WEBVTT 00:00:00.000 --> 00:00:02.500 So what if a brand new AI company, I mean, really 00:00:02.500 --> 00:00:05.660 just starting out, somehow secured $2 billion, 00:00:05.940 --> 00:00:08.259 not some later stage round, not a tech giant, 00:00:08.380 --> 00:00:11.880 $2 billion in its seed round. It's just a massive 00:00:11.880 --> 00:00:13.140 number. Yeah, you heard that right. Seriously, 00:00:13.400 --> 00:00:15.880 this is not your grandma's seed round. This past 00:00:15.880 --> 00:00:19.539 week, the AI funding scene, it's gone. Absolutely 00:00:19.539 --> 00:00:22.079 bonkers. Just wow. Welcome to the Deep Dive. 00:00:22.100 --> 00:00:24.960 Today, we're going to unpack a whole stack of 00:00:24.960 --> 00:00:27.480 sources detailing this latest and frankly, kind 00:00:27.480 --> 00:00:30.800 of mind boggling AI investment landscape. Right. 00:00:30.879 --> 00:00:32.640 Our assignment here is to navigate this, well, 00:00:32.700 --> 00:00:36.780 wild flow of cash into AI. We're looking at the 00:00:36.780 --> 00:00:40.259 week of June 20th to 26th, 2025. We'll explore 00:00:40.259 --> 00:00:42.340 who got funded, sure. But more importantly, what 00:00:42.340 --> 00:00:44.219 kind of cutting edge AI they're actually building. 00:00:44.380 --> 00:00:46.640 I mean, it touches everything from legal tech 00:00:46.640 --> 00:00:50.909 to, well. Smart cow callers. Seriously. OK, yeah. 00:00:50.990 --> 00:00:52.549 We'll definitely highlight the biggest players, 00:00:52.590 --> 00:00:54.409 maybe some surprising applications and try to 00:00:54.409 --> 00:00:56.950 figure out what it all means for, you know, technology 00:00:56.950 --> 00:01:00.229 and maybe beyond. OK, let's dig in. We really 00:01:00.229 --> 00:01:01.929 have to start with the one that just broke all 00:01:01.929 --> 00:01:04.730 the records. Thinking Machines Lab. They just 00:01:04.730 --> 00:01:09.209 secured an astonishing two billion dollars in 00:01:09.209 --> 00:01:12.000 a seed round. That amount of capital right out 00:01:12.000 --> 00:01:14.680 of the gate, it just signals this huge vote of 00:01:14.680 --> 00:01:16.579 confidence. Yeah, what's fascinating here isn't 00:01:16.579 --> 00:01:18.400 just the number, the two billion itself, though 00:01:18.400 --> 00:01:21.060 that's wild. It's that it's a seed round. It 00:01:21.060 --> 00:01:23.519 tells you investors believe they're on to something 00:01:23.519 --> 00:01:26.840 truly monumental, like potentially landscape 00:01:26.840 --> 00:01:28.780 changing. So what are they building with all 00:01:28.780 --> 00:01:31.560 that money? What's the focus? Well, they're focused 00:01:31.560 --> 00:01:34.819 on next generation multimodal. So dealing with 00:01:34.819 --> 00:01:37.319 different types of data agentic foundation models. 00:01:38.250 --> 00:01:40.129 Yeah. Think of AI that doesn't just, you know, 00:01:40.129 --> 00:01:42.450 chat or make an image. It understands complex 00:01:42.450 --> 00:01:44.829 goals. Yeah. And then it takes multiple steps 00:01:44.829 --> 00:01:47.829 kind of autonomously to actually achieve those 00:01:47.829 --> 00:01:50.269 goals. Ah, OK. So like a really smart digital 00:01:50.269 --> 00:01:52.430 assistant that actually does things for you, 00:01:52.469 --> 00:01:55.769 not just fetches info, but acts. Exactly. Precisely. 00:01:55.769 --> 00:01:57.469 It's about AI becoming more of an independent 00:01:57.469 --> 00:02:00.010 actor, not just a tool you specifically command 00:02:00.010 --> 00:02:03.329 for each tiny step. This funding gives them this 00:02:03.329 --> 00:02:07.590 massive war chest to go after truly. autonomous 00:02:07.590 --> 00:02:11.830 really capable ai it's a huge bet on that future 00:02:11.830 --> 00:02:14.530 so what's the sort of core insight from such 00:02:14.530 --> 00:02:17.650 a massive initial investment like that i think 00:02:17.650 --> 00:02:20.250 it's pretty clear investors are betting big on 00:02:20.250 --> 00:02:24.250 ai autonomy okay now beyond these these giants 00:02:24.250 --> 00:02:27.189 there seems to be a really clear trend in ai 00:02:27.189 --> 00:02:30.169 for healthcare our sources point to big raises 00:02:30.169 --> 00:02:33.370 for both uh a bridge and commure yeah bridge 00:02:33.370 --> 00:02:36.889 raised 300 million dollars They're aiming to, 00:02:36.990 --> 00:02:40.990 like, eliminate physician burnout using ambient 00:02:40.990 --> 00:02:43.449 listening clinical documentation. Ambient listening? 00:02:43.669 --> 00:02:45.629 Right. It basically acts like a medical scribe 00:02:45.629 --> 00:02:48.270 in the background. Converts the natural conversation 00:02:48.270 --> 00:02:50.750 between a doctor and patient directly into clinical 00:02:50.750 --> 00:02:52.849 notes. Wow. So doctors can actually focus on 00:02:52.849 --> 00:02:54.210 the patient instead of typing everything out 00:02:54.210 --> 00:02:56.289 on a keyboard. That feels revolutionary. It really 00:02:56.289 --> 00:02:58.189 could be. Then you've got Khmer. They secure 00:02:58.189 --> 00:03:01.650 $200 million. Their thing is a full -stack healthcare 00:03:01.650 --> 00:03:04.750 AI platform. It combines that ambient note -taking 00:03:04.750 --> 00:03:07.930 with revenue cycle management, specifically for 00:03:07.930 --> 00:03:10.009 large health systems. So it's optimizing the 00:03:10.009 --> 00:03:13.020 admin side, too. And we also saw Foresight Robotics 00:03:13.020 --> 00:03:15.900 getting funding, right? $125 million for robotic 00:03:15.900 --> 00:03:18.159 surgery. That's a different angle. Definitely 00:03:18.159 --> 00:03:20.479 different, yeah. Details in the sources are a 00:03:20.479 --> 00:03:23.740 bit light, but robotic surgery fundamentally 00:03:23.740 --> 00:03:27.800 relies on incredibly advanced AI. You're talking 00:03:27.800 --> 00:03:30.699 machine vision, complex algorithms for making 00:03:30.699 --> 00:03:34.780 decisions in real time, and just achieving superhuman 00:03:34.780 --> 00:03:37.740 precision in really delicate operations. It's 00:03:37.740 --> 00:03:40.069 about augmenting the surgeon. So looking at these 00:03:40.069 --> 00:03:41.590 health care investments together, what's the 00:03:41.590 --> 00:03:44.969 main impact we should expect? I'd say AI is rapidly 00:03:44.969 --> 00:03:47.110 becoming health care's operational backbone. 00:03:47.370 --> 00:03:50.110 OK, let's move out of medicine and into, say, 00:03:50.229 --> 00:03:53.090 the world of law and finance. Harvey secured 00:03:53.090 --> 00:03:56.810 $300 million for legal workflow automation. That's 00:03:56.810 --> 00:03:59.379 significant. Yeah, Harvey develops these. pretty 00:03:59.379 --> 00:04:01.500 sophisticated large language models, you know, 00:04:01.520 --> 00:04:05.039 LLMs, AI trained on massive text data sets, but 00:04:05.039 --> 00:04:07.699 specifically tailored for legal workflows. So 00:04:07.699 --> 00:04:10.099 they automate things like legal research, drafting 00:04:10.099 --> 00:04:12.759 initial contracts, analyzing documents. Think 00:04:12.759 --> 00:04:14.719 about the sheer volume of text lawyers have to 00:04:14.719 --> 00:04:16.980 wade through. Right. So lawyers can maybe ditch 00:04:16.980 --> 00:04:18.980 some of those late night research marathons and 00:04:18.980 --> 00:04:21.180 actually, you know, focus on higher level stuff. 00:04:21.399 --> 00:04:23.620 That seems to be the aim. Yeah. More time for 00:04:23.620 --> 00:04:25.939 strategy, client interaction, the complex thinking. 00:04:26.300 --> 00:04:30.779 We also see Finam raising $133 million. They're 00:04:30.779 --> 00:04:34.060 doing AI -driven business banking, automating 00:04:34.060 --> 00:04:36.180 things like invoicing and expense management, 00:04:36.339 --> 00:04:40.180 mainly for SMEs in Europe. Pretty practical stuff. 00:04:40.279 --> 00:04:42.019 And for financial planning, Conquest Planning 00:04:42.019 --> 00:04:45.500 pulled in $80 million. Right. Their system uses 00:04:45.500 --> 00:04:49.079 a generative planning engine. It helps financializers 00:04:49.079 --> 00:04:51.560 create personalized plans way faster than the 00:04:51.560 --> 00:04:54.339 old way. So again, it lets the advisors focus 00:04:54.339 --> 00:04:56.220 more on the strategy and the client relationship, 00:04:56.439 --> 00:04:58.839 not just the number crunching. Scaling expertise, 00:04:59.199 --> 00:05:01.100 basically. Got it. And there were a couple others, 00:05:01.220 --> 00:05:04.740 too. Neural with $31 million for enterprise business 00:05:04.740 --> 00:05:07.660 process automation. And Spinwheel with $30 million 00:05:07.660 --> 00:05:10.120 for AI and liability management, helping people 00:05:10.120 --> 00:05:12.439 manage debt. Yeah, all about automating complex 00:05:12.439 --> 00:05:14.819 flows. So what's the common thread running through 00:05:14.819 --> 00:05:17.560 these business and finance AI applications? I 00:05:17.560 --> 00:05:20.300 think it's that AI is automating core professional 00:05:20.300 --> 00:05:23.000 knowledge work. Okay, let's pivot now to the 00:05:23.000 --> 00:05:26.399 more physical and operational side. Our sources 00:05:26.399 --> 00:05:29.740 mention Gal - bit, from Beijing, getting $153 00:05:29.740 --> 00:05:33.180 million for embodied AI manufacturing robots. 00:05:33.579 --> 00:05:36.060 Yeah, embodied AI. That means physical robots, 00:05:36.220 --> 00:05:39.160 not just software. Robots that can intelligently 00:05:39.160 --> 00:05:40.839 perceive and interact with their environment 00:05:40.839 --> 00:05:43.439 right there on the factory floor. So not just 00:05:43.439 --> 00:05:45.540 repetitive arms. Exactly. These are designed 00:05:45.540 --> 00:05:47.860 for more complex, maybe more adaptable manufacturing 00:05:47.860 --> 00:05:50.949 tasks. like intelligent workers, really. Interesting. 00:05:51.050 --> 00:05:54.730 And then Physics X raised $135 million for industrial 00:05:54.730 --> 00:05:57.209 AI and engineering simulation. That sounds a 00:05:57.209 --> 00:05:59.569 bit more abstract. It sounds abstract, but it's 00:05:59.569 --> 00:06:01.769 actually super practical. They combine physics 00:06:01.769 --> 00:06:05.430 principles with AI to simulate and optimize designs 00:06:05.430 --> 00:06:08.180 for... Well, almost anything. Race cars, wind 00:06:08.180 --> 00:06:10.980 turbines, all virtually. It dramatically speeds 00:06:10.980 --> 00:06:13.279 up the design process. You cut down on needing 00:06:13.279 --> 00:06:15.600 lots of expensive physical prototypes. So you're 00:06:15.600 --> 00:06:18.079 optimizing the physical world using digital tools. 00:06:18.220 --> 00:06:20.759 Makes sense. Now, switching gears again, customer 00:06:20.759 --> 00:06:23.860 service. Decagon secured $131 million for an 00:06:23.860 --> 00:06:26.500 AI agent customer service platform. Right. And 00:06:26.500 --> 00:06:28.699 these AI agents, they're meant to go way beyond 00:06:28.699 --> 00:06:31.100 simple chatbots. They're designed to handle complex 00:06:31.100 --> 00:06:33.980 queries, understand context, remember past interactions, 00:06:34.360 --> 00:06:37.259 really have human. unlike conversations to solve 00:06:37.259 --> 00:06:39.779 problems, often without needing a human to jump 00:06:39.779 --> 00:06:42.519 in. So maybe fewer frustrating phone trees and 00:06:42.519 --> 00:06:45.660 more actual help quickly. That sounds appealing 00:06:45.660 --> 00:06:48.360 to, well, everyone. Chuckles slightly. Yeah, 00:06:48.420 --> 00:06:50.860 definitely. And related to that, BotPress got 00:06:50.860 --> 00:06:54.040 $25 million for AI agent infrastructure. They 00:06:54.040 --> 00:06:56.019 provide the underlying tools for developers. 00:06:56.259 --> 00:06:59.079 Ah, the building blocks. Exactly. The tools to 00:06:59.079 --> 00:07:01.399 build, manage, and deploy these high -quality 00:07:01.399 --> 00:07:04.600 AI agents and chatbots reliably and at scale. 00:07:05.100 --> 00:07:07.040 Like the Lego blocks for building sophisticated 00:07:07.040 --> 00:07:09.860 AI conversations. So how are these companies 00:07:09.860 --> 00:07:12.139 in the industrial and service spaces changing 00:07:12.139 --> 00:07:14.759 things? Well, fundamentally, AI is driving a 00:07:14.759 --> 00:07:17.680 new era of intelligent automation, physical and 00:07:17.680 --> 00:07:19.620 digital. Okay, this next one you mentioned earlier. 00:07:19.759 --> 00:07:22.819 It is genuinely kind of wild. Holter in New Zealand 00:07:22.819 --> 00:07:25.660 raised $100 million for a smart collar herd management 00:07:25.660 --> 00:07:28.220 system. Chuckles. Wait, seriously. Smart collars 00:07:28.220 --> 00:07:31.709 for cows. Like Fitbits for the herd. Yeah. Exactly 00:07:31.709 --> 00:07:34.050 like that, basically. These are solar -powered 00:07:34.050 --> 00:07:36.889 collars. They use AI, computer vision, analytics, 00:07:37.170 --> 00:07:40.430 all to remotely guide herds, set up virtual fences 00:07:40.430 --> 00:07:42.829 for grazing, and even detect early signs of health 00:07:42.829 --> 00:07:45.889 issues in individual cows. Whoa. Okay, just imagine 00:07:45.889 --> 00:07:48.970 scaling that level of... Like individual animal 00:07:48.970 --> 00:07:51.689 care across millions of farms. The efficiency 00:07:51.689 --> 00:07:54.269 gains, the animal welfare benefits. That's actually 00:07:54.269 --> 00:07:56.329 incredible. It really is. A great example of 00:07:56.329 --> 00:07:58.709 AI reaching unexpected places. Definitely. Then 00:07:58.709 --> 00:08:02.029 we also saw XBOW raising $75 million for offensive 00:08:02.029 --> 00:08:05.230 cybersecurity. Offensive? Yeah. Using AI to actively 00:08:05.230 --> 00:08:07.470 simulate attacks, find vulnerabilities in systems 00:08:07.470 --> 00:08:10.430 before the bad guys do. So it's proactive defense 00:08:10.430 --> 00:08:13.589 through simulated offense. Got it. And Centific 00:08:13.589 --> 00:08:16.430 raised $60 million. They call themselves an AI 00:08:16.430 --> 00:08:18.720 day. data foundry. What's that about? Think of 00:08:18.720 --> 00:08:21.639 a metal foundry forging steel. Centific basically 00:08:21.639 --> 00:08:24.060 forges high quality data. They clean it, label 00:08:24.060 --> 00:08:26.220 it, structure it specifically to train powerful 00:08:26.220 --> 00:08:28.480 enterprise AI models because, you know, data 00:08:28.480 --> 00:08:30.420 is the absolute fuel for AI. They're making sure 00:08:30.420 --> 00:08:32.899 it's premium grade fuel. Okay. And ClearSpeed 00:08:32.899 --> 00:08:36.409 got $60 million for voice analytics AI. Detecting 00:08:36.409 --> 00:08:38.409 risk just from the sound of someone's voice. 00:08:38.629 --> 00:08:40.690 Yeah, without even analyzing the words they're 00:08:40.690 --> 00:08:42.970 saying. It's about the how you say it, not the 00:08:42.970 --> 00:08:45.769 what. Looking for patterns in tone, cadence, 00:08:46.049 --> 00:08:49.529 stress that might indicate risk. It's kind of 00:08:49.529 --> 00:08:52.570 spooky, but also potentially powerful. And OpenRouter 00:08:52.570 --> 00:08:56.360 raised $40 million for a unified LLM API. You 00:08:56.360 --> 00:08:58.440 described it as like a switchboard. Yeah, basically. 00:08:58.580 --> 00:09:01.080 It intelligently routes your request, your prompt 00:09:01.080 --> 00:09:03.779 to whichever AI model is best suited for that 00:09:03.779 --> 00:09:06.500 specific task, like a smart concierge for accessing 00:09:06.500 --> 00:09:08.840 different AI brains. And just quickly, MetaView 00:09:08.840 --> 00:09:11.120 with $35 million for recruiting intelligence, 00:09:11.299 --> 00:09:13.559 helping with hiring. Right, analyzing interview 00:09:13.559 --> 00:09:16.679 dynamics. And WhisperFlow got $30 million for 00:09:16.679 --> 00:09:19.879 a hands -free AI dictation platform. Useful for 00:09:19.879 --> 00:09:22.320 doctors, sure, but maybe anyone who needs to 00:09:22.320 --> 00:09:24.340 dictate notes while doing other things. So looking 00:09:24.340 --> 00:09:26.580 at this incredibly diverse set of applications, 00:09:26.759 --> 00:09:29.899 from cows to cybersecurity to voice analysis, 00:09:30.200 --> 00:09:32.480 what does it tell us overall? I mean, it just 00:09:32.480 --> 00:09:34.879 shows AI's influence is pervasive, transforming 00:09:34.879 --> 00:09:36.980 basically every industry. Mid -roll sponsor, 00:09:37.200 --> 00:09:39.100 Reed. So let's try to pull this all together. 00:09:39.159 --> 00:09:42.820 From that, that just jaw -dropping $2 billion 00:09:42.820 --> 00:09:46.570 seed round for Thinking Machines Lab. all the 00:09:46.570 --> 00:09:49.370 way to smart collars for cows in New Zealand, 00:09:49.549 --> 00:09:52.269 this past week showed an absolutely incredible 00:09:52.269 --> 00:09:56.509 flood of cash into the AI ecosystem. Yeah, and 00:09:56.509 --> 00:09:58.549 if you connect the dots, looking at the bigger 00:09:58.549 --> 00:10:01.070 picture, it's just crystal clear that investors 00:10:01.070 --> 00:10:04.259 have this monumental confidence in AI. Not just 00:10:04.259 --> 00:10:06.480 for the future, but for right now, for immediate 00:10:06.480 --> 00:10:09.100 applications. We're seeing AI getting embedded, 00:10:09.220 --> 00:10:11.659 becoming really foundational across basically 00:10:11.659 --> 00:10:13.779 every sector you can think of. You said it before, 00:10:13.860 --> 00:10:15.820 like the early Internet, but on steroids. Exactly. 00:10:15.820 --> 00:10:18.419 But maybe even faster and with way more capital 00:10:18.419 --> 00:10:20.700 chasing these really transformative ideas from 00:10:20.700 --> 00:10:22.440 the get go. And it really highlights the speed, 00:10:22.460 --> 00:10:24.100 right? The speed of innovation, the speed of 00:10:24.100 --> 00:10:26.440 investment. And this isn't just a few big tech 00:10:26.440 --> 00:10:28.919 companies anymore. It's hundreds of companies 00:10:28.919 --> 00:10:32.159 all trying to solve specific real world problems 00:10:32.159 --> 00:10:35.220 in all sorts. of different industries. And that 00:10:35.220 --> 00:10:36.860 common thread we kept seeing, the push towards 00:10:36.860 --> 00:10:40.019 more autonomous, more agentic AI. Yeah. That 00:10:40.019 --> 00:10:41.879 feels like a really significant theme here. These 00:10:41.879 --> 00:10:44.139 systems aren't just tools anymore. They're being 00:10:44.139 --> 00:10:46.879 designed to understand complex goals and then 00:10:46.879 --> 00:10:49.750 act on them independently. That's a major leap 00:10:49.750 --> 00:10:51.809 from where we were even just a year or two ago. 00:10:51.970 --> 00:10:54.470 I have to admit, I still wrestle with just how 00:10:54.470 --> 00:10:56.809 quickly these capabilities are emerging and how 00:10:56.809 --> 00:11:00.509 we as a society are supposed to adapt to it all. 00:11:00.570 --> 00:11:02.610 It's moving so fast, challenging a lot of our 00:11:02.610 --> 00:11:04.450 assumptions about work, about problem solving. 00:11:04.649 --> 00:11:06.490 It's a lot to take in for sure. So this deep 00:11:06.490 --> 00:11:08.389 dive, it's not just about the investment numbers. 00:11:08.470 --> 00:11:11.330 It feels like a roadmap showing where AI is heading 00:11:11.330 --> 00:11:13.750 next. Yeah. And it raises a really important 00:11:13.750 --> 00:11:16.029 question, I think, for you listening right now. 00:11:16.389 --> 00:11:19.149 Given this huge surge. of investment and just 00:11:19.149 --> 00:11:22.230 the incredible diversity of AI applications we've 00:11:22.230 --> 00:11:25.490 talked about. Where do you see AI making the 00:11:25.490 --> 00:11:28.850 most profound or maybe the most surprising impact 00:11:28.850 --> 00:11:31.750 on your own daily life in, say, the next five 00:11:31.750 --> 00:11:34.460 years? Think about those implications. Are we 00:11:34.460 --> 00:11:36.659 really on the cusp of truly intelligent agents 00:11:36.659 --> 00:11:39.379 fundamentally changing how we work, how we live? 00:11:39.639 --> 00:11:42.000 Or is it more about just making current things 00:11:42.000 --> 00:11:44.080 more efficient? It's something to really ponder 00:11:44.080 --> 00:11:46.519 as you look at your own smart devices. Or maybe 00:11:46.519 --> 00:11:51.509 your cows, if you have any. Chuckles. Right. 00:11:51.509 --> 00:11:53.590 Well, that's it for this deep dive. We hope this 00:11:53.590 --> 00:11:55.710 exploration gave you some fascinating insights, 00:11:55.990 --> 00:11:57.950 maybe a bit of a shortcut to feeling informed 00:11:57.950 --> 00:12:00.429 about this crazy landscape. Yeah. Until next 00:12:00.429 --> 00:12:02.549 time, keep digging and keep learning. Out to 00:12:02.549 --> 00:12:03.070 your own music.