Microsoft Cuts Jobs as Part of Their AI Restructure | Tech Field Day News Rundown: July 9, 2025

Is that micro rubia or is that an AI impersonation? Core weave buys core scientific, and Arista requires VeloCloud. Ingram Micro is hit with ransomware.

And can you escape a large language model by using dense words? Open AI gets data centers from Oracle, and Microsoft is replacing its human workforce with ai. All this and more in the tech field Day rundown.

Welcome to the Tech Field Day rundown, where every time we meet, every week, we run down the greatest IT news of the week with a variable degree of snarkiness. I'm your host Alistair Cook, and joining me as a co-host since Tom is out at, uh, networking Field Day and Stephen is buried in meetings. I have the great delight of having Gina Rosenthal.

Welcome to the show, Gina. Hi, so glad to be here with you today And I welcome you on National Dimples Day. Um, it's ing that it's, it's, it's a plural.

My, uh, out younger daughter has a single temple just in one cheek, but it is also one of Stephen Scot's favorite days. It is National Durian Fruit Day. Uh, remember, this is a fruit that you cannot take on public transport, at least in Singapore.

Launching Straight into our highlight story at the beginning, someone's impersonating Senator Marco Rubio using AI voice and chat on signal. Uh, though the targets aren't named, the story highlights a broader trend. Uh, Trump aid, Susie Wales had her phone hacked, leading to calls to top officials and the FBI has warned of ongoing impersonation campaigns targeting US leaders.

Russian agents are faking Ukrainian security contacts to recruit saboteurs, and Canada's issued a similar alert about senior officials being iner impersonated in calls and texts. Gina, have you been impersonated by ai? Is that really you?

You'll never know. I think it's really me, Finch. Uh, yeah, this is kind of a really interesting and and terrifying story when you get over the, you know, it kind of sounds funny on the surface of it, but to have, uh, the United States Secretary of State, um, impersonated so well, by the way, he writes in a, in a chat in the way he speaks, which is pretty easy because he's, he's been a senator and, uh, Republic representative in Florida forever.

So his voice is everywhere that he's a secretary of State right now. And I think the, the crazier thing is just his, the tone of how he writes in a text perspective and how he would res, uh, you know, ask someone to get him in contact with somebody else or to give him money, which is what the, um, the, the article talked about. So, um, it's very dangerous to have that high level of an official, and even the White House secretary, uh, is, is pretty scary because she knows everybody and how to contact everybody.

So someone that was able to hack into her phone and then use the correct phone to then impersonate her, her, um, is, is terrifying. So, I mean, AI's come a long way. And when you look at what's, what the ransomware gangs are up to, and then you think about nation states that, um, have this ability, which, you know, we definitely know between Russia and, and Ukraine, that could be, it was terrifying.

They actually were recruiting members of the Ukrainian public to help them with suicide missions. They were wanting to mess up missions, um, in the Ukraine. So there, there's obvious reasons why nation states would do it.

Money is the reason that ransomware gangs will do it, but this is no longer just kitty script stuff, although it's easy enough and available enough for people who are just messing around and messing about, um, to pick up some extra coin, make it very easy. So where do we go as a society if you don't, can't trust what you hear or see, I don't know, core Weave. Once the whole cloud enchilada buying Core Scientific to ca gain control of their AI data center density for $9 billion, core Weave will add at least two gigawatts of data center capacity, which already host the core Weave AI cloud.

Even better, it will save $10 billion in leasing those data centers from Core Scientific Scientific. Is this how a Neo Cloud provider effectively competes with the existing hyperscale clouds? Well, I think it is this vertically integrated, we own it from this.

Well, sometimes like to say from soup to nuts, it was the name of a podcast on virtualization a while ago. Uh, it's really is this idea that in order to get the efficiencies of scale, the efficiencies of, of operations, you just pull the profits out in one place once. Uh, so you need to own everything from the beginning to the end.

So Core Weave is a provider of this sort of neo cloud capacity, this GPU first cloud infrastructure. And they previously simply had their applications running inside these data centers that belong to Core Scientific. Uh, here they're acquiring that.

6 billion worth of assets. Well, that definitely stacks up for that $9 billion of spend. But there's a bigger picture in here, which is that Core Scientific has contracts around the power supply to run those data centers.

And that's really the asset that's being bought in here. And we'll see this as a recurring theme around AI data centers. Having enough power to run these data centers is a concern.

Having a commitment to that power for a long period of time is the way that you protect your, your, um, business for the longer term. Definitely having a, a single entity that owns everything from the data center ground all the way through the application software that's running on top of that to deliver this cloud out is vital in order to efficiency. Uh, neo clouds are gonna be just as competitive on price as the, uh, hyperscaler clouds, and we'll see more and more neo clouds, um, coming up trying to differentiate in the market.

We've seen this at AI infrastructure field data where we saw a couple of solutions that were, uh, about building data centers in places that power costs will lower, because for some of these neo cloud use cases, it's more cost effective to move your data. Where the power costs are on the data center is lower than it is to build your, uh, AI data center close to your data. It's a little bit of a flip to how we've previously looked at building data centers for, uh, for our environments.

We've typically said data has a high gravity, and you really tend to accumulate compute close to your data. These neo clouds are sometimes saying, we aren't you gonna move the compute or move the data to where the compute is cost effective. The VeloCloud SSIS solution is moving from Broadcom to Arista.

VeloCloud was part of the VMware when they were acquired by Broadcom and isn't part of the core VMware Cloud Foundation product that Broadcom sees as being the future of VMware. So we aren't surprised by the, the sale, uh, Arista gains a new SSI product which deliver as a secure WAN connectivity to thousands of locations using the velo cloud manufactured network devices and the cloud services. Does Arista want the SASS e business, or is it the AI that's actually running all of this in the valid cloud solution?

So is it, I thought it was always safe, but if it's sass e Okay. Like Sache, but, um, it's the secure access Service edge. Um, so it's different than what your networking would be for, um, a a data center or for, uh, inside of an organization.

Um, but what they've, what Arista has gained from this is the virtualization of those components that are required to talk on the edge of their, their service areas. And with the virtualization, you also get the ability to run it as infrastructure, as code, which, um, ma makes everything easier to change on a dime, to protect, to segment all the other things that we know, um, virtual networking does within a data center, traditional data center. Um, so is this for, that's a good, good question.

Is this gonna be for AI and, um, I think, so it could be for ai, but it could also be for gathering the information that's shed from Edge locations. How do you get that quickly into where the data is gonna be com, um, gonna be worked on by different algorithms? Uh, how do you isolate networks so you can get them from the edge into the core?

Uh, I would guess all of that goes into that so that you don't have to worry about just having a normal sd-wan. You actually have, you're able to move data from one place to another. Quickly.

Moving on to ransomware, again, to the these bad actors, it hasn't magically, ransomware has not magically gone away. Ingram Micro was infected this week and had staff work from home while critical systems were shut down. BLE computer reports that Safe Pay ransomware was the culprit, and the attackers were able to compromise the company's Global Protect.

VPNI hope Ingram Micro are using one of the ransomware products they distribute, and we will be back in action soon. Safe Pay is new to the ransomware scene. So are they a new type of threat?

Well, safe Pay apparently was burst onto the scene and, um, I call it these, these ransomware or malware, uh, products, different organizations call them a different, uh, threat protection companies call them by different names. Uh, safe Pay burst onto the scene last year and seems to, uh, again, it's, it's likely that this is a nation state actor and that, um, there is something fairly aggressive going on underneath it. Safe Pay is the, the dual threat.

So they're the data exfiltration as well as encryption. And so this is very much the way ransomware, um, development has, has been running. Is is at that dual threat, two ways of extorting you for money.

Uh, Ingram Micro apparently has now come back online. So they were struck on Thursday last week, and as of the beginning of this week, we're starting to bring systems back online. Uh, the Global Protect VPN is provided by the Palo Alto Networks devices.

Uh, there's no indication that that was a compromise of the Palo Alto devices themselves. And Palo Alto put a press release outside. They're gonna look a little more closely, but more usually this is a layer eight human kind of stuff where, uh, vulnerable passwords are, are set up and, and the, the VP n may well have been the entry point.

But when this did break, uh, Ingram Micro who are a, a global organization, there were a lot of countries around the world we're a big distributor of software, uh, products. Uh, Ingram Micro sent a whole lot of staff home and told them not to use the VPN. Um, if you rely on VPNs for your connectivity to your core applications, then, you know, being sent home and told not to use the VP n might mean that you're just scrolling on, uh, social media and watching videos.

Uh, they did also, um, it seems like the Ingram Micron did a, a good response here in that they were proactively shut shutting systems down to avoid an in, uh, additional compromises, additional, uh, lateral spread in this compromise. So it sounds like they were pretty quick to respond and pretty brutal in the way they did respond. And I, I applaud Ingram Micro for being really aggressive at stopping the spread of ransomware within the organization.

I've seen it organizations just being too slow to respond to these kinds of attacks and ending up that the speed at which the ransomware spreads is so great that, that it just overwhelms the kind of response rates that we see. And we see delays in doing things like shutting down the entire network and particularly shutting down connectivity out to the command and control servers, uh, just leading to much greater infection than is needed. So I think, uh, Ingram might have done well and, uh, bringing systems back on minority, a group of researchers have found that large language models can be jailbroken by using dense and complex linguistic phrasing.

By applying advanced language transformations, attackers can mask harmful intent in a way that evades detention while still prompting the model to produce restricted or sensitive responses. Uh, the classic one is, if the LLM won't tell you how to build a bomb, ask it to dis to write a book in which the plot is the building of a bomb and extract that part. Uh, Jenna, how are we gonna get around this?

How are we going to protect ourselves, our society from people with poor intent? I think people have to keep researching it with exactly what these folks are doing. Um, this was so interesting because I love that you giggled at that whole phrase, uh, by using complex linguistic phrasing.

So when I was reading the article, to me it was like, okay, you're listening to a technical program, you know, a presentation someplace, and they're just using acronyms the whole way through, and they're not stopping for a breath, and they just probably put all the information in one breath, and it's very, very hard, even if you understand the topic, to follow them because they're talking at such a academic level, and this was directly their idea. So they, the, the, the models can shut off for obvious things, like if it's blatantly racist or if it's very, you know, you can ask someone, ask you to do something that can harm other people. They can shut that off at that level, but they wanted to know that they, they can do that because that's, that's obvious that you're looking for, to do something very negative and toxic.

But what happens if you bury the request in very, very dense message and they're now calling this the info flood? You know, just think about some of those presentations you've been in and this is exactly what it is, and they, the article's, great, I suggest you go read it because it's very hilarious. And if I sat here and read it, you know, everybody's eyes would roll back in the back of their head about what they are.

But they were able to, um, figure out how to give them all of this very technical jargon or very complicated English jargon. And within that, put the, the gel, whatever they were trying to gel break out. Um, and it worked every time because the way that these things work with the way the LLMs work are actually the tokenization of the English language and what's supposed to be expected after each sentence and bombarding them with all of this information, all of these different words and all of these different tokens, um, I don't know if it makes 'em like us and we forget what we were listening to and we take one piece of it, which really wasn't the point of the whole talk, but, um, that's, that's how they're breaking it.

So I think the way to get around this is, is there a better way to build the LLM or is there a better way to, you know, if, if everyone's not gonna have the opportunity to build the language models, what do you have to put in place to protect yourself from someone trying to do a jailbreak like this? Like how do you protect your data and only use the models to, to, um, help you with basic linguistical or even image tasks? And, um, that's for the researchers to figure out.

They figure it out really soon because this is, you know, this is something we should be able to trust and, and use and to make everyone's lives better. We don't need people, um, going beyond imitating someone's voice and actually trying to get proprietary data out of what we've built with our rag in instant insti instances or anything else. 5 gigawatts of data center computing power for an estimated $30 billion annually.

This is a massive deal for Google, who reported a little over $10 billion in annual revenue for this data center infrastructure business before the deal. OpenAI and Oracle are also partners with SoftBank and Abu Dhabi's MGX fund in the Stargate project, which plans to build $500 billion worth of data centers around the world. Is the whole world just gonna be one big AI data center?

It certainly feels that way. These are massive amounts of data center capacity that are being built out. I mean, this is absolutely an awesome deal for Oracle three times.

The what quadrupling this, this scale, this is a new deal for three times the previous size, and that means four times the size of business now, uh, four and a half gigawatts of computing patterns. And interesting that as you get to larger data centers and particularly cloud provider scale data centers, you don't measure them by square feet. You measure them by the power demand, the number of megawatts, or in this case gigawatts of power, the data center consumes, because that's really the design point for it.

This is huge. And in that larger context of Stargate, it's going to be even huger. I mean, 50 500 billion, half a trillion dollars worth of data centers around the worlds.

Quite a bunch of those are being built in the US but also in other countries around the world. 'cause of course, um, there's lots of places where there's demand for this. Um, yeah, four and a half gigawatts currently that's, uh, a contract for roughly a quarter of the current, uh, data center capacity in the United States.

So that would definitely involve a huge build out by Oracle, supported by this contract. Uh, potential new sites for this spread all across United States, Texas, Michigan, New Mexico, through to Wyoming and Pennsylvania. Uh, also close to the head office of the tech field day team in Ohio.

So this is a, a lot of, um, build out. Uh, there's a, a bunch that's being built out in Abilene, Texas. 2 gig gigawatts of the Stargate is being built out there.

And we heard from the, the, the data center startup Cruso on, uh, our infrastructure field down there, one of the companies that is helping build out new clouds and locations where power is potentially otherwise, uh, uh, being wasted or being, uh, delivered at very low cost. So this whole theme around putting data centers anywhere there is power to be had, is going to continue, particularly with this massive growth of AI's, uh, data center sizes. Um, Oracle is planning to buy about 400,000 of NVIDIA's, um, gb, 200 chips to power just the Avalon data center.

Uh, that's a massive amount of, uh, compute power that's being pushed into one place. Personally, I keep seeing this infinite growth and anytime I see, uh, this sort of exponential increase in the size of something, I know for sure it can't go on forever. And exponential growth by definition cannot go on forever.

It always has to come to a, a crisis at some point. Uh, I personally am very much hoping that the crisis is that we find a much more efficient and better way of running these, uh, AI applications and delivering value out. As Gina just covered, there's some pretty big challenges with the way LMS work.

They're not necessarily delivering us the general purpose AI that we would like. So keep watching this space, massive build outs, uh, and investment is, is awesome. Uh, hopefully massive value delivered back from them.

It's time for us to take a little bit of a closer look. And this is, uh, an interesting story that continues to be seen. We've seen multiple angles on this before.

Uh, Microsoft recently laid off about 9,000 employees. That's about 4% of its total workforce. These layoffs within the tech industry or risk reduction in force are fairly common.

Uh, typically a seasonal thing that we see a chunk of the workforce laid off from an organization. And over a period of time, a new, uh, workforce gets hired in because the company shifts where its focus is. And so they need to lay off the people who, who can't be relocated into what they're doing.

Now, the difference here is that Microsoft is shifting to AI to replace these humans. And, uh, whilst the company leaders say that AI will eliminate many routine jobs, but it'll also create new opportunities in advanced areas, thousands of tech workers were displaced, but mind for AI experts has sawed with companies offering high salaries to attract, attract top talent. How do you think these sh shifts will impact the future of Microsoft Gina?

Well, I think it's already had a bit of an impact because the, the, the shutdowns are global. They're not just, you know, in the United States, uh, and the shutdowns are pretty complete. There's complete lines of business that are being switched right away.

Um, and so that has an impact not only on the, the individuals being rift, but it also has an impact on the local economy. It has an impact on the greater economy because we see a, a huge trend right now in, um, outsourcing jobs and saying that they're being removed for reasons, for AI reasons, which it turns out that that's not always the case. So, um, you know, of course I, I have a product marketing agency.

I've seen this happen to my own agency, um, and I have a friend who does special effects, his own special effects company. He's seen it happen in, in their organization too. And the problems I see with Gen generative AI replacing humans is, especially in the fields where you are using, um, words to define things and you're doing things with words and you need creativity, uh, AI can't replace it.

And starting to see that in my own business, starting to see business coming back a little bit, um, starting to see a lot of cleanup work, which I predicted that would happen if they did this, that would be cleanup work. Um, I think it's bad, uh, for the entire stream of work, right? So this happens, if this happens, this is knocking out a lot of senior workers.

That means the new people have to go in and try to use AI without having any context of how the business works. They don't have anybody to mentor them. Um, it just leaves a lot of gaps.

And I think it's, uh, I'm not sure if it's shortsighted because I, I think this is the intention that Microsoft had and where they wanted it to go. Um, it'll just remain to see if they are, um, being a little too lackadaisical in their approach with this to, to replace knowledge workers with ai. I don't know.

What do you think? Well, I think there's, there's a couple of parts to this. One is that these, these riffs are routine, uh, hanging a banner of everything's happening with ai.

Um, comes up, I, when I say routine, they happen pretty much every year. I mean, they're horrible for the people affected, but they happen every year. They happen across almost every organization that we deal with.

That's a, a reasonable size in the industry. Hanging the AI banner across that, there's a couple of pieces to that. One is everything's AI now.

So these, there's refs have to be ai, but also Microsoft is saying you can get huge amounts of benefit from using AI and copilot in your own business. So they, they have to, they have to show that they're getting huge amounts of benefit. I think, uh, I agree with you that they probably are over rotating on this and they may find themselves in the same situation.

I think it was IBM found themselves, they, they laid off a whole bunch of, uh, sales staff because they were going to replace them with AI and then had to turn around and re-recruit those sales staff because the AI just was not doing the job that was required. We may see if, if the, the truth in this is that the, the staff members are, are being replaced with ai, we may well see that same wind back happen here and it'll probably be nice and quietly it'll just be quietly rehiring staff hiring staff to do the jobs. Uh, you don't wanna admit that you made that kind of mistake.

I'm sure I, you know, I've said for a long time, a long time for like probably 20 years now, that in knowledge workers working positions, the means of production is no longer in the hands of the companies or the owners or the managers. It's inside of our heads of knowledge workers heads. So what to me has been happening is you've now got, um, a lot of companies, Intel is another one that is now doing layoffs today and replacing all of their marketing team sending it to Accenture that's going to use AI to do the, the marketing.

So when you do that, you're, you're taking that means of protection back in house, but you're trusting a large language model. That's where the means of production is now. So we know what the troubles and how that does not work.

And uh, we talked about that forever. We talked about it today. Um, so it's just, I think it's an attempt at if to use pure, um, capitalism type of language.

It's a mean to reclaim means to reclaim the means of productions no longer in the heads of the workers. It's in the code of the law, of the language models. Um, and I don't think, you know, good luck to them, but, you know, I don't, I don't think that that's the way to go.

Now, having said that, I use AI every day in my work. I like using ai, I like using the l large language models. But um, I also have a context for, for how it should be used because I have a context of the whole field of marketing and how what we exist and what our goals are to try to do things with, and that guides my prompts and how I'm doing things and how I use that for my clients.

So I think there is a way to use AI to make things faster, to get rid of some of the dr work, to help make the changes faster, all the rest of the things that they seem to want to do. But I don't think it can be done without humans. And if it is, we'll see how that turns out.

I think that the people that will decide will be the people that consume the messaging and you know, that have to use the code that's built by AI and we'll, we'll see how that turns out. We will indeed. And other things we'll see is that this week Tom Hollingsworth, my usual co-host here is actually at Networking Field Day 38.

So today and tomorrow you can tune in for all of the livestream goodness and the replays both on LinkedIn as well as on Techstrong tv. Coming up in August, we will have the Tech Field Day extra at Share Cleveland. So, uh, Steven Foskett is going to just drive up through Ohio to get to Cleveland for a share.

And then in September, I will be making the big trip across the Pacific Ocean for AI infrastructure field Day three, that will be September 10th and 11th and later on that Tom takes back on the baton. He has Security Field Day, September 24th and 25th. Check out the Tech Field Day website for all the details of all of the upcoming and all the past events from Tech Field Day.

So thank you very much for watching this episode of The Tech Field Day Rundown. You can catch new episodes every Wednesday as a YouTube video or on your favorite podcast application. The rundown is streamed on Techstrong TV as well.

And you can catch us and other Techstrong and future and group programs right there on Techstrong tv, including on your smart device with the tips drawing hat. We'll be back next Wednesday to talk about all the IT news in the week. That was until then for myself and for Jen Rosenthal, for from All of us here at Tick Field Day.

Thanks very much and wishing you and yours a great week.