This is the cleanest chart I've seen for understanding the AI infrastructure trade Memory prices UP, token prices DOWN If cheaper AI meant less demand for hardware, these lines would move together. They're doing the exact opposite. Here's why: A token getting cheaper doesn't mean the task got smaller. Answering a question, running an agent, writing code... it takes roughly the same number of tokens as it did back in May when the price was double Same tokens = same compute and memory burned per task If anything it goes the other way. When tokens cost $2 per million, engineers optimized every prompt. At 97 cents, nobody bothers. Cheap tokens make people more lazy with tokens (I've watched it happen) So the per-task hardware bill doesn't fall when token prices fall, what changes is the NUMBER of tasks Every leg down in token prices unlocks use cases that were unprofitable before. More agents running, more workflows automated, more code generated. Total token consumption keeps climbing even as the unit price collapses And all of those new tokens need memory and compute underneath them. DDR5 spot prices are up over 50% this year and analysts don't see supply relief before late 2027 (Intel's CEO says the industry told him 2028) The market keeps reading falling token prices as bearish for AI. This chart is telling you that the cheaper intelligence gets, the more of it we consume, and the more hardware we need to serve it Cheaper output, scarcer input. You want to own the scarce input That's a big part of why I hold $MU in my Milk Road PRO portfolio. You can track 5 analysts' real time portfolios and research with live trade notifications inside and it's just $1 to try it out (insane price just to check it out). Learn more here: Don't forget to give me a follow @kylereidhead for more insights on AI and markets

OpenAI just unveiled a killer AI model The chart compares GPT-6 Astra with GPT-5.6 Sol, several Claude models, and Gemini 3.8 Flash across difficult evaluations and Astra is shown leading nearly every category. Astra’s strongest results are in advanced technical reasoning. The model reportedly scored 97.6% on FrontierMath Tier 4, a benchmark built around extremely difficult mathematics problems, and 96% on GPQA Diamond, which tests graduate level science knowledge. The most dramatic result is ARC-AGI-3, where Astra is shown scoring 98.6%, compared with 7.8% for GPT-5.6 Sol and 30.2% for Claude Opus 5. ARC-AGI-3 tests whether an AI agent can learn unfamiliar tasks through interaction instead of simply answering standard questions. Astra also appears to be stronger at coding and software automation. It scores 74.1% on DeepSWE v1.1 and 41.4% on AutomationBench, compared with 70.8% and 18.1% for GPT-5.6 Sol. If these results hold up, Astra could be better at writing code, debugging systems, using software tools and completing long technical workflows. The cybersecurity results may be the most important. Astra reportedly achieved 100% on ExploitBench and 99.2% on SRE-Bench, suggesting strong abilities in vulnerability discovery, exploit development and security testing. OpenAI says this performance was powerful enough to place Astra in its highest cybersecurity risk category. That capability could help security teams identify weaknesses before criminals exploit them but it also creates serious risks if the model receives access to code, networks, and powerful tools. The chart also shows Astra performing well in healthcare and chemistry, with scores of 63.4% on HealthBench Professional and 49.7% on MedChemBench. These results suggest advanced scientific reasoning, but they do not mean the model is ready to replace doctors, researchers, or other professionals. Astra also scores 0% on the auto review circumvention test, where a lower score is better. This suggests that it reportedly did not try to bypass its safety review system after being blocked. Astra is being positioned as a more autonomous system that can reason through complex problems, use tools, write software, conduct research, and perform multi step work in areas such as engineering and cybersecurity. Bullish on OpenAI!

The AI bull run is just getting started and here is how you want to position before the biggest spending wave (Save this). The chart shows hyperscaler capital spending rising from $491 billion in 2025 to an estimated $950 billion in 2026 and $1.4 trillion in 2027 and by 2030, spending could reach approximately $3 trillion. The right side of the chart is especially important because analysts have continued raising their estimates. The 2026 forecast increased from $731 billion to $950 billion, while the 2027 estimate rose from $833 billion to $1.4 trillion which suggests the AI infrastructure buildout is happening faster and at a larger scale than previously expected. Now here is how you can benefit from all of this. Nvidia is the obvious beneficiary but investors should also look at the companies supplying the less visible parts of the AI ecosystem. Credo Technology makes high speed connectivity products that allow AI chips, servers, and switches to communicate while Astera Labs provides connectivity solutions that link CPUs, GPUs, memory, and storage inside AI servers. As AI clusters become larger, these companies could benefit from the need to move data faster between processors. Celestica manufactures and integrates servers, networking systems, and other data center hardware for large technology customers while Fabrinet produces complex optical and electronic equipment for other companies. These businesses may benefit as hyperscalers outsource more of the manufacturing required to build AI infrastructure. Applied Optoelectronics is a more direct optical networking play and it has announced a volume order for 1.6T data-center transceivers, which are designed to move data between next-generation AI systems. Coherent and Lumentum also provide lasers, photonics, and optical components used in high-speed networks. Semtech supplies signal conditioning and connectivity technology that helps preserve data quality as transmission speeds increase while Arista Networks and Cisco could benefit from selling the switches and networking systems that connect AI servers across data centers. Marvell is exposed to custom AI chips, networking, and optical connectivity and ass cloud companies develop their own AI processors, Marvell could benefit from helping them design and connect those systems. The power side of the buildout could create another group of winners. Advanced Energy Industries supplies power conversion systems used in data centers and semiconductor equipment while Modine provides thermal management products, while Vertiv supplies cooling, power, and data center infrastructure. This is exactly why we’re positioned across the entire AI infrastructure stack at Milk Road, not just there big names. If you want to see the trades we’re making around this spending wave, join us using this link.

Robinhood found a new growth engine and Wall Street is starting to price it like a financial super app (Save this). Robinhood shares are up 15% after strong analyst upgrades and record activity on Robinhood Chain. Morgan Stanley raised its price target to $150, while Scotiabank set a $136 target and Piper Sandler raised its target to $145. Robinhood Chain also generated $4.45 million ranking among the highest fee blockchain networks in the world. Those fees do not flow directly into Robinhood’s financial statements but investors view them as evidence that the company’s blockchain is attracting real activity. Robinhood Chain launched in July 2026 and is designed to support tokenized stocks, stablecoins, decentralized finance and trading around the clock. The company says its tokenized stock products are available in more than 120 countries, although availability depends on local regulations. The larger opportunity is that Robinhood is expanding far beyond commission free stock trading. The company now generates revenue from equities, options, cryptocurrency, prediction markets, interest income, subscriptions, securities lending, retirement accounts, banking, and other financial products. In the second quarter of 2026, Robinhood reported $1.31 billion in revenue while transaction based revenue increased 44% to $776 million, while event contract revenue reached $156 million, more than 10 times higher than the previous year. Robinhood also reached 28.4 million funded customers and $369 billion in platform assets and more customers and larger account balances give the company additional opportunities to earn trading revenue, interest income, subscription fees, and lending revenue. Robinhood Gold is another important growth driver because subscribers pay recurring fees and tend to use more products. The company has also been expanding into banking, managed investing, crypto derivatives, futures, and AI-powered trading tools. The bull case is that Robinhood becomes a single financial platform where customers can trade stocks, options, crypto, prediction markets, tokenized assets, and financial products from one account. Robinhood Chain could eventually create additional revenue through transaction fees, token issuance, lending, and decentralized finance applications. Our Head of Research, @KyleReidhead called Robinhood at just $35 and Milk Road subscribers have been riding the move ever since. If you want to see the next trades our analysts are making across fintech, AI, and other high growth themes, come join us using the link below.

Robinhood found a new growth engine and Wall Street is starting to price it like a financial super app (Save this). Robinhood shares are up 15% after strong analyst upgrades and record activity on Robinhood Chain. Morgan Stanley raised its price target to $150, while Scotiabank set a $136 target and Piper Sandler raised its target to $145. Robinhood Chain also generated $4.45 million ranking among the highest fee blockchain networks in the world. Those fees do not flow directly into Robinhood’s financial statements but investors view them as evidence that the company’s blockchain is attracting real activity. Robinhood Chain launched in July 2026 and is designed to support tokenized stocks, stablecoins, decentralized finance and trading around the clock. The company says its tokenized stock products are available in more than 120 countries, although availability depends on local regulations. The larger opportunity is that Robinhood is expanding far beyond commission free stock trading. The company now generates revenue from equities, options, cryptocurrency, prediction markets, interest income, subscriptions, securities lending, retirement accounts, banking, and other financial products. In the second quarter of 2026, Robinhood reported $1.31 billion in revenue while transaction based revenue increased 44% to $776 million, while event contract revenue reached $156 million, more than 10 times higher than the previous year. Robinhood also reached 28.4 million funded customers and $369 billion in platform assets and more customers and larger account balances give the company additional opportunities to earn trading revenue, interest income, subscription fees, and lending revenue. Robinhood Gold is another important growth driver because subscribers pay recurring fees and tend to use more products. The company has also been expanding into banking, managed investing, crypto derivatives, futures, and AI-powered trading tools. The bull case is that Robinhood becomes a single financial platform where customers can trade stocks, options, crypto, prediction markets, tokenized assets, and financial products from one account. Robinhood Chain could eventually create additional revenue through transaction fees, token issuance, lending, and decentralized finance applications. Our Head of Research, @KyleReidhead called Robinhood at just $35 and Milk Road subscribers have been riding the move ever since. If you want to see the next trades our analysts are making across fintech, AI, and other high growth themes, come join us using the link below.

Robotics VC funding hit an all time high and here are some of the companies that are set to benefit from this (Save this). From 2021 through 2024, robotics deal activity was flat, somewhere between $2–5 billion per quarter, deal count hovering around 200. Then in Q1 2026 it went nearly vertical, 500 deals in a single quarter and $16+ billion deployed, more than the entire year of 2021 and 2022 combined. The reason is AI got good enough to give robots a brain. For the past decade, robots were only useful in highly structured, repetitive environments because they couldn't handle variation. The moment vision models and language models became capable enough to generalize, the hardware problem suddenly looked solvable. On the private side, the biggest names are Figure AI ($2.4B raised, $39B valuation), Physical Intelligence (Google-backed, reportedly raising at $11B), Apptronik (backed by Google, Mercedes-Benz, John Deere, and Qatar's sovereign wealth fund), and NEURA Robotics in Germany (backed by SoftBank and Tether). China accounts for roughly 31% of global robotics VC by dollar volume and is closing the gap fast, with Galbot, LimX Dynamics, and dozens of others each raising hundreds of millions in early 2026 alone. For public market investors, the clearest ways to get exposure are. Nvidia, its Jetson and Thor chips power the AI inference layer of nearly every robot being built today, and it has made direct investments in Figure AI, Apptronik, and Skild AI. Tesla, deploying Optimus humanoids in its own factories today, with stated ambitions to produce millions of units annually. Hyundai / Boston Dynamics, Boston Dynamics is now a Hyundai subsidiary, and Atlas is being rolled out into industrial settings at scale. ABB, one of the largest legacy industrial robot manufacturers on earth, now integrating AI into an installed base of millions of machines. Fanuc, the other dominant industrial robotics incumbent, similarly adding AI capabilities to existing products used across automotive and electronics manufacturing. Intuitive Surgical, the dominant player in surgical robotics, compounding revenue at 15%+ annually, and increasingly using AI to improve its da Vinci systems. The picks and shovels play that most people miss is memory and compute. Humanoid robots running real time AI inference need fast, low power DRAM which brings it right back to Micron as well. Milk Road is tracking every layer of the humanoid robot supply chain, from the memory inside the brain to the gears inside the joints and the companies positioned to win before the mainstream catches on. Come join Milk Road Pro and get our full analysis every day using the link below!

The Milk Road Macro Index just hit a 5-month low at -0.6. Last time it did this, the S&P 500 dropped 9%. It hasn't printed this weak since April. Last time we were here, MRMI ran to about -2.5 and sat there for weeks. The S&P 500 dropped 9% through that window. We're back in the red now. The index just punched through -0.5. That's the line where this thing flips to risk-off. The main drivers pulling this index down are growth impulses and market breadth, both of which have deteriorated significantly over the last few days. So is this the time to cut risk? At minimum, it’s worth paying close attention: yields are exploding, consumer spending is trending down, oil is approaching $100, odds of rate hikes are at 50%, and the S&P 500 is less than 2% from ATH. I’m trimming a few positions to reduce risk and build up cash. But I'm not treating this like the March washout until I see follow-through. I'm watching the next few MRMI prints and reading comments from our macro expert @BitcoinJesusETH. If you are worried as well and not sure how to navigate through these times, join MR PRO to see how 5 analysts are reacting to this turbulence:

Sam Altman says AI usage could grow from 100,000 tokens per month in 2020 to hundreds of billions today, creating enormous demand for the companies powering the AI economy (Save this). That would represent roughly a million fold increase in six and a half years. Tokens are a way to measure how much information an AI model processes, so this growth shows that AI is moving from occasional chatbot questions to continuous use for coding, research, customer service, and business automation. OpenAI has reportedly seen its heaviest users consume around 100 billion tokens per month. Some extreme users have processed several hundred billion tokens in just 30 days. If usage continues expanding, demand will rise across the entire AI supply chain and here is some of the stocks that will benefit from this. NVIDIA remains the clearest beneficiary because its GPUs, networking products and software are used to train and run AI models. AMD could benefit as cloud companies and enterprises look for alternatives to NVIDIA’s chips. Broadcom and Marvell are important networking and custom chip suppliers and as AI models process more data, data centers need faster connections between servers, memory, and processors. Micron benefits from demand for high-bandwidth memory, which is essential for advanced AI processors. Super Micro Computer and Dell can benefit from demand for AI servers, storage systems, and complete data-center installations. Arista Networks supplies high-speed networking equipment for data centers, while Amphenol and TE Connectivity provide connectors and other components used to connect servers, racks, and communication systems. The AI boom also requires enormous amounts of electricity and cooling. Vertiv provides data-center cooling and power-management systems. Eaton and Schneider Electric benefit from electrical distribution, backup power, automation, and data center infrastructure. GE Vernova, Constellation Energy, and Vistra could benefit from the rising electricity demand created by AI data centers. The stronger AI adoption becomes, the more power companies and utilities may need to build or expand generation capacity. Equinix and Digital Realty provide data-center space and connectivity. Their facilities can benefit as companies lease additional capacity for AI workloads. The opportunity also extends to industrial automation. Siemens and Schneider Electric provide factory automation, industrial software, sensors, and control systems. If AI moves from the cloud into factories, warehouses, and robots, these companies could benefit from the physical deployment of intelligent machines. If you enjoyed reading this, make sure to follow @MilkRoadAI for more AI infrastructure and semiconductor insights and turn on post notifications on.

Robotics VC funding hit an all time high and here are some of the companies that are set to benefit from this (Save this). From 2021 through 2024, robotics deal activity was flat, somewhere between $2–5 billion per quarter, deal count hovering around 200. Then in Q1 2026 it went nearly vertical, 500 deals in a single quarter and $16+ billion deployed, more than the entire year of 2021 and 2022 combined. The reason is AI got good enough to give robots a brain. For the past decade, robots were only useful in highly structured, repetitive environments because they couldn't handle variation. The moment vision models and language models became capable enough to generalize, the hardware problem suddenly looked solvable. On the private side, the biggest names are Figure AI ($2.4B raised, $39B valuation), Physical Intelligence (Google-backed, reportedly raising at $11B), Apptronik (backed by Google, Mercedes-Benz, John Deere, and Qatar's sovereign wealth fund), and NEURA Robotics in Germany (backed by SoftBank and Tether). China accounts for roughly 31% of global robotics VC by dollar volume and is closing the gap fast, with Galbot, LimX Dynamics, and dozens of others each raising hundreds of millions in early 2026 alone. For public market investors, the clearest ways to get exposure are. Nvidia, its Jetson and Thor chips power the AI inference layer of nearly every robot being built today, and it has made direct investments in Figure AI, Apptronik, and Skild AI. Tesla, deploying Optimus humanoids in its own factories today, with stated ambitions to produce millions of units annually. Hyundai / Boston Dynamics, Boston Dynamics is now a Hyundai subsidiary, and Atlas is being rolled out into industrial settings at scale. ABB, one of the largest legacy industrial robot manufacturers on earth, now integrating AI into an installed base of millions of machines. Fanuc, the other dominant industrial robotics incumbent, similarly adding AI capabilities to existing products used across automotive and electronics manufacturing. Intuitive Surgical, the dominant player in surgical robotics, compounding revenue at 15%+ annually, and increasingly using AI to improve its da Vinci systems. The picks and shovels play that most people miss is memory and compute. Humanoid robots running real time AI inference need fast, low power DRAM which brings it right back to Micron as well. Milk Road is tracking every layer of the humanoid robot supply chain, from the memory inside the brain to the gears inside the joints and the companies positioned to win before the mainstream catches on. Come join Milk Road Pro and get our full analysis every day using the link below!

Sam Altman is saying that OpenAI plans to build a humanoid robot, along with other designs because the world around us was built for humans (Save this). Doors, stairs, computers, tools, kitchens, vehicles, and factory equipment are all designed around the human body, a robot with a similar shape could therefore perform useful tasks without requiring people to redesign the entire world. His bigger vision is that one day, everyone could have a personal robot that handles the jobs they do not want to do like cleaning, carrying things, operating equipment, helping elderly people, or completing repetitive work. That would take artificial intelligence out of the computer and place it directly into the physical economy. This will create a massive new market beyond chatbots and software. The companies that benefit is not only be the robot manufacturers but the real picks and shovels will be the suppliers that provide the robot’s brain, eyes, muscles, joints, sensors and nervous system. Here are some of the stocks that will benefit from this. NVIDIA could benefit from the computing power required to process vision, language, movement, and real time decisions. Ambarella is another potential beneficiary because its chips are designed for video processing, computer vision, AI inference, robotics, and industrial applications. Harmonic Drive Systems and Nabtesco are important names in precision gears and reducers, which help robotic joints move smoothly and accurately. Nidec provides exposure to motors, while companies such as TE Connectivity and Amphenol supply connectors, sensors, and electrical components that help link the robot’s hardware together. Texas Instruments could also benefit from the large number of chips needed for motor control, power management, sensing, and communications. These companies may be attractive because they already serve multiple industries, meaning investors are not depending entirely on humanoid robots becoming popular. For more direct exposure, investors can look at Tesla, which is developing its Optimus robot, while Hyundai offers indirect robotics exposure through Boston Dynamics. OpenAI has also previously collaborated with Figure AI, a humanoid robotics company developing robots for industrial and commercial applications. The opportunity is that every successful robot maker could need many of the same components. If Tesla, Figure, Chinese robotics companies, and other manufacturers all scale production, suppliers of motors, gears, chips, sensors and connectors could sell into the entire industry rather than relying on one robot brand. Of course, humanoid robots still face major challenges, including cost, battery life, safety, reliability, manufacturing, and proving that customers are willing to pay for them so the companies that benefit most may not necessarily be the flashiest robot makers, but the diversified suppliers quietly selling the essential parts to everyone. If you enjoyed reading this, make sure to follow @MilkRoadAI for more robotics and semiconductor insights and turn on post notifications so you don't miss a single update.

Sam Altman is saying that OpenAI plans to build a humanoid robot, along with other designs because the world around us was built for humans (Save this). Doors, stairs, computers, tools, kitchens, vehicles, and factory equipment are all designed around the human body, a robot with a similar shape could therefore perform useful tasks without requiring people to redesign the entire world. His bigger vision is that one day, everyone could have a personal robot that handles the jobs they do not want to do like cleaning, carrying things, operating equipment, helping elderly people, or completing repetitive work. That would take artificial intelligence out of the computer and place it directly into the physical economy. This will create a massive new market beyond chatbots and software. The companies that benefit is not only be the robot manufacturers but the real picks and shovels will be the suppliers that provide the robot’s brain, eyes, muscles, joints, sensors and nervous system. Here are some of the stocks that will benefit from this. NVIDIA could benefit from the computing power required to process vision, language, movement, and real time decisions. Ambarella is another potential beneficiary because its chips are designed for video processing, computer vision, AI inference, robotics, and industrial applications. Harmonic Drive Systems and Nabtesco are important names in precision gears and reducers, which help robotic joints move smoothly and accurately. Nidec provides exposure to motors, while companies such as TE Connectivity and Amphenol supply connectors, sensors, and electrical components that help link the robot’s hardware together. Texas Instruments could also benefit from the large number of chips needed for motor control, power management, sensing, and communications. These companies may be attractive because they already serve multiple industries, meaning investors are not depending entirely on humanoid robots becoming popular. For more direct exposure, investors can look at Tesla, which is developing its Optimus robot, while Hyundai offers indirect robotics exposure through Boston Dynamics. OpenAI has also previously collaborated with Figure AI, a humanoid robotics company developing robots for industrial and commercial applications. The opportunity is that every successful robot maker could need many of the same components. If Tesla, Figure, Chinese robotics companies, and other manufacturers all scale production, suppliers of motors, gears, chips, sensors and connectors could sell into the entire industry rather than relying on one robot brand. Of course, humanoid robots still face major challenges, including cost, battery life, safety, reliability, manufacturing, and proving that customers are willing to pay for them so the companies that benefit most may not necessarily be the flashiest robot makers, but the diversified suppliers quietly selling the essential parts to everyone. If you enjoyed reading this, make sure to follow @MilkRoadAI for more robotics and semiconductor insights and turn on post notifications so you don't miss a single update.

Elon says AI could become smarter than all of humanity combined within the next five years. @elonmusk also suggested that humans may no longer be in control of AI within the next decade. Musk believes the biggest transformation will happen when advanced AI is combined with humanoid robots. AI would provide the intelligence, while robots would perform physical tasks in factories, warehouses, hospitals, homes, and other parts of the economy. He has suggested that there could be at least 100 million humanoid robots within five years, with the possibility of that number eventually reaching one billion. If that happens, companies could produce far more goods and services with far fewer human workers. Musk describes this potential future as an age of amazing abundance, where people could have access to almost anything they want. He even predicted that money may no longer matter by 2036 because AI and robots could make production extremely inexpensive. However, this would not mean that the transition would be easy. If AI can perform most digital jobs better than people, workers in areas such as software development, customer service, administration, and research could face significant pressure. Musk has also said that work may eventually become optional, comparing employment in the future to gardening today, where people do it because they enjoy it rather than because they have to survive.

Elon says AI could become smarter than all of humanity combined within the next five years. @elonmusk also suggested that humans may no longer be in control of AI within the next decade. Musk believes the biggest transformation will happen when advanced AI is combined with humanoid robots. AI would provide the intelligence, while robots would perform physical tasks in factories, warehouses, hospitals, homes, and other parts of the economy. He has suggested that there could be at least 100 million humanoid robots within five years, with the possibility of that number eventually reaching one billion. If that happens, companies could produce far more goods and services with far fewer human workers. Musk describes this potential future as an age of amazing abundance, where people could have access to almost anything they want. He even predicted that money may no longer matter by 2036 because AI and robots could make production extremely inexpensive. However, this would not mean that the transition would be easy. If AI can perform most digital jobs better than people, workers in areas such as software development, customer service, administration, and research could face significant pressure. Musk has also said that work may eventually become optional, comparing employment in the future to gardening today, where people do it because they enjoy it rather than because they have to survive.

SK Hynix could be entering one of the most profitable memory cycles in history, and the opportunity will extend across the entire memory industry (Save this). UBS estimates that SK Hynix’s revenue could rise from 97 trillion won in 2025 to approximately 601 trillion won in 2027, while operating profit could approach 500 trillion won. The forecast highlights the enormous operating leverage in the memory business when demand remains stronger than supply. AI servers require far more memory than traditional servers, especially high bandwidth memory, which allows GPUs to access data quickly and operate at maximum performance. SK Hynix is one of the leading HBM suppliers, making it a direct beneficiary of the AI infrastructure buildout. However, the bull case is not limited to SK Hynix or HBM because Micron could benefit from growing demand for HBM3E, HBM4, conventional DRAM, and enterprise SSDs as cloud providers build larger AI data centers. Samsung could benefit across HBM, server DRAM, NAND flash, and solid state storage because of its scale across nearly every major memory category. UBS estimates that SK Hynix’s DRAM revenue could grow from approximately 269 trillion won in 2026 to 461 trillion won in 2027, while NAND revenue could increase from roughly 86 trillion won to 139 trillion won. This shows how the AI boom could expand beyond HBM and create a broader memory supercycle. Demand could rise because companies are buying more GPUs, while each new generation of AI accelerator requires more memory attached to it. At the same time, memory supply cannot be expanded instantly because HBM requires advanced manufacturing, complex stacking, and sophisticated packaging. If demand continues to exceed supply, SK Hynix, Micron, and Samsung could maintain higher prices and unusually strong profit margins. This is exactly why we’ve stayed so bullish on the memory supercycle at Milk Road. Milk Road subscribers are already up massively on our memory trades, and if you want to see exactly how we’re positioned around Micron, Samsung, and the rest of this cycle, check out the link below for more!

SK Hynix could be entering one of the most profitable memory cycles in history, and the opportunity will extend across the entire memory industry (Save this). UBS estimates that SK Hynix’s revenue could rise from 97 trillion won in 2025 to approximately 601 trillion won in 2027, while operating profit could approach 500 trillion won. The forecast highlights the enormous operating leverage in the memory business when demand remains stronger than supply. AI servers require far more memory than traditional servers, especially high bandwidth memory, which allows GPUs to access data quickly and operate at maximum performance. SK Hynix is one of the leading HBM suppliers, making it a direct beneficiary of the AI infrastructure buildout. However, the bull case is not limited to SK Hynix or HBM because Micron could benefit from growing demand for HBM3E, HBM4, conventional DRAM, and enterprise SSDs as cloud providers build larger AI data centers. Samsung could benefit across HBM, server DRAM, NAND flash, and solid state storage because of its scale across nearly every major memory category. UBS estimates that SK Hynix’s DRAM revenue could grow from approximately 269 trillion won in 2026 to 461 trillion won in 2027, while NAND revenue could increase from roughly 86 trillion won to 139 trillion won. This shows how the AI boom could expand beyond HBM and create a broader memory supercycle. Demand could rise because companies are buying more GPUs, while each new generation of AI accelerator requires more memory attached to it. At the same time, memory supply cannot be expanded instantly because HBM requires advanced manufacturing, complex stacking, and sophisticated packaging. If demand continues to exceed supply, SK Hynix, Micron, and Samsung could maintain higher prices and unusually strong profit margins. This is exactly why we’ve stayed so bullish on the memory supercycle at Milk Road. Milk Road subscribers are already up massively on our memory trades, and if you want to see exactly how we’re positioned around Micron, Samsung, and the rest of this cycle, check out the link below for more!

Elon Musk thinks humanoid robots could become a bigger industry than almost anyone expects (Save this). @elonmusk said the usefulness of a humanoid robot depends on three factors, the quality of its artificial intelligence software, the performance of its onboard chip and the dexterity of its mechanical systems, especially its hands. Because all three areas are improving rapidly, even small advances could multiply together and make robots significantly more capable over time. Musk also believes robots could eventually help manufacture more robots, creating a self reinforcing production cycle that accelerates after starting slowly. He has suggested that there could be more than 1 billion humanoid robots within the next decade, with each robot potentially producing several times more output than a human worker. If this vision becomes even partially accurate, the opportunity will extend far beyond Tesla and other robot manufacturers. Here is some of the companies that will benefit from this. The supply chain could benefit from rising demand for artificial intelligence models, processors, actuators, sensors, cameras, batteries and memory. Tesla and NVIDIA could benefit from the software, chips, and computing systems required to help robots understand instructions, process information, and make decisions in real time. Actuator manufacturers such as Harmonic Drive and Regal Rexnord could benefit because robots need precise motors and mechanical systems to walk, balance, lift objects, and move their hands. Companies such as Sony, Intel, and RoboSense could benefit from supplying cameras, LiDAR, image sensors, and other technologies that allow robots to understand their surroundings. Battery suppliers such as CATL and Panasonic could also benefit because humanoid robots will require compact, high energy density batteries to power their motors, sensors, and onboard computers. The biggest opportunity may be in companies that supply critical parts to several robot manufacturers at the same time. If you enjoyed reading this, make sure to follow @MilkRoadAI and turn on post notifications for more AI and robotics investing insights. If you want to learn more about the companies positioned to benefit from the humanoid robotics boom, check out the link below.

Elon Musk thinks humanoid robots could become a bigger industry than almost anyone expects (Save this). @elonmusk said the usefulness of a humanoid robot depends on three factors, the quality of its artificial intelligence software, the performance of its onboard chip and the dexterity of its mechanical systems, especially its hands. Because all three areas are improving rapidly, even small advances could multiply together and make robots significantly more capable over time. Musk also believes robots could eventually help manufacture more robots, creating a self reinforcing production cycle that accelerates after starting slowly. He has suggested that there could be more than 1 billion humanoid robots within the next decade, with each robot potentially producing several times more output than a human worker. If this vision becomes even partially accurate, the opportunity will extend far beyond Tesla and other robot manufacturers. Here is some of the companies that will benefit from this. The supply chain could benefit from rising demand for artificial intelligence models, processors, actuators, sensors, cameras, batteries and memory. Tesla and NVIDIA could benefit from the software, chips, and computing systems required to help robots understand instructions, process information, and make decisions in real time. Actuator manufacturers such as Harmonic Drive and Regal Rexnord could benefit because robots need precise motors and mechanical systems to walk, balance, lift objects, and move their hands. Companies such as Sony, Intel, and RoboSense could benefit from supplying cameras, LiDAR, image sensors, and other technologies that allow robots to understand their surroundings. Battery suppliers such as CATL and Panasonic could also benefit because humanoid robots will require compact, high energy density batteries to power their motors, sensors, and onboard computers. The biggest opportunity may be in companies that supply critical parts to several robot manufacturers at the same time. If you enjoyed reading this, make sure to follow @MilkRoadAI and turn on post notifications for more AI and robotics investing insights. If you want to learn more about the companies positioned to benefit from the humanoid robotics boom, check out the link below.

Humanoid robots will become one of the biggest industrial markets of the next decade. The chart estimates that the global humanoid robot TAM could grow from approximately $613 million in 2025 to $138 billion by 2035. That would represent an extraordinary expansion as robots move from prototypes and pilot programs into factories, warehouses, logistics centers, and other commercial environments. The forecast also shows annual shipments increasing from approximately 14,700 robots in 2025 to nearly 6.5 million robots by 2035. The economics could also become increasingly attractive as production scales and manufacturing improves. The chart estimates that the average selling price could decline from approximately $41,800 in 2025 to about $21,300 by 2035. At the same time, the bill of materials could fall from approximately $27,700 to roughly $13,500, creating more room for manufacturers and suppliers to earn attractive margins. This cost reduction is important because robots do not need to replace every human worker to create demand. They only need to become economically competitive in industries facing labor shortages, rising wages, unsafe working conditions, or high employee turnover. Here is how you can benefit from all of this. The supply chain could be one of the largest beneficiaries because every humanoid robot requires processors, memory, cameras, LiDAR, sensors, actuators, precision gears, batteries and power management components. NVIDIA, Intel, and Qualcomm could benefit from supplying the computing hardware, while companies such as Harmonic Drive, Nidec, Regal Rexnord, Hyundai Mobis, and Inovance could benefit from supplying motors, actuators, and motion control systems. CATL, LG Energy Solution, Samsung SDI, SK On, and Panasonic could benefit from the battery demand created by large robot fleets. Companies such as Sony, Murata, Novanta, Hesai, RoboSense, Ouster, and LG Innotek could benefit from supplying cameras, sensors, LiDAR, and other perception technologies. The opportunity will extend beyond the initial sale because humanoid robots will require software updates, replacement parts, maintenance, fleet management, charging infrastructure, and ongoing artificial intelligence services. Goldman Sachs previously estimated a $38 billion humanoid robot market by 2035, while Morgan Stanley has projected that the broader humanoid economy could eventually reach approximately $5 trillion by 2050. The near term opportunity is likely to come from industrial automation, but the long term opportunity could expand into healthcare, retail, construction, hospitality, and household applications. If you enjoyed reading this make sure to follow @MelvinInvests for more robotics and semiconductor insights, and if you want to see exactly what I'm buying as an analyst at Milk Road Pro, check out this link and come join us.

There it is! @gavinsbaker is telling you the EVERYTHING bull market is coming from AI too This is the exact thesis I have been laying out for the last few months "Maybe everyone wins from AI. Anthropic wins, OpenAI wins, SpaceX wins, Meta wins. Google wins by selling a lot of TPUs. Open source wins, NeoClouds win, inference clouds win.Applications win too." Everyone is so focused on what is going to go wrong and they are missing the fact that AI is providing an ROI for everyone across the entire stack From infrastructure, to the model layer, to the application layer Of course, there is a bit of hyperbole here. There will be some losers in terms of specific companies within specific layers But the point of the EVERYTHING bull market is that every layer of the AI stack is currently winning and I don't see that slowing down anytime soon So long as the application layer continues to see improved ROI then the demand will continue all the way down This is why I continue to remain super bullish across the entire stack and hold a portfolio that is diversified across each layer If you want to see my entire real-time portfolio, you can track it alongside my research with live trade notifcaiton inside Milk Road PRO. There are 5 top-tier anlaysts all doing the same there. Learn more here: