Mike
@MikeLongTerm • 25,240 subscribers
Long Term Investor Largest Holding $AMD $PLTR $TSLA Others $XYZ $HIMS $GRAB $TSM $AMZN $NVDA $LMT $ETH $BTC $META $GOOGL $WING $ADBE $BROS Not Financial Advice
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$AMD is easily a $1,200 stock IMO| CPUs TAM 🧵 Not Financial Advice! DYOR! In this thread, I want to discuss the actual TAM for CPUs data center for just 2026, where many are giving different ranges, where I don't agree with. I will explain in detail why I disagree with these research firms and financial analysts using Math. And this thread should not be treated as Financial Advice. I'm just explaining my research and thought process so we can have a discussion. In 2024/2025, I gave out $620 PT for FY2026 was too conservative for AMD potential. At the time, It was early and many were just laughing, that PT was unrealistic and the AI world is run on GPUs only. Today, most of these folks are laughing with me. That is ok, I dont offer financial advice, and I do not need everyone to agree with me. I respect other opinions. If you enjoy this kind of thread, slap the like/repost/bookmark. If you want to support my work further and gain more in-depth analysis, consider subscribe! In early 2026, hyperscalers, enterprises, and OEMs are scrambling as Intel and AMD server CPUs are largely sold out for the year, with prices jumping 10–20% and lead times stretching from weeks to months (or longer for certain SKUs). What was once a GPU dominated story has flipped: the shift to explosive Agentic AI with its multi-step reasoning loops, tool calling, multi-agent orchestration, real-time data movement, and reinforcement learning, is dramatically tightening CPU:GPU ratios from the old training-era 1:4–8 all the way to 1:1 to 5:1 or even CPU-heavy configurations. CEOs across NVIDIA, AMD, Intel, Google, Meta, Microsoft, and public companies have been sounding the alarm on CNBC, Bloomberg, and earnings calls. CPUs are “cool again,” and in many agentic deployments they are becoming the new bottleneck alongside (or even ahead of) GPUs and custom ASICs. In 2025, roughly 12-15m AI GPUs + AI ASICs GPUs shipped, and is expect to be 15-20m units by 2026, where it suggesting Training demand is not going away. The actual TAM is structural, multiplicative demand that has already forced AMD to double its long-term server CPU TAM forecast to >$120 billion by 2030 (>35% CAGR), with Dr. Lisa Su noting Q2 2026 server CPU sales expected to surge 70%+ year-over-year and demand “far exceeding expectations.” At the same time, AMD’s secured 30–40% share of TSMC’s initial 2nm capacity (behind only Apple’s >50%) positions it to ramp Zen 6-based EPYC Venice exactly when this agentic wave hits hardest but even that aggressive five-fab 2nm expansion (with plans scaling toward 11 total advanced facilities) cannot instantly close the gap in the near-term. Supply constraints on wafers, advanced packaging, and power are compounding the squeeze, just as hyperscalers forward-buy and lock in long-term deals. 1. The actual potential TAM Various sources and institutions are giving $50-$160-$200B CPUs TAM toward 2030, and i disagree, where supply is severely behind vs Demand by at least 2-3 years or even longer by some estimates. The actual TAM will probably be 15-20m for FY2026. The typical average selling price from low to high end is $5,000 to $15,000, but due to rising memory, and different inflationary pressures on Semi, it would be more logical to think between $7,000-17,000. A. CPU:GPU Ratio at 1:1 A basic calucation at mid range =12,000 x 15-20m CPUs= $180-$240B TAM B. CPU:GPU Ratio at 5:1 = $12,000 x 75m-100m CPUs= $900B-$1.2T TAM Of course TSMC cannot even supply 20% of this massive inflection TAM in 2026. But do we think of Demand for TAM or Supply for TAM? Hence we are seeing massive 2nm Ramp from TSMC for $AMD. IMO, conservatively, I would take down 15-20% on 1:1 or $135-$192B TAM for just 2026. Im not even talking about 2030. We are just months into this, it is impossible to estimate Cagr atm, but this is 1-5 agents running tasks, I wrote a thread on 24/7 autonomous agents thread, where companies could use 50-250 agents to run tasks for them 24/7. It would require a different structural CPU:GPU to bring down the cost of token as well as handling the Orchestration bottleneck. GPUs would be useless and sit idle waiting for CPU due to highly CPU-intensive nature. The cost per Million tokens must come down more rapidly for this 50-250 autonomous agents to work, otherwise the token cost would be too enormous. Helios Rack is estimated to bring inference cost down to $0.0003-$0.0005/M tokens with 18 EPYC Venices along with 72 MI455x and other chips+ Components. A heavier or CPUs dense rack would bring down inference cost further. EPYC Verano(2027 gen 7 AI-optimized) is expected to drive inference costs meaningfully lower than the Venice baseline likely to the $0.00002–$0.00025 per million tokens range (or even sub-$0.00015 in highly optimized agentic/batch workloads). Verano have higher core counts than Venice, LPDDR5X SOCAMM2 memory support, more AI optimized and Next-Gen rack density & efficiency. 2. $AMD secured at least 30-40% of TSMC 2nm capacity and Memory from Samsung through 2028-2030. 2 2nm fabs are entering ramping phase toward 60-65k wafers per months and 5 dedicated 2nm fabs entering mass production/ramp in 2026. Will link sub threads below if you are interest for full detail. Apple is reported to secure 50%+ 2nm capacity for Iphone 18 and Mac chips and AMD secured at least 30-40% capacity while $NVDA $AVGO $ARM $AMZN $GOOGL and others are on 3nm. This broader aggressive ramp from TSMC to target up to 11 fabs is to address $AMD massive growth ahead. Where $ARM is facing massive CPUs supply constraints as they have to compete with other Mega Cap players on 3nm allocation. And $INTC is also facing supply constraints for data center CPUs and PC per management with lead times extrended to longer than 12 weeks. Dr. Su is aiming for higher than 50%+ Market share, and I believe it is achievable in 2026 or 2027 as AMD has the strongest CPUs offerings. Dr. Su did not want to take advantage of the shortage and she said during the Q1 earning call, AMD is prioritizing Units shipped while guiding margin to be inching 60%. If Jensen were in charge, I'm sure margin would be 70-75% in this kind of severe CPUs shortage condition. But that is not how Dr. Su operates for more than a decade. She wants most market share. So we will see it in revenue growth, but as TSMC ramps faster and faster, AMD Operating and FCF margin will massively improve vs prior decade. A significantly higher margin profile than before. 3. How I came up with $1,200 withint 12-18 months? At $1,200/ share, that would be around $2 Trillion MC. I expect FY2027 revenue to be $124-$144B where data center revenue dominates overall revenue. AI GPUs: I will stick to the lowest end so show u that I'm conservative at $18B for each GW vs $NVDA Rubin is $30B+ (most likely Helios Rack in the $20B+ due to memory price rising). We know deals with OpenAI and Meta are around 12GW and additional multi-customers at multi-GW scale were hinted and will be revealed as we get to July 22-23 2026 Advancing AI event. For now I will conservatively add a bit more to this model. (3-6GW Helios Rack Range) EPYC Venice is reported to be in $15,000-$20,000. However large customers will likely to enjoy $10-$12k discount. I expect AMD to be able to ramp 7m EPYC Venice for entire 2026 and 3-4m of EPYC Verano(higher price than Venice). If we take an average selling price of $10,000 to be on the conservative side. Take down another 30% to be even more conservative on projection. I like to be conservative. That would be ~ 7m EPYC CPUs(Venice + Verano) for FY2027 or 583,000 units per month or 15,000 additional 2nm wafers per month which is completely reasonable for current TSMC Ramp, and I may be too conservative here. EPYC Verano and MI500 series will also be on 2nm. AI GPUs: 3GW x $18B= $54B EPYC CPUs: $10k x 7m CPUs= $70B = Data center revenue alone is $124B Other segments= probably in the $20-$25B FY 2027. FY2027 revenue = $124-$149B At 7m EPYC CPUs for entire 2027, that would be more than 50% market share when we comp it to availability from supply side, not from total Demand. It is possible that TSMC could significantly ramp even more capacity in 2027, so we will see. Metric Q1 2026 FY2027 Gross Margin 55-56% 60-62% Operating Margin 25-26% 32-35% Net Income Margin ~22% 26-30% FCF Margin 25% 28-30% At $124-$149B Revenue FY 2027 Net Income would be $32-$44B EPS would be $20-$27 (GAAP) Non-GAAP would be $25-$31 At $1,200 a share or $2T valuation that would be: 13.4-16x Price to Sales (P/S) 38-48 P/E At this kind of growth of AI SuperCycle, I think it is very reasonable valuation. If we use today at $406/share or $661B MC: 2027 P/S = 4.4x-5.3x 2027 P/E = 13x-16x Is AMD today expensive or cheap to you? Above is already a very conservative where I trimmed 20-30% of doable units. Meaning, there could be upside if TSMC is able to ramp meaningfully like they are planning. Conclusion: A $1,200 per share valuation IMO for AMD in FY2027 is not expensive at all; it is, in fact, conservative when viewed against the structural explosion in agentic AI demand we have mapped out. With server CPU TAM potentially scaling into the $100–$200B+ range in just CPU:GPU 1:1 Ratio for just 2026. AMD positioned to capture 50%+ share thanks to its 2nm TSMC allocation advantage and full-stack leadership, the company could realistically deliver $124–149B in total revenue and $25–$31+ non-GAAP EPS. At those levels, $1,200 implies a 2027 P/E = 13x-16x. Entirely reasonable for a company that will have become the clear Inference Queen (and in many workloads the preferred) AI infrastructure provider, with operating margins expanding above 30% and tens of billions in high-margin rack-scale AI revenue. Dr. Lisa Su was right presciently so about the Agentic AI inflection all the way back to her early 2022–2023 commentary on the coming shift from pure training to inference and orchestration-heavy workloads. While the broader market only fully woke up to this in 2026 when she doubled AMD’s long-term server CPU TAM forecast to >$120B by 2030 (with >35% CAGR), Dr. Su and her team have consistently positioned the company at the center of the CPU renaissance. The explosive demand we are seeing today, sold-out lines, rising ASPs, and hyperscalers forward-buying entire gigawatts of Helios-class systems is exactly the outcome she forecasted years ago. Not Financial Advice! DYOR!
Mike283,548 Aufrufe • vor 29 Tagen
BREAKING $PLTR $225 PT| BUY Rating 🚀🚀🚀 $1 Trillion Market Cap Target 🚨🚨🚨 Rosenblatt's analyst John McPeake Reiterated BUY Rating on Palantir and maintained $225 Price Target. We visited with the Palantir CFO David Glazer, Chief Architect Akshay Krishnaswamy, and Head of Strategic Initiatives Cary Li at their New York offices yesterday afternoon and held a call with a key Palantir implementation partner FoxTrot today. The two events combine to give us increased conviction in both our recently raised $225 target and our long term view that PLTR can join the $1T+ market cap club over a five-year period ($415 target). The AIP/Foundry offering is an arbiter and optimizer of multiple LLMs and MLs, and we see the likelihood of a working AIP/Ontology/Foundry alternative being assembled from piece parts or a future AI-conjured solution as unlikely over the investable time horizon. The call with Chris Willis of FoxTrot today suggests that business momentum for Palantir remains strong, with their business set to at least triple this year. With PLTR now down 24% YTD vs. the IGV down 13% and the NTM PE on the name down to ~1x their growth rate (80x), we are reiterating our Buy on PLTR and $225 price target."
Mike125,720 Aufrufe • vor 16 Tagen
$PLTR $AMD $TSLA $GRAB $HIMS Far way too many people trying to go $100,000 to $1m in a month than $100,000 to $10,000,000 in 10 years. I can't understand this gambling rush nature. The truth is, most of these folks blew up their accounts, and came back much more conservative than before. Then they go heavy on Indexes or $COST, $AAPL or $KO or SP500. Especially young kids, why do you need to rush? You have plenty of time, 5-10 years aint that long. Don't listen to anyone, put in the countless hours and get started. Do your own DD 🫵 Research high quality growth businesses, and know what you own. And write down on a paper: ~What is your financial goal to retire and where? ~What can you do to increase your income to contribute more monthly? ~What makes you happy? ~And lastly, What is your long term goal? Not Financial Advice!
Mike665,965 Aufrufe • vor 6 Monaten
$AMD $620/share is too conservative for 2026 🧵 Some quick facts before I dive into this super long thread: $META allocated 42% GPUs to $AMD and 58% to $NVDA OpenAI allocated 6GW(38%) to $AMD and 10GW to $NVDA My $620 PT below by end of 2026 was only for 10-15% market share. I believe $AMD is going to have much much higher market share than I projected. The AI accelerator market is exploding, projected to reach $500 billion by 2028(is now heading $1Tril), driven by insatiable demand for training and inference compute in large language models (LLMs), recommendation systems, and autonomous systems. Nvidia ($NVDA) has long held a stranglehold, commanding over 90% market share through its CUDA ecosystem and superior rack-scale solutions. However, AMD is mounting a formidable challenge, leveraging cost advantages, open-source software momentum, and hyperscaler partnerships to erode Nvidia's moat. Recent deals—such as Meta's ($META) allocation of 42% of its GPU capacity to AMD and OpenAI's commitment to 6GW of AMD compute (versus 10GW for Nvidia)—signal a tipping point. At the forefront is AMD's Instinct MI450 series, a next-generation AI GPU slated for H2 2026 launch, which promises "no-excuses" leadership in training, inference, and distributed workloads. This analysis dissects how AMD will capture more market share and why hyperscalers like $Meta , xAI , Oracle , and others are poised to become voracious buyers of the MI450. AMD's AI GPU revenue has surged from negligible levels in 2022 to an estimated $4-5 billion in 2025, capturing ~6% of the data center GPU market. This growth stems from the Instinct MI300X, which offers 141GB of HBM3 memory and competitive FP8/FP16 performance at 20-30% lower cost than Nvidia's H100. Hyperscalers, facing NVIDIA 's overcharging, have turned to AMD for diversification. Meta, for instance, plans 600,000 H100-equivalent GPUs by end-2024, with ~42% (or 250,000+ units) sourced from AMD's MI300 series for inference tasks like image editing and AI assistants. Similarly, OpenAI's recent multi-year deal commits to 6GW of AMD compute—equivalent to ~300,000-400,000 MI450 GPUs—starting with 1GW in 2026, explicitly to counterbalance its 10GW Nvidia allocation. These aren't one-offs. Microsoft Azure, Amazon AWS, and Oracle Cloud Infrastructure (OCI) have integrated MI300X for AI workloads, with Oracle deploying 30,000 MI355X units in zettascale clusters. xAI, Elon Musk Musk's AI venture, ran 30% of Grok-1's production traffic on MI300X GPUs and has confirmed ongoing purchases. Collectively, these partners represent over $400 billion in projected AI infrastructure spend through 2028, with AMD targeting up to 40% market share. For those that subscribed, I wrote a specific thread on how AMD "secret weapon" is going to change the game in 2026 with an improved designs on all its products, yes AMD has patent on it. Software is the linchpin. AMD's ROCm platform, once derided as "half-baked," now supports day-zero integration for Llama-4, DeepSeek V3, and GPT-OSS models—closing the CUDA gap. Benchmarks show MI355X (MI450 precursor) outperforming Nvidia's B200 in inference by 1.5-2x on memory-bound tasks, at 25-35% lower TCO. For training, MI450's rack-scale IF128 configuration (128 GPUs, 1.4 PB/s intra-rack bandwidth) rivals Nvidia's VR200 NVL144, enabling clusters like xAI's Colossus (scaling to 1M GPUs). My below thread projected Etimated conservative FY 25 revenue: $34-$36B Estimated conservative FY 26 revenue: $55B-$62B Below is why $AMD is revenue is going to be much higher after OpenAI deal. 1. OpenAI 1GW in 2026. With high demand for MI355X at $30,000k+ per unit, with MI450 is likely to be sold in the $45k-$55k. We can safely calcuate 1GW would require roughly 400,000 MI450 GPUs. or Roughly ~$20B revenue in 2026 alone from OpenAI. That would mean $AMD would hit $56B just from one partnership(OpenAI) in 2026 2. $META, the biggest spender on AI Infrastructure right now, Daddy Zuckerberg bought 250,000+ MI300, and is buying MI355X for recommendation engines and Llama training. It is very unlikely for Daddy Zuck to slow down AMD Chips, due to its Inference superiority to NVDA Chips. Most likely we will see at least 300,000-400,000 MI355X ordered from now toward end of H1 2025. And another 300,000-500,000 MI450 by H2 2025. Or ~$20B from just Meta in H2 alone, excluded H1. 3. xAI : Musk confirmed "AMD GPUs work very well" for Grok's small/medium models, with 30% of Grok-1 on MI300X. xAI's Colossus (200K+ GPUs, targeting 1M) and Oracle partnership (via OCI's MI355X cluster) position it for MI450 trials in H1 2026. With $6B funding and Grok integration into Oracle services, xAI could allocate 10-20% ($10B-$15B) to MI450 for distributed inference. We haven't heard the detail from Daddy Elon Musk yet, but most likely not going to be spending less than OpenAI or Sam Altman 4. Oracle ($ORCL): A multi-billion-dollar MI355X deal powers OCI's AI superclusters, with $500B+ remaining performance obligations. Larry Ellison's zettascale ambitions and xAI/OpenAI integrations make Oracle a MI450 anchor tenant—projected 50-100k units ($15B+ spend) for enterprise AI platforms. $ORCL is likely to spend more on the new "secret weapon" due to its capability in AI inference and cost advantage for $500B backlog. 5. Others ( Microsoft , Amazon , Saudi+other countries): Microsoft (Azure MI300X for training) and Amazon ($148B 15-year spend) test MI450 via Stargate ($500B with Oracle/SoftBank). Emerging buyers like G42 (5GW UAE campus), Crusoe, and Hot Aisle add 5-10GW demand. These potentially would add $15B-$30B in 2026 alone. We also need to factor in $TSM supply constraint( $NVDA is TSMC favorite), so $AMD market cap/growth is being tamed by TSMC. So what are you saying Mike, well $AMD 2026 revenue could hit $90-$100B by end of 2026 or nearly 185% growth YoYo. So what does that mean for valuation? I have no idea how Mr. Market gonna value AMD in 2026 with 3 digits growth. My Conservative $620 was my best projection until today with OpenAI partnership. I'm telling you as one of the biggest AMD bull, that I will leave it to "smart money" and other investors to do the price discovery while I'm chilling and writing DDs daily. Lastly, AMD's MI450 isn't hype—it's a calibrated strike at Nvidia's vulnerabilities, amplified by hyperscaler bets like Meta's 42% allocation and OpenAI's 6GW lifeline. By prioritizing inference efficiency, rack-scale innovation, and open ecosystems, AMD will siphon 10-15% share in 2026, scaling to 20%+ as TCO trumps CUDA loyalty. Meta, xAI, Oracle et al. aren't passive; they're active co-designers, betting billions on MI450 to fuel AGI pursuits without Nvidia's premium. For investors, this is AMD's inflection Per Dr. Lisa Su Not Financial Advice!
Mike700,734 Aufrufe • vor 8 Monaten
$HIMS| Adjustment on Growth toward 2030🧵 Not Financial Advice! FY2025: Revenue: $2.35B or 58% YoY (weightloss $740), Core $1.61B FY2026: Revenue $3.2B(36%) where weightloss may be down by 10-15% or flat. FY2027: Revenue $4.16B(30%) FY2028: Revenue: $5.2B(25%) FY2029 Revenue: $6.5B(25%) FY2030 Revenue: $8.12B(25%) I expect management to ramp up buyback from FCF generation while company is trading at under 2x P/S andrewdudum. The discontinuation of Hims & Hers' compounded oral semaglutide pill in early February 2026(after 2 days), prompted by FDA regulatory actions and legal pressures from Novo Nordisk, introduces near-term challenges to the weight loss segment but does not derail the company's broader growth trajectory, as it pivots aggressively toward diversification and high-potential expansions The weight loss category bolstered by liraglutide injectables, generic semaglutide in Canada, and non-GLP-1 personalized kits retains strong momentum, contributing approximately 31% of total revenue in 2025 and projected to grow at 15-20% annually through 2030, down from prior 60%+ rates but still adding $150-250 million yearly through cross-selling and retention. Offsetting this moderation are ambitious new expansions: international markets, now accounting for an initial 5-10% of revenue but scaling to 20% by 2030 via Canada entry (projected 10% growth contribution in 2026 from generic semaglutide and Livewell acquisition) and Europe/UK via Zava (adding 8-12% incremental growth through telehealth in Germany, France, and Ireland); diagnostics and labs, launched in late 2025 with Quest Diagnostics partnership and YourBio Health's pain-free blood sampling tech, offering 50-120 biomarker tests across heart, metabolism, hormones, inflammation, and stress, expected to generate 12-18% of total revenue by 2027 and ramp to a standalone $1 billion segment by 2030. Preventive care and longevity initiatives, set for full 2026 rollout including peptide manufacturing (via acquired U.S. facility, contributing 10-15% to growth through vertical integration and supply control), coenzymes, GLP/GIP blends for performance and recovery, and a $325 million Grail investment enabling multi-cancer early detection blood tests (projected to add 8-12% revenue uplift starting in 2026 by enhancing subscription retention); and hormone health expansions like menopause/perimenopause and low testosterone treatments, already driving 10% of 2025 growth and poised for 20-25% annual expansion through data-driven personalization. Multi-cancer early detection (MCED) blood testing via the Galleri® test from GRAIL in the prior breakdown, even though it was bundled under longevity/preventive care. This is a significant new offering launched on February 4, 2026, providing subscribers (via the Labs platform) access to a simple annual blood test that screens for signals shared by over 50 types of cancer (including hard-to-detect ones like pancreatic, liver, ovarian, and lung) before symptoms appear. Hims & Hers is offering it at a discounted ~$700 (vs. retail $949), following their participation in GRAIL's $325 million private placement investment in late 2025, which strengthens the partnership and positions this as a core pillar of proactive/longevity care. This could help push Average growth to 30-35% vs 28.2%(my above revised projection). These levers, combined with a subscriber base exceeding 2.5 million (up 31% YoY) and AI-enhanced platform efficiency under new CTO leadership, support an upward revision to growth rates targeting 22-25% CAGR from 2026-2030 to meet the company's $6.5 billion revenue goal, far outpacing prior conservative estimates of mid-teens expansion. This high-growth scenario assumes execution on global scaling, regulatory navigation (FDA approvals for compounded alternatives), and margin recovery to 74-78% via vertical integration, positioning Hims & Hers as a comprehensive digital health ecosystem rather than a GLP-1-dependent player, with potential upside from emerging trends like peptide demand (up 144% in Google searches) and proactive wellness adoption. Not Financial Advice!
Mike250,235 Aufrufe • vor 3 Monaten
$AMD $AMZN partnership will 🚀 in 2026 🔥 Amazon/AMD partnership is hidden among hot headlines from OpenAI $NVDA $ORCL... TLDR: Amazon refused to bid up the overpriced $NVDA chips among other hyperscalers, and decided to work closely with $AMD. Amazon is expected to spend up to $10-$20B a year on 2026 EPYC breakthrough Gen and Future Gen. Dr. Su confirmed "we have plenty for other large customers". For its 2026 EPYC "Venice" processors, AMD is using a multi-node manufacturing strategy: the CPU core complex dies (CCDs) are built on TSMC's 2 nm-class node (N2), while the I/O die (IOD) uses the N3P (3 nm) process. Context: Andy Jassy Amazon Web Services has been working with AMD on EPYC processors since November 2018. With this "secret weapon" breakthrough(patented), this long time partnership has expanded to New breakthrough 2026 EPYC Gen. AMD's 6th Gen EPYC "Venice" processors, slated for 2026, introduce New Chiplet design breakthrough. a revolutionary chiplet interconnect fabric that redefines server scalability for AI. This isn't just faster silicon; it's a paradigm shift for AWS, enabling hyper-efficient, rack-scale AI inference that slashes costs and latency while boosting throughput. AMD to benefit AWS's $100B+ AI opportunity along with $ORCL $MSFT $GOOGL $META Saudi, UAE ,38+ countries and startups. In early October, Amazon/AWS announced the new EC2 M8a instances as their latest-generation, general-purpose compute instances now powered by AMD EPYC 9005 "Turin" processors. Amazon announced the M8a as having up to 30% higher performance and up to 19% better price performance over M7a. With my testing of both at 32 vCPUs, the new AMD EPYC Turin instance provided 1.59x the performance over the prior-generation EPYC Genoa instance! How will this impact AWS AI Inference? ~Cost Efficiency: Inference is 80%+ of AI workloads and latency-sensitive (e.g., chatbots need <1s responses). "Secret weapon" enables 35x better inference perf (per AMD's CDNA roadmap tie-in), cutting AWS's energy use by 50%+ in clusters. With $118B 2025 capex, this could save $20–$30B annually in OPEX, boosting margins to 35%-40%. ~Scalability for Agentic AI: Supports "Helios" rack-scale platforms (up to 128 GPUs + EPYC hosts), delivering 3.58x FP6 perf for distributed inference. AWS can run 700K+ more tokens/sec in 1,000-node clusters (via EPYC 9575F boosts), enabling real-time apps like personalized search or fraud detection at enterprise scale. ~Adoption Catalysts: Early partners like Oracle signal broad uptake; AWS's existing AMD instances G4ad with Radeon GPUs) pave the way. By 2026, EPYC could power 40%+ of AWS AI infra, outpacing Nvidia's GPU lock-in via open standards (ROCm 8 software). Lastly, Amazon’s trajectory toward a $320 stock price is not a speculative leap but a grounded projection rooted in its unmatched fundamentals and strategic AI leadership. With Amazon Web Services poised to surpass $100 billion in annual revenue by 2026, driven by explosive AI inference demand, Amazon is redefining cloud computing’s future. The adoption of AMD’s 2026 EPYC processors with "Secret" architecture is a game-changer, slashing costs by up to 50% and boosting inference throughput 3x, enabling AWS to dominate enterprise AI workloads with unmatched efficiency. This technological edge, combined with Amazon’s e-commerce dominance and high-margin advertising growth, supports a valuation rerating to 22x EV/EBITDA, and it is still a discount to historical highs. Trading at $222, $AMZN is undervalued for its 15–20% revenue CAGR and 25%+ EPS growth through 2030.
Mike449,843 Aufrufe • vor 7 Monaten
$GRAB AI SuperApp Valuation is STUPID👀 Video was from CNBC w/ Howard Marks, a major shareholder on $GRAB. $GRAB is now trading at 3.5 P/S FY 2026 revenue($6.2B) after $GOTO Mobility/Delivery Acquisition with $6B+ in cash and very little debt. Expected growth after 90-95% market share consolidation is 40%+ top and bottom line. This is when $GRAB introduces higher margin services as it has the monopoly in SEA or 700m population. For example, Dine-Out has 70-80% margin (20-30% commission), and this new services drove 1/3-1/4 of all new users growth. And Grab is only 6.5% penetration(700m), 14% thesis (5 billion people TAM). We are very EARLY! Long term shareholders should also expect expansion shortly after this consolidation. Most likely H2 2026 or H1 2027. You can hate Grab or call it a Chinese company based in Singapore as much as you want, but this valuation is stupid. This balance sheet and this kind of growth deserve a premium 8-10 P/S. I will be here to enjoy the ride when the market prices this SuperApp correctly.
Mike278,941 Aufrufe • vor 6 Monaten
$PLTR Software is Free 🧵 Palantir's software is effectively “free” upfront because the company absorbs 100% of the risk of value creation and only gets paid a share(often structured as a percentage or portion) of the actual, measurable value or cost savings it helps generate for the customer. Dr. Karp has repeatedly explained this as Palantir’s core philosophy and competitive edge. In his words: “We absorb the risk of creating value.” He contrasts it sharply with the traditional software industry model, which he describes as one where “your customer thinks they’re getting laid, but they’re getting effed.” In that old model, companies sell licenses or subscriptions upfront, take the money, and leave the customer to figure out whether any real ROI ever materializes. Here is some of the example why bears misunderstood this company, and the explosive growth is going to continue for years to come 1. Airbus- Skywise Palantir helped accelerate A350 aircraft production by 33%, averting a potential ~$1 billion contractual crisis from delays. The broader Skywise platform (powered by Palantir) enables industry-wide predictive maintenance and operations optimization. Independent third-party analysis estimates >$1.7 billion in annual cost savings for airlines + >$850 million in annual revenue opportunities. Over time, this has supported maintenance optimization on issues worth tens of billions of dollars. And Palantir long term parternship with Airbus was valued at $1B over 10 years or $100m a year. Realistically speaking, the Software is FREE. Multi-billion annual ecosystem value vs. ~$100M annualized from the recent deal. Palantir's involvement started with targeted production fixes and scaled into an industry platform. 2. SOMPO $60M profit improvement over 3 years previously, with another $100M expected; newer AI agents targeting $10M annual improvement in financial results via better risk evaluation and decision support. Multi-year expansions, including a $50M add-on in 2023 and further extensions (ongoing platform use across subsidiaries with thousands of daily users). =>Cumulative $160M+ projected gains vs. known expansions in the tens of millions. 3. bp (Energy) Triple-figure returns (hundreds of percent ROI) year-over-year on Palantir investments; broader operational efficiencies cited in the hundreds of millions to $1B range in some energy contexts. bp signed a new 5-year enterprise agreement that explicitly includes Palantir AIP (Artificial Intelligence Platform) capabilities on top of the existing Foundry foundation. This built on prior work and expanded AI-driven decision support for engineers. Older reference from priot renewal cited $100m+ in multi-years, so this 5 years extension will probably be north to $150-$200m This model is why Dr. Karp argues Palantir wins in large enterprises and governments that are tired of “science projects” or expensive software that never pays for itself. It de-risks adoption for the customer while forcing Palantir to stay laser-focused on real, quantifiable value creation rather than just selling seats or licenses. As Dr. Karp puts it, everyone in tech will eventually be paid this way on the actual value delivered, not promises. Palantir's software is free to the customer because the software works, and it does all the heavy lifting. When customers win, Palantir wins! Not Financial Advice!
Mike82,553 Aufrufe • vor 1 Monat
BREAKING Palantir Dr. Karp on CNBC🔥🔥 Brandnew Interview after Q3 2025 Earning! Dr. Karp said this is market manipulation, implying Michael Moron Burry and Andrew Moron Left!🐻 Shorting $PLTR and $NVDA is shorting AI! Shorting 2 fastest growing companies is "BATSHIT CRAZY! And they will lose! If you want to short Palantir, be my guest! We are PRINTING CASH! Source & Credit: CNBC
Mike249,669 Aufrufe • vor 7 Monaten
$AMD Valuation at $70-$100B Revenue in 2026🧵 As of December 4, 2025, AMD's stock trades at approximately $220, with a market cap of $355billion. Revised Valuation with $70B Revenue Earnings Per Share (EPS): Assuming a 40% operating margin (consistent with historical trends, probably higher), $70 billion in revenue translates to $28 billion in operating income. After taxes and interest, net income could be $20 billion, or $12.50 EPS Forward P/E: At 50x-60x (a premium due to growth), the stock price could reach $650-$750 EV/EBITDA: With $28 billion EBITDA, at 40x, EV is $1.12 trillion. Subtracting $5 billion net debt, equity value is $1.115 trillion, or $697 per share. Revised Valuation with $100B Revenue EPS: $100 billion revenue at 45% margin yields $45 billion operating income, $35 billion net income, or $22 EPS. Forward P/E: At 50x-70x, the stock price could reach $1,100-$1,540 EV/EBITDA: $40 billion EBITDA at 45x EV/EBITDA yields $1.8 trillion EV. Subtracting $5 billion net debt, equity value is $1.795 trillion, or $1,122 per share. The market's willingness to assign a high P/E multiple to AMD will be based on the anticipation that these partnerships will translate into substantial revenue and earnings growth. The P/E ratio for the semiconductor industry is approximately 58.57, a significant increase from previous years because of AI CapEx Growth and we are only 2nd year of 10 years cycle. Hence, if $AMD grew to $70B-$100B revenue in 2026, 50x-70x P/E is justified. AMD's existing partnerships with OpenAI , $Meta, $MSFT, $AMZN, $GOOGL, $DELL, $HPE, $SMCI,xAI , Oracle, Vulture combined with new collaborations with international 40+ countries like Saudi,UAE form a solid foundation for revenue growth. The OpenAI deal alone could contribute $25 billion to $28 billion(2026), while Meta's expanded allocation and Oracle's increased orders with the rest add substantial upside of 1m+ GPUs(FY2026) . Technological Leadership: The MI450 GPU, with its superior inference and training capabilities, positions AMD to disrupt Nvidia's market dominance. Benchmarks show 1.5-2x performance advantages at 35-50% lower TCO, making it an attractive choice for hyperscalers. The ROCm platform's maturity, supporting day-zero integration for major AI models, closes the software gap with CUDA, enhancing AMD's competitiveness. In conclusion, AMD's combination of strategic partnerships, technological leadership, and favorable market dynamics positions it to achieve $70 billion to $100 billion in revenue by 2026. This growth is not merely aspirational but grounded in real demand signals and execution capabilities. While risks remain, the upside potential is significant, making AMD a the best AI Name in this AI Supercycle trading at extreme cheap valuation. Not Financial Advice!
Mike187,491 Aufrufe • vor 6 Monaten
$BMNR Thomas (Tom) Lee (not drummer) FundstratDirect.com Tom Lee said we will see $ETH at $16,000
Mike285,132 Aufrufe • vor 10 Monaten
$GRAB Secret Sauce 🧵 How this company will thrive to $300B MC and beyond! It took me a while to gather the material for this thread. I will link down below other threads I talked extensively on all current and future $GRAB services to avoid making this thread too long. It is very important to understand product roadmap on the SuperApp, and how it will make money over the long-term, and transfer that value creation to shareholders. The closest analogy for new investors to understand is Amazon obsession over customers where $AMZN makes a little bit of money on each transaction to break even, but make the most money on Prime Membership. Or Costco obsession over customers where $COST makes 10-15% margin or lower on most products to break even on operation, but to make the most money on Costco membership fees. Jeff Bezos famously said "investors should invest in the company that obsesses customer experiencein the long term, there's never any misalignment between customer interests and shareholder interests!" The TLDR version: Being Customer Obsessed over Competition. We never heard much where Anthony Tan described or bitter about competition. Because Anthony does pay attention to competition, but he is more focused or obsessed on how to serve customers better at the lowest price possible, those that pay for $GRAB services. It is not just a business, it is a mission from first day of $GRAB or formerly known as MyTeksi. Anthony Tan and Co-founder Hooi Ling Tan both met at a class “Business at the Base of the Pyramid.” This class shaped the years of $GRAB success and today mission, creating a valuable business servicing the mass market, the lower income communities. Now, lets start with Customer Obession. $Grab does not see just users as customers, Anthony Tan views drivers, merchants, and partners are customers as well for long term success of the company. This is a big differentiator that contributed to GRAB success today. A. Hyperfocus on users: Grab emphasizes safety, with 99.9% of rides completed without incidents, and offers affordable options like Saver rides (26% of mobility transactions, 1.5X higher order frequency) alongside high-value services like Premium Rides and GrabUnlimited (3.7X more frequent usage, 2X higher retention). This likely enhances user satisfaction and retention, driving revenue growth, as seen in their Q1 2025 earnings of $773 million, up 18% year-over-year. But it does not stop at rides, it translate this obsession into food/grocery/financial and other services. Anthony Tan centered $GRAB success on affordability and reliability over the long-term since its early startup day. Essentially, the long-term TAM for servicing 2- 3 billion people is to get 30-50% of them on GrabUnlimited. Now it is $4.99 a month, will probably be adjusted to $7-$10 adjusted to inflation 10-15 years from now or around $7-$10B or more subscription revenue straight to net income B. Hyperfocus on Merchants: Grab has significantly focused on merchant growth as a core strategy to expand its ecosystem, particularly through its GrabFood, GrabMart, and financial services like GrabFinance. The reason is simple, these merchants/businesses are bringing in user growth. Businesses also pay GRAB on ea transaction very well, and at the same time using Cheap Loan(provided by Grab) to expand, and pay on GrabAds(this will have the highest margin after GrabUnlimited up to 50-60%). Grab also investing heavily on #AI to help merchants with OpenAI and Anthropic partnerships. The impact is unreal with this core strategy, many merchants today have more than 50-60% of its monhtly sales from $GRAB SuperApp(grew from 10-15% in 2021-2022). This approach has positioned Grab as a leader in Southeast Asia’s on-demand market, with significant potential for further expansion as it continues to innovate and optimize C. Hyperfocus on Drivers: In today world, you will never see $uber or Lyft talking about seeing drivers as customers. GRAB is the only company that sees Drivers as customers, and this focus is critical to maintaining a robust supply of driver-partners to meet consumer demand for ride-hailing, food delivery, and other services. Grab has scaled its driver network significantly since going public day with 5-6m registered driver-partners. Expanding rental/low fee fleets to secure drivers, creating stable employment in its current 8 countries. President Ferdinand R. Marcos Bongbong Marcos recently acknowledged $GRAB's significant impact on employment in the Philippines. All of 8 countries Grab operates in, all presidents and PM have praised Grab contribution on employment in their countries. GRAB makes its the company mission to expand more drivers registered on $GRAB SuperApp. Last Fun Fact, GRAB drivers in its 8 market have much higher income than BA degree holders and in many cases x2 or x3 the average salaries due to Grab Dynamic Pricing to bring supply and demand back to lowest price. AKA when demand is mad high, price will be higher to attract more drivers to bring down price. Drivers financial success is Grab long-term success. Conclusion: Grab's SuperApp success, as evidenced by Q1 2025 financials, is tied to putting customers, drivers, and merchants first. Their focus on safety, affordability, financial inclusion, and upskilling creates a robust ecosystem, reflected in increased MTUs, revenue growth, and profitability. The SuperApp will expand to 3 billion people TAM or more over the long term. 1. User Growth(Transactional Users) 2. GrabAds (expanding beyond SuperApp into Physical Grocery/Fleets) 3. GrabUnlimited( Expanding valuable services/features to make it stupid not to have it) Over the long-term, $GRAB will expand beyond SuperApp. Just like when Amazon has some spare computer capacity and decided to rent it out and became the AWS today, which is a behemoth that's now >4 times bigger than its original shopping business. No, I'm not saying $GRAB is the next Amazon. I'm telling you that with this "Secret Sauce" strategy of customer obsession, Anthony Tan can expand to other ventures with the massive FCF+ and profitable SuperApp to fund it. Disclaimer: I do own a large position in the Private Portfolio, and currently 100% on $GRAB on small public portfolio. This is the public portfolio where I contribute $500-$1000 of my own money. This public portfolio is not intended to be just 100% pure $GRAB, but it is the first position. I will try to keep it under 10 companies, and high quality growth businesses ONLY. I will not bother with garbage or hyped businesses where people just hype x10 x100 x1000 next week/year. You can follow others for that. Everything I wrote here is NOT Financial Advice! Source: Private Sources, Grab Dot Com, Webull, TOS, Bloomberg, Various Asian Media Outlets, Youtube, Anthony Tan, WSJ, Financial Times, Yahoo, Reuters, Jakarta Globe...
Mike209,603 Aufrufe • vor 10 Monaten
When $GRAB is above $20 👌 I firmly believe $GRAB is misunderstood as SEA Uber. When the stock price gets to above $20, that is when investors/institutions start to accept it as a SuperApp or the SEA "WeChat & Amazon". Until then, it is up to investors and institutions to study the business model and to understand how cheap it is right now for its potential. SEA is a difficult market to build the infrastructure like $GRAB today from drivers to merchant network. The regulatory nature or complexity add to the cost for new players, part of the reason why competitors lost or are losing to $GRAB. New players think that they can enter with endless incentives/promo will lose eventually. Longer term, consumers will feel GrabUnlimited as "must have" as it is daily essential saving. Consumers in SEA are extremely price sensitive, and they are addicted to saving/discount. Subscription is the ultimate SuperApp core profitability, similar to Amazon Prime. Ads will also be similar to amazon App, and GrabFin will be similar to Wechat Fin services. Grab knows margin on Mobility/Delivery overall are very low. The real money is in ~Added higher margin services on top of Mobility/Delivery(Luxury rides/Dineout/Faster Delivery/Quick Commerce...) ~GrabFin as the Digital Financial infrastructure for everything ~GrabAds ~GrabUnlimited ~B2B SaaS service tiers ~Tourism(booking, bundle booking, Groupon-like booking...) Then GrabCoin(Loytalty program) to keep the flywheel spinning forever. $GRAB should start generating $ per MTUs at above 200m MTUs or GrabUnlimited after 150m+ members. Just don't forget, GRAB is the only company that is actually proving Bottom Of the Pyramid(BoP) profitable and at scale. Expanding to 5B people TAM is inevitable long term as they generate more FCF and acquire more markets like FoodPanda Taiwan. The BoP is the most difficult group due to high operational costs, low profit margins requiring massive vol/freqency, and the time to earn trust from highly price sensitive consumers. The "Secret Sauce" is to treat Merchants,Drivers and Users as customers, where the rest only prioritizes customers. This makes Grab the highest quality business with massive growth potential in the next 10-15 years in SEA. SuperApp Monopoly is ineviable. Grab will have short sellers fake news. Grab will have competitions. Grab will have Global Monetary Policy Volatility. Grab will have up and down (price action). But GRAB will win long term! Not Financial Advice!
Mike56,824 Aufrufe • vor 2 Monaten
$AMD $5 Trillion MC Is Inevitable Long Term👑 This thread will focus more on Inference! 2026 EPYC "Venice" $TSM 2nm to save Large GW Scale Inference by 40% more than Prior Turin gen. Context: EPYC Turin achieves ~$0.001 per million tokens for batch inference vs $0.02-$0.12/ million tokens as I wrote the thread below. Venice is going to lower cost down to $0.0005-$0.0006/Million Tokens. OpenAI spent roughly $20B on Inference and Training, where 80-90% of that was for Inference per Analysts. AKA Renting Compute is Expensive AF! In this thread, I want to focus on why most analysts and investors are underestimating the role EPYC "Venice" and future Gen on overall Data center revenue. And $TSM ramping up 2nm supply early is a confirmation that AMD will be a major buyer long term. I will also link the thread the Gap between AMD Analysts & Reality and 2nm Ramp Thread so you have more comprehensive view of what I'm writing here. Before I go into detail this is my 2026 Projection: AI GPUs: $35-$50B EPYC Data Center: $15B-$17B Client Segment: $12-$13B Gaming: $6B Embedded: $4B-$5B Total Revenue $70-$100B Non-GAAP net income $18B-$25B Non-GAAP EPS $10.97-$15.40 Foward P/E 55x-70x= $603-$1,078 AMD's Analysts are projecting $0 Revenue for MI450 and sluggish EPYC Growth. Meaning, all analysts are either full of 💩 or Sexist, you decide! Analysts are also projecting 0% growth on AMD "Secret Weapon" Chip as $MSFT said we are at significant Windows refresh and upgrade cycle. Do you think TSMC would allocate more 2nm supply to $AMD at $0 MI450 revenue and sluggish EPYC? 1. EPYC is going to be the leader in lowest Inference! Current Turin cost saving is 95% vs $NVDA or 98-99% on Inference cost when you factor in renting Inference compute from Amazon Web Services, Microsoft Azure, or $NVDA Neocloud pets. TSMC claimed: 10-15% higher performance at iso-power, 25-30% lower power at iso-speed, and ~15% higher transistor density compared to 3nm. This reduces operational expenses (energy, cooling) while increasing throughput per chip. EPYC Turin achieves ~$0.001 per million tokens for batch inference (via vLLM on models like Llama 3 70B), driven by high core counts and low hardware costs. EPYC Venice offers ~1.7x overall performance and up to 70% more compute capability per core, with up to 256 cores (512 threads). Enhanced vector/AI instructions and open-source firmware (openSIL) optimize for inference workloads. AMD Incorporates AI Engines (now part of AMD's XDNA) for on-chip acceleration, improving efficiency for low-latency and edge inference. This reduces reliance on discrete GPUs, lowering system complexity and TCO. Venice SKUs are projected at $3,000-$15,000 ($5,000 for 256-core flagship), far below NVIDIA Rubin ($50,000-$90,000) or AMD's own MI450 GPUs ($40,000-$50,000). High memory bandwidth (up to 1.6 TB/s) supports efficient batch inference. Venice is designed exactly for Large customers that want to lower Inference Cost and MI450 Helios is for Customers that want Training at lowest TCO, TDP as well as lower Upfront 1GW scale(Full build $35-$40B vs $NVDA $55B-$80B). 2. Real World Example: OpenAI's 2025 inference spend reached ~$20B, escalating to even higher total compute rental (mostly inference) amid token volume growth(from video generating). By 2026, with usage doubling (consistent with industry trends: token demand grows 2-5x YoY), assume OpenAI processes ~1,800 billion million-tokens annually $NVDA Blackwell at $0.02-$0.12 is $36B(most optimized) Rubin is projected to be at $0.01/million tokens or $18B annual Inference Cost vs $AMD Venice $0.0005/million tokens or $0.9B annual Inference Cost => Massive saving for OpenAI or anyone that are paying 80-90% Annual Bill for Inference compute. In short, it is unsustainable to pay this much rent vs owning for all current AI players for the medium to long term. Rubin excels in low-latency decode (if Groq integration from $20B deal in 2027-2028), but Venice dominates batch (80% of inference by 2030). Actual savings depend on deployment scale (OpenAI's 6GW AMD plans), electricity rates, and software maturity. If Rubin only hits $0.03, savings swell to $53.1B vs. $17.1B. 3. Will running Inference on Venice and future Gen slow down response generation in 2026 and beyond? Human perception of "fast enough" for chat, agents, search augmentation, summarization, coding assistance is roughly Meaning, EPYC may generate $100B a year on data center revenue, Hence $MSFT $AMZN $META $GOOGL OpenAI xAI and 42+ Countries are leaning AMD for Inference, because the cost saving is MASSIVE! 4. Regular users (you, me, people using ChatGPT, Claude, Gemini, Grok, Perplexity...) are extremely unlikely to notice any slowdown and in many cases might even experience slightly faster or more consistent response times if the industry heavily shifts toward AMD EPYC for inference. What actually happens when companies save massively on inference? When OpenAI , Anthropic , Gemini , Grok Meta .... save billions on the batch/enterprise/RAG layer using EPYC Venice, they typically do one or more of these things with the savings, none of which make your chat slower but enhancing their bottom line(Profit) ~Keep prices the same → make more profit ~Lower subscription prices / increase free tier limits ~Train bigger & better models more frequently ~Offer longer context windows ~Add more reasoning steps / tool calls / agents per query ~Improve multimodal capabilities ~Build more data centers / reduce throttling during peaks In practice the consumer experience usually gets better, not worse, when inference becomes dramatically cheaper. Prime example is $META leaning AMD heavily or currently AMD largest customer. or Grok 2 to Grok 3 heavily used AMD for Inference saving. And most Grok Users reported Groke responses snappier, not slower. 5. What does this mean for potential Revenue? Noted that TSMC is massively ramping 2nm supply for $AMD both MI450 and EPYC. EPYC Conservative projection: FY2025: $10.5B(best Est) FY2026: $16B FY2027: $29B FY2028: $49B FY2029: $75B FY2030: $100B Large customers: $META OpenAI $MSFT $AMZN $GOOGL xAI (Apple?) Smaller customer: $DELL $HPE $SMCI and 42+ other countries. The roadmap to $5 Trillion is very much inevitable as Inference Cost from Renting or owning $NVDA are too high, but $NVDA will still dominate Training market share, where MI families are likely to take 15-20% market share, but the TAM is also expanding Rapidly. Most Institutions are projecting $2-$3Trillion TAM by 2030. $NVDA said $4 Trillion. Dr. Lisa Su said $1 Trillion+ by 2030. So you decide on how much TAM. If you enjoy this kind of analysis, Slap the Like/Repost and Bookmark to please the X Algo as it is Free.99! If you want to support my work further, consider subscribe to see more in-depth analysis! Alright, that is it. Not Financial Advice!
Mike102,223 Aufrufe • vor 5 Monaten
$AMD $MSFT Partnership is MASSIVE in 2026 🚀 If you were excited about my thread on $AMD $AMZN AWS long time partnership, you will be even more excited about what Microsoft gonna do with 2026 AMD EPYC "Venice". Historical Context: The relationship between AMD and Microsoft began in the early 2000s, with Microsoft initially focusing on Intel's x86 architecture for its Windows operating system and server products. However, AMD's entry into the server market with its Opteron processors in 2003 marked the beginning of a competitive dynamic that eventually led to collaboration. The partnership intensified with the launch of 3rd Generation EPYC "Milan" in 2021, powering Azure's N2D and C2D VM families. By 2025, Microsoft had integrated 5th Generation EPYC "Turin" into new compute-optimized instances, reflecting a strategic shift towards AMD for cost and performance benefits. This "Secret Weapon" breakthrough will mark another inflection point for AMD Microsoft Azure relationship, will probably be more aggressive than EPYC "Milan" moment in 2021. We can call it EPYC "Venice" moment 2026" 1. Technical performance of AMD EPYC "Venice" (2026) AMD's 6th Gen EPYC "Venice" processors, slated for 2026, introduce New Chiplet design breakthrough. a revolutionary chiplet interconnect fabric that redefines server scalability for AI. This isn't just faster silicon; it's a paradigm shift for Microsoft Azure , enabling hyper-efficient, rack-scale AI inference that slashes costs and latency while boosting throughput. ~Up to 256 Zen 6 cores, a 70% performance increase over "Turin," optimized for AI and HPC. ~Memory and Bandwidth: 1.6 TB/s per socket, doubling "Turin's" capability, with support for MR-DIMM/MCR-DIMM. ~Efficiency: 1,500-1,700W power draw, a 50% reduction, aligning with Microsoft's sustainability initiatives. ~Interconnect: PCIe 6.0 and a new chiplet fabric for rack-scale AI, reducing latency and enhancing scalability. 2. Why $MSFT will adopt $AMD YPYC Share to 50%+ in 2026. AMD EPYC Share: ~30-35% of Azure's x86 CPU-based business while Intel Xeon share is 65% Microsoft's Azure has been progressively integrating AMD EPYC, with "Venice" expected to expand this footprint: A. Dominance of AI Inference Workloads ~AI inference constitutes 80% of AI workloads in cloud environments, with latency-sensitive applications like chatbots, recommendation engines, and fraud detection requiring sub-second response times. ~"Venice's" 35x inference performance uplift directly addresses these requirements, outperforming Intel's offerings and custom Arm solutions in multi-threaded scenarios. B. Cost Efficiency and Operational Savings ~Azure's 2025 capex of $118B is under pressure to deliver returns. "Venice" can reduce operational expenses by $20-30B annually due to its power efficiency and performance gains, improving Azure's margins to 35-40%. ~The cost per inference operation is significantly lower with "Venice," estimated at 24-31% less than Intel-based alternatives, enhancing Azure's competitiveness against AWS and GCP. C. Scalability for Enterprise AI: ~"Venice" supports rack-scale AI deployments, enabling Azure to scale AI services for enterprise customers. For example, a 1,000-node cluster can process 700,000+ tokens per second, crucial for large-scale AI applications like personalized marketing and predictive analytics. ~This scalability is particularly important as Azure aims to capture the $100B+ AI opportunity by 2026, as stated by Microsoft CEO Satya Nadella. D. Reduction of Nvidia Dependency ~While Nvidia ( $NVDA) dominates AI accelerators, AMD's integrated EPYC-GPU solutions (MI450 with "Venice") offer a balanced approach, reducing Azure's reliance on Nvidia's high-cost GPUs. ~"Venice" enables hybrid inference models, where CPU-based inference handles 80% of workloads, and GPU acceleration is reserved for training and complex tasks, optimizing resource allocation. 3. Financial Implication: ~Revenue from Azure could reach $15-18B annually by 2026, part of a total revenue projection of $70-100B ~Profit margins could improve to 55-60%, boosting net income to $20-25B, supported by scale economies and reduced production costs. Intel could respond by giving more aggressive discounts, but this breakthrough has been a decade long of $AMD R&D, or rethinking chiplet design, a complete new approach. "Venice's" lead in AI inference and efficiency is challenging to match. Broader Industry: Other hyperscalers ( Amazon Web Services , GCP) and enterprises will follow Azure's lead, standardizing EPYC technology and pressuring Intel further. This could lead to a broader industry shift towards AMD, enhancing its ecosystem and bargaining power. Conclusion: The strategic adoption of AMD's 6th Generation EPYC "Venice" processors by Microsoft Azure in 2026 marks a pivotal moment in the evolution of cloud computing, particularly for AI inference capabilities. "Venice's" groundbreaking chiplet design, offering a 35x performance uplift for AI inference tasks, a 50% reduction in power consumption, and unparalleled scalability, positions Azure to leapfrog its competitors in the race for AI dominance. This technical superiority, combined with significant cost savings potentially $20-30B annually in operational expenses; aligns perfectly with Microsoft's ambitions to capture the $100B+ Revenue AI opportunity by 2026. The shift to 50% x86 market share for AMD within Azure is not merely a technical transition but a strategic realignment that redefines the competitive landscape. Historically, Microsoft's partnership with AMD has evolved from niche deployments to a core component of Azure's infrastructure, and "Venice" accelerates this trend. The 30-35% AMD EPYC share in 2025 is expected to double, driven by new VM families like C4D and H4D, which will dominate AI-intensive and HPC workloads. This migration is incentivized by "Venice's" efficiency gains, reducing dependency on Intel and Nvidia, and enhancing Azure's sustainability profile. Not Financial Advice!
Mike141,018 Aufrufe • vor 7 Monaten