President’s Council of Advisors on Science & Technology | Tech Field Day News Rundown: April 8, 2026

OpenAI and Anthropic are going public. Maine might freeze AI. Amazon is going global STARM, while IBM and Arm huddle up for AI.

Komprise cuts AI storage costs. Microsoft fact-checks itself, and the president appoints a science council. " Welcome to the "Techfield Day Rundown," where each week we run down the news of the week and discuss it with variable levels of snark.

I'm your host, Alistair Cook, and it is my pleasure to join you on International Zoo Lovers Day. Ooh. Also joining us today is my co-host, a special co-host, Gina Rosenthal.

How are you doing, Gina? Hello, Alistair. I'm good.

How are you? I'm great today. And I should also remind those of you in the United States that it is National Empanada Day, so make sure you get out and get yourself a good feed from somebody.

It's easy in Austin, plenty of places. Oh, yeah. Not so easy here, but then it's not National Empanada Day in New Zealand.

There you go. Our lead story is around OpenAI and Anthropic. They're our leading AI powerhouses, and they're racing towards potentially record-breaking initial public offerings.

But their financial disclosures reveal an unprecedented cost of building their super intelligence. OpenAI could spend $121 billion on computing by 2028, with a projected loss of $85 billion for that year alone. Both companies are exploring profitability, and particularly excluding their research and training costs to make it appear that they have ongoing profitability.

Full-scale AI development breaks even maybe a decade away. From investor strategies to policy proposals shaping AI economy. Gina, there's ridiculously large amounts of money turning around, and yet these AI companies seem to be planning to become profitable.

It's an interesting thing, isn't it? So when you think about what they're trying to do, they have a new way of doing computing that they're purporting is going to bring all this profitability. At the same time, they're really not sure what they're doing.

I think it's interesting that you have one company, OpenAI, that's mostly backed by Microsoft. While on the other hand, you have Anthropic, which is mostly backed by AWS and Google. Of course, that's who owns Anthropic.

But on the back end, when you start looking at it more, everybody's investing in everything else. So they know that... It's almost like they have this supposition that one platform is going to rule them all.

One is going to be the conqueror, and one's going to be the absorbent. I'm not sure that's true. But when you look into what it takes to build out an AI infrastructure, it's very expensive.

Lots of money for procuring the land, for getting the agreement of local governments to put either their power grid and their water at risk, or put their clean air and their water at risk. And then just who are you going to get to build the buildings that are going to house them? In the United States, up to 50% of the skilled labor and construction are immigrants.

And right now, construction sites are a favorite place for ICE to go and round people up. So who's actually going to build them? Which municipalities are going to allow them to be built?

And if we build out everything that's projected and on the books and planned right now, do we really need that much infrastructure? This coming from an infrastructure person, I'm questioning that more and more. Or is this just what they're doing to beef up how they look to people that don't understand what's coming?

Which is important. It's important to have AI. It's important to have the infrastructure to run them.

But I think even looking at the cost sheets, the run books for these companies, they're not making any money right now, in large part because companies are having a hard time buying in. Companies are having a hard time doing the simple operational things, like getting their GPUs to be constantly in motion all the time, running jobs. So we've got an arms race to get the blue ribbon is almost what it is, versus an arms race to be able to do the right thing.

So I think all this just remains to be seen. Will somebody be profitable? Yeah.

What if it's neither one of these companies? What if the people that are going to be profitable are the ones that really buckle down to the computer science of this and start building operational areas that are a little friendlier to the environment and a little friendlier to the neighborhoods they're built in, and friendlier to people that consume them? IBM has partnered with Arm to bring hybrid architecture to enterprise AI workloads, enabling Arm-based software to run seamlessly within IBM systems.

The collaboration focuses on virtualization, performance compliance, and expanding the enterprise ecosystem, allowing organizations to modernize without abandoning legacy infrastructure. Dual-architecture systems could reshape AI deployment, improve efficiency, and offer greater flexibility in the AI area. And this is a really interesting partnership that's going on.

One of the things that IBM often gets looked at as being a really legacy organization that is focused on older mainframe systems, the boat anchors of enterprise IT, if you will. And yet Arm is the darling of the smaller, newer, faster-moving, changing things. And so the partnership together is really intriguing.

It focuses on a few key things. One of the things that's in here is the idea of having the capability to run virtualization and to run Arm-based applications on IBM platforms through virtualization. Now, you've got to think that's going to have some Arm CPUs underneath since it's virtualization.

Another element in here is performance and compliance, and this is one of the places where IBM is renowned for having all of the control and governance processes around data and systems. This is where the IBM consulting business has its strength, is in all of the checklists and the validation that they do to make sure that the systems that are built are compliant with both good practices, but also whatever legislative regime or industry standards are required. So this area of performance and compliance is a really significant one, and I'd focus particularly on the compliance piece as being something that's a little unique to IBM in here, just because of their history of doing large scale, massive, highly regulated environments through banking and defense, that compliance thing has been really vital for them.

But the third piece in here is expanding an ecosystem. And I think this is one of the big things that Arm brings in, because Arm has always been an ecosystem customer business. They've always been about licensing intellectual property to organizations that can then integrate with their systems, and having a unified platform of intellectual property across all the way from the embedded system, the things that you see in your telephone and your mobile phone, all the way up to the high performance that we see in the NVIDIA's Vera Rubin, their Vera CPU is Arm-based.

So that ecosystem play for modern applications, modern architectures based on Arm, combined with the huge legacy that IBM has working in large-scale enterprise regulated environments, I think this is potentially a very powerful partnership. Of course, there'll be some challenges along the way because all of the Arm innovation and the Arm partnership requires Arm CPUs. Now, absolutely, Arm will be very happy to license that CPU architecture to IBM to produce and integrate into their newer systems.

It may well turn up as an add-on to all of your existing IBM mainframe systems. It may be just a sidecar that's attached. Not quite sure how that's going to play out in the future, but there is a discussion in here around adding capabilities to your existing IBM infrastructure rather than having to build something completely new or buy completely new product.

So I think this is going to be really cool. As always with these kinds of partnerships, the devil will be in the detail, what actually gets shipped out to customers, how usable it is for customers, and what problems it really solves for those customers. I didn't see a lot of AI washing on this, which makes me feel really positive when the vendors can make a standalone talk of, "These are the things we're actually delivering," and not have to take whatever the latest hype is in their announcement.

I think that's a really good thing, too. And again, that's an IBM all over, that we'll stand on top of the really good things that we do and not necessarily get into the latest high-fashion topics. Maine is moving to pause the construction of large-scale AI data centers until at least 2027, potentially setting a nationwide precedent, and if you watched last week's rundown, running a bit afoul of the plans of the current administration.

Lawmakers in Maine cite rising energy consumption, high electricity costs, and environmental concerns, even as these facilities promise jobs and tax revenue. There's a tension between AI infrastructure growth and sustainability. And Maine's decision could influence the future of data center development across the US.

Well, Gina, do you think that the federal government is going to step in and actually put a block on these blocks? Block the blocks. That's a very interesting way to put it.

I don't know, but it is very interesting, especially for an administration that really seems to uphold the idea of states' rights and the states' rights to do what's the best for their own citizens. And Maine's not alone, and Maine wasn't the first governmental group to do a moratorium. The Seminole Nation of Oklahoma actually used that same hard stop model before them.

They also have passed a moratorium on generative AI technology and the HyperSale data center development for the same reasons. The reasons we talked about earlier, in fact, that these data centers require enormous amounts of water. They require enough energy to support entire cities, and if they promise to keep it off the grid, what they're doing is they're bringing in generators that, of course, the byproduct is pollution and kind of eliminate the clean air in these countryside areas where the developers are looking to build these data centers.

I find the Indian country angle pretty interesting. The Creek Nation also stopped a project, a data center project. And part of the problem and the reason that the Creek council member stopped it, the Muscogee, I'm sorry, the Muscogee council member stopped it was because all of the people that were involved in signing the project agreements from the Creek Nation were actually put under NDA, and they couldn't explain what was going on to the council members, which was very much contrary to their Constitution and to how they run things as a tribe.

So that's why the tribal members decided to put the moratorium on it until they could understand what's going on. So it's interesting because it shines a light on what the model is that these developers are doing. They're going in, they're promising lots of jobs, which they can't promise because they bring in the trade labor to build it, and then, of course, they leave with maybe 50 jobs because the data centers are not managed on-site.

" And we've seen that a lot in Texas as well. Right now, there's a growing movement from an organization called Honor the Earth that's tracking the data centers that are being planned on tribal nations' land. But that's happening all over the place.

I know here in Texas, that's also happening. One of the ones that has kind of got to me the most was there's a state park that is full of dinosaur footprints. It's a dinosaur state park is how everybody talks about it, and they're looking to put one of the data centers right next to it.

And it's not just the fact they're putting up the building. Then if you look at what's happened with the Meta data center in northern Louisiana, it changes everything because they have to build roads that were never there because it's a very rural area. They have to build roads.

There's constant traffic back and forth carrying materials to build the buildings. Total influx of people to build it, which results in man camps, which results in their own kind of issues. So, the states have every right to say, "Whoa, what's going on with this?

" And the latest tribal nation to do that was the Cherokee Nation in Oklahoma. Taking a look at what is this going to do for the nation, and what will we give up in order to have this here on our tribal lands? So, I think the states and the municipalities need to do that.

I think it's worth it for everybody to look into what's going on, and the only really good thing I can see from it is, hey, people care about data centers for the first time in my life, and I can actually explain it to them, and they don't roll their eyes like they don't care. So it's pretty cool. Komprise has introduced FlashStretch, a tool designed to help IT teams optimize flash memory usage and control rising storage costs driven by AI demand.

By analyzing data based on type, age, and usage, it identifies cold data that can be moved or tiered, freeing up capacity for high-performance workloads and reducing the need for additional storage. The approach helps organizations cut costs, streamline memory usage, and address ongoing DRAM and SSD constraints in the AI era. There's been huge cost increases for both SSDs and DRAM since the massive build-out of AI.

Data centers has been chewing up all of the potential supply. So these long-term contracts to acquire huge amounts of memory and huge amounts of SSD to go into these massive AI data centers that may or may not be built is driving up the cost of SSDs and DRAM for everybody else. What Komprise is doing here is providing a tool to take a look at your environment and maybe help you avoid having to buy additional DRAM and SSD capacity while these prices are so high.

You do that by taking the large amount of your data that's sitting on expensive SSD and migrating it to lower-cost, higher-capacity locations. Often with Komprise, this is moving it out to maybe some older NAS or something that's just got a lot of hard drives in it. So this is something we've always known is a good idea.

It's just that when the cost of SSD was very low, there wasn't actually that much return on investment to do this. As we're seeing higher than 100% increase in the cost of both SSD and DRAM, it makes more economic sense to start looking at efficiently using what you have rather than trying to acquire a huge amount more. Now, all the projections are that this is a transitory increase in cost.

This is not a permanent increase, that what we'll see is a return of supply over time. It'll come back one of two ways. Either new fabs will be built, in which case it'll take three to five years to resolve that, or some of those orders that are chewing up all of the projected production for the existing fabrication capacity, maybe those will get canceled because these AI data centers are being stalled.

Refer to our previous story. So Komprise is helping customers. Komprise, of course, would like you to use their software to do the migration and management of where these files reside and migrating the unused data out onto lower-cost storage.

Komprise has great products to help you do that. But this FlashStretch assessment tool is a great start to identifying whether you can get the benefits you need. Your data set may not be the same as everybody else's.

By the way, it probably is, and it probably does have 70% of the data stored on your high-performance, high-cost storage not being accessed in the last three to six months. So there's obviously potential for cost saving or cost avoidance using some tools that migrate across. " Amazon's reportedly in talks to acquire the satellite communication company Globalstar for a $9 billion price, and it's aimed at accelerating the Amazon Leo project, or what was previously called Kuiper.

This is the competition to Starlink from SpaceX. So this acquisition by Amazon could provide key assets as well as spectrum licenses and an established customer base to pay for things, as well as existing infrastructure, which will help that competition against SpaceX. But the deal may have some challenges along the way, particularly because Apple has a stake in Globalstar and uses Globalstar for that emergency satellite contact with Apple's iPhones.

Gina, do you think that this is going to go ahead? Is Amazon successfully going to acquire Globalstar, and will it make a difference and save them from launching a whole lot of satellites? Well, we're going to have to see, but this is another one of those interesting stories that have to do with the big companies, right?

So just like you said, this is Amazon sayingI'm tired of trying to play catch up, so this is how we're going to do it. That's why they're in talks to buy Globalstar for $9 billion. So where we're starting at is Amazon has about 200 satellites in orbit.

Starlink has 10,000 satellites in orbit. So that's how big the gap is that they're starting at. And of course, the Amazon stake in Globalstar is going to complicate the deal.

It's not a two-company negotiation. It's at least a three-body problem. The other person, the other guest in the room would be regulators.

So, Amazon's asking the regulators for more time to launch 1,600 satellites by July 26. So if this deal can go through, then they're able to buy some time with FCC because they acquired those satellites that they needed. And what Globalstar is, what they'll get for that is voice, data, and asset tracking across government, enterprise, and consumer markets.

So, of course, this made Wall Street go all crazy. They had a 15% pop right after this report launched, but it's still just a reported talk. It's not something that's gone through yet.

I'm guessing Amazon is going to really, really hope it goes through, but it probably is going to be at some cost to them, being that Apple has such a big stake and seems to be a big customer as well. So that's the thing to think about. Will this go through, and can Amazon continue to accelerate deployment and integrate assets so that they can have a chance of catching up with Starlink?

That's going to be tough to do even if it does go through. Microsoft field engineers have developed Project Nighthawk, a six-agent research system built into VS Code that retrieves, verifies, and documents answers to complex Azure Kubernetes Service and Azure Red Hat OpenShift questions. Unlike typical AI tools, Nighthawk works directly with live code repositories and official documentation to produce fact-checked, source-cited, and technical reports in minutes.

Its agent-based design, featuring roles like classifier, researcher, synthesizer, and fact checker, sets a new standard for reliable DevOps and internal AI research workflows. I think this is a proof of concept. I think this is more to show you how to build a complex tool.

When they talk about agents in here, they're really talking about what I think of as a microservice. Go out and use AI to retrieve some information or analyze some information. So although there's a lot of discussion here and in general about agents as being a separate thing, they're just event-driven microservices that happen to use AI.

This particular case, they're highlighting that those microservices, those agents, need to just do one task. One goes out and retrieves information. Another one of these microservices or these agents analyzes the retrieved information.

Another one produces the actual report. And so there's that segregation of duties that we've seen in microservices architectures for a long time in enterprise building new applications or modern applications. Now, the proof in this one is around looking at a complex system that is deploying maybe new compute nodes into a Kubernetes cluster, whether it's the Azure Kubernetes cluster or whether it's a Red Hat OpenShift Azure service.

Huh, that's two different cluster Kubernetes services on Azure. This particular tool lets you ask simple language questions against this set of agents, and so it allows you to be a lot more natural language in trying to find information. " Those of you who've not watched British comedy, maybe go look for that.

It's terrible, but rather funny. Another interesting thing in the coverage here is that it's returning to the idea that AI tools tend to hallucinate, and so they need to be grounded in facts. And this is one of the things that's really core in here.

One of the insights in this is that you can't just use a general purpose AI model by itself. You need to ground it in some facts, and that might be the documentation for how the service should work, the documentation for how the service should report its errors, but also the source code for whatever infrastructure as code you're using to deploy this new node or maybe deploy some pods on top of Kubernetes. That grounding of the individual AI components in some verifiable, citable facts is a really important part for using these agents to take action, not just report back to a human who will then validate.

So I think there's some really good things to learn from Project Nighthawk and to look at how it works together, how it builds these collection of agents, microservices, to build together a larger tool. Always liked seeing AI being used to achieve something rather than just as a user interface, so seeing these large language models working with the individual services. Another of the really important things about breaking up into multiple agents is you can use the right large language model or small language model or ML rather than generative AI.

You can use the right tool in each of the agents to achieve the thing that this agent is supposed to do. And this is the only way we're going to efficiently use AI over time. If we continue to use generic AI models to do every single task, we're doing things very inefficiently.

It's like not having any specialists on your team, only having generalists. Having language models that are suited to specific tasks is going to be important. I like this.

I think this architecture, this design of using essentially a microservices architecture with your AI agents is a really good thing, and we need to see more organizations doing this. Not just for operating their DevOps environments and their Kubernetes environments, but actually for operating their businesses. And fundamentally, this is why these kinds of papers are being published out, to show you how to operate using AI.

Now it's time for a little bit of a closer look. And President Donald Trump has appointed a high-profile group of tech leaders to the newly formed President's Council of Advisors on Science and Technology, PCAST. That group of high-profile leaders includes Mark Zuckerberg, Jensen Huang, Larry Ellison, and Sergey Brin.

They're tasked with shaping the US AI policy. Science and technology is all about AI. The council signals a push into accelerating innovation, streamlining regulation, and maintaining American leadership across the global AI race, particularly in competition with China.

The appointments highlight the council's potential impact on AI, national security, and the future of tech regulations, and it strikes me that all of the people that are named in the initial announcement are leaders of very large companies that have a vested interest in AI. Many of them are involved in the huge amounts of money that is changing hands to build out AI. What I'm looking for is some announcements of the remaining people.

And as we look through the list that's actually on this executive order that Donald has put out, we just see big business in here. We don't see a representation of any other interests beyond the core, people who are building AI things. And so I'm hoping that when this builds out to the full 24 members that the executive order tells us are going to be there, we'll see some representation of some other interests, that it won't just be a self-serving, let's build more AI and America has to be the only place where AI is being built, those kinds of ideas.

The actual executive order reads very much like a bunch of chest-beating and claims of the wonderful future of America can only be built by this board, and it's the leaders of big industry that are going to shape everything positive in the United States. Coming from a smaller country, I have a bit of a view on wanting to see some considerations other than sheer dominance. And so there are 11 more seats here on this council.

I hope we'll see some ethics and environmental considerations from the other members of the council over time. And it will be interesting to see whether they can get all of these luminaries within the IT industry to come together and actually meet and talk. It would be an interesting thing to see whether things actually go ahead.

Gina, is domination of the world of AI vital to the security interests of the United States and the best interests of the citizens of the United States? All I can say, especially today, is I don't think what's coming out of the White House represents how most Americans feel, especially since I'm on here with someone from a foreign country. We do not see things and feel things the same way.

And dominance is an interesting word to say, right? I think in the past, this kind of competition, and I think there are dangers from foreign states. We talk about it all the time when we talk about backup and recovery, and there's definitely foreign states, including the United States, use AI and technology against their enemies, right?

So it's interesting how it's phrased. It sounds like it's more of a TV blurb or a movie blurb, an entertainment blurb than it sounds appropriate for a presidential executive order. So having said that, I think it is important to understand that militaries will always use the latest technology either to protect themselves or to attack others, and we're seeing that play out in real-time, unfortunately.

So it's just part of the game. So, yeah, I think that's something all countries do, and I would imagine there's lots of countries doing that against us right now, the US. I also, getting back to the list, I found it funny that Musk is not on the list.

Elon Musk is not here. So that must have been a pretty bad bromance breakup. If you look at the other people, most of them are infrastructure folks with the exception of Zuckerberg.

But I want to focus on that one and draw a circle around it. They eliminated their ethics group. Most of the companies, the big companies, have eliminated their ethics groups.

So that's a problem there. They love to compare, they being the White House, loves to compare this AI act that they're doing to what Franklin Delano Roosevelt did back in the '30s. However, I'm pretty sure that he included scientists and not just people from IBM.

So there's a lot to be said for that. We don't have any scientists. We don't have any universities where all of this stuff was actually, it started out.

You want to find out about ML, and what really AI is, AI is a marketing term. It has been for the whole 50-something years it's been around. So if we want to find out about HPC, and we want to find out about machine learning and deep learning, universities is where you need to really have some of that inclusion too, because they're working on that.

The problem is thatThey also apply ethics and humanity, and investigate a lot of that. When we're working with a tool that can take data and manipulate it and display it in a different way, if you don't have some type of ethics... I came through from a technical viewpoint through college.

My bachelor's was from the School of Library Science. How do people look for information? How do they retrieve it?

What fills an information need? With a lack of that, you end up with a machine that can create, promote propaganda at the very least, when you look at the LLM side of the world, the information side of the world. So it's dangerous.

" I think what we can do is just remember, and now that we have everybody's attention with what is a data center, we can tell them this is what a data center does, and these are the words you need to be looking out for, and these are the things you need to question. And if there's a town meeting about these kind of things in your town, show up and ask the questions. You should do it, because we're going to give you the basic words for what we've been doing in our careers that you thought was just fixing your laptop when we came home to see you, into how data centers work.

And now you can go and have an authoritative voice and ask questions based on reality, because it's important. So I think the sun's going to come up every day. We got to remember that.

We're going to be here too, and there are ways to make sure that we get through this in a scientific, technical manner. But some of that's going to mean teaching your mom and dad what data center is. I think that's really important.

Yeah. Well, it is important to remember the sun will come up tomorrow. And it's already tomorrow here, and I can tell you the sun is coming up.

Being in New Zealand, I come from the future, and the sun has come up today. I really look forward to this Council of Advisors on Science and Technology having some people whose focus is on science and technology rather than simply on business. Not discounting the technical know-how of the people who are on this panel.

I would like to see, as you would, some more focus on those science foundational people who aren't necessarily just involved in commercial. Something that you should focus on right now. Right now, the Networking Field Day 40 is on.

So Tom Hollingsworth is not with us today because he, of course, is leading Networking Field Day 40. When you're listening to this, if you're listening to us as we release, as soon as we finish, you should head straight across and follow the rest of Networking Field Day. That's today, tomorrow, and Friday.

com, but also on our YouTube channel. A couple of weeks' time, we'll have the Tech Field Day experience at ClickConnect. So Stephen's heading out to ClickConnect in Orlando, if I remember rightly.

He's going to have a couple of days with some fun people out there. And then at the end of the month, it's going to be Security Field Day 15, and Tom is going to be once more in the West Coast and hosting a whole bunch of people. So look forward to those events.

Check out all of our upcoming events on the Tech Field Day website, as well as on our YouTube and LinkedIn. Of course, Gina will be out at ClickConnect with Stephen, so look forward to seeing all of her things she's learning and her insights there. For today, thanks for watching the Tech Field Day Rundown.

You can catch new episodes every Wednesday as a YouTube video on your favorite podcast application. The Rundown's also streamed on Techstrong TV, and you can often catch us on other Techstrong and Futurum Group programs. We'll be back next week to talk about all of the IT news that was, and until then, for myself, for Gina Rosenthal, and for all of us here at Tech Field Day, here's to wishing you and yours a great day.