What is true on Funding?

a16z Frontier

Jensen closed his GTC Berlin 2026 keynote with this Hermes Agent demo as the finale. He introduced it by saying the way to build an agent is to ask an agent to build it for you, so he installed and set up a customized Hermes in one prompt. Then he used Hermes, running on @nvidia RTX Spark, to create a simulated training environment for the @huggingface Microduck. Hermes planned an obstacle course with Nemotron and had GPT-6 Astra build it using FreeCAD, Omniverse libraries, Blender, Newton, and Isaac Lab. Hermes trained thousands of simulated ducks on that course until the validated policy was ready to run on the real robot in the physical world. At Nous, we believe open source is a practical tool as much as a philosophical ideal. It gives users the ability to build powerful, complex workflows chaining numerous local+cloud models, devices, and tools themselves instead of waiting for a company to enable them.

The AI compute shortage is getting WORSE and what's happening with NVIDIA's B200 GPUs right now is absolutely INSANE. According to Ornn Exchange, rental prices for NVIDIA's B200 GPUs just reached a new all time high of $8.54 per GPU hour, with prices climbing another 12.9% in just the past trading week. Normally, as technology gets older and more capacity comes online, you would expect rental prices to gradually decline. But we're seeing the exact opposite happening with B200s. Rental prices are moving higher, which shows that customers are willing to pay a premium just to secure access to compute. This is an incredibly BULLISH signal for the economics of AI infrastructure because higher utilization and stronger rental pricing can translate into better returns on deployed GPUs, especially for operators that have already secured capacity. And this is exactly why I remain so bullish on the long term opportunity for neoclouds. These companies are spending billions building out AI infrastructure and one of the biggest concerns investors have had is whether all this capacity will eventually lead to oversupply and collapsing rental prices but right now, the data is telling us a VERY different story. And demand for compute is already this strong TODAY, imagine what happens as these technologies begin scaling across the global economy.

Robots learn by watching people work. Most of what they watch is staged. At @Maxinsights, we capture real work at natural speed in real homes, restaurants, and hotels. 2M+ hours so far. Today we’re announcing a $30M seed round led by @PeakXVPartners, plus two new products: MaxLoop: same-day quality scores on every clip MaxGlove: touch and force data a camera can't capture Thank you to our investors, builders, operators and customers. More to come.

From raw HTTP requests and HTML parsing to Selenium, Playwright, Puppeteer, CAPTCHAs, production scraping and modern AI-driven tools like Firecrawl, Apify and crawl4ai. Want to learn it for free, check it out here: https://t.co/AVCpAXucy9 Thanks to Remi Taffin for authoring! https://t.co/8P8tNKWh0b

Nebius just secured a $3.5 billion financing facility from Citi to help fund its global AI infrastructure expansion, including data centers and GPU purchases. What makes this particularly interesting is the financing terms. The facility has a 364 day maturity and carries an initial interest rate of SOFR + 2.75%, potentially increasing to SOFR + 3.50%. SOFR is essentially a benchmark interest rate that banks use when lending money, meaning Nebius is borrowing at a relatively modest premium above that benchmark. Now, remember one of the biggest concerns surrounding neoclouds recently has been their ability to secure financing at attractive rates. Investors have been worried that companies like Nebius and CoreWeave would struggle to raise the billions of dollars needed to continue expanding, especially with borrowing costs remaining elevated and credit markets becoming increasingly cautious. Well, this announcement directly challenges that concern, at least for Nebius. Not only has Nebius secured another $3.5 billion in financing, but it has managed to do so at what I consider fairly attractive rates for a capital intensive AI infrastructure company. And here’s another important point. Nebius already has more than $40 billion in long term customer commitments from investment grade customers, including Microsoft and Meta. Those contracts give lenders greater confidence that the infrastructure being financed will eventually generate revenue. I’ve said this repeatedly, I don’t believe every neocloud will survive this AI infrastructure buildout. Access to capital is going to separate the winners from the losers, and Nebius continues to demonstrate why I believe it will be among the survivors. This is a very encouraging development for $NBIS shareholders, especially after all the concerns surrounding financing and the recent selloff.

BenchmarkGate is a real thing Don’t blindly trust benchmarks even popular ones We need to be doing evals on our evals https://t.co/JU7uYx1L4L

What Higgsfield is doing should be illegal, you should not be allowed to scam normal unaware users like this. "Genjutsu Lite" is Wan 3.0. "Genjutsu" is Seedance 2.5. They rename other companies' models and sell them as their own. Here is every proof, from their own API docs -> Genjutsu Lite = Wan 3.0 • Pricing: 480p $0.05 / 720p $0.10 / 1080p $0.20 per sec • Out of 40+ models on their API, only ONE other has this exact pricing: Wan 3.0 • Resolutions: 480p / 720p / 1080p, same as Wan 3.0 • References: Lite takes 1 video + 8 images. Wan 3.0 takes 5 videos + 10 images. Lite is Wan 3.0 with a fixed prompt and settings locked -> Genjutsu = Seedance 2.5 • Reference images: Genjutsu takes up to 30. Seedance 2.5 takes exactly 30. Wan caps at 10 • Video length: Genjutsu takes 4–30s. Seedance 2.5 is exactly 4–30s • Price: $0.318 / $0.681 / $1.632 per sec, which is Seedance 2.5 video-edit pricing + ~20–30% markup -> It's not just Genjutsu • Cinema Studio 4.0: $0.2057 / $0.4623 per sec • Seedance 2.5: $0.2056 / $0.4622 per sec • That's Seedance 2.5 again • "3.5x cheaper" isn't a breakthrough. They swapped Seedance 2.5 for Wan 3.0, a cheaper model, and called it "Lite" • Real Wan is listed as alibaba/wan-3.0. The same model is sold as higgsfield/genjutsu-light • They never tell you what's underneath I have never seen such a big company being untruthful to their users outright like this.

消息称，DeepSeek在最新一轮融资中筹集了约1000亿元，宁德时代与腾讯领投。据悉深度求索与投资者洽谈期间至少两次上调融资目标，从500亿元提高到800亿元。 https://t.co/RoRF96579T https://t.co/bU0JOZehwK

What if exposure to private robotics investments could be traded before an IPO? RCM Assets are designed to make that possible, while connecting private market investments to the broader onchain economy. Building RCM 04 ↓ https://t.co/gBiKRrNg25

🇺🇸 @ElonMusk’s two biggest companies, SpaceX and Tesla, report earnings this week. @SpaceX reports today, @Tesla tomorrow. Both are aggressively building for SI: last quarter alone, SpaceX put $15.8 billion of its $18.4 billion investment budget into it. That’s the kind of infrastructure spend that can actually scale superintelligence, robotics, and mass-to-space. Investors are also watching for any further alignment between the companies. Tesla’s new shareholder filing includes standard change-in-control provisions in Elon’s long-term stock awards (common in executive packages to protect incentives in a major deal). Any combination would still need the proper process, but the overlap in AI, chips, energy, and robotics keeps growing.

According to RBC Capital Markets, SpaceX could acquire Tesla in an all-stock deal valued at $480 per share, creating a combined company worth $3.74 trillion 🔥 Under the hypothetical buyout, $TSLA investors would receive roughly three SpaceX shares for each share they own, securing a 30% premium paid entirely in equity 🔥 That swap would give Tesla shareholders a 48% ownership stake in the merged giant, down from the 54% RBC calculated in July despite the offer price remaining unchanged. The ultimate payout and ratio would still hinge on prevailing market prices and finalized agreement terms 🔥

ARK just released its new Tesla model, it sees $TSLA worth $17.5 TRILLION by 2031 ($4,400 per share!) Here's how they get there: 1. Units in 2031: 8.1M robotaxis, 10.2M cars sold, 1M Optimus robots and 2,278 GWh of storage 2. Revenue by product: robotaxi $753B (52%), cars $320B (22%), Optimus $212B (15%) and storage $163B (11%) 3. 2031 financials: $1.449T in revenue, $902B EBITDA at a 61% margin 4. Robotaxi makes up ~80% of Tesla's enterprise value and Optimus is 14% 5. ARK sizes the humanoid robot market at ~$26T, bigger than the $10T-$15T it sees for robotaxi 6. Cybercab's cost per mile is ~40% below Waymo's next-gen robotaxi 7. Tesla's AI infrastructure spend reaches ~$225B cumulative by 2031, including Terafab with SpaceX Also, NOT in the model but an interesting take, a possible SpaceX merger, which would mean $3.8T in combined 2031 revenue and $2.74T in EBITDA At those numbers, the combination of these two companies would be larger than $50 TRILLION in market cap Personally, I have not modelled this far out for the two companies, but I do believe that SpaceX will become the largest company in the world and the first to reach $100 Trillion The combination of Tesla and SpaceX is ultimately how they get there, which I explained in detail in the post below This is a big reason I gave Milk Road PRO members the signal to buy $SPCX when it hit $115 a few months back. For more signals like this and to see my entire real-time portfolio (and 4 other analysts), check out Milk Road PRO here: https://t.co/0kheLn0QRB

NVIDIA MAY ALSO BE A BIDDER FOR AMBARELLA ( $AMBA ) - BETAVILLE

In just the first 72 hours since Gemini 4 Argon launched, we processed ~25 trillion tokens, the demand for intelligence is incredible and still under appreciated!

The majority of neocloud companies will NOT survive. I strongly believe we're going to see a MASSIVE amount of consolidation across this industry over the next several years, and only a handful of companies will come out on top. Personally, I think $CRWV and $NBIS will be the top 2. Just look at how competitive this industry is becoming. You have the traditional hyperscalers like Microsoft, Amazon, and Google spending hundreds of billions of dollars building their own AI infrastructure. Then you have companies like CoreWeave, Nebius, Crusoe, Lambda, and several others trying to capture a piece of that same market. As we know, building a neocloud is EXTREMELY capital intensive. We're talking billions of dollars in GPUs, data centers, power infrastructure, networking equipment, and everything else required to operate these facilities. And that's before you even consider the cost of financing all of this. Not every company is going to have access to the capital necessary to compete, and more importantly, not every company is going to have customers willing to sign multibillion dollar contracts. This is why I believe we're eventually going to see smaller neoclouds either go bankrupt or get acquired by larger players. I wouldn't be surprised if the industry eventually becomes dominated by just a few major independent GPU cloud providers. But here's why I'm particularly bullish on CoreWeave and Nebius. Both companies have already demonstrated that some of the largest technology companies in the world are willing to commit billions of dollars to their infrastructure. CoreWeave has built an enormous contracted backlog, while Nebius has secured major agreements with Microsoft and Meta. And then there's $NVDA, which I think is one of the most underrated parts of this entire conversation. Jensen Huang has a HUGE incentive to make sure the neocloud industry succeeds. Think about it. Why would Nvidia want the entire AI infrastructure market controlled by Microsoft, Amazon, Google, and Meta when it can help create another group of major customers buying billions of dollars worth of GPUs? We've already seen Nvidia make strategic investments across this ecosystem, including its investment in Nebius. Now, that doesn't mean Jensen is going to bail out every struggling neocloud, but I do believe Nvidia will continue supporting strategically important partners where it makes financial sense. And this brings me back to what's happening with CoreWeave right now. Investors are absolutely freaking out over its borrowing costs, and I understand why. Financing an enormous infrastructure buildout when interest rates are elevated is not easy, especially when you're already carrying significant debt. But I think people are confusing financing risk with demand risk. The demand for AI compute hasn't suddenly disappeared. If anything, the latest growth we're seeing from companies like Anthropic suggests we're going to need substantially MORE computing capacity over the next several years. That doesn't guarantee CoreWeave or Nebius will succeed. Both still need to execute, manage their capital requirements, and eventually demonstrate that their businesses can generate sustainable free cash flow. But I think the companies that survive this period could emerge in a MUCH stronger competitive position as weaker players get pushed out of the market. You can check out the full podcast here: https://t.co/sShRsqUUHG

We are excited to work together with @FireworksAI_HQ on the early-launch of EAGLE-4. Check out our technical blog to understand how EAGLE-4 works and why it matters for creative workflows: https://t.co/YnYzQ89uCv https://t.co/02VMIubVgg

🇺🇸 Trump has arrived in Greenville, North Carolina, aboard Air Force One for his next midterm election rally. The event at Pitt-Greenville Airport is scheduled for 7pm ET, with Trump appearing in support of Republican Senate candidate Michael Whatley, who is running against former Democratic Gov. Roy Cooper.

You can build an 8-servo robotic hand for under €200 in parts. The AmazingHand by Pollen Robotics has two options: DIY: source 8 Feetech SCS0009 servos, print the mechanical structure in 3D and assemble the linkages using the free GitHub files. Seeed Studio kit around $89, or €119.43 including VAT at RobotShop Europe. It includes the structure, 8 servos, a XIAO-compatible control board, power supply, cables and hardware. Both require assembly. The DIY route gives you the parts list and printable design. The kit bundles the components. Which route would you take to build your own robotic hand?

We're about to witness one of the BIGGEST wealth transfers in the history of the technology industry. According to Morgan Stanley, hyperscalers and neoclouds are projected to spend a staggering $1.58T in capital expenditures in 2027, including operating leases but what's even more interesting is where all of that money is actually going. We're talking about Google spending an estimated $375B, $AMZN $270B, $META $221B, $MSFT $209B, $SPCX $132B, $ORCL $97B, $CRWV $47B, and $NBIS $37B. These companies are collectively pouring more than a TRILLION dollars into building the infrastructure required to power AI, and that money doesn't simply disappear. It flows directly into the companies supplying the chips, networking equipment, memory, storage, power infrastructure, and data centers required to make all of this possible. Morgan Stanley estimates that approximately $672B will flow into semiconductors and servers, making this by FAR the largest category of spending. This is why companies like $NVDA and $AVGO remain so important to the AI buildout. Every time a hyperscaler or neocloud expands its compute capacity, it creates additional demand for GPUs, custom AI accelerators, and the supporting infrastructure. But it doesn't stop there. Another $215B is expected to flow into networking and optical infrastructure, benefiting companies that help connect these massive AI clusters together. As AI systems continue scaling, networking becomes increasingly important because having the fastest GPUs in the world means very little if they can't communicate efficiently. Then you have $217B going toward memory and storage which is why I remain so bullish on companies exposed to HBM, DRAM, NAND, and enterprise storage. And let's not forget the $119B flowing into data center infrastructure, including power equipment, cooling systems, electrical infrastructure, and the physical equipment needed to actually operate these facilities. And the way I see it, some of the biggest investment opportunities over the coming years won't necessarily come from the companies building AI models themselves, but from the companies supplying the critical infrastructure that everyone needs to compete. That's exactly why I remain so bullish on the picks and shovels side of this AI revolution and I believe we're STILL in the early innings of this entire infrastructure buildout.

@EkaRobotics has raised a $150M Series A. Generality v/s Performance is the fundamental tension at the frontier of robotics. Generality without performance is just a prototype. Performance without generality is just a single-purpose tool. Customers shouldn’t have to choose. Eka breaks the tradeoff. Powered by our Vision-Force-Action (VFA) model, we deliver the performance and versatility customers need to put robots to work every day. Eka is built on three convictions: ⚡️Force is the language of manipulation. 🚀 Reinforcement learning is how dexterous manipulation scales. 🎂 System 1—fast, reliable physical execution—is the bottleneck to solve. With this funding, we will scale our model and accelerate customer deployments. Grateful to be building alongside a dream team and investors who share our ambition.

@EkaRobotics has raised a $150M Series A. Generality v/s Performance is the fundamental tension at the frontier of robotics. Generality without performance is just a prototype. Performance without generality is just a single-purpose tool. Customers shouldn’t have to choose. Eka breaks the tradeoff. Powered by our Vision-Force-Action (VFA) model, we deliver the performance and versatility customers need to put robots to work every day. Eka is built on three convictions: ⚡️Force is the language of manipulation. 🚀 Reinforcement learning is how dexterous manipulation scales. 🎂 System 1—fast, reliable physical execution—is the bottleneck to solve. With this funding, we will scale our model and accelerate customer deployments. Grateful to be building alongside a dream team and investors who share our ambition.

Memory stocks just lost about $738 BILLION in market value. According to Goldman Sachs, shares of the major memory makers fell between 11% and 26% after China's CXMT announced its new DRAM cell architecture. SK Hynix fell about 25%. Samsung fell about 20%. Even CXMT itself dropped about 15%. Goldman still sees Samsung and SK Hynix moving to more advanced 1c nodes while CXMT stays mostly on older 1z technology through 2027. The market sold first. Now it has to decide if the tech gap really closed. $MU $SKHY

China just put its own chip know how on its export control list. The draft covers AI processor designs at 14nm or below, DRAM designs at 18nm or below, and advanced 3D NAND designs. It also covers the interconnect for AI clusters with more than 10,000 accelerators. This is still a proposal and public comments run until mid November. China is no longer just on the receiving end of chip restrictions.

据《每日电讯报》，微软退出 Nscale 英国埃塞克斯 Loughton 旗舰数据中心的锚定租户协议，因电网接入或要等到 2030 年代；此事冲击 Nscale 计划中约 350 亿美元估值的 IPO。 来源：BBN Times https://t.co/l1aokVMGyx #AInews #LetsConnect #蓝V互关 #浇朋友 #蓝朋友 #gm #蓝v互关 https://t.co/tZ1B34Pj5n

Financing conditions can affect both neoclouds’ cost of capital and their customers’ ability to pay. Neolabs have become important marginal buyers of short-term GPU capacity, paying high rental rates despite uncertain business models. As we flagged on a client call last month, we think their funding could support roughly six to twelve months of spending, after which continued purchases would depend on raising more capital. $CRWV $NBIS $IREN Read more in our weekly post: https://t.co/MWKTtVsXmO

Power is the BIGGEST constraint in the entire AI buildout right now. Morgan Stanley estimates that US data centers could require roughly 160 GW of power by 2029, but even after accounting for data centers under construction, additional utility grid access, behind the meter generation, and potential nuclear capacity, there could STILL be a 76.5 GW power shortfall. Think about how INSANE that is. We're talking about nearly HALF of projected US data center power demand potentially going unmet and here's why this matters so much. We can manufacture more GPUs, build better AI models, and raise hundreds of billions of dollars to finance new infrastructure. But none of that matters if you can't actually power the data centers. Electricity isn't something you can simply scale overnight. Building new transmission infrastructure, expanding grid capacity, securing interconnection agreements, and developing new power generation can take YEARS. And with AI workloads becoming increasingly compute intensive, demand for electricity is only going to accelerate as inference, autonomous agents, robotics, and physical AI continue scaling. This is exactly why I think POWER is becoming one of the most valuable assets in the entire AI ecosystem. And I think @elonmusk understands this better than almost anyone and it's also why I remain so bullish on neoclouds like $NBIS, $IREN, $SPCX. These companies are becoming incredibly important because they're helping solve one of the biggest bottlenecks in the AI industry turning massive demand for compute into actual operational capacity. The companies that can secure large amounts of power, develop data center campuses, deploy GPUs, and get that infrastructure operational FAST are going to have an enormous competitive advantage. And as power becomes increasingly scarce, the value of existing infrastructure with secured electricity and grid access could become significantly more valuable. You can't have an AI revolution without compute, and you can't have compute without POWER. If you want to see how I’m investing around the AI power bottleneck and the infrastructure companies I think benefit most, check out my portfolio below. https://t.co/MMkdjfqLsf

Anthropic says Claude will lead 80–90% of building the next Claude. The question for the rest of us is which 10% we keep. At the IMF AI & Cyber Risks panel, Anthropic's Michael Sellitto said Claude's share of leading next-gen model work went from 0% in January to 3% in April and 26% in August, and could hit 80–90% sometime in 2027. https://t.co/b2u0M9aTXj

Spent years watching models ace a single image and completely whiff on anything that moves or changes angle. Today we’re fixing that. Try Glimpse now, our first visual thinking model with competitive frontier performance compared to Astra on key public visual reasoning benchmarks.

Introducing Hugo: the first human companion robot. At Boston Dynamics, I was Chief Strategy Officer, bringing robots into the real world. My co-founder, Farbod Farshidian, led research at the RAI Institute. Together, 15+ years teaching robots to run, jump, and work. So we asked: what if robots could connect with people? Hugo runs on the first Vision-Language-Expression (VLE) model. He links what he sees and hears to movement, expression, and gesture. He notices you, reads the room, and reacts in real time. And he's only the first. Dynamic Creatures is @BostonDynamics' official entertainment and hospitality partner. We're building a cast of characters with film studios, resorts, and theme parks. https://t.co/z6iUo6btek

Thrilled to announce that @origin_autonomy has raised $20M in total funding, co-led by @Accel and @ZacuaVentures. Excited to be building this with @ashishxdaga, @tusharmakkar08 and the super talented team at @origin_autonomy. We’re building general-purpose robots for interior construction. Special thanks to @johnkoetsier at @Forbes for covering our journey. News Article: https://t.co/YxjoyLdAfi

China will be making a LOT of RAM in 2028 https://t.co/RiBFTe6JIC

2026 年 Q3，具身智能领域最有冲击力的变化，来自一个通用模型：9 月初 OpenAI 发布 GPT-6 Astra 后，具身从业者们发现，Astra 不只理解任务、拆解任务，还能输出机器人末端执行器的位姿，完成了本该属于 VLA 等物理 AI 模型的部分工作，而且还做得很不错。 在部分测试中，直接把 Astra 当做策略模型（VLA、WAM 等都是机器人上的策略模型类型）的成功率已超过了一些专门为机器人任务和物理世界操作训练的具身模型。 这动摇了数字世界 AI 和物理 AI 的边界，也引发了一个灵魂拷问： GPT、Fable 之类的通用模型是否会吃掉 Robotics？ 同时已经发生的事实是：OpenAI、Anthropic、DeepSeek、Kimi 等多数通用前沿模型公司都正酝酿进入 robotics。 除了 Astra 冲击外，本期具身季报还关注以下 4 个行业进展和事件： - AMD 拟以 82 亿美元收购 World Labs - 宇树 IPO 及连锁反应 - 有可能大幅压缩部署成本的 “上下文学习” - 美国 FCC 实际禁止了中国机器人进口 对一些人来说，Astra 的变化已经撼动了独立的具身智能公司的发展叙事和估值逻辑。至少，现在到了重新思考物理 AI 与通用 AI 边界的时刻。 https://t.co/ZRNrzkIDMe

BREAKING: Jensen has just announced that @nvidia in investing $1bn+ into 5 UK startups: >> Boltz which is building biomolecular models and AI agents that helps scientists predict molecular structures and interactions >> Foresight which helps owners of major infrastructure projects predict completion dates, mitigate risks and accelerate time to revenue. >> Hiverge which is building an AI discovery engine that automatically writes and optimizes algorithms for tasks such as faster AI training and complex logistics planning. >> Prima Mente which focuses on building biological foundation models to decode complex diseases and identify novel therapeutic targets, starting with Alzheimer’s, Parkinson’s and ALS. >> Riverlane which builds real-time error correction hardware and software that work across all major qubit types, helping quantum computers become reliable enough for practical use. He announced the news in London this evening. Apologies for the terrible pic which includes @rowlsmanthorpe’s side profile

The cost for frontier LLMs to complete a robot subtask halved every 3 weeks, from $2.36 in July to $0.38 in September 2026. https://t.co/6XHOI3ZaSk

Everyone needs to STOP worrying so much about this neocloud selloff. I think people are forgetting just how important companies like $CRWV and $NBIS are to the entire AI ecosystem, especially $NVDA. And remember what Jensen Huang announced just TWO months ago? Nvidia partnered with BlackRock, Blackstone, Goldman Sachs, Apollo, Brookfield, and KKR to help mobilize over $500 BILLION in financing for AI infrastructure. Think about what that actually means. Jensen understands that the biggest bottleneck in AI isn't necessarily demand anymore, it's getting enough capital, power, and infrastructure to actually meet that demand. Also, Jensen NEEDS these neoclouds to succeed because they give Nvidia leverage against the hyperscalers. Companies like $MSFT, $AMZN, and $GOOGL are developing their own custom AI chips to reduce their dependence on Nvidia over time. And that's exactly why neoclouds are so important. Companies like CoreWeave and Nebius are building enormous amounts of GPU infrastructure centered around Nvidia's technology. They give AI companies another place to access compute without having to rely entirely on the traditional hyperscalers. The stronger these neoclouds become, the more alternatives customers have and the less dependent Nvidia becomes on a handful of hyperscalers controlling AI infrastructure spending. Now imagine what happens if these neoclouds suddenly struggle to finance their expansion, which is exactly what we're starting to see with $CRWV. CoreWeave's bond yields just surged to over 15%, which is a warning sign. For context, these bonds were issued at a 9.625% yield just four months ago and now investors are demanding significantly higher returns to hold that debt. Essentially, the bond market is telling us that investors are becoming increasingly concerned about CoreWeave's financial risks, which could make future borrowing a lot more expensive. And that's a massive problem for $NVDA because these companies are buying billions of dollars worth of GPUs and helping expand the market for Nvidia's technology. This is why I believe Jensen will step in to support strategically important partners like CoreWeave if financing conditions become difficult. Nvidia has already demonstrated that it's willing to put capital behind this ecosystem. I'm not saying Jensen will bail out every neocloud, but I find it very hard to believe he'll just sit back and watch one of his most important customers struggle to finance its expansion, especially when Nvidia needs these companies to compete against the hyperscalers.

NVIDIA has just announced a $250m compute commitment into the the UK! 🇬🇧 The money is to: “strengthen the UK’s agentic safety and security research capability” This includes $50m in accelerated computing access annually through BOLD at the University of Oxford, SOFAIR at UCL and Imperial College London.  NICE

Tonbo Imaging IPO: Understanding the Business Before the Deep-Tech Narrative Many people are referring to Tonbo Imaging as a deep-tech business. But before getting carried away by the label, I think it is important to understand what the company actually does. Tonbo Imaging operates in the defence technology space, developing advanced electro-optical and imaging systems used for surveillance, target detection and military operations. In eazy words, think of the systems that help a soldier or a defence platform see, detect and identify things that the human eye may not be able to see clearly, especially at night or in difficult conditions. The business can broadly be understood through a few areas: 1. Thermal imaging and night vision: Systems that help detect people, vehicles and other objects using heat signatures, even in low-light conditions. 2. Surveillance and reconnaissance: Imaging systems that help monitor an area, detect potential threats and provide better situational awareness. 3. Weapon sights and fire-control systems: Technology that helps military personnel identify, track and aim at targets more accurately. 4. Missile seekers and targeting technology: Systems that help identify or track targets and support precision-guided defence applications. The important distinction is that Tonbo is not simply selling cameras. It develops specialised imaging and sensing technology that integrates optics, electronics, software and image processing for demanding defence applications. This is also what makes the business interesting to study. These are specialised products where performance, reliability, integration capabilities and customer qualification can matter significantly. Posting this because, we do not get regular exposure to many such specialised defence-technology businesses in our everyday investing journey. So, irrespective of whether one eventually invests in the IPO, Tonbo is worth studying to understand how this category of business operates. First understand the business. Then evaluate the economics. And only then look at the valuation.