WEBVTT 00:00:00.000 --> 00:00:02.459 Imagine a single company, just starting out, 00:00:02.560 --> 00:00:06.480 raising $2 billion, yes, a billion, in one week. 00:00:06.700 --> 00:00:09.220 That's the kind of wild, truly unprecedented 00:00:09.220 --> 00:00:13.140 money flowing into AI right now. Beat. Welcome 00:00:13.140 --> 00:00:15.519 to the Deep Dive. We're your shortcut to understanding 00:00:15.519 --> 00:00:18.899 complex topics. Today, we're plunging into the 00:00:18.899 --> 00:00:21.600 latest wave of AI funding. It's been a fascinating, 00:00:21.960 --> 00:00:24.260 really record -breaking week in artificial intelligence. 00:00:24.539 --> 00:00:27.000 Our mission? Pretty simple. Uncover what these 00:00:27.000 --> 00:00:29.120 companies are building, why this massive investment 00:00:29.120 --> 00:00:32.179 matters, and what it all means for you. We'll 00:00:32.179 --> 00:00:34.640 navigate through the biggest deals, from foundational 00:00:34.640 --> 00:00:37.439 AI to much more niche applications, and try to 00:00:37.439 --> 00:00:39.500 reveal the pattern shaping tomorrow. Yeah. And 00:00:39.500 --> 00:00:41.960 this deep dive comes from AI Grant News, specifically 00:00:41.960 --> 00:00:44.960 their top 20 investments list for July 11th to 00:00:44.960 --> 00:00:47.579 17th, 2025. So it's a real snapshot, like right 00:00:47.579 --> 00:00:50.020 now where the smart money is flowing in AI. Right. 00:00:50.119 --> 00:00:52.159 And it's everywhere from deep tech to, you know, 00:00:52.159 --> 00:00:53.899 everyday tools. The pace is just incredible. 00:00:54.020 --> 00:00:56.880 OK, so kicking things off, we have the absolute 00:00:56.880 --> 00:01:01.619 headline grabber, Thinking Machines Lab. A staggering 00:01:01.619 --> 00:01:06.280 two billion dollars in a seed round. Announced 00:01:06.280 --> 00:01:08.120 July 15th. I mean, that's just unprecedented 00:01:08.120 --> 00:01:11.180 for a company so new. Okay, let's try and unpack 00:01:11.180 --> 00:01:14.239 this. $2 billion. For a seed round, what exactly 00:01:14.239 --> 00:01:17.560 does agentic AI mean? And why is it worth so 00:01:17.560 --> 00:01:21.000 much so early? Right. So agentic AI, what's really 00:01:21.000 --> 00:01:23.680 revolutionary here is that these are systems 00:01:23.680 --> 00:01:26.439 designed to reason, plan, and then execute complex 00:01:26.439 --> 00:01:29.129 multi -step goals autonomously. They're moving 00:01:29.129 --> 00:01:31.549 beyond being just passive tools. They become 00:01:31.549 --> 00:01:34.010 active, goal -oriented partners. It's often called 00:01:34.010 --> 00:01:36.530 the holy grail of AI research. Beat. Because 00:01:36.530 --> 00:01:37.909 it could just revolutionize entire workflows. 00:01:38.310 --> 00:01:40.109 Investors, well, they see this as the next frontier 00:01:40.109 --> 00:01:42.609 for massive efficiency games. Think drug discovery, 00:01:42.730 --> 00:01:44.590 scientific research automation, transforming 00:01:44.590 --> 00:01:47.250 business ops. Fundamentally, they're really investing 00:01:47.250 --> 00:01:49.269 in the future of work itself, I think. So does 00:01:49.269 --> 00:01:51.689 this mean AI could soon act like a highly capable 00:01:51.689 --> 00:01:54.590 colleague, an autonomous one? Yes, exactly. Performing 00:01:54.590 --> 00:01:56.909 complex, multi -step tasks independently. Okay. 00:01:57.280 --> 00:02:00.280 Moving on then, we also see significant investments 00:02:00.280 --> 00:02:04.260 in securing our worlds, both digital and physical. 00:02:04.459 --> 00:02:06.920 Hadrian, for example, they raised $260 million, 00:02:07.439 --> 00:02:10.379 Series C, for offensive cybersecurity. That was 00:02:10.379 --> 00:02:12.740 July 17th. That's right. Offensive cybersecurity, 00:02:12.900 --> 00:02:15.300 or you might know it as ethical hacking or penetration 00:02:15.300 --> 00:02:18.020 testing. It's basically simulating cyber attacks 00:02:18.020 --> 00:02:21.219 to proactively find vulnerabilities before the 00:02:21.219 --> 00:02:23.780 bad guys do. Hadrian uses intelligent agents, 00:02:23.900 --> 00:02:26.099 AI agents, to automate this whole process at 00:02:26.099 --> 00:02:34.659 huge speeds. And then there's Open Evidence, 00:02:34.680 --> 00:02:36.719 a company that really made a splash during the 00:02:36.719 --> 00:02:39.219 pandemic. They just secured $210 million in Series 00:02:39.219 --> 00:02:41.599 B funding. And this is specifically for medical 00:02:41.599 --> 00:02:44.020 research AI. Yeah, Open Evidence is fascinating. 00:02:44.280 --> 00:02:47.300 What they do is leverage AI to read and synthesize 00:02:47.300 --> 00:02:48.919 millions of medical papers, clinical trials, 00:02:49.020 --> 00:02:52.219 research findings almost instantly. It identifies 00:02:52.219 --> 00:02:54.819 key findings, emerging trends, even like hidden 00:02:54.819 --> 00:02:56.879 connections that human researchers might take 00:02:56.879 --> 00:03:00.099 years, literally years to uncover. Imagine its 00:03:00.099 --> 00:03:02.419 ability to cross -reference tiny data points 00:03:02.419 --> 00:03:05.139 from totally different studies. It just accelerates 00:03:05.139 --> 00:03:07.159 discovery for researchers and clinicians. It's 00:03:07.159 --> 00:03:09.840 huge. So what's fascinating here is how AI finds 00:03:09.840 --> 00:03:11.939 hidden connections in just vast amounts of data, 00:03:12.000 --> 00:03:14.840 stuff humans miss. Precisely. It connects dots 00:03:14.840 --> 00:03:17.879 humans miss, accelerating discovery. Okay, let's 00:03:17.879 --> 00:03:20.150 shift gears a bit. enhancing creativity in how 00:03:20.150 --> 00:03:22.789 we access information. There's Lovable, a Swedish 00:03:22.789 --> 00:03:25.930 company, $200 million Series A for something 00:03:25.930 --> 00:03:30.449 they call AI vibe coding, which sounds delightfully 00:03:30.449 --> 00:03:32.870 intriguing, I have to say. Hey, yeah, vibe coding. 00:03:33.069 --> 00:03:35.770 It's essentially an AI coding assistant, but 00:03:35.770 --> 00:03:37.650 it's designed to make software development feel 00:03:37.650 --> 00:03:41.069 much more intuitive, supportive even. It learns 00:03:41.069 --> 00:03:42.949 a developer's unique style, their preferences, 00:03:43.189 --> 00:03:45.310 and then it automates the repetitive stuff, the 00:03:45.310 --> 00:03:48.990 boilerplate code. The goal is really about reducing 00:03:48.990 --> 00:03:51.490 developer burnout, letting engineers focus on 00:03:51.490 --> 00:03:53.710 the bigger picture, the problem solving, the 00:03:53.710 --> 00:03:55.930 actual innovation. It's kind of like having a 00:03:55.930 --> 00:03:58.030 co -pilot that actually understands your creative 00:03:58.030 --> 00:04:00.870 flow. You know, I still wrestle with prompt drift 00:04:00.870 --> 00:04:03.409 to myself sometimes, trying to get just the right 00:04:03.409 --> 00:04:06.169 output from AI. Vibe coding sounds like a dream 00:04:06.169 --> 00:04:08.250 for that. Like the AI really gets what you're 00:04:08.250 --> 00:04:10.490 trying to do. And then Substack, they received 00:04:10.490 --> 00:04:13.830 $100 million, Series C, for newsletter platform 00:04:13.830 --> 00:04:16.350 features. Yeah, for SubSec, that investment likely 00:04:16.350 --> 00:04:18.990 means a whole suite of new AI features to help 00:04:18.990 --> 00:04:22.050 writers and publishers. Think AI editing assistants 00:04:22.050 --> 00:04:24.910 to polish your writing, or maybe headline optimizers 00:04:24.910 --> 00:04:27.449 to get more clicks. Or even personalized content 00:04:27.449 --> 00:04:30.209 recommendations, helping readers find new newsletters 00:04:30.209 --> 00:04:32.290 they'll actually love. They could also use it 00:04:32.290 --> 00:04:35.009 to generate AI audio versions of articles. Makes 00:04:35.009 --> 00:04:37.709 things more accessible. Right. And Perplexity 00:04:37.709 --> 00:04:40.410 AI, a name I think many of us know now, they 00:04:40.410 --> 00:04:43.310 secured $100 million for their AI search engine, 00:04:43.430 --> 00:04:45.569 an extension around Series E. Yeah, and this 00:04:45.569 --> 00:04:47.750 really raises questions about how we get information, 00:04:47.910 --> 00:04:50.269 right? Unlike traditional search engines that 00:04:50.269 --> 00:04:52.990 just give you a list of links, an AI search engine 00:04:52.990 --> 00:04:55.910 like Perplexity gives you direct synthesized 00:04:55.910 --> 00:04:58.610 answers. It pulls from multiple sources, gives 00:04:58.610 --> 00:05:00.850 citations. It acts much more like a research 00:05:00.850 --> 00:05:03.160 assistant. Cuts straight to the info you need. 00:05:03.360 --> 00:05:05.680 Saves you time sifting through pages and pages. 00:05:06.060 --> 00:05:08.740 So what does this all mean for creators and how 00:05:08.740 --> 00:05:11.459 we find information? AI seems to be bringing 00:05:11.459 --> 00:05:14.079 personalized tools and more direct answers. Yes, 00:05:14.079 --> 00:05:15.959 it brings personalized tools and direct answers. 00:05:16.279 --> 00:05:18.439 Streamlines things. Okay, shifting gears again 00:05:18.439 --> 00:05:21.899 slightly. Mantis VC, they raised $100 million 00:05:21.899 --> 00:05:24.600 for a new venture fund. Now this is different, 00:05:24.660 --> 00:05:26.560 right? It's not money for building AI directly, 00:05:26.740 --> 00:05:28.980 but for investing in other AI companies. That 00:05:28.980 --> 00:05:31.139 feels like a crucial distinction. Oh, absolutely. 00:05:31.360 --> 00:05:33.860 That's a great point. Mantis VC's role is crucial. 00:05:34.060 --> 00:05:36.379 They provide that vital early stage capital, 00:05:36.519 --> 00:05:38.860 the seed money, for the very startups we're discussing. 00:05:39.300 --> 00:05:41.579 This kind of investment just fuels the whole 00:05:41.579 --> 00:05:43.720 AI ecosystem. It's a catalyst for innovation. 00:05:44.019 --> 00:05:46.579 It lets smaller teams with big ideas actually 00:05:46.579 --> 00:05:48.839 bring their products to market. And speaking 00:05:48.839 --> 00:05:51.620 of funding innovation, Moon Valley, they got 00:05:51.620 --> 00:05:54.800 an additional $84 million for their AI video 00:05:54.800 --> 00:05:58.939 generation platform. Generative video. Platforms 00:05:58.939 --> 00:06:01.060 like Moon Valley let you create pretty stunning 00:06:01.060 --> 00:06:04.339 video clips just from text prompts or even static 00:06:04.339 --> 00:06:07.100 images. This really democratizes video creation, 00:06:07.300 --> 00:06:09.459 takes it out of specialized studios and puts 00:06:09.459 --> 00:06:11.500 it into the hands of, well, anyone with an idea. 00:06:11.680 --> 00:06:13.579 Now, it's incredibly computationally intensive, 00:06:13.819 --> 00:06:16.519 generating high quality, longer videos. But this 00:06:16.519 --> 00:06:18.160 funding will definitely help them. scale up. 00:06:18.259 --> 00:06:21.220 Whoa. Imagine scaling that, creating like Hollywood 00:06:21.220 --> 00:06:23.660 level video from just a few words. The potential 00:06:23.660 --> 00:06:26.560 is just incredible. Two sec silence. Yeah. So 00:06:26.560 --> 00:06:28.500 how critical are these kinds of funds, these 00:06:28.500 --> 00:06:31.040 VC funds for AI innovation across the board? 00:06:31.290 --> 00:06:33.629 Crucial. They fuel the next wave of AI products, 00:06:33.790 --> 00:06:36.110 definitely. Which, you know, it raises an important 00:06:36.110 --> 00:06:39.410 question. Where isn't AI making an impact? When 00:06:39.410 --> 00:06:41.110 you look at the rest of these significant investments, 00:06:41.410 --> 00:06:43.689 the sheer breadth of AI's application is just 00:06:43.689 --> 00:06:46.990 striking. It reaches far beyond the obvious stuff. 00:06:47.089 --> 00:06:49.230 We're seeing it infuse deeply into almost every 00:06:49.230 --> 00:06:52.610 industry, from super technical processes to just, 00:06:52.649 --> 00:06:55.230 you know, daily operations. It's true. It really 00:06:55.230 --> 00:06:56.589 is everywhere. Let's maybe group some of these. 00:06:56.689 --> 00:06:58.649 How about we start with AI pushing into industrial 00:06:58.649 --> 00:07:02.670 optimization and energy? See, Amagi, they raised 00:07:02.670 --> 00:07:04.550 $80 million for ammonia -to -power solutions, 00:07:04.769 --> 00:07:07.170 clean energy tech. AI here is going to be key 00:07:07.170 --> 00:07:09.490 for the complex control systems, maximizing efficiency, 00:07:09.910 --> 00:07:12.009 ensuring safety in these new kinds of energy 00:07:12.009 --> 00:07:14.129 applications. Now, there's QAnaghi, a German 00:07:14.129 --> 00:07:16.449 company. They got $62 million. That's around 00:07:16.449 --> 00:07:21.110 $65, $70 million U .S. for photonic deep tech 00:07:21.110 --> 00:07:24.079 aimed at industrial quantum sensing. Okay, jargon 00:07:24.079 --> 00:07:26.100 to hurt. Photonic just means it uses light, so 00:07:26.100 --> 00:07:28.259 it's super fast, energy efficient. And quantum 00:07:28.259 --> 00:07:30.800 sensing. That uses quantum mechanics for incredibly 00:07:30.800 --> 00:07:33.180 precise measurements, like hyper -accurate navigation 00:07:33.180 --> 00:07:35.720 without GPS, detecting diseases way earlier, 00:07:35.860 --> 00:07:37.779 or creating totally new sensors for manufacturing 00:07:37.779 --> 00:07:40.040 that spot microscopic claws. Really deep tech 00:07:40.040 --> 00:07:42.699 stuff. And RealSense, $50 million. They work 00:07:42.699 --> 00:07:45.000 on AI -powered computer vision. Basically letting 00:07:45.000 --> 00:07:47.040 machines see and interpret the visual world. 00:07:47.199 --> 00:07:49.379 Think quality control on assembly lines or retail 00:07:49.379 --> 00:07:51.620 analytics. Optimizing store layouts, security. 00:07:52.180 --> 00:07:54.990 Lots of use. Oh, and Geologic AI, $44 million. 00:07:55.449 --> 00:07:58.139 Applying AI in geology. Analyzing rock samples 00:07:58.139 --> 00:08:00.959 incredibly fast for resource exploration, for 00:08:00.959 --> 00:08:03.500 mining, unlocking insights from the earth itself. 00:08:03.839 --> 00:08:06.740 That's incredible precision, materials, energy. 00:08:06.980 --> 00:08:09.240 It really shows how fundamental AI is becoming. 00:08:09.480 --> 00:08:13.139 What about how AI is optimizing business operations 00:08:13.139 --> 00:08:15.040 and professional services? Absolutely. Okay, 00:08:15.079 --> 00:08:17.699 so Boulevard raised $80 million. They're a client 00:08:17.699 --> 00:08:20.379 experience platform, likely using AI for smart 00:08:20.379 --> 00:08:22.740 scheduling, personalized recommendations, often 00:08:22.740 --> 00:08:25.519 wellness and beauty sectors. Then Unify. $40 00:08:25.519 --> 00:08:27.699 million. They're building an AI -native go -to 00:08:27.699 --> 00:08:30.240 -market platform. Now, AI -native means it's 00:08:30.240 --> 00:08:32.120 built from the ground up with AI at its core. 00:08:32.279 --> 00:08:34.820 It's not just bolted on. This lets it predict, 00:08:35.000 --> 00:08:37.019 analyze, automate marketing and sales processes 00:08:37.019 --> 00:08:39.360 almost autonomously. Beyond just finding leads, 00:08:39.539 --> 00:08:41.399 it's orchestrating campaigns, predicting customer 00:08:41.399 --> 00:08:45.019 success, heron data, $16 million, automating 00:08:45.019 --> 00:08:47.460 finance workflows, think streamlining loan processing, 00:08:47.679 --> 00:08:50.019 transaction monitoring, that kind of thing, and 00:08:50.019 --> 00:08:52.399 Calidus AI. $10 million seed round, building 00:08:52.399 --> 00:08:55.320 an AI -powered litigation platform. So AI helping 00:08:55.320 --> 00:08:56.820 with e -discovery, legal research, maybe even 00:08:56.820 --> 00:08:58.480 predicting case outcomes, really changing how 00:08:58.480 --> 00:09:01.820 legal pros work. Wow. It sounds like AI is just 00:09:01.820 --> 00:09:03.980 quietly becoming the backbone for so many industries. 00:09:04.139 --> 00:09:06.220 And what about the actual infrastructure and 00:09:06.220 --> 00:09:08.139 development, the stuff needed to build all this 00:09:08.139 --> 00:09:10.460 AI? Right. The picks and shovels, kind of. Crash 00:09:10.460 --> 00:09:13.419 Override got $28 million. They focus on engineering 00:09:13.419 --> 00:09:17.360 security or DevSecOps. DevSecOps basically means 00:09:17.360 --> 00:09:19.399 integrating security right into software development 00:09:19.399 --> 00:09:22.019 from the very beginning. And AI helps find vulnerabilities 00:09:22.019 --> 00:09:24.899 in code much, much faster than humans looking 00:09:24.899 --> 00:09:29.080 manually. Panama, $27 million. They're a development 00:09:29.080 --> 00:09:31.960 company. Venture Studio, just building new AI 00:09:31.960 --> 00:09:34.580 -powered products across different areas. Spico, 00:09:34.779 --> 00:09:37.299 $22 million. They build custom AI platforms. 00:09:37.580 --> 00:09:40.419 So tailored AI solutions for big companies using 00:09:40.419 --> 00:09:42.879 their own private data to create unique AI applications. 00:09:43.259 --> 00:09:46.059 And Gig .io, $21 million, first part of a Series 00:09:46.059 --> 00:09:48.340 B. They work on software -defined infrastructure 00:09:48.340 --> 00:09:51.320 for AI workloads. Basically, this tech allows 00:09:51.320 --> 00:09:53.740 flexible on -demand combining of computing resources 00:09:53.740 --> 00:09:56.639 like powerful GPUs, absolutely essential for 00:09:56.639 --> 00:09:58.460 training these huge AI models we keep talking 00:09:58.460 --> 00:10:00.730 about. Okay, so if we connect all this back to 00:10:00.730 --> 00:10:04.350 the bigger picture, how will this whole wave 00:10:04.350 --> 00:10:07.049 of funding really change our daily lives? Often, 00:10:07.190 --> 00:10:10.090 maybe, without us even realizing it. AI will 00:10:10.090 --> 00:10:12.370 quietly optimize countless hidden processes, 00:10:12.730 --> 00:10:15.289 making systems run smoother behind the scenes. 00:10:15.470 --> 00:10:19.419 Yeah. This deep dive into the latest AI investments, 00:10:19.539 --> 00:10:22.200 it paints a very clear picture. Money is flowing 00:10:22.200 --> 00:10:24.980 at just an unprecedented scale, especially into 00:10:24.980 --> 00:10:28.419 that foundational AI, those really powerful agentic 00:10:28.419 --> 00:10:31.019 models. But AI isn't just about the cutting edge 00:10:31.019 --> 00:10:32.840 labs anymore, is it? It's truly transforming 00:10:32.840 --> 00:10:35.500 every single industry from cybersecurity to medical 00:10:35.500 --> 00:10:38.259 research, content creation to geology. AI is 00:10:38.259 --> 00:10:40.740 becoming deeply embedded in our world. The focus 00:10:40.740 --> 00:10:43.120 seems clear. Automate complex tasks, enhance 00:10:43.120 --> 00:10:45.519 what humans can do and provide deeper, more actionable. 00:10:45.610 --> 00:10:47.570 insights pretty much everywhere. Exactly. And 00:10:47.570 --> 00:10:49.529 the speed of innovation right now is just incredible. 00:10:49.710 --> 00:10:52.710 It's such a dynamic, rapidly evolving landscape, 00:10:52.889 --> 00:10:55.269 these investments. They're just a snapshot of 00:10:55.269 --> 00:10:57.870 that momentum, which, you know, raises an important 00:10:57.870 --> 00:11:00.269 question for you listening. Beyond what we've 00:11:00.269 --> 00:11:02.169 talked about, what surprising new industries 00:11:02.169 --> 00:11:04.789 do you think AI will disrupt next? How might 00:11:04.789 --> 00:11:07.389 this reshape how you work or even how you live 00:11:07.389 --> 00:11:09.490 your everyday life in ways we haven't even touched 00:11:09.490 --> 00:11:11.769 on yet? Keep exploring. Keep asking questions. 00:11:12.070 --> 00:11:14.679 It's moving fast. Thank you for diving deep with 00:11:14.679 --> 00:11:16.759 us today. We hope you feel a little more well 00:11:16.759 --> 00:11:19.720 -informed and maybe a lot more curious about 00:11:19.720 --> 00:11:22.559 the future of AI. Until next time, keep learning. 00:11:22.759 --> 00:11:23.700 Out -y row music.