Welcome to the podcast.
I'm your host, Jaden Schaefer.
Today on the podcast, we're covering the top four AI news stories happening today.
There is one that I'm super excited about.
I posted about this over on LinkedIn, but there is an LM engineer.
He just used chat, GPT and some AI tools to design a personalized cancer vaccine for his dog and actually shrink the tumor.
NVIDIA is preparing to unveil its next generation of AI chips.
OpenAI is reportedly working on a massive enterprise partnership with PE firms, which is kind of interesting.
And then the big story I want to talk about that everyone is talking about is that Meta is preparing to lay off potentially more than 20 of its workforce while ramping up AI spending.
So they're making a lot of money.
They're just cutting their workforce to spend more on AI.
And this is what we've already seen from a bunch of other players in the industry.
So let's get into all of it and the implications in the whole industry of AI.
Before we do.
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All right, let's get into the first story.
Today is this kind of cancer vaccine that was created for a dog.
So basically, this is coming out of australia.
It's pretty wild.
There's a tech entrepreneur named paul conaham and he decided to try something.
Basically, he went to the vet and they told him that his rescue dog rosie, only had a few months left to live because she had a really advanced cancer.
So I think, instead of doing what a lot of people do most, I mean everyone really and just kind of accepting the prognosis, he decided to use AI tools, including chat, GPT and then Google's alpha fold, to analyze the tumor.
So he had Rosie's healthy DNA, and then he had her DNA sequenced. from the tumor.
And then he converted the tumor tissue into data and used ChatGPT to identify the mutations that were driving the cancer.
This is incredible.
Not because, you know, not because I think a lot of people will be like oh, he's like kind of in tech.
So that's how he was able to do this.
He has no background in biology, right?
He's just literally working with ChatGPT and asking how to do this.
How do I sequence DNA?
How do I like, what do I do with the tumor data that they gave me?
And he was able to take all of this.
And then he went and found some researchers at New South Wales and they designed a custom mRNA vaccine tailored specifically to Rosie's tumor.
The thing that took the longest because they actually got that done pretty quick.
The thing that took the longest is that they had to wait three months just for the regulation to approve that it was going to be safe to vaccinate his dog, which kind of is horrible, considering it only had months left to live and he's probably super stressed about it.
And the regulation took longer than them cranking out this vaccine just with chat GPT.
And then Rosie received her first injection in December.
And then by March she had about a tennis ball-sized tumor and had shrunk about 75 and continuing to shrink.
So researchers believe that this might be the first kind of personalized cancer vaccine ever created for a dog.
But this also will work for humans.
And I think the bigger implication here is that the same approach is already being tested in humans by companies like Moderna, Merck and Pfizer bio and tech.
Now, of course, when we're doing humans, there's so much red tape and regulations probably won't be available for years, which is honestly a huge shame in my opinion.
And don't even get me started on my thoughts on the pharmaceutical industry in this regard, and perhaps as regulation in America, but I don't know, not my favorite thing.
It's incredible that he was able to make this for his dog really quick and get it ready in three months a custom vaccine.
So I think this obviously started out as a really desperate attempt to save his dog, but I think it's actually a preview of AI-driven personalized medicine that we're going to see more of, and hopefully we'll see this for humans in the future.
Next up, NVIDIA is preparing a major AI chip reveal.
NVIDIA's massive AI conference is called GTC.
It's kicking off, and Jensen Huang is expected to unveil the company's next generation of AI chips.
These chips are designed for the next wave of AI models and large-scale inferences. workloads.
I think right now we're really entering a phase where companies aren't just training models, they're actually deploying them everywhere.
And so that means that the demand for the inference compute is exploding.
And Nvidia to this point has already become really the central infrastructure provider for the AI boom.
And I think you know, every new generation of chip basically resets the performance ceiling for the entire industry.
So if Nvidia, you know, reveals another major leap, I think it's going to accelerate the entire AI ecosystem again.
So that is what I would say to look out for at GTC.
Another thing that's incredible right now is that OpenAI is exploring a 10 billion enterprise AI venture.
They're in talks with several major private equity firms about launching a joint venture which is focused on deploying AI across corporate America.
Now, why is this important?
It's like, oh, great, another OpenAI corporate kind of partnership.
We've seen a bunch of these enterprise partnerships, yada, yada, what's the big deal?
I think what's interesting is who's involved here.
So the firms that are involved in this are TPG, Bain Capital, Advent and Brookfield.
And the venture could be valued at about 10 billion.
About 4 billion of that is in outside investment.
Oh my gosh.
I don't know if you guys can hear me, but I'm in North Carolina right now and there's a huge thunderstorm going outside.
I just heard a huge crack of thunder.
My audio enhancing software probably cut it out, but just throwing that out there for you.
It's exciting times over here while we're.
It's an ominous sound as I'm talking about this 10 billion deal, but not really.
I think it's actually a cool deal.
Private equity firms.
Right now, they own thousands of companies across a lot of different industries.
So basically, if OpenAI tools are getting rolled out across all of the portfolios, right?
So how it works is those four major PE companies.
They're going to roll out OpenAI software across all of their portfolio companies.
And I think that is going to help the AI adoption scale very fast in those organizations if they can pull this off correctly.
Now, are those portfolio companies not already using AI is the question.
If they're tech companies, I think they probably are.
But There's a lot of industries where AI is very good and proficient and the firms are just not using it.
And Anthropic recently put out a report on this whole thing, where they were kind of showing where AI was very proficient at different tasks and where it was being used.
And there were some huge gaps.
For example, engineers.
AI is great at a lot of engineering tasks and it's less than 2 of engineers for, like architectural engineers, that are using AI in their workflows and what they're doing.
So These types of deals are actually pretty big if they can get into those types of organizations.
And I think it also helps.
And beyond just, you know, helping AI adoption.
I mean, it's obviously helping OpenAI's AI adoption, because perhaps if those companies are using AI, they're using Google or Cloud or another player.
So this is pretty interesting.
Instead of selling tools one company at a time.
If you just hit all of the big owners, these big private equity owners that own multiple companies, you can get it rolled out much faster.
So this is going to be interesting.
The biggest story of the day though, is that Meta has kind of announced or there's leaks from inside Meta that they might cut up to 20 of their entire company.
And they're doing all of this to expand AI inside their organization.
So after there was kind of these leaks, meta stock jumped about three percent.
After the report surfaced um, that there was kind of this massive round of layoffs that was going to be tied directly to ai spending.
This is all, according to a report out of routers, by the way.
So senior leaders inside of meta have been asked to prepare plans that could reduce the company's workforce by more than 20.
If it happens, it could affect over 15 000 employees.
This could be one of the largest layoffs in meta's history.
The company had about 79000 employees at the end of 2025.
And I think these potential cuts would really dwarf the 11000 person layoffs that they announced back in 2022.
So they have been, you know, cutting people or they've been known to do these types of cuts before.
But over 15,000 employees could be one of their biggest yet.
Meta hasn't confirmed this report.
You know they're just like oh, this is just speculative, aka like they're just figuring it out right now.
But I think the context about the story is telling us a lot.
Basically, Meta right now is planning an absolutely enormous AI spending push.
They're planning on, you know, it's... you know, astronomical how much they want to spend on AI.
And because of this, they need to come up with the money somewhere.
And this is part of it.
Meta says that our AI related capital expenditures this year will fall somewhere between 115 billion and 135 billion, as they're building out new AI infrastructure.
That's part of a 700 billion total AI spending wave that we're expecting across a bunch of these big companies.
Amazon Microsoft Alphabet Meta, all of them are.
You know they have basically CapEx plans that are putting them at about 700 billion that are going to be coming over the next few years.
And I think right now the message from the leadership over at Meta is pretty clear.
You know, AI is now their top priority.
Zuckerberg has been, you know, kind of framing 2026 as a year that Meta pushes towards what he's calling personalized superintelligence.
Last year, they spent $14.3 billion investing in scale AI.
Then they hired their CEO, Alexander Wang, with a bunch of their other top researchers.
So I think we're starting to see this kind of strategy change, this clarity in their strategy right now.
Right, they're spending these huge amounts of money on ai infrastructure and talent.
Right, because there was, like you know, reports that some of these deals were worth a billion dollars.
Um when, just like, hiring talent like the top researcher would cost a billion dollars, and that's because they're, you know, give them a couple hundred million dollars and then tons of stock and equity and stuff, they got to stick around for like five or six years.
So Anyway, or maybe it was like an eight year deal, a billion dollars for eight years for some of these top AI researchers.
So anyways, I mean, and that's all speculative and that depends on the stock price and a bunch of other things.
But like Meta is spending a ton of money.
And I think that that is very clear.
But of course, They have to offset those costs because that money isn't coming out of thin air.
And so what I will also say is Meta's not the only one that's doing these layoffs.
Block also recently announced layoffs.
There was about 4,000 employees.
And I believe that that was like 40% of the entire company of Block.
We're just seeing companies want smaller teams that can move faster with AI.
Amazon is cutting 16,000 roles earlier this year.
Atlassian just announced that they're cutting 10 of their workforce and they are redirecting all of that money into AI.
And then there's also a consulting firm, Challenger Grain Christmas.
And they said that AI has already been cited in more than 12000 job cuts in the US this year so far.
And it's kind of interesting because I believe it's actually higher.
But companies like Amazon, when they cut 16,000, people are like, oh, it's not related to AI.
We're just, you know, trimming up the company and rearranging things a little bit.
But honestly, I believe it's due to a lot of shifts that are happening in industries now.
Is Amazon and Meta and Elasti and all these other companies.
Are they permanently cutting these roles?
I don't think so.
I think in the next couple of years, we'll bring them all back in.
But I do think that we're reevaluating and we can do more with less due to AI.
So I think we're going to see kind of this initial wave of layoffs.
And then I think, as the companies kind of find their equilibrium again, they'll start hiring people back and making sure that everyone they hire is kind of AI first and understands how to use these tools.
Some analysts say that companies are just basically using the AI as a convenient explanation for layoffs right.
Like, hey, we got to become more profitable.
We're going to do layoffs and let's just blame it on AI.
But I think I think that's maybe partially true.
But I do believe that AI is actually, you know, dramatically increasing productivity.
And so you just don't need the same headcount to grow revenue.
And if meta actually follows through with the cuts that they're doing at this scale, while also ramping up AI spending, I think it could become one of the biggest signals yet of how the AI economy is reshaping the tech industry.
So I guess, if we just kind of zoom out on all of these stories I covered today, they basically all have the same theme, which is that AI is not just this kind of like cool technology experiment that it feels like we've been doing for the last couple years.
Right now I think we're seeing 2026.
I mean, especially with all the layoffs that it is restructuring the entire industry, personalized medicine, you know, trillion dollar chip infrastructure that's being built out.
There's private equity deploying AI across thousands of companies.
I think now is potentially one of the biggest workforce restructurings in, you know, big tech history that we're about to see.
I think the AI era is not coming, as I've been saying for a long time.
I think it's already here.
And this is probably going to accelerate on almost all of these kind of genres that I covered today.
So the Thank you so much for tuning into the podcast.
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All right, I'll catch you on the next episode.
