The $85 Billion AI Signal and Star Trek Computing I 4th June

Google's parent company just raised a record-breaking $85 billion for AI investments while Nvidia is already planning chips that could create Star Trek-level computers. Meanwhile, OpenAI and Anthropic are teaming up to prevent AI bioweapons, Trump finally signed his AI executive order, and Anthropic might be going public. From massive funding rounds to sci-fi computing goals to real biosecurity concerns, today's AI landscape is moving at warp speed and we're breaking down what it all means for you.

Transcript

SPEAKER_01 0:00

Genuine question. If you found out that Alphabet just raised eighty-five billion dollars specifically for AI development, and I told you that was a record-breaking amount, would your first reaction be excitement or terror?

SPEAKER_00 0:12

Honestly, both. Like, that's more money than the GDP of most countries being thrown at artificial intelligence. My brain immediately goes to holy crap, they must see something massive coming. And also, what exactly are they planning to build with all that cash?

SPEAKER_01 0:31

Right? Because $85 billion isn't let's see what happens money. That's we know exactly where this is going, and we're betting everything on it, money.

SPEAKER_00 0:39

And when you combine that with what NVIDIA's planning, which we'll get to, it feels like we're watching the foundation being laid for something completely different than what we have today.

SPEAKER_01 0:51

Something that might look a lot like science fiction becoming reality.

SPEAKER_00 0:55

But but here's what gets me. If Google feels they need that much capital to stay competitive, what does that say about how fast this space is moving? Like, are they responding to something we don't know about yet?

SPEAKER_01 1:09

That's exactly what I was thinking. This feels less like opportunistic fundraising and more like emergency preparation for whatever's coming next in AI. You're listening to Build by AI. I'm Alex Shannon, and that record-breaking funding round is just one of several major stories we're diving into today.

SPEAKER_00 1:28

And I'm Sam Hinton. We've got NVIDIA literally planning Star Trek computers, AI companies joining forces to prevent bioweapons, and what might be the biggest AI IPO filing we've seen. Plus, Trump finally signed that executive order everyone's been waiting for.

SPEAKER_01 1:53

It's June 4th, 2026, and honestly, it feels like every single story today is about setting up the next phase of AI development.

SPEAKER_00 2:01

Yeah, like we're watching the chess pieces being moved into position for whatever comes next. All right, let's start with that massive Alphabet raise and figure out what the hell is actually happening here.

SPEAKER_01 2:19

So, according to early reports from TechCrunch, Alphabet just completed what they're calling a record-breaking $85 billion stock sale. And this isn't just any fundraising. This is specifically being framed as a signal of massive investor confidence in AI-related investments and business opportunities.

SPEAKER_00 2:37

Dude, let me put this in perspective. $85 billion is more than the annual revenue of most Fortune 500 companies. This isn't venture capital or even a typical public offering. This is Alphabet saying we need war chest money for AI, and the market saying, here, take all of it.

SPEAKER_01 3:03

Right, and the timing is interesting too. Why now? What are they seeing in their internal AI development that made them go we need this much capital immediately?

SPEAKER_00 3:12

That's exactly what I'm thinking about. Because Google already has massive cash reserves, right? They're not hurting for money. So this feels less like we need funding, and more like we need to move faster than anyone else can possibly move. It's like they're trying to create an insurmountable advantage.

SPEAKER_01 3:30

But here's what I'm wondering. Is this actually good for innovation? Or does this kind of massive capital concentration mean that smaller AI companies are basically done? Like, how do you compete against $85 billion?

SPEAKER_00 3:44

Oh, that's a great point. We might be watching the AI equivalent of the railroad boom where whoever has the most capital to lay the most track wins everything. But I think there's still room for specialized players. The question is whether they'll stay independent or just become acquisition targets for Google.

SPEAKER_01 4:06

And for regular people and businesses, what does this mean? Because that money isn't going to sit in a bank account. It's going to get deployed into AI products and services pretty quickly.

SPEAKER_00 4:17

Exactly. I think we're about to see a massive acceleration in AI capabilities across Google's entire ecosystem. Gmail, search, cloud, Android, everything is about to get a serious AI upgrade. But also this signals to every other tech giant that if you're not raising billions for AI, you're already behind.

SPEAKER_01 4:37

So keep an eye on whether Microsoft, Amazon, and others start announcing similar massive funding rounds. Because if they don't, Google might just run away with this whole thing.

SPEAKER_00 4:48

You know what's wild though? The fact that the market had this much appetite for an AI-focused raise. Like, investors are literally betting that AI is going to generate returns that justify $85 billion in new investment. That's not just confidence, that's conviction.

SPEAKER_01 5:12

Which brings up another angle. What happens if Google doesn't deliver on the implicit promises of this raise? Because when you take that much money for AI development, expectations are going to be astronomical.

SPEAKER_00 5:24

True. But honestly, given what we're seeing in terms of AI capabilities right now, I think the bigger risk might be that they deliver too well too fast. Like what if this money actually does help them build something that completely disrupts every other tech company?

SPEAKER_01 5:42

That's probably the scenario that keeps Microsoft's executives up at night. Because Google isn't just raising money. They're signaling that they think the AI race is about to enter a completely different phase, and they want to make sure that they win it decisively.

SPEAKER_00 5:55

And if you're a developer or a business owner listening to this, the takeaway might be to start thinking about how Google's massively upgraded AI capabilities are going to affect your products and services. Because this isn't abstract. This is going to impact real businesses in the next year or two.

SPEAKER_01 6:14

Absolutely. Whether it's through better AI assistance, more sophisticated search, or completely new AI-powered tools we haven't seen yet, $85 billion of development is going to show up in products you actually use. Alright. Speaking of massive investments in AI's future, let's talk about what NVIDIA's planning. According to The Verge, they're already developing next generation N2X and N3X chips. And here's the kicker. Their stated goal is to create advanced AI computing capabilities comparable to Star Trek's computer systems.

SPEAKER_00 6:47

Wait, hold on. They literally said Star Trek computer? Like Jensen Huang stood up and said, We're building the enterprise computer because that's either the most brilliant marketing I've ever heard, or they're genuinely serious about creating something that ambitious.

SPEAKER_01 7:03

Right. And they mentioned something called RTX Spark as an intermediate development step. So it sounds like they have an actual roadmap from where we are now to apparently science fiction-level computing.

SPEAKER_00 7:14

Okay. But let's think about what a Star Trek computer actually does. It understands natural language perfectly, it can analyze massive amounts of data instantly, it can run complex simulations in real time, and it basically serves as an intelligent interface to all of human knowledge. That's not just better chips, that's a completely different paradigm.

SPEAKER_01 7:34

But here's what I'm skeptical about. Is this actually achievable with better hardware or are they overpromising? Because we've seen plenty of companies promise revolutionary breakthroughs that turn out to be incremental improvements with better marketing.

SPEAKER_00 7:49

You know what though? Nvidia has actually delivered on their bold promises before. They basically created the entire modern AI boom with their GPU architecture. And if anyone has the engineering talent and resources to attempt something this ambitious, it's them. Plus, when you combine this with Google's $85 billion war chest, you start to see how this could actually happen.

SPEAKER_01 8:19

That's a good point. And for developers and businesses, what does this mean practically? Because if Nvidia is planning chips that are orders of magnitude, more powerful than what we have today, that could completely change what's possible with AI applications.

SPEAKER_00 8:34

Absolutely. Imagine being able to run GPT-4-level models on your laptop or having real-time AI video generation or actually useful AI assistance that can handle complex multi-step tasks. We might be looking at the hardware foundation for true artificial general intelligence.

SPEAKER_01 8:55

Although, let's be honest, if they actually achieve Star Trek level computing, the real question becomes whether we're ready for the social and economic implications of that kind of technological leap.

SPEAKER_00 9:07

But here's what I find fascinating about the timeline. The fact that they're already planning N2X and N3X suggests they think this is achievable within the next few hardware generations. That's not 20 years out. That's maybe five to seven years.

SPEAKER_01 9:23

Which is insane when you think about it. Like if someone in 2016 had told you we'd have chat GPT by 2022, you would have laughed. And now NVIDIA is basically saying, hold our beer, we're building the enterprise computer by 2030.

SPEAKER_00 9:38

Exactly. And the RTX Spark as an intermediate step makes me think they're not just throwing around sci-fi references for fun. They have actual technical milestones mapped out. It's like they're treating the enterprise computer as an engineering problem rather than science fiction.

SPEAKER_01 9:55

From a business perspective, this is also smart positioning. By publicly stating such an ambitious goal, they're essentially claiming leadership of the long-term AI hardware vision. Even if they only get halfway there, that's still revolutionary.

SPEAKER_00 10:10

True. But it also puts enormous pressure on them to deliver. Because if competitors start making progress towards similar goals and NVIDIA falls behind on their own roadmap, this bold vision could backfire spectacularly.

SPEAKER_01 10:25

Good point. And there's the question of whether the software side can keep up with the hardware ambitions. You can build the most powerful chip in the world. But if developers can't figure out how to use it effectively, it doesn't matter.

SPEAKER_00 10:37

Although that's where the ecosystem comes in. Nvidia has been really smart about building not just chips but entire development platforms. CUDA, their AI software stack, all the tools that make it easier for developers to actually use their hardware. So they're not just betting on raw computing power.

SPEAKER_01 11:00

And if this works, if they actually deliver something close to Star Trek computing, the ripple effects are going to be everywhere. Education, healthcare, scientific research, entertainment. Basically every industry that involves information processing, which is most of them.

SPEAKER_00 11:17

The other wild thing is imagining what this means for personal computing. Like, if your smartphone has Star Trek computer capabilities, what does that look like? How do you even interface with something that powerful?

SPEAKER_01 11:31

Right, we might need completely new user interface paradigms. Touch screens and keyboards might start to feel as outdated as punch cards. But honestly, that's a problem I'm excited to have. Now shifting from the exciting possibilities to the serious responsibilities, OpenAI and Anthropic have signed a joint letter to lawmakers urging them to implement better tracking systems for synthetic DNA sequences that could be misused for creating bioweapons. This is verified across multiple sources, including Wired and TechCrunch.

SPEAKER_00 12:03

Okay, this is huge, and I'm glad these companies are taking this seriously because we've been talking about AI risks in abstract terms, but this is concrete. AI is already capable of helping design biological sequences, and that same capability that could cure diseases could also create really dangerous pathogens.

SPEAKER_01 12:25

What's interesting is that open AI and anthropic are usually competitors, but they're coordinating on biosecurity issues. That suggests this threat is serious enough that they're willing to work together on policy responses.

SPEAKER_00 12:38

Exactly. Um and it's not just them. The letter mentions leading AI labs and scientists are coordinating on this. That tells me the technical experts are genuinely worried about near-term risks, not just hypothetical future scenarios. When competitors start working together on safety issues, that's a strong signal.

SPEAKER_01 12:56

But here's what I'm wondering about the practical implementation. How do you actually track synthetic DNA sequences without creating massive privacy and research freedom issues? Like, are we talking about monitoring every biology lab in the world?

SPEAKER_00 13:11

That's the trillion-dollar question, right? You need oversight that can catch bad actors without strangling legitimate research. I imagine it's something like monitoring certain high-risk sequences or requiring reporting for specific types of synthesis. But yeah, the implementation details are going to be crucial.

SPEAKER_01 13:32

And this raises bigger questions about AI governance. If AI companies are taking the initiative to self-regulate on biosecurity, what other areas might need similar proactive approaches? Are we going to see more industry-wide coordination on AI safety issues?

SPEAKER_00 13:48

I think we have to, because the alternative is waiting for governments to figure out how to regulate technologies they barely understand, and by then it might be too late. This letter feels like a template for how the AI industry could handle other risk areas, cybersecurity, misinformation, autonomous weapons.

SPEAKER_01 14:08

So this might actually be one of the most important stories we're covering today, even though it's getting less attention than the funding rounds and chip developments.

SPEAKER_00 14:16

Absolutely. Because what this shows is that AI companies are starting to think seriously about dual-use technologies. The same AI that helps scientists discover new medicines could help bad actors design biological weapons. That's not science fiction. That's a real capability we need to manage carefully.

SPEAKER_01 14:38

And I appreciate that they're being proactive about it rather than reactive. Too often in tech, we see companies wait until there's a crisis before they take responsibility seriously. This feels different.

SPEAKER_00 14:49

It really does. Although I wonder if this is also strategic positioning. By taking the lead on AI safety and regulation, these companies might be trying to shape the rules in ways that work better for them than for potential competitors.

SPEAKER_01 15:03

That's possible, but honestly, even if there are strategic motivations, the outcome could still be positive. Better biosecurity frameworks benefit everyone, regardless of who proposed them.

SPEAKER_00 15:14

True. And uh the fact that it's a joint effort between OpenAI and Anthropic specifically is interesting. Uh these are arguably the two most prominent I uh safety-focused companies, so that their collaboration on this issue carries extra weight.

SPEAKER_01 15:33

What this really highlights is how quickly AI capabilities are advancing into areas with serious security implications. Biological research is just one domain. Imagine similar concerns around AI designed cyber weapons or autonomous military systems.

SPEAKER_00 15:49

Yeah. And uh the the time frames are compressed too. Traditional biological weapons development might take months or years of specialized expertise. AI could potentially accelerate that process dramatically, which is why the tracking systems need to be in place now, not later.

SPEAKER_01 16:07

For people working in biology or related fields, this is probably something to watch closely. These tracking systems could affect legitimate research workflows, so understanding what's coming is important.

SPEAKER_00 16:19

And for everyone else, it's a reminder that AI development isn't just about cool new products. We're dealing with technologies that have serious implications for global security, and the companies building these systems are starting to take that responsibility seriously.

SPEAKER_01 16:36

Which honestly gives me more confidence in the direction of AI development. When the leading companies are actively trying to prevent misuse of their technologies, that suggests we might be handling this transition better than some of the more dystopian predictions. Let's talk about the policy side for a minute. President Trump signed a new AI executive order on Monday night, and this comes after an earlier version of the order was previously shelved. Multiple sources, including Wired and MIT Technology Review, are reporting this represents a shift in the administration's approach to AI regulation.

SPEAKER_00 17:09

Yeah, the fact that they shelved an earlier version tells us there was some serious internal debate about how to approach this. The question is, what changed? Did they get spooked by something specific, or did they finally figure out a regulatory framework that actually makes sense?

SPEAKER_01 17:29

Right. And the timing is curious too. You've got Google raising $85 billion for AI, Nvidia planning Star Trek computers, and AI companies coordinating on bioweapon prevention. It feels like the administration is responding to the pace of development rather than trying to get ahead of it.

SPEAKER_00 17:46

You know, that's been the challenge with AI policy all along, though. The technology moves faster than government can keep up. But I'm actually encouraged that they they took time to revise instead of just rushing something out. Better to get it right than to create regulations that become obsolete in six months.

SPEAKER_01 18:03

Although we don't have details yet about what's actually in the executive order. For all we know, it could be mostly symbolic or it could be pretty substantive. The devil's going to be in the details. Absolutely.

SPEAKER_00 18:16

Um and honestly, given everything else happening in AI right now, uh this feels like one of those moments where government policy either helps accelerate beneficial AI development or accidentally slows down American competitiveness. There's a lot riding on getting this balance right.

SPEAKER_01 18:40

Especially when you consider the global competition aspect. China isn't sitting around waiting for perfect AI regulations. They're moving fast and breaking things.

SPEAKER_00 18:50

Exactly. So so the real test will be whether this executive order creates guardrails that actually work while still letting American companies innovate and compete. We'll have to see what the implementation looks like over the next few months.

SPEAKER_01 19:06

Definitely something to keep watching, especially as more details emerge about what specific requirements and frameworks are included.

SPEAKER_00 19:14

But you know what's interesting? The fact that there was an earlier version that got shelved suggests there might have been some pretty significant disagreements within the administration about how aggressive to be with AI regulation.

SPEAKER_01 19:29

That makes sense because you've got competing interests here. On one hand, you want to ensure AI development is safe and beneficial. On the other hand, you don't want to kneecap American AI companies while China and other countries pull ahead.

SPEAKER_00 19:51

Tech companies want one thing, healthcare companies want another. Defense contractors want something else entirely.

SPEAKER_01 19:58

Which might explain why it took so long to finalize. Writing AI policy that satisfies all those stakeholders while actually being effective is probably incredibly difficult.

SPEAKER_00 20:08

True. And honestly, given the complexity of AI technology and its potential applications, I'd rather see thoughtful, well-considered policy than rushed regulations that sound good but don't actually work.

SPEAKER_01 20:21

The question now is whether other countries look at this as a model for their own AI policies, or whether we're going to see completely different regulatory approaches around the world.

SPEAKER_00 20:31

That's huge. Because fragmented AI regulations could create real challenges for companies trying to build global AI products. You don't want to be in a situation where your AI system is legal in one country, but not another.

SPEAKER_01 20:51

And for businesses using AI, regulatory uncertainty is killer. If you don't know what the rules are going to be, it's hard to make long-term investments in AI capabilities.

SPEAKER_00 21:02

So hopefully this executive order provides some clarity and stability, at least for the next few years. Even if it's not perfect. Predictable rules are often better than no rules or constantly changing rules.

SPEAKER_01 21:17

First up, early reports suggest Meta's AI agent for WhatsApp business is now available globally, with businesses charged based on token usage.

SPEAKER_00 21:27

This is smart positioning by Meta. WhatsApp has massive global reach, especially for business communications, and an AI agent that can handle customer service automatically could be huge for small and medium businesses. The token based pricing makes it accessible too.

SPEAKER_01 21:44

And it's interesting that Meta is going after the business market rather than just consumer features. That suggests they see real revenue potential in B2B AI applications.

SPEAKER_00 21:55

Absolutely. Plus, WhatsApp business already has built in billing. And business verification systems. So adding AI agents is a natural evolution. This could be a significant revenue driver for Meta if businesses adopt it widely.

SPEAKER_01 22:12

Next, we've got Lovable signing a multi-year expansion deal with Google Cloud that involves a five times increase in usage and expanded access to Anthropic's clawed AI model.

SPEAKER_00 22:23

Okay, this is interesting because it shows how the cloud providers are becoming AI distribution channels. Google Cloud isn't just selling compute anymore. They're selling access to the best AI models. And a 5x usage increase suggests Lovable is seeing serious demand for AI-powered development tools.

SPEAKER_01 22:45

That 5x expansion is massive. Either Lovable's business is growing incredibly fast, or they're planning something big that requires way more AI compute than they're currently using.

SPEAKER_00 22:55

And the fact that it includes expanded access to Claude specifically is notable. That's Anthropic's most advanced model. So Lovable must be building some pretty sophisticated AI features. This could signal where AI-powered development tools are heading.

SPEAKER_01 23:12

Then we have UK regulators requiring Google to offer publishers an opt-out tool for generative AI search features, with testing in the UK before global rollout.

SPEAKER_00 23:22

This feels inevitable, right? Publishers have been complaining that AI search summaries reduce traffic to their websites. An opt-out tool is probably the minimum viable solution, though I'm curious how many publishers will actually use it versus just demanding better revenue sharing.

SPEAKER_01 23:40

It's a tricky balance because users probably prefer AI summaries over clicking through to multiple websites. But publishers need traffic to survive. This opt-out tool might be the first step toward more comprehensive revenue sharing agreements.

SPEAKER_00 23:54

And testing in the UK first is smart. It's a significant market, but not so large that major mistakes would be catastrophic. If it works there, global rollout becomes much safer.

SPEAKER_01 24:06

And finally, Anthropic has made a confidential SEC filing as it moves toward a potential Wall Street debut.

SPEAKER_00 24:14

Whoa. That's actually huge news buried in the rapid fire section. An anthropic IPO could be massive, especially given their reputation for AI safety leadership and their clawed models capabilities. This could be the first major AI-focused public offering since the current boom started. That's definitely worth watching closely.

SPEAKER_01 24:37

The timing is interesting too. If Anthropic goes public now, they'd be capitalizing on peak AI hype while also getting access to public market capital to compete with Google's $85 billion war chest.

SPEAKER_00 24:50

And for retail investors, this could be the first chance to directly invest in a pure play AI company rather than just tech giants that happen to do AI. That could drive serious demand for the stock.

SPEAKER_01 25:05

Alright. If you zoom out and look at everything we covered today, record-breaking funding, next generation computing hardware, proactive safety coordination, policy responses, and potential IPOs. What's the pattern here?

SPEAKER_00 25:19

It feels like we're watching the AI industry mature in real time. Like we're moving from the let's see what's possible phase to the let's build the infrastructure for the next decade phase.

SPEAKER_01 25:38

Right. And there's this interesting tension between moving incredibly fast, like NVIDIA planning Star Trek computers, while also taking responsibility seriously enough that competitors are coordinating on safety issues.

SPEAKER_00 25:51

Yeah, it's like the industry is growing up. They're starting to think beyond just the next product release to the long-term implications of what they're building, whether that's bioweapon prevention or sustainable business models or regulatory compliance.

SPEAKER_01 26:07

So the question for people listening is are you ready for this pace of change? Because if today's stories are any indication, the next few years are going to make the last few years look slow.

SPEAKER_00 26:18

And honestly, I think the companies that figure out how to adapt quickly while maintaining some ethical guardrails are going to be the ones that succeed in this next phase. It's not just about having the best technology anymore. It's about having the best technology that people actually trust and want to use.

SPEAKER_01 26:37

But let's talk about what this means for different groups of people. If you're a developer, you're probably looking at this and thinking about how to position yourself for a world where AI capabilities are exponentially more powerful than today.

SPEAKER_00 26:50

Absolutely. And if you're running a business, you need to start thinking strategically about how these AI advances are going to affect your industry. Because Google's $85 billion isn't going to sit idle. It's going to turn into products and services that could disrupt everything.

SPEAKER_01 27:14

For policymakers, there's this challenge of writing regulations that can adapt to the pace of AI development. Today's executive order might be obsolete by the time Nvidia's N2X chips actually ship.

SPEAKER_00 27:25

And for regular consumers, I think the big question is whether all this AI advancement actually translates into better daily experiences, or whether it just makes technology more complex and harder to understand, harder.

SPEAKER_01 27:42

That's a great point. Because Star Trek computers sound amazing in theory, but in practice, do people want to talk to their devices like their crew members on a starship? Or do they just want their current tools to work better?

SPEAKER_00 27:55

I think it depends on the implementation. If AI makes technology feel more natural and intuitive, people will love it. But if it makes simple tasks more complicated, because now you have to negotiate with an AI assistant that could backfire.

SPEAKER_01 28:11

And there's the broader economic question too. All this AI investment and development is going to create winners and losers. Some jobs are going to get way better, others might disappear entirely.

SPEAKER_00 28:22

Which is why I think the biosecurity coordination we talked about is so important. Shows that at least some AI companies are thinking about the broader implications of their technology, not just the immediate business opportunities.

SPEAKER_01 28:38

True. And maybe that's the most encouraging thing about today's news. Yes, we're seeing massive investments and ambitious technical goals, but we're also seeing proactive responsibility and policy engagement.

SPEAKER_00 28:51

Exactly. It's not just a race to build the most powerful AI anymore. It's it's becoming a more mature conversation about how to build powerful AI systems that actually benefit society.

SPEAKER_01 29:04

Although, let's be honest, $85 billion still suggests the race element isn't going anywhere. It's just that now the race includes safety and responsibility as part of the competitive landscape.

SPEAKER_00 29:16

Which might actually be the best outcome. If being responsible and trustworthy becomes a competitive advantage, then market forces start working in favor of beneficial AI development.

SPEAKER_01 29:28

And looking ahead, I think we're going to see this pattern continue. Massive technical advances paired with increasing attention to governance and safety. The question is whether we can maintain that balance as the capabilities get even more powerful. That's all for today on Build by AI. If you're not already subscribed, definitely hit that button because this stuff is moving way too fast to miss episodes.