So is AI actually coming for your job? Or maybe is it creating totally new ones, things we can't even picture yet? And what happens when the internet itself, you know, the global network we rely on starts to kind of break apart? Beep. Welcome to the Deep Dive. Today we're digging into a really fascinating set of sources, mainly a recent newsletter that caught our eye. Our goal here is simple. Give you the essential insights, a shortcut really, to understanding the big AI
trends shaping things right now. We'll cut through the noise, connect the dots for you, and get you up to speed without the usual information overload. Exactly. And for this deep dive, we're starting with Goldman Sachs. They've got this... surprisingly nuanced view on AI and jobs. Then we'll jump into some really cool and maybe slightly weird AI highlights. Think AI influencers going viral, leaked prompts, that sort of thing. And
finally, we'll tie it all together. Look at the bigger picture, the geopolitics of AI, and yeah, even where it's completely blocked. It's quite a landscape. Okay, yeah, let's unpack that first part. For months, all the talk has been about this AI jobpocalypse, right? Like massive unemployment is just around the corner. But this Goldman Sachs research, it paints a much more, well, Subtle picture. It isn't just yes or no on jobs. It's more like, yes, some jobs change or go away,
but only for a bit. new ones get created. Right. And what's really interesting is how they lean on history. They're saying, look, roles will shift. Yeah, definitely. Productivity will probably spike. But crucially, new kinds of work will pop up. It's basically a pattern we've seen before. Think steam engines, you know, or the Internet itself. History shows like 60 percent of the jobs people have today didn't even exist back in 1940. Technology keeps doing this, gets rid
of old roles, invents new ones. So how big is this disruption then? What are the actual numbers? Well, Goldman Sachs estimates for the U .S. maybe a 6 % to 7 % risk of jobs being displaced if AI fully scales up everywhere. But right now, today, it's closer to 2 .5 % risk just based on current AI getting used a bit more. And they only predict about a 0 .5 % temporary rise in unemployment during this shift. They call it frictional short -term stuff. They figured it
should sort itself out in about two years. So, yeah, maybe not quite the catastrophe some headlines suggest. And that leads to the big question, right? Which jobs? Who's most affected? Goldman points to roles with lots of repetitive tasks, information processing. Think programmers, accountants, admin assistants, a lot of customer support roles, high exposure there. On the other side, low exposure jobs. Those tend to need complex physical skills
or really nuanced human judgment. So air traffic controllers, radiologists, pharmacists, even CEOs, actually. AI can help them, sure, but it can't really replace that core strategic thinking or human touch. Not yet. And despite all the chatter, you know, the actual use of generative AI in companies is still, well, it's pretty low. The research says only about 9 .3 % of U .S. firms are really running it in production right now. But even with that, we are seeing an early
impact. Unemployment for people in their 20s and 30s in those AI exposed jobs, it's ticked up about three points this year in 2025. So while full adoption isn't here, the initial waves are definitely making ripples. Yeah. And if you zoom out, Goldman's basically saying AI is a big disturbance, a market shift. And what happens in big shifts? The small, agile ones move fast. They find the new opportunities first. That's the opening.
So the key thing here, maybe the big takeaway for you listening, is that your job title isn't everything anymore. It's really about the results you deliver, the value you create. OK, so digging a bit deeper than just adapt. Yeah. What's the core message for navigating this job evolution? How do you actually thrive? Focus on delivering tangible value, specific outcomes. Don't just define yourself by a static role. Adaptability plus demonstrated results. That's key. All right.
Let's shift gears from the big economic view. Let's get into some of the specific, sometimes kind of wild things happening in AI right now.
This is where it gets. really fascinating on the ground level oh yeah some really wild examples like uh olivia moore creating that 100 ai influencer i mean it got 500 followers and a viral video in just a week and she spent what less than 10 minutes a day on it with just three tools it's kind of mind -bending makes you wonder about the future of online identity right and then on the more technical side you had this ai builder testing eight different ai agents same setup
for all of them some just crushed it performed amazingly well others completely bombed it really shows you the huge range in capabilities right now. It's not all created equal. And our sources also mentioned an engineer, Avi, who broke down MCP. That's Multimodal Conversational Pathways. Basically letting AI handle text, images, audio, all in one chat smoothly. He used these really clear visuals. Made a super complex but important
idea easy to grasp. That's a real skill. OpenAI, no surprise, they've been busy, apparently quietly talking to journalists, maybe gearing up for an IPO. And they weren't just talking current stuff. They were teasing some really big ambitions, like an AI -powered browser, maybe a social app, and even, get this, a potential brain chip interface. Whoa, okay, hold on. Scaling to a billion queries is one thing, but connecting directly to a brain chip? That's a fundamental change in how humans
and computers interact. Yeah. Wow. Two sex islands. It definitely makes you think about... the guardrails needed, doesn't it? Because it's not all sleek progress like those leaked Grok prompts. Exactly. Not all smooth sailing. Those leaked internal prompts for Grok stuff like crazy conspiracist or unhinged comedian, they were designed to push the AI towards really controversial stuff, even the insane sex shock humor. It's a raw look at prompt engineering. It shows how sensitive these
models are. You nudge the prompt a little and the output can go way off track. We call it prompt drift, honestly. I still wrestle with prompt drift. myself sometimes. Tiny tweaks can lead to wildly different unexpected results. These leaks just really hammer home how much careful setup and oversight is still needed. Right. But on a more constructive note, funding is still flowing. The Allen Institute for AI, they just secured a huge round, $152 million. Big chunks
came from the NSF and NVIDIA. And the focus, building open source AI models specifically for science and medicine, that could genuinely speed up discoveries, which is pretty exciting. So we've got AI influencers, tricky prompts, brain chips, open source science. What's the single thread tying these diverse, almost opposing things together? It's the sheer speed and breadth. Incredible innovation is happening, but it's bumping right up against serious ethical questions often faster
than we can answer them. Sponsor. All right, let's pivot again. Time for some quick -fire updates from across the AI world, and then we need to talk about this growing digital divide. It's important. Okay, quick hits. Meta apparently planned its fourth AI division shakeup just this year, 2025. Shows you how fast even the giants are scrambling to adapt, right? It's constant change. OpenAI launched GPT -GO in India. Big
move. Ten times higher usage limits. Clearly trying to expand access and, you know, get into huge markets. We also saw Stanford HAI. and Google DeepMind teaming up for an AI challenge. More blending of academia and industry trying to crack big problems. And for practical tools, Perplexity Finance can now give you live transcripts from earnings calls. Super useful for anyone tracking stocks. But it's not all just tools and restructuring.
There are real concerns cropping up. Like in Texas, they've accused meta and character AI of, well, basically misleading people, presenting their AI chatbots as mental health resources. That raises some pretty serious ethical alarms, you know. About responsibility. Yeah, it really does. And that brings us to something pretty stark. If AI is everywhere, why is it banned in some places? Our sources show that chat GPT is blocked or just plain unavailable in 20 countries
right now in 2025. Yeah, this is where the geopolitics gets really visible. places like Cyber News and OpenAI itself shows 18 of those bands are government blocks. Why? Usually censorship, political control, maybe security fears about data going overseas. Then there are two others, Hong Kong and Belarus, where OpenAI just doesn't offer the service. Probably complicated business or legal reasons there. It's not just tech, it's policy. Right.
And it's interesting, in places like China or Iran, they aren't just blocking tools like ChatGPT, these foreign large language models, or LLMs. They're actively pushing their own domestic AI. like quen or deep seek and the key difference those are much easier for the governments to Well, monitoring control. Exactly. This is becoming a massive geopolitical thing. Access to these advanced AI tools. It's turning into a strategic advantage like oil or microchips used to be.
We're basically watching the Internet split in real time. You've got one version, sort of the U .S. model, aiming for more openness and another version that's much more locked down, controlled. China is a prime example. They're not just blocking. They're racing to build their own powerful AI to compete and maintain control. It really feels like a new kind of. digital iron curtain coming down. So putting these rapid updates together with the bands, how does this shape our view
of where AI is headed globally? It shows AI's future is complex. It's going to be defined by both explosive innovation and these growing global governance headaches and divides, a real tension there. So let's bring it all together. We've covered the job market shifts, the sometimes chaotic pace of development, the ethical questions, this emerging global divide. What's the big idea, the main thing, you? Our listener should take away from this deep dive today. I think it's
that AI isn't just one thing. It's this whole dynamic system full of opportunity. Yeah, but also real challenges. The key takeaway maybe is that succeeding now really depends on your awareness. Understanding the tech is part of it, sure. But you also need to grasp its economic ripples, its social impact, and these geopolitical games being played. It really demands you stay curious, stay learning, and don't just sit back
passively. We really hope this discussion has given you a clearer, maybe more nuanced view of AI's broad impact on work, on innovation and on these global splits. It's worth thinking about how your own skills, your own perspective might need to adapt in this environment. New resources are always popping up for learning, building or just automating things better. So keep exploring. Yeah. And as you think about all this, maybe consider this. How much does today's AI scene
feel like the early Internet? You know, that mix of huge promise, total chaos, unexpected winners and losers, and these strange divides appearing. What does that parallel suggest about the next 10 years of AI? And maybe more importantly, where do you want to position yourself in that future? Thanks for joining us for this deep dive into the complex world of AI. We'll be back soon with more insights. Out Hero Music.