. Zoom expects fiscal 2025 revenue to be between $4.63 billion and $4.64 billion with non-GAAP earnings of $5.29 a share and $5.32 a share.

With all those numbers out of the way, the primary takeaway is that concerns about Zoom growth remain, but the company is building a platform play that may add growth in the future. Zoom had 191,600 enterprise customers and 3,933 customers contributing more than $100,000 in trailing 12-month revenue.

Zoom CEO Eric Yuan said Zoom Contact Center is starting to scale with its biggest deal to date and packages that leverage AI for agents. Yuan said:

"In Q2, we landed our largest deal for a new Contact Center customer, who chose our top-tier Elite CX package coupled with Zoom Phone. We are seeing increased adoption of our advanced Contact Center packages, as customers seek to utilize our AI capabilities to enhance agent performance. Of our top 10 Contact Center wins, all represented displacements of major contact center vendors, and 40% were migrations off of first-generation cloud-based solutions."

TIAA was a big Zoom Contact Center win as was Lyra Health. Rival contact center players have noted economic headwinds and longer sales cycles from customers. Yuan said Zoom Contact Center's integration as well as feature set is winning customers. Zoom has also added new pricing tiers but remains competitive in the field.

In addition, Yuan said Zoom's Contact Center roadmap and architecture is winning as proof-of-concept projects win out against rivals.

Yuan added that Zoom Contact Center is being paired with Zoom Workplace as enterprises aim to meld customer experience and employee experience. Zoom AI Companion is also being used by more than 1.2 million accounts and sits across multiple Zoom products.

Zoom will advance its AI strategy at Zoomtopia in October with multiple enhancements to AI Companion.

Outgoing Zoom CFO Kelly Steckelberg said Zoom is seeing strong enterprise demand. "We've had a lot of stability in terms of our retention rates and this is going to show up eventually in our net dollar expansion that we expect to start to reaccelerate as we come to like the middle of next year," said Steckelberg, who said SMB is still seeing macro headwinds.

Constellation Research's take

Constellation Research analyst Liz Miller said:

"Perhaps the most interesting snippet of Yuan’s remarks is that Zoom Contact Center is displacing "first-generation cloud-based solutions." This should be a bit of a wake up call for the market, but also one that Yuan should keep in mind as what he himself is positioning as a "second-generation cloud-based solution" – nothing in cloud is forever. The market is experiencing a bit of a malaise as customers who shifted quickly from on-prem solutions to CCaaS have now completed that honeymoon phase of speed and perhaps some initial cost savings. But there are growing grumbles about not fully realizing the operational efficiencies expected from the transition. Even more are questioning the ever-expanding function sets especially as AI gets integrated across suites and price increases take hold. In reality, the market is seeing those inaugural cloud migrations start to kick off limited experiments and explorations with other providers and vendors. Some are choosing to move forward with a more hybrid approach of on-prem telephony and over the top AI and digital business applications purpose built to leverage cloud to accelerate process and efficiencies.

So yes, Zoom and Yuan will likely be the beneficiaries of some of this exploration, but the question becomes what happens when second-generation migrations start to get hungry to explore the third generation?

It is also worth noting that Zoom has yet to fully realize what it is as a platform. Right now, Zoom is focused on articulating its integrated communications strategy, but this CCaaS + UCaaS story has become a familiar refrain for those of us following other players like RingCentral. And similar to RingCentral, Zoom has also invested in an Events business. So where does that start to come into play? Right now, both RingCentral and Zoom segment their events businesses as separated entities due to segmented buying centers. But when does that end to end capability to engage, sell and influence business through integrated omnichannel communications step into the limelight?"

Future of Work Next-Generation Customer Experience zoom B2C CX Chief Customer Officer Chief Information Officer Chief Technology Officer

Revenue Platforms: AI and Focus on Full Journey Are Changing the Game

Revenue Platforms: AI and Focus on Full Journey Are Changing the Game

The #revenue platforms market continues to evolve rapidly. This is due to several factors—namely that most businesses are continuing to transform their #business models to better support a “retention-focused” economy and that businesses must rethink their #growth strategies in the wake of this development. Revenue platforms, which previously focused solely on sales actions, need to accommodate more stakeholders along the journey, including #customer-success in addition to other postsale departments.

This means that revenue platforms are evolving to include more datasets, and data sources, to better support a full-journey approach to growth. In addition, the workflow capabilities need to expand to support more end-to-end processes and experiences—incorporating task management that spans #Sales, #Marketing, Customer Service, and Customer Success.

And finally, just as in many other sectors, artificial intelligence (#AI) is changing the game. AI can bring more predictive insights to revenue teams as well as streamline productivity by automating many of the more mundane and low-impact actions sellers and other revenue stakeholders perform on a daily basis. Also, generative AI (#GenAI) tools can help build revenue platforms into more intelligent full-journey tools that ideally help better orchestrate engagement in such a way that no potential growth opportunities get lost in the shuffle.

Enjoyed the preview? Access the full report here: https://www.constellationr.com/research/revenue-platforms-ai-and-focus-full-journey-are-changing-game

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Video Transcript (Disclaimer: this transcript has not been edited and may contain errors)

Hi. This is Martin Schneider, Vice President and Principal Analyst at Constellation Research. Wanted to talk to you really quickly about my new market Overview Report, which is called revenue platforms, how AI and focus on full journey are changing the game? One of the reasons why I came to constellation is because there's this really interesting transformation happening around a big area of tech, around sales automation, rev ops automation, and even, you know, just CX in general, where we're really transforming from these kind of commoditized and very transactional systems of record to really transformational, really supporting a full journey growth optimization strategy that companies need to have to remain competitive in this day and age, right?

So what we're really seeing is tools like AI are making not just smarter systems, but really joining up with workflow and other capabilities to create this kind of just in time, joined up full journey concept where we're really, you know, able to kind of predict how our growth is going to happen in ways that we really couldn't before we went from a big focus on kind of net new sales and really leads and the pipeline and conversion metrics and things like that, being the KPIs that matter to really looking at this full journey, holistic growth concept, it's very new, and not a lot of people have mastered it yet, and that's why, and kind of that's why I'm here.

But really, you know what we're talking about is there's some new kind of buyer requirements and new challenges we need to be thinking about when we look at our revenue platforms, and which ones are really platforms, rather than point solutions. I go over the vendor landscape and look at about more than a dozen vendors in this report, and really how they kind of hash out in terms of that platform scalability, as well as that full journey and AI focus that's really needed to be effective moving forward. And then I talk about a lot of best practices that you can be thinking about when you're either deploying a revenue platform for the first time and making that selection, or trying to optimize existing tools that you may have among the shortlist that also recently came out for revenue platforms that I just put out last week.

So check out on the Constellation Research website. Grab the report if you can, and if you remember, if you're not, become a member, because this is some really transformational stuff, and it's just the beginning. So I'll be talking a lot about this and writing a lot about this. Thank you. Applause.

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Snowflake reports better-than-expected Q2, ups product revenue outlook

Snowflake reports better-than-expected Q2, ups product revenue outlook

Snowflake reported strong product revenue growth 29% in the second quarter and raised its outlook.

As usual with Snowflake, it takes a long scroll to figure out what the company actually made or lost. Snowflake reported a second quarter net loss of $317 million, or 95 cents a share, on revenue of $868.82 million. Non-GAAP second quarter earnings for Snowflake were 18 cents a share.

Wall Street was expecting Snowflake to report second quarter non-GAAP earnings of 16 cents a share on revenue of $850.15 million.

Sridhar Ramaswamy, CEO of Snowflake, said the company was seeing "great traction in the early stages of our new AI products." Snowflake needs its AI lineup to be a hit as it competes with Databricks.

As for the financial outlook, Snowflake projected third quarter product revenue of $850 million to $855 million, up 22%. For fiscal 2025, Snowflake sees product revenue of $3.356 billion, up 26%.

The company also said it authorized another $2.5 billion to buy common stock through March 2027.


Constellation Research analyst Holger Mueller said Snowflake's reported strong growth but burned cash. He said:

"Snowflake blew through $1 billion in cash in 6 months. Snowflake had a very good quarter on the revenue side – growing 30% but its net loss is up more than 40%. And all that despite a rosy outlook thanks to AI. But something will have to give in the second half as somehow Sridhar Ramaswamy and team want to end the fiscal year with an operating income of 3% down from 5%. The question is – when will Snowflake turn profitable on a GAAP basis. Looks like not this fiscal year."

Speaking on a conference call, Ramaswamy said:

"In the first half of this year alone, we brought as much product to market as we did all of last year. We are making Snowflake the best cloud for computation, collaboration, and application on all data. And we are leveraging the power of AI to make all of these easier to create, maintain and use. This is what our team is aligned around. And I can tell you, that our customers are adopting the new capabilities at an incredible base."

Ramaswamy cover the following topics:

  • Security: "We obviously had some rough headlines in the quarter as some of our customers dealt with cybersecurity threat. As extensively reported, the issue wasn't on the Snowflake site. However, we understand that when it comes to cybersecurity, we are all in it together," he said. "My one ask of all businesses around the world, whether they are a Snowflake customer or not, is to enable and enforce multi-factor authentication in your organization and ensure that you have network policies that are as strong as possible."
  • Product availability. "In Q2, we made nine net -- nine net new product announcements and brought more than 15 and product capabilities to general availability to the market, that's what we call, progress," said Ramaswamy.
  • AI. "As of the end of Q2, more than 2,500 accounts were using Snowflake AI on a weekly basis. We expect that option to continue to increase and revenue contribution to follow. Our Notebooks offering is also seeing great traction in public preview, with more than 1,600 accounts, using that feature. This is critical to engage with data sciences on will unlock new opportunities that we previously did not address," he said.
     

Data to Decisions snowflake Chief Information Officer

New Research: Revenue Platforms: How AI and Full Journey Focus Are Changing the Game

New Research: Revenue Platforms: How AI and Full Journey Focus Are Changing the Game


One of the main reasons I joined Constellation Research was because I see a fundamental shift happening in how we approach growth strategies, and that the technology supporting go-to-market teams needs to adjust significantly. That is why my first major research piece focuses on how Revenue Platforms are transforming to better support the new requirements of growth operations teams. 

You can access the report, Market Overview: Revenue Platforms - How AI and Focus on Full Journey are Changing the Game here. The report outlines the major developments across the revenue Platforms market - and how capabilities like AI and advanced workflow are enabling users to truly rethink how they approach their growth strategies. Companies need to be thinking about how every phase of the customer journey can be accountable in contributing to growth - so revenue platforms are no longer the remit of “sales” but rather an enterprise-wide strategic platform. 

In the report I analyze the vendor landscape, and look at more than a dozen providers and reveal how their offerings best utilize AI and other tools to support a full journey approach to growth. There are some surprises as newer entrants to the space have been challenging the more entrenched vendors thanks to the speed and alacrity that AI enables from an innovation perspective. 

Finally, I outline some best practices and some questions to ask as enterprises both rethink their approach to growth but also how they either initially deploy, or optimize and existing revenue platform. 

This is just the first of many research pieces I will be releasing in the coming months that tackles this increasingly important topic of growth transformation. Look for more reports and “big ideas” around growth operations, the emergence of the Chief Growth officer, and more! 

Next-Generation Customer Experience Revenue & Growth Effectiveness Marketing Transformation New C-Suite Data to Decisions Innovation & Product-led Growth Future of Work Tech Optimization Digital Safety, Privacy & Cybersecurity Marketing B2B B2C CX Customer Experience EX Employee Experience AI ML Generative AI Analytics Automation Cloud Digital Transformation Disruptive Technology Growth eCommerce Enterprise Software Next Gen Apps Social Customer Service Content Management Collaboration Machine Learning LLMs Agentic AI business SaaS PaaS IaaS Enterprise IT Enterprise Acceleration IoT Blockchain CRM ERP finance Healthcare Chief Revenue Officer Chief Marketing Officer Chief Executive Officer Chief Information Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

Why Internal Candidates Matter | SuperNova Interview with Peraton's Cari Bohley

Why Internal Candidates Matter | SuperNova Interview with Peraton's Cari Bohley

Peraton, a next-generation national #security company, is continually searching for talent including employees with high-security clearances. But the real win for Peraton has been courting internal candidates.

The company is an integrator and enterprise IT provider for the US government. Peraton provides #cybersecurity, #digital, #cloud, operations and #engineering services for #space, #intelligence, homeland security, health and #defense, among others.

In Peraton's Supernova Award entry, the company noted it saw internal job board applicants increase 9.8% and more engagement overall. Larry Dignan, Editor in Chief of Constellation Insights, caught up with Cari Bohley, Vice President of Talent Management at Peraton, to discuss the Supernova finalist entry in the Future of Work: Human Capital Management category.

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Access the full video transcript here: (Please note this transcript is not edited and may contain errors) 

Hi. I'm Larry Dignan for Constellation insights, and we're here with supernova Award finalist Carrie Boley. She's a VP of talent management at paraton. Hi, Carrie, thanks for joining us. Well, thanks for having me. 

So I guess let's just start from the top and explain what paraton does. It looks like you all have some cool projects you work on. Yeah, we are a government services contractor. And really what that means is that all of the work that we do is for the US Federal Government. We are really a national security company. Is a good way to describe the type of work that we do for the federal government. Work on things like launching rockets in the intelligence space, collecting and analyzing intelligence, data, maritime security, it modernization, I mean, just a lot of really cool projects for the federal government we're getting now into space exploration, space resiliency. So a lot of exciting projects and exciting work that we do really to keep our country and our nation and its citizens safe.

And the company was built by mergers and acquisitions, yeah. Well, Paraton itself started as a spin off of a company called l3 back in 2017. I joined the company in 2022 and at that time, we had just gone through quite a significant amount of M and A activity with the IT Services Division of Northrop Grumman, as well as the acquisition of the entirety of a company called perspecta, which in and of itself was the legacy of several different mergers and acquisitions. So here we are, almost three years later, and we're about 19,000 employees, and in doing really well, it's a really exciting time, because really, even though we've been around since 2017 and if you can, if you count the legacy of all the different companies, we've got people that have, like, 30 years of tenure, but because of years of service, but we're really just a young company, you know. 

So we operate as a young company, being only about three years old, as this talent pool built, built, I recall in your application, you know, you need some way to filter through the talent. Can you walk me through the project and what aI had to do with it? Yeah, so, like many companies, I mean, there's, there's a lot of great talent out in the industry, but the market is very, very competitive. And so when you open up a requisition for a job, the competition is fierce, and we've got some very, very unique requirements that we're trying to fill. So to really parse through, really effectively, parse through all of that information. It takes a lot of time and effort, so without having something like AI to really look for some unique information and indicators, it's really difficult.

The other piece of that is looking for what we call passive talent. So not everybody's always actively looking for a job. So you know, like many companies, we're also looking for people who aren't necessarily looking for a new job. And an AI helps us identify who that talent is. Helps us look across different areas of the internet to find who that talent might be, people who maybe have written white papers, people who have, you know, a profound on LinkedIn or other social media sites, people who don't use social media, but, you know, maybe they presented at a conference and presented something really interesting that we may, we may want to get in touch with. So we've got different ways to find individuals who may be somebody that we want to talk a little bit further with.

When did it hit you you needed AI as a front end or what? I guess, when did it hit you that the scale of finding talent was challenging?

Um, you know, in 2022 we've worked with this company. We've worked with seekout for a few years. A lot of companies in the space, a lot of companies across multiple industries, work with companies like seekout. And it wasn't until we've, we've recognized that we needed to have more power than just, you know, trying to find this passive talent and that the type of work that we were bidding on in the government was much more complex, much more complicated, and the level of effort that it takes to submit proposals for the government, because that's essentially how we work, was becoming increasingly complex, and part of that effort requires being able to put together things like staffing plans, so without having a tool in place to help us that could leverage AI that could again go through large amounts of data in short periods of time, it really handicaps what you're able to do. 

And so when we look at, you know, all of the different tools that are out there, when we looked at the relationships that we had already in place with seekout, it just made sense for us to explore some of the expanded capabilities that they already had that we weren't taking advantage of. And that's really when we started putting two and two together. And it's like, you know, it just makes sense to go further down the road with them. And then, in addition, we were also looking at, you know, we can bring talent in the door. How does what seek out offers also play into our retention strategies and that's where we started looking at some of their other modules around career development and career growth, and it really played right into what we were trying to accomplish from a career development standpoint for our employees. Really played right into the data that we were seeing from our employee engagement strategies, and it really complemented what we were trying to do and help our helping our employees build their careers, so they felt that they had a place to stay with paraton. They didn't have to go and look someplace else for a job.

What were some of the main business metrics you used to justify the project?

Turnover is the biggest one. So retention, yeah, retention and being able to ensure that we could keep our employees within the company and that we could so retention is the starting point, and then mobility is another. So not only do we retain our employees, but we have a place for them to grow their careers so that we can move them throughout the organization. And if we were able to do that, then we could bring in, you know, new employees from outside the company and staff programs from the bottom, and help build employees' careers throughout the organization. 

So, I mean, it's, it really becomes an end-to-end process for helping our folks build their careers within the company, starting from when they when they sign on with us. You know, they can look and see that hey, you know, it's not only just this project that I, that I started with, or this job that I started with, but there are other places where I can go. I don't have to stay in this one position and be here for the entirety of my time with paraton, I can move around to different types of jobs and different types of opportunities within the organization, but being able to create the picture that you know, we can reduce turnover, we can increase engagement, we can increase mobility and staff our programs internally, instead of having this churn of people coming in and having this revolving door of employees. I mean, those are the things that are the metrics that our leadership team paid attention to, what roles are most difficult to hire and retain in our industry, it's really highly clear talent. These are the people that are doing top-secret work for the government. And there is, you know this, you would think that it's a pretty big market, but it's not. 

It's a very, very small market. There's several companies that do the type of work we do, but it's really a very small industry, very small. And so trying to find the right talent to do the work that we have to do to keep our nation safe is challenging and that's the that's the talent that that we use, you know, our partner and seek out, that we use them to help us find what were some of the surprises with this project? 

See, some of the surprises was, I would say at the beginning, it was really creating a business case that resonated with our leadership team. In hindsight, it's like, oh, it makes so much sense to just pick out these couple of metrics, and that's what everyone is gonna buy into. But in creating the story that was a strong business case, and making sure that we had that business case in place, is something that it's a, it is it is an effort to do that, so that you do it. Well, certainly not impossible, obviously, because we did it, but making sure that you've got a strong business case so that you can get the buy in that you need, and having a sponsor to help you with that is incredibly important. And I.

Yeah. And I think probably the most surprising thing for me was that when you have all of those things in place, it becomes much easier to position a project like this and an investment like this to an organization. What does seek out to sit on top of is it sit on the HR system or, I guess, what? What's it? What's it integrated with? Yeah, we integrate it with a couple of different systems. We integrate it with our talent acquisition system, our ATS, we integrate it with our HRIS system, we integrate it with our learning management system. We integrate it with it's not really an integration, but we input our career development framework into it so that it understands all of the different job families and things like that. So it really is like a hub that sits on top of all of these different tools and systems, so that, depending on what we're using it for, it gives us, it gives our employees the information that they need.

You know, for example, on the talent acquisition side and on the career mobility side, like it knows all of our open positions, so that you know, if I'm an employee that's looking for a new role, I can see what all those roles are. And because we feed all of our HRIS system, it knows who I am, and because our job families are in there, it knows what what is next in line for me, if I were to go on a kind of a step by step approach, but also because it sits with our on our HRIS system, it knows other people who are like me in the company, who have maybe gone down a different path, and it aggregates that data so that it gives me good recommendations that Maybe are things that I haven't thought of before. So it's not just a traditional career path of if I were in finance, moving, you know, finance analysts, 123, but maybe I want to go into data science and I, or maybe I hadn't thought about going into data science, but because, you know, there's some overlap between skills, between finance and something like data analytics, it will show me those different career paths that maybe I hadn't considered before, and so that opens up a whole world of opportunity for our employees. And then it'll also feed me from our learning management system, the type of training that maybe I haven't had that will help me develop in that area, so that I become upskilled, and then can start to apply for those types of positions.

What are some of the differences between sourcing talent internally versus externally? Quite if there's a few differences. I mean, internally, we know our candidates. We know you know where they're coming from. We know the types of projects that they've worked for. You know, we know what their performance has been on. So, you know, they're a known quantity. When we're sourcing candidates internally, you know, versus externally, when you know it's we don't have that level of data. There's not fidelity in the data on that individual and those candidates that are out in the external to the organization. So it's, you know, when we're looking for, especially for more strategic positions, it really helps us to be able to source internally when we've got so much more data on our employees and on the individuals that are that we're trying to position for those types of roles in the organization.

From an external standpoint, you know, looking at Canada candidates externally, there's also, you know, if they're, if they're posting for a position with us, they can also be posting for a position with, you know, five other companies. So they're much less committed to a position than somebody who's already within the organization. They're already on our payroll, they're already getting our benefits. So their stickiness, if you will, just doesn't exist. So from a value proposition standpoint, if we can source our candidates internally whenever possible, then you know, that's, that's what we want to be able to do now, with a company like ours, where growth is part of our strategy. It's not always possible, it's not always desirable, but when it makes sense, where we can do that, that's part of our strategy. What? What advice would you give HR, leaders, going into AI?

You have to go into AI. You don't have a choice. It is, it is part of our future. One thing that there are a couple of things. One is that AI is going to be one of your best employees. It's going to be an employee. I use AI a lot because I have a very lean team, so I use AI in a couple of different ways. When I'm going through a lot of data, when I'm trying to develop a new training module, when I'm looking for ideas on how to further a strategy, I use AI because I don't have the people resources to do so.

AI also helps me with my team in terms of giving them new opportunities. So there's really a lot of, you know, there's a lot of ways to apply AI that we hadn't thought that we, you know, haven't been doing traditionally in an HR in an HR role. So it's not just for the tech folks that are out there. It's really for all of us to take advantage of. And honestly, if you're not ready for that yet, it's really time for you to start doing some research, reading up on it, and time to get ready for it. Otherwise it's you're just going to be left behind. All right. Thanks for joining us, and congrats on being a finalist. Thanks so much.

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Why aren't genAI projects scaling? Data issues, says Deloitte

Why aren't genAI projects scaling? Data issues, says Deloitte

Data management and data quality is getting more investment from enterprises because it's the biggest risk factor in moving generative AI to production, according to a Deloitte survey.

Deloitte’s State of Generative AI in the Enterprise report for the third quarter found that data quality is the biggest risk to generative AI projects, according to a survey of 2,770 director-level to CxO respondents.

According to Deloitte, 75% of organizations are increasing their technology investments around data management. Data related issues also caused 55% of survey respondents to avoid certain genAI use cases. "Most organizations do not have enough data to get to a level of precision their stakeholders will trust," said Constellation Research CEO Ray Wang.

The data quality issue is core to driving value with generative AI. Deloitte said in its report:

"The clock is ticking for organizations to create significant and sustained value through their Generative AI initiatives. Promising pilots have led to more investments, escalating expectations and new challenges. During this pivotal phase, C-suites and boards are beginning to look for returns on investment. There is a chance that their interest in Generative AI could wane if initiatives don’t pay off as much, or as soon, as expected."

Also see: 

Among the key findings:

  • 42% of respondents cited improved efficiency, productivity and cost reduction are the top benefits from genAI to date.
  • 58% said genAI also gave them increased innovation, improved products and services and enhanced customer relationships.
  • Two of three organizations are increasing their genAI value.
  • But 41% of organizations struggled to define and measure the exact impacts of their genAI efforts.
  • Nearly 70% of organizations said they have moved 30% or fewer genAI experiments into production. Data issues are limiting adoption.
  • Only 23% of respondents said they were highly prepared for genAI risk management and governance.
  • More than 40% of respondents said their companies are struggling to define and measure impacts of genAI initiatives.
  • The majority of companies don't consider themselves prepared for the infrastructure, data management, strategy, risk and talent.

More:

 

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Lowe's bets on AI, technology to navigate slowing demand

Lowe's bets on AI, technology to navigate slowing demand

Lowe's said it is navigating a "challenging industry backdrop for the homeowner" with technology projects that drive productivity, enable omnichannel retailing and customer experiences.

On Lowe's second quarter earnings conference call, the company outlined a bevy of technology projects even as it reported mixed results and cut its fiscal 2024 outlook.

Here's a look at some of the technology projects outlined by Lowe's.

Apple Vision Pro. Lowe's CEO Marvin Ellison said the company is working with Apple to help customers visualize and design new kitchens. "This past quarter, we piloted an in-store design experience for our customers in three test markets, where with the help from a Lowe's associate, customers could wear the Apple Vision Pro and use the Lowe's Style Studio app to explore and customize hundreds of kitchen designs in 3D using products, fixtures and appliances all available at Lowe's," said Ellison.

Leveraging AI to improve customer and associate experiences as well as "improve how we sell, shop and how we work." Ellison cited partnerships with Nvidia, OpenAI and Palantir. Lowe's used Palantir's AIP as a customer service engine. Here's how Palantir AIP navigates a customer journey and what's on tap.

Lowe's is also creating custom GPTs for product recommendations with OpenAI and digital twins with Nvidia technology.

Perpetual productivity improvement (PPI). Those AI investments fall under Lowe's PPI efforts. The company cited its In-Store Mode on its mobile app where they can navigate detailed product and location information. Lowe's also said it has used technology to reduce returns to historic lows, said Joe McFarland, Executive Vice President, Lowe's Stores.

"We're only in the middle innings of the productivity journey, a lot of runway still in front of us. I've talked about things in the past, front-end transformation," said McFarland. "We're not even 50% through our front-end transformation. This is not only focused on the operations side, but also the sales side."

Enterprises start to harvest AI-driven exponential efficiency efforts

Associates are using quick-scan devices that immediately account for returns. In addition, Lowe's is collecting information on why an item was returned to collaborate with vendors. Lowe's is also reducing damage on more fragile items in the supply chain.

Lowe's CFO Brandon Sink noted that Lowe's has offset more than $500 million in associate wages, inflation and strategic investments with PPI.

Delivery service integrations. Lowe's said it has added Uber Eats as a delivery service to go with DoorDash, Shipt and Instacart as well as its OneRail last-mile technology partner. "As we continue to involve our omnichannel strategy, we've learned that having multiple delivery platforms extend our reach into both urban and suburban areas and helps us drive incremental sales with different types of customers, especially younger generations who are more digitally savvy," said Ellison.

More retail, experiences and technology.

 

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OpenAI launches GPT-4o fine tuning

OpenAI launches GPT-4o fine tuning

OpenAI said GPT-4o fine tuning, which will enable you to customize the company's best model with proprietary data sets, is available to developers across all paid usage tiers.

In a post, OpenAI said fine tuning for GPT-4o was one of the most requested features from developers. OpenAI said that it will offer 1 million training tokens per day for free through Sept. 23. For GPT-4o mini, OpenAI is offering 2 million training tokens per day for free through Sept. 23.

Fine tuning will enable developers to customize GPT-4o for various use cases. Enterprises will be interested in fine tuning for GPT-4o since it can lower costs.

The models available for fine tuning include:

  • gpt-4o-2024-08-06
  • gpt-4o-mini-2024-07-18
  • gpt-4-0613
  • gpt-3.5-turbo-0125
  • gpt-3.5-turbo-1106
  • gpt-3.5-turbo-0613
  • babbage-002
  • davinci-002

GPT-4o fine tuning will cost $25 per million tokens and inference is $3.75 per million input tokens and $15 per million output tokens.

OpenAI highlighted examples of companies using GPT-4o for fine tuning and noted that enterprises have full ownership of their business data and all inputs and outputs. Common use cases for fine tuning include setting style, tone and format, improving reliability, correcting failures, handling edge use cases and performing a new skill that's hard to articulate in a prompt.

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