Malaysia
Joined August 2011
OOI CHEA WEI retweeted
$VIX Over the years i have pioneered VIX strategy to trade every day , everyone uses it now days. Back in day folks used to Argue about it. Life Changing Strategy indeed, Today if you knew power of VIX 18, you got in all the bounces Learn-> ripstereducation.com/spy-vix…
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Japan is funding up to $21B of new fabs that $GFS will operate. Let's check out the structure: → Japan provides the investment capital → GFS gets paid for construction, operations and licensing its technology → Apple and Renesas are identified as initial customers The first ~$10B fab is targeted to come online in 2029. A second would follow with additional investment. We’ve been talking about GFS getting more out of its existing fabs through optical growth and better utilization. Now they could earn additional income from a much larger manufacturing footprint financed by outside capital. The fee terms and retained obligations will determine how attractive that income is. Management’s webcast is today at 10 AM Pacific.
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Eleven Labs 的 CEO估计现在不太好受 。商业护城河一夜之间没了 Fish Audio新模型重磅开源,也是我一直在用来创作视频的音频。 不论你是视频创作者,还是想跟你自己搭建的 AI 模型电话聊聊投资,我认为这都是第一选择,简单好用,效果出奇的好 这次 Drama3 Model 不仅开源,能够通过符号来控制情感输出,而且提供了 fix 单一音节发音的功能。做长音频输出的朋友都知道这意味着什么
$52M seed round. 15M+ users. But this is what we're most proud of yet. Introducing Drama 3: the most emotive and controllable TTS model in the world And yes, it's open-weight. You can now control how even a single word should sound, change its tone, and shift your voice mid-sentence. Uncle Roger was impressed too. Try it here: s.fish.audio/rqh0l8 Comment “DRAMA” within the next 48 hours for 1 month free. If you're an enterprise your first month is on us: s.fish.audio/qz9r0t
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OOI CHEA WEI retweeted
$52M seed round. 15M+ users. But this is what we're most proud of yet. Introducing Drama 3: the most emotive and controllable TTS model in the world And yes, it's open-weight. You can now control how even a single word should sound, change its tone, and shift your voice mid-sentence. Uncle Roger was impressed too. Try it here: s.fish.audio/rqh0l8 Comment “DRAMA” within the next 48 hours for 1 month free. If you're an enterprise your first month is on us: s.fish.audio/qz9r0t
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OOI CHEA WEI retweeted
$AAOI’s earnings could get a lot bigger without gross margins moving much at all. Look at Q2 results versus the midpoint of management’s Q3 guidance: Revenue: $192M → $273M Adjusted net income: $5.5M → $17M Gross margin: roughly 30% in both quarters That’s 42% more revenue and roughly 3x the adjusted profit, with essentially flat gross margin. If AAOI delivers, investors will have a much larger earnings base to value. Any sustained gross-margin improvement would give that earnings story another push.
$AAOI earnings TLDR: > ~$1.1B 2026 rev target reaffirmed. Mgmt thinks Q4 can do >$500M. > Q3 guide looked light, but ~$20M-$25M of 100G rev got pushed because a customer can’t source enough switches. Excluding that, Q3 growth would have been >50%. > 800G was only $12.8M in Q2, softer than I wanted. But they expect it to grow nearly 5x in Q3 to around $60M-$65M. > 1.6T qualification should finish in 2-3 weeks. Shipments start late Q3 and they expect $70M-$80M of 1.6T rev in Q4. > The $471M/month mid-2027 data center target was explicitly reaffirmed. > Demand is apparently 20%-40% above what AAOI can supply and expected capacity through Q2 2027 is already spoken for. Basically, if they can make qualified product, they have buyers for it. > 800G/1.6T capacity doubled from ~100K units/month exiting Q1 to nearly 200K today, with 650K/month still targeted by year-end. > Substrate supply looks much better. They say they have enough through YE27 and are already discussing deeper partnerships / potential JVs with suppliers for the massive 2028/29 laser ramp. > CPO was surprisingly strong. They’re working with at least 5 customers, several have already qualified AAOI lasers, and management says capacity is the limiting factor rather than performance/customer interest. > U.S. manufacturing is becoming an even bigger selling point. Early feedback around potential China restrictions has customers asking for more U.S.-made supply. The concerns: > Q4 execution bar is enormous. > Gross margin improvement is slower than hoped, with Q4 now looking closer to 32%-33%. > DSP/TIA supply is constraining 800G/1.6T. > Some of the >$200M 1.6T order may spill into 2027. > CapEx + dilution remain huge. Overall, the thesis is on track. Demand, capacity, substrates, 1.6T and CPO all gave me more confidence. Now they have to execute the insane Q4 ramp they just underwrote.
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We talk a lot about $NOK for AI data center infrastructure. Bell Labs has some pretty wild projects going on too: • Robot fleets: Getting robots from different manufacturers to coordinate and move around factories together. Tested in Nokia’s own factory. • 6G sensing: Turning wireless networks into radar that can detect objects and movement while carrying data. • Quantum computing: Working on more stable qubits to tackle one of the biggest obstacles to useful quantum computers. • Fiber as a sensor: Using communications cables to detect vibrations and environmental changes, potentially spotting trouble before a cable fails. • AI-powered wireless: Teaching networks to decode difficult signals and carry more traffic over the spectrum operators already own. • Lunar communications: They built cellular hardware that actually landed and powered up on the Moon in 2025. From coordinating robots on a factory floor to connecting machines on the Moon. Nokia has a fascinating research pipeline behind the infrastructure business.
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OOI CHEA WEI retweeted
$DE and $AGCO got hit this week after the FTC and USDA opened an inquiry into competition in the farm equipment market, including barriers farmers face when buying and maintaining machinery. That adds uncertainty around how these businesses make money from equipment and servicing it. I’m still really interested in what AI can do on a farm. The economics are easy to understand. You can do things like identify weeds and spray only where needed, place seeds more precisely, and automate work that takes hours of someone’s day. Deere says its targeted spraying technology covered 5M+ acres in 2025, with customers using nearly 50% less non-residual herbicide on average. That’s a meaningful reduction in something farmers pay for every season. AGCO’s approach is interesting because it can upgrade machinery farmers already own, including other brands. A farmer can add smarter spraying or planting technology while keeping the tractor or sprayer they’ve already paid for. For these businesses, that creates an opportunity to sell more technology across the huge fleet already working in the fields. Farmers have to see a payback they can afford. The suppliers that consistently deliver those savings could build a very valuable business as adoption grows. That’s the longer-term opportunity I want to understand further.
There's some really cool Physical AI applications I'm doing a lot of reading on agriculture right now Companies like $DE $AGCO I wrote out an intro here if you want to read it: gaetanoresearch.substack.com…
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Teaching a robot to move creates a whole new market for training data. $INOD just opened a motion-capture lab to go after it. The lab records human and robot movement in 3D. Developers can buy existing datasets, commission recordings for specific tasks or bring their robots in for independent testing. Think about teaching a robot a new physical job. Someone needs to capture what doing it correctly looks like, then measure whether the robot actually learned it. Innodata wants to get paid for that work. Its broader AI-data business generated $92.1M in Q2 revenue, up 58% YoY. The September 30 lab opening adds a direct robotics opportunity on top of that foundation.
I think Physical AI could create investment opportunities across a very wide set of companies $OUST $AMBA $QCOM $INOD $RRX $AGCO etc. I’ve broken the trade into 11 layers to figure out where the money goes Bookmark this! 1 - Training & Model Development: teaching machines how to perform useful tasks. 2 - Simulation & Synthetic Data: giving them a virtual world to practice in. 3 - Perception: sensing and understanding their surroundings. 4 - Edge Compute: processing information close enough to react immediately. 5 - Software & Planning: deciding what to do and how to do it. 6 - Control Systems: making those actions precise and safe. 7 - Motion & Actuation: motors, gearing and actuators that create movement. 8 - Power & Energy Delivery: powering the machine efficiently and keeping it working longer. 9 - Connectivity & Fleet Coordination: getting hundreds of machines to communicate and work together. 10 - Systems Integration & Deployment: installing everything into a customer’s actual operation. 11 - End Markets: where customers pay for better outcomes in warehouses, farms, hospitals, defense and beyond. I’m working through the public companies in each layer, digging through their financials and building my Physical AI portfolio along the way. Eight layers covered so far. My latest report screens 65+ U.S.-listed companies across power and energy delivery, then narrows down the businesses and prices that interest me. You can read that one here as a free sub! gaetanoresearch.substack.com…
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OOI CHEA WEI retweeted
Some interesting things being presented at OCP this week: $CRDO: A micro-emitter optical backplane for scale-up, plus 1.6T modules combining its DSP with in-house silicon photonics. $CIEN: Liquid-cooled 12.8T optical modules and a 6.4T pluggable optical engine for scale-up and scale-out networks. $LITE + $ORCL: A joint session on automated optical circuit switching for hyperscale AI networks. Lumentum is also presenting on external lasers for CPO and 12.8T VCSEL solutions. $ALAB: Memory expansion and pooling for agentic AI, plus NPO/CPO architectures for scale-up networks. $KEYS: Eight-port 1.6T Ethernet testing and multi-vendor network validation, with demonstrations involving NVIDIA, Cisco and Alibaba Cloud. $VRT / $ETN: 800V DC power architectures, with Vertiv discussing megawatt-scale compute and Eaton showcasing power equipment. A packed week no doubt!
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OOI CHEA WEI retweeted
$GFS manufactures specialty chips for smartphones, cars and AI infrastructure. Its SiPh and SiGe technologies help move data through the optical connections inside data centers. Q2 revenue reached $1.79B, +6% YoY and +9% QoQ. Adjusted gross margin expanded 470bps YoY to 29.9%. Within that, communications infrastructure and data center revenue grew 62% YoY. Management raised its 2026 growth outlook for that business to 50–60%, from the high-30% range previously. And customers are committing to more capacity: $MRVL expanded its multi-year agreement with GFS to add SiGe capacity in Vermont for next-gen pluggable transceivers, NPO and CPO. GFS gets a direct manufacturing role as Marvell scales its optical connectivity business. The new $2B, five-year TSMC agreement adds silicon interposers for advanced AI packaging. Volume production is expected to start ramping in H1 2028. There’s also a nearer-term earnings driver with selective price increases agreed with customers are expected to start contributing in 2027. Communications infrastructure and data centers represented 16% of Q2 revenue. As that share grows, these faster-growing, higher-margin optical technologies can have a much bigger influence on GFS’s overall growth and profitability. NFA, I am long GFS as a multi quarter hold
I have become more bullish on $GFS lately TLDR: > Communications + Data Center rev grew 62% YoY in Q2. FY26 growth outlook raised to 50-60%. > Silicon photonics rev expected to more than double this year. > SiGe is already larger than SiPh and oversubscribed through 2027. > $MRVL just signed a multi-year agreement to expand SiGe capacity for pluggables, NPO and CPO. > The U.S. Commerce Department signed an LOI for an expected $300M award to accelerate GF’s next-gen silicon photonics development. > And underneath all of this is already a ~$7B revenue business with $3.3B of cash and a ~10% FY26 adjusted FCF margin target. In the $40s, I think $GFS is still being valued far too much on what it has historically been, and far too little on what its AI infrastructure business is becoming. NFA, DYOR . I could be wrong
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Why does everyone want to buy $AMBA? We’ve heard reports linking both $NXPI and $QCOM to a potential acquisition. Neither has announced a deal though. So whether it happens or not, let’s think through why AMBA could be attractive. Both potential buyers already have substantial edge-AI businesses. NXP has its own embedded processors and bought Kinara, which develops AI accelerators. Qualcomm already has powerful camera processing, automotive perception and a growing robotics platform. AMBA would bring another established portfolio of vision-focused chips, software and customer designs into those businesses. Its expertise is getting camera processing and AI inference to work together within tight power and heat limits. More than 50 million Ambarella AI chips are already deployed across its markets. For NXP, the potential appeal is adding more integrated vision technology to the processors and control chips it sells into automotive and industrial customers. There would be overlap with Kinara, particularly as AMBA expands into standalone AI accelerators. For Qualcomm, the case could be expanding its footprint in camera-based equipment and adding customer programs that would otherwise take time to win organically. A larger buyer could then put AMBA’s products in front of more customers through its existing sales channels. It’s easy to see why AMBA could attract attention as more machines need to see, understand and react. I own all 3 companies so I'll probably feel short term pain and gain at the same time with a deal announcement But I would hope for an all cash offer above $105 for my AMBA shares. But again, no formal deal has been presented.
I think Physical AI could create investment opportunities across a very wide set of companies $OUST $AMBA $QCOM $INOD $RRX $AGCO etc. I’ve broken the trade into 11 layers to figure out where the money goes Bookmark this! 1 - Training & Model Development: teaching machines how to perform useful tasks. 2 - Simulation & Synthetic Data: giving them a virtual world to practice in. 3 - Perception: sensing and understanding their surroundings. 4 - Edge Compute: processing information close enough to react immediately. 5 - Software & Planning: deciding what to do and how to do it. 6 - Control Systems: making those actions precise and safe. 7 - Motion & Actuation: motors, gearing and actuators that create movement. 8 - Power & Energy Delivery: powering the machine efficiently and keeping it working longer. 9 - Connectivity & Fleet Coordination: getting hundreds of machines to communicate and work together. 10 - Systems Integration & Deployment: installing everything into a customer’s actual operation. 11 - End Markets: where customers pay for better outcomes in warehouses, farms, hospitals, defense and beyond. I’m working through the public companies in each layer, digging through their financials and building my Physical AI portfolio along the way. Eight layers covered so far. My latest report screens 65+ U.S.-listed companies across power and energy delivery, then narrows down the businesses and prices that interest me. You can read that one here as a free sub! gaetanoresearch.substack.com…
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$QCOM’s CFO said automotive chip content increases 8× between its Gen 2 and Gen 4 solutions. The business is already growing fast. Fiscal Q3 automotive revenue reached $1.59B, up 61% YoY from $984M. That’s $604M of additional quarterly revenue. Qualcomm can supply the connectivity, digital cockpit and computing behind driver-assistance systems. As automakers adopt more capable platforms, the amount of technology Qualcomm can sell into each vehicle expands. Growth can come from winning more customers and earning more per car, even when overall vehicle sales are slow. New vehicle launches bring those design wins into production over time. This is part of why the broader Physical AI opportunity interests me. As robots and other machines become smarter, the computing inside them can become more valuable too. Automotive gives us a real financial example of that opportunity.
I think the next few years could change how people value $QCOM. Automotive revenue grew 61% last quarter. Qualcomm is taking more of that computing expertise into robotics, while its CFO expects a wave of personal AI devices over the next 6–9 months. I own it in my Physical AI portfolio. My updated article breaks down what these developments change in my earnings model and why I think a higher valuation multiple could be justified. Full thesis and financial model: gaetanoresearch.substack.com… NFA, long term investment for me
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Will $MP earn a place in my Physical AI portfolio? The more I look at the magnets behind robotics, the more interested I get. Robot joints need compact motors that deliver strong, precise movement. Drones need efficient propulsion without adding much weight. Rare earth magnets help make both possible. MP mines and refines the materials and is building out U.S. manufacturing of the finished magnets. That puts it upstream of my Motion & Actuation layer, with potential exposure across a wide range of machines. There’s already a concrete push into drones. In July, MP launched Project Swarm, allowing U.S. and allied manufacturers to reserve future magnet capacity and work with its engineers on designs. Those reservations are still nonbinding, but they give us something specific to follow. The broader expansion has substantial government backing, including a 10-year NdPr price floor and purchase support for its planned magnet facility. That helps fund a domestic supply chain serving commercial and defense customers. Q2 revenue grew 89% YoY to $108.5M. Finished magnets were still moving through customer qualification, so the financial upside depends heavily on successfully scaling that manufacturing business. What interests me is owning a supplier that could benefit as many different robotics companies grow. MP could add an entirely different kind of exposure to the portfolio. It’s earned a closer look. Now I want to understand how much of that future is already in the price. NFA
I believe Physical AI Is the Next Supercycle It is much much more than humanoids There are companies making money NOW And there are companies that will make a lot of money in several years There are so many layers to this investment landscape And I am just now covering it in depth on my Substack If you are interested in the research behind this sector, check this out: cruxcapitalgroup.substack.co…
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I think $GOOG could become the assistant people trust to handle a growing part of their daily lives. Google already has a huge head start. Your inbox contains reservations and receipts. Your calendar tells it when you’re free. Years of activity across its services can provide useful context, if you choose to connect them. Gemini can turn an email thread and related files into a working document, or build a spreadsheet from a folder in Drive. Google also supports agentic checkout at select merchants in the U.S. and Australia. Now think about where that could go. You ask it to organize a family trip. It could work around your schedule, remember the kinds of hotels you like, compare available options and handle bookings with your approval. Then keep track of the trip and help deal with changes afterward. The more reliably it handles that work, the more reasons you have to start the next task with Google. That’s the relationship I’m interested in as an investor. It also changes what Google knows at the moment someone is ready to spend. An agent helping you choose a hotel could understand your budget, dates and preferences in much greater detail than a short search query. If that produces better conversions, businesses have a reason to pay to reach those customers. Google is already testing offers inside its AI shopping experience. Paid access to useful agents creates another revenue opportunity alongside that advertising business. My thesis is that Google could move much further into the decisions and tasks that follow a search. It already has the distribution and much of the context. We’re now seeing the first pieces of what that broader customer relationship could look like. I think we are very early and honestly its kind of hard to tell the level of adoption across the population. But I personally believe that when it becomes way more efficient and seamless to just talk to a ring or watch or glasses and tell it what you need done, people will gravitate towards it. Slowly, then all at once. I personally have several agents that just do stuff for me each day without prompting that are just mindless tasks that would take up unnecessary time.
What happens to $MSFT $GOOG $META $AMZN $ORCL when AI agents start doing more of the work for us? An agent could choose what we buy before we ever open Amazon. Inside a business, one employee could delegate work that creates more paid software usage without adding another person. That could move a lot of profit around. These companies already own much of the infrastructure and customer relationships agents will need, but they have very different ways to earn from that activity. I went company by company in my latest report and built the earnings models behind how I want to own this group. Link in quoted post!
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$NOK doing things
$NOK just coined a new term for AI networking: "Scale Beyond" The idea: extend AI networking beyond data centers. Just as video streaming drove the rise of CDNs, distributed AI could trigger a new wave of telecom infrastructure investment. One of the reasons $NVDA invested.
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Sure... Random train of thoughts on markets now, optics like $LITE / memory + $IREN / Anthropic. On Memory: - Demand visibility on $MU / Samsung / SK Hynix extend into 2030-2031. Samsung has LTAs covering 70% of their capacity into 2031 (likely with SK Hynix type price floors)... and their operating profit is already absurd. There's a consensus that shortage in 2027 will be much more severe than 2026... Even $SNDK expends gross margins to exceed 80% entering 2030. You're going to hear Acer and other CEOs that want memory prices to go down cite bear cases like CXMT/YMTC, and Chinese players. But just looking at supply procurement that $NVDA is doing + hyperscalers, demand visibility is absurd for the next 5 years. And by that time, cumulative FCF coming in from these take/pay + pricing floor contracts might exceed some of their entire marketcaps so it feels like there's some baseline. Near-term is always volatile (IV dropped a ton across $EWY to $DRAM to $MU), so people with call options likely got nuked, along with underlying prices. But if Samsung is 3x 2027E, has 5 year LTAs with 70% of capacity committed from hyperscalers, and price floors, it's kinda hard to see these names suffer a sustained crash... For optics: - $LITE is literally sold out into 2029, starting discussions into 2030. With demand visibility lasting into 2031… with hyperscalers largely funding the capacity buildout. Their 2028 Greensboro fab expansion was ~$5B in UHP laser capacity revenue alone, yet it’s basically allocated toward $NVDA (50%+ with options for more) and co from channel checks. Existing supply chain bottlenecks are extremely severe as optical content/XPU skyrockets entering 2027-2028. So everything from DSPs/TIAs, photodiodes, lasers, InP/SOI substrates, wafers (epi, SOI, etc) are expected to go brrr. And what does that imply to anyone else with enormous amounts of capacity coming online like $AAOI + $SIVE + $MTSI capacity expansion in 2027? Or other players like Sumitomo / Furukawa? But again it's not quite the same situation as memory since the BOM % is extremely low in a cluster... If micron/samsung raised another 2000% hyperscalers would go bankrupt. But doing that for InP substrates seems possible. Or a 100% increase on CW laser content. I actually thought $LITE was overvalued at $100B+ MC, relative to capacity expansion on your smaller optical players to their respective MCs. So I chose to position accordingly (But lumentum does deserve premiums for demand visibility). For the companies leading the charge like $NVDA / $AVGO / $MRVL: - Nvidia has 70% forward revenue growth FY2028 which is supply constrained growth. - Broadcom 100% Y/Y for 2027/2028 which is also supply constrained growth. - Marvell FY2031 upgraded guidance to $70B-$90B from $46B analyst projections... They all seem to be very happy.... and read through on demand for next 2-3 years is enormous (also echoing what $INTC CEO said today on the panel with $AVGO CEO). So you have overwhelming growth on memory + photonics + from the leaders... But the nuance is not everything in the AI supply chain get the same economic benefit. HBM/Laser/CPU/MLCC and other players in the bottlenecks look to be printing money. And seem to be the largest beneficiaries of the current bottlenecks. Test players are also getting price hikes + capacity allocated by players like $NVDA, but economic impact seems a tad lower than other players since forward P/E for many I modeled were still in the 45x+ range even if you hiked prices like 10-30%. As for capex intensive players... there's some like $IREN ($25-30B for 2027) that despite a deal with Anthropic ended up dropping. I don't think markets seem to appreciate players spending a lot of money + ongoing financing (think they're like halfway through their $6B ATM). Just some hopium for $IREN investors, $NBIS also signed a deal with $META at the start of the year (but markets didn't care at all, since Nebius dropped to ~$70-80 at the lowest point?). But did 6 months later, as the time to revenue inflection gets closer and you're past the ATM/capex window, markets would likely care more. I don't think it's irrational but at the same time, the fundamentals have improved from Mirantis acquisition to others. I also think it was known for awhile it was either OpenAI/Anthropic from CEO comments earlier too? But either way to be a more risk-off environment where funds seem to be rotating to larger names as a flight to safety. $CRWD / $PLTR as just two example, but my take is that the valuations of these rotations are reaching clown levels. And that certain AI supply chain beneficiaries in comparison are undervalued now. I was thinking markets would just rotate to names that are extremely profitable like Samsung or names that have <2X P/E, so it was surprising to see $KOSPI and some legacy memory players get sold off today. Since all of this is colliding with uncertainty about sht macro environments and renewed sustainability concern of AI capex/commitments from frontier labs like OpenAI/Anthropic from due to that FT piece recently. I've always been sounding the alarm about the contractual backlog OpenAI has with $CBRS, $MSFT, $ORCL and others earlier in the year. But OpenAI did just raise $122B or so , so I don't quite think they're at risk of going down anytime soon. I also don't think overall capex can just exponentially go up, but even if it stalls / hovers around a certain point or even drops... Capex toward certain areas like optics will still explode as hyperscalers fight over allocations when CPO scale up comes about, but might drop in others where more capacity comes online like test or DRAM. So it's a lot more nuanced than capex down = everything down or vice versa. I also slightly agree with community agreements that open weight models wouldn't lessen demand on AI infrastructure (otherwise $NVDA wouldn't be funneling funds into Reflection), but all the contractual obligations that Anthropic has might get messy if their models/company get cannibalized. Either way, I'd expect some of these frontier lab valuations to likely compress but I do think Jensen knows what he's doing though to avoid contagion. But basically: - Extremely difficult market now, can't just throw money at any AI supply chain company like $GLW and expect it to go up. There's cause for concern of rate hikes mixed with financing per $AVGO CEO but not to the point you just blindly sell off everything. Also I think markets are stupid and ties baskets together so that leads to mispricing + individual buying opportunities with certain chokepoints too. If capacity + demand is visible and forward p/e compresses like $AAOI to single digits off hundreds or thousands of percent growth from hyperscalers off $471m transceiver revenues and hundreds of thousands of monthly ELSFP capacity. Or $SIVE coming online with 100M+ laser capacity + multiple foundries with ASP hikes on lasers. I wouldn't lump them into other AI supply chain names in IP like $RMBS or others. My take is that AI supply chain beneficiaries with closer inflection points, demand visibility, and forward P/E compressing due to economic leverage would likely outperform medium term despite current volatility. TLDR: - Memory strongest risk/adjusted return with LTAs + pricing floors extending to 2030's + buybacks. - My opinion is that optical supercycle for 2027-2028 with CPO/NPO is going to look absurd relative to capacity coming online of smaller suppliers. - Overwhelming fundamentals/growth colliding with sht macro + media scares - Markets are stupid and groups things in baskets and sells them all off together or buys overvalued names, creating short/long opportunities I'd give a prayer to people on short term options given underlying drop + IV decline, but there could be a reversal... who knows. Most valuable thing right now is time.
Serenity please give us some cope we are panicking out here with photonic stocks and memory 😭
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Some of my long term $AMZN thesis Businesses are going to spend more on AI, and they already have the customer relationships to capture that spending through AWS. Training models and deploying agents create more demand for compute. AWS grew 37% YoY in Q2, with operating profit growing 63%. Their own chips give them more control over the cost of serving that demand. That business is already above a $25B annualized run rate. Better economics can help them attract customers and earn more from their usage. They also get paid when people shop and when sellers advertise to reach them. Advertising grew 26% YoY. More automation in fulfillment gives them another way to improve how much profit they keep from each order. The big financial opportunity is what happens as the new data centers fill up. They’re spending more than their operating cash flow today. Jassy expects much of the 2026 AWS investment to monetize in 2027–2028, with substantial customer commitments already in place. NFA
I want hyperscalers to be a major investment sleeve over the next few years... $META $ORCL $AMZN $GOOG $MSFT These businesses already sit inside so much of what we do. AI gives them a way to earn more from those existing relationships as software starts doing more of the work. The earnings opportunity is enormous. So is the cost of building it. I’ve spent a few weeks digging into all five and building 2028 models to figure out where the potential returns justify that spending. Full report coming, with how I want to allocate across them and why.
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Physical AI + Humanoids are the next progression of AI. $NVDA CES 2025 projections and Elon's prediction on $TSLA + 1 Billion humanoids in the next decade, seems to be speeding up. New statement from Unitree CEO after testing GPT-6 on their humanoid program was that: - In August, before GPT-6's release, Wang said the industry could take two to three years at its fastest pace, or as long as a decade, to reach its "ChatGPT moment" - Now, OpenAI's GPT-6 model prompted expectations that a breakthrough could happen "within 1 or 2 years" - He defined that moment as robots being able to complete around 80 per cent of tasks in 80 per cent of unfamiliar environments using voice or text commands. - "It's possible that, say, a GPT-7 model released next year could directly crack the problems of embodied intelligence" - "The whole embodied intelligence industry has been shaken up after the release of GPT-6" Just looking at some benchmarks on robotic hand manipulation, "On the bowl task Astra placed the block in 19 of 20 trials, against Fable 5.1's 8 of 20". But for the puzzle task "Astra completed the insertion 2 times in 20 against Fable 5.1's 2 in 20"".. so we're getting there. But going from 2-3 years (potentially to a decade), and compressing that down to 1 or 2 years (to achieve 80%+ of tasks in unfamiliar environemnts) is a significant change in outlook.
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Two names included in the $NVDA / $CSCO discussion are $APH and $TEL. Both are explicitly involved in developing the cages, connectors and modules around the new USFP format. The proposed first configuration is 16 lanes at 400G, giving 6.4T in roughly today’s OSFP footprint. The 12.8T figure is the future 32-lane configuration. Packing that much bandwidth into a small space requires a new connector design. That gives these suppliers another opportunity to sell more sophisticated hardware as networks upgrade. Laser and transceiver awards haven’t been disclosed, but theres only so many options...
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$AGLT (Agility Robotics) has cleared SEC review for public listing through $CCXI If you want an estimate timeline: ~Oct 13 (today): SEC S-4 declared effective ~Nov 2nd (shareholder vote): for merger approval ~November: Merger closing and ticker goes live for trading. Company’s official statement was: “The business combination remains subject to approval by Churchill XI shareholders and other customary closing conditions, and is expected to close in November 2026.” So likely less than a month away for the first pure play US humanoid company to go live!
One step closer to Nasdaq: the SEC has declared effective our Form S-4 for the proposed business combination with Churchill Capital Corp XI (Nasdaq: CCXI). Expected ticker: AGLT Read the announcement: agilityrobotics.com/content/…
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