Waymo Total California Trips $GOOG https://t.co/6Kvz5AGEEq
5 STOCKS BUILT TO LEAD THIS MARKET The names institutions are watching. The names retail is sleeping on. Here’s why these five aren’t just holdings — they’re market leaders in the making. $NVDA — The Infrastructure of Intelligence → Every AI model runs on Nvidia silicon → Blackwell demand is backlogged into 2026 → Data center, sovereign AI, robotics — all roads lead here → Not a chip company. It’s the picks & shovels of the entire AI supercycle $MU — Memory is the Next Bottleneck → HBM3E demand exploding as AI models scale → Direct Nvidia supply chain play — feeds the beast → Massive pricing power cycle just beginning → Most underappreciated AI infrastructure stock in the market right now $PLTR — The Software Layer Governments Trust → AIP platform turning enterprise & defense data into decisions → US Gov + NATO contracts = durable, sticky revenue → Becoming the operating system of AI-powered warfare & intelligence → Commercial growth accelerating — this is still early innings $TSLA — More Than a Car Company → FSD + Robotaxi = a monetization model Wall Street hasn’t fully priced → Optimus humanoid robot could be the largest revenue opportunity in history → Energy storage division quietly compounding → Love it or hate it — the optionality here is unmatched $GOOG — The Sleeping Giant Waking Up → Gemini integration across Search, Cloud, YouTube & Workspace → Google Cloud catching fire — enterprise AI deals accelerating → Waymo is the most undervalued autonomous asset on the planet → Trading at a discount to peers despite owning some of the best AI infrastructure on earth → Each one owns a critical layer of the next decade’s economy → Infrastructure. Data. Software. Autonomy. Intelligence. → These aren’t trades. They’re positions. Not financial advice.
One AI Supercycle - 10 Layers. 10 Tickers. Layer 1 — Power | $BE A single AI data center can consume 100–500MW. The US grid wasn’t built for this. Bloom Energy sits at the intersection of distributed power generation and the insatiable energy appetite of hyperscalers. Power is the foundational constraint — before chips, before cooling, before anything else. Layer 2 — Substrates | $AXTI InP (Indium Phosphide) and GaAs (Gallium Arsenide) wafers are the raw material for photonic components — lasers, modulators, detectors. AXT Inc supplies these specialty substrates to the photonics supply chain. Demand is structurally rising as Co-Packaged Optics (CPO) and 1.6T transceivers scale. Tight supply, long qualification cycles, few alternatives. Layer 3 — Chips | $NVDA H100. H200. Blackwell. Each generation widens the moat rather than narrowing it. CUDA lock-in is one of the deepest competitive advantages in tech history. $NVDA isn’t just a chipmaker — it’s the operating system of the AI era. Layer 4 — Memory | $MU HBM3E (High Bandwidth Memory) is the bandwidth interface between the GPU and data. Without it, the most powerful chips in the world are throttled. Micron is one of only three companies globally that can produce HBM at scale — alongside SK Hynix and Samsung. Supply is tight. ASPs are rising. The AI upgrade cycle is a multi-year HBM demand wave. Layer 5 — Photonics | $AAOI As data centers scale from 400G to 800G to 1.6T optical speeds, the components inside transceivers — lasers, modulators, detectors — face an exponential demand surge. Applied Optoelectronics is a pure-play photonics manufacturer benefiting directly from this cycle. Margin expansion + volume ramp = a powerful setup. Layer 6 — Optics | $LITE If photonics makes the components, optics assembles them into the interconnect. Lumentum is a leader in optical networking — coherent transceivers, 3D sensing, EML lasers. The 800G → 1.6T transition is a hardware replacement cycle that touches every hyperscaler and co-lo data center globally. This isn’t incremental demand. It’s a full network overhaul. Layer 7 — Cooling | $VRT Vertiv designs and manufactures liquid cooling, immersion systems, and thermal management infrastructure for high-density AI racks. As GPU power density climbs past 1kW per chip, traditional air cooling fails. Vertiv is already embedded with the largest hyperscalers. Backlog is growing. Lead times are extending. Layer 8 — Networking | $ANET Arista Networks builds the high-speed Ethernet switching fabric that connects thousands of GPUs inside AI training clusters. Their software-defined architecture and 400G/800G switching platforms are designed for exactly the traffic patterns AI workloads generate. AI networking is a separate, incremental growth vector on top of their already dominant enterprise business. Layer 9 — Data Centers | $NBIS Nebius Group is building AI-native data centers — purpose-built for GPU density, liquid cooling, and low-latency networking. Unlike legacy co-los retrofitting old facilities, Nebius is starting from scratch for the AI era. Backed by Yandex’s original infrastructure DNA, they’re scaling fast in a market where capacity is chronically constrained. Layer 10 — Hyperscalers | $GOOG Google has committed $75B in capex for 2025 alone. Their TPU buildout, data center expansion, and AI product integration (Gemini, Search, Cloud) make them both a consumer and a builder across the stack. Every dollar they spend flows down through layers 1–9. The AI supercycle isn’t a software story — it’s a physical infrastructure buildout that rivals the railroad era. Every layer of this stack is capacity-constrained, capital-intensive, and structurally undersupplied relative to where demand is heading. Most investors own one or two names at the top of the stack. The opportunity is in understanding all 10 layers — and sizing accordingly. Not financial advice .
$GOOG https://t.co/UIWjKJzj5s
0DTE Watch — If Market Bounces Today, It’s monthly OPEX Friday. Futures red. Inflation fear. But dip buyers have shown up 7 weeks straight. If the bounce comes — here’s where the 0DTE setups live. $MU $TSLA $GOOG $NVDA $PLTR
Some loser to me in 2004 "No no if you assume those growth rates for $GOOG it'll be a bigger market cap than the GDP of almost every country in the world." Me.. https://t.co/SsePBN0YsA
The “Inflation Era” of AI Compute is Breaking Out Across the Board Every layer of the AI infrastructure stack is seeing demand explosion — and the winners aren’t just $NVDA. Here’s the full supply chain map 👇 ⚙️ FOUNDATIONAL INFRASTRUCTURE → PCB: $TTM, $JBL → CCL: $ROG → MLCC: $VSH → Liquid Cooling & Thermal: $VRT 🔴 CORE COMPUTE & MEMORY AI Silicon: → $NVDA $AVGO $AMD $INTC Memory / Storage: → $MU $SNDK $WDC $STX $INTC Power Management / Analog: → $TXN $ADI $NXPI $STM $MPWR $VICR Wafer Foundry: → $TSM $GFS $UMC Advanced Packaging / OSAT: → $TSM $ASX $AMKR 🔵 OPTICAL COMMUNICATIONS NETWORK Optical Components: → $LITE $COHR $AAOI Optical Fiber & Cable: → $GLW Silicon Photonics Foundry: → $TSEM $GFS INP: → $AXTI Optical DSP / Interconnect Silicon: → $MRVL $FN ☁️ CLOUD & AI PLATFORMS → $AMZN $GOOG $BABA $BIDU The AI compute supercycle isn’t one stock — it’s an entire ecosystem repricing in real time. Not financial advice. DYOR.
ANTHROPIC REVENUE TRAJECTORY IS BREAKING MATH → Jan 2025: $1B ARR → Dec 2025: $9B ARR → Apr 2026: $30B ARR That’s a 30x in 15 months. One analyst is now projecting $100B by end of 2026, $340B in 2027, and $2T+ by 2030. Compare that to Google’s current revenue run-rate. The forecast says Anthropic could surpass it by mid-2028. Is it too aggressive? Probably. But the direction of travel is real. The bigger signal here isn’t Anthropic specifically — it’s what this means for the compute stack. If AI model companies are monetizing this fast, demand for chips, memory, networking, power, and cooling is going to be far larger than the market priced in. The infrastructure thesis just got stronger. Before a potential Anthropic IPO, here’s where you can get exposure today: → $AMZN — lead cloud partner + investor → $GOOG — major backer + TPU development partner → $NVDA / $AMD / $AVGO — AI chip layer → $TSM — foundry capacity → $MU — HBM + DRAM demand surge → $MRVL / $FN / $LITE / $COHR — optical networking → $VRT / $MPWR — power & cooling Pre-IPO fund exposure: → $VCX — Anthropic ~20.7% of portfolio → $DXYZ — meaningful Anthropic position → $AGIX — one of the few ETFs with direct private AI exposure → $BSTZ — private market tech exposure including Anthropic The AI model race winner is still unknown. The infrastructure winners are less uncertain. Not financial advice.
Colleague at lunch today going on about how he finally bought $NVDA . Said it like he discovered fire. I nodded. Asked how it was going. He said he was up a bit, felt good about it. Asked what I own. I started to explain. Got one sentence into $IREN before his eyes glazed. Tried $ONDS. He asked if that was a pharma company. I mentioned $RKLB and he said “oh like Virgin Galactic?” I stopped explaining. Smiled. Said “yeah, something like that.” Here’s what I actually own: $IREN 4.5GW secured power. $9.7B Microsoft deal. The hyperscaler for hyperscalers. $NBIS $50B+ contracted backlog. Goldman at $205. NVIDIA invested $2B. $CIFR $AMZN + $GOOG colo. AWS capacity starts July. $ONDS Only FAA-certified autonomous drone company in the US. 605% revenue growth. $RKLB $1.85B backlog. The only real commercial SpaceX alternative. $AAOI $200M hyperscaler transceiver order. $1B+ 2026 revenue guidance. $AMPX Batteries. 2.5x Q1 revenue growth. $PNG.V Anduril supply chain. NATO naval modernization. $OUST Digital lidar. Autonomous infrastructure layer. He would not have known a single one. That is not a criticism. That is the SIGNAL. The names nobody recognizes at the lunch table are the names still in the entry window. -BP Not financial advice. Do your own research.
$GOOG was $318 and now $400 Premarket and not done IMO
$GOOG $396-$400 target is coming
Don't forget advertising is cyclical $GOOG
$GOOG https://t.co/YHG8ceFpT6
$AMZN reported EPS: $2.78 vs $1.64 expected. AWS grew 28%, fastest in over three years.Fine. But here is what the financial media is not saying: CEO Andy Jassy said AWS revenue would have been HIGHER if capacity had kept pace with demand. Cloud backlog: $364 billion (up 49% QoQ from prior quarter). The binding constraint on Amazon’s biggest growth business is not demand. It is compute infrastructure. $200 billion in capex this year. Still demand exceeds supply. Read that again. Two hundred billion dollars in spending. Still can’t build fast enough to serve customers who are already committed to paying. This is the single most important data point that came out of earnings season. Not $META capex number. Not $GOOG 63% Cloud growth. This. When the world’s most operationally disciplined company says it is supply-constrained after spending $200B, that is a statement about where the infrastructure opportunity actually lives. The AI infrastructure build cycle is not in the stocks of the companies doing the spending. It is in the companies building what those $200B programs actually need. Power. Data centers. Optical interconnect. Compute density. The people ignoring the infrastructure layer; $IREN $NBIS $AAOI $SIVE today will be buying it at higher prices in 12 months. -BP Note: This is not financial advice.
Here’s my 15-stock AI infrastructure watchlist AI INFRASTRUCTURE CORE $MRVL → Custom AI silicon for hyperscalers like Google and AWS → Data center now the core growth engine → Strong XPU positioning in AI compute $CRDO → Critical connectivity layer inside AI clusters → Expanding into silicon photonics and optical transceivers → Direct beneficiary of hyperscaler GPU scaling $ALAB → PCIe/CXL connectivity solving AI server bottlenecks → Key enabler for GPU communication efficiency → Strong execution and AI infrastructure leverage $AAOI → Riding the 800G and 1.6T optical upgrade cycle → Vertical integration gives margin and supply edge → Hyperscaler demand remains strong $MXL → Emerging optical DSP player in AI infrastructure → Pivoted from broadband into data center growth → Early in hyperscaler qualification cycle MEGA-CAP AI COMPOUNDERS $MSFT → Enterprise AI leader via Copilot and Azure → Massive distribution advantage through software ecosystem → AI monetization still in early innings $GOOG → Search funds AI innovation and cloud expansion → Strong custom silicon and AI infrastructure strategy → Multiple growth engines beyond search $AMZN → AWS remains the AI cloud backbone → Aggressive AI infrastructure spending → Retail and ads fuel long-term AI investment SEMICONDUCTOR CYCLE PLAYS $AMD → Leading Nvidia alternative in AI compute → Enterprise traction growing with MI300 → Multiple cycle tailwinds in AI and PCs $MU → HBM memory is essential for AI GPUs → Direct play on AI compute demand → Strong AI-driven memory cycle setup $INTC → Foundry turnaround with strategic US importance → Big upside if execution improves → High risk, high reward setup $ARM → Royalty model across global chip ecosystem → Expanding into AI edge and data center → Benefits from industry-wide chip growth CONNECTIVITY, POWER & INFRA $SIMO → Storage controllers powering AI data growth → NAND cycle recovery adds tailwind → Undervalued storage infrastructure play $NOK → Optical and fiber backbone for data traffic growth → Beneficiary of telecom and hyperscaler upgrades → Defensive infrastructure exposure $BE → On-site energy for power-hungry AI data centers → Solves grid bottleneck challenges → Direct energy infrastructure AI play AI is not one stock. It’s chips, memory, optics, networking, storage, and power. Follow the infrastructure. That’s where the real compounding happens. Not financial advice.
TECH EARNINGS TODAY $MSFT — ✅ BEAT ✦ Cloud + AI demand staying strong, Azure delivered ➕ Revenue $82.9B (+18%) | EPS $4.27 vs $4.07 est  ➕ Azure +29% | Commercial RPO surged 99% to $627B  ➖ Capex acceleration commentary spooked $GOOG — ✅ MONSTER BEAT ✦ Google Cloud going parabolic — AI thesis fully intact ➕ Revenue $109.9B (+22%) | Cloud up 63% to $20.03B — crushed estimates  ➕ Operating margin expanded to 36.1% | Shares up ~4% AH  ➖ EPS of $5.11 inflated by $36.9B unrealized equity gains — clean operating picture still strong but headline overstates it  ➖ Capex guide raised again to $180–190B  $AMZN — ✅ BIG BEAT ✦ AWS back in acceleration mode — AI tailwind is real ➕ Revenue $181.5B (+17%) | EPS $2.78 vs $1.64 est — massive beat  ➕ AWS +28% YoY — fastest growth in 15 quarters | Ad revenue also accelerating  ➖ Free cash flow collapsed 95% to $1.2B on $44.2B capex — spending is enormous  $META — ✅ BEAT (w/ asterisk) ✦ Ad engine firing on all cylinders — but user growth and capex raise are the flags ➕ Revenue $56.31B (+33%) — fastest growth since 2021 | Q2 guided $58–61B  ➕ Ad impressions +19% | Avg price per ad +12% | Operating margin held at 41%  ➖ EPS $10.44 boosted by $8.03B one-time tax benefit — clean EPS closer to $7.31  ➖ DAP missed at 3.56B vs 3.62B est | QoQ user drop blamed on Iran internet disruptions  $QCOM — ✅ BEAT ✦ Diversification working — autos + data center offsetting handset weakness ➕ EPS $2.65 vs $2.55 est | Stock up ~4% AH  ➕ First data center silicon shipments to a hyperscaler — margin accretive | Auto run rate guided above $6B exiting FY2026  ➖ Chinese handset customers cutting inventory on memory pricing pressure — headwind expected to last through Q3  $VIAV — ✅ BLOWOUT ✦ Photonics + network test demand exploding — data center spending flowing through ➕ Revenue $406.8M (+42.8% YoY) | NSE segment up 54.4% | Stock up ~13% AH 🚀  ➕ Non-GAAP operating margin expanded 430 bps to 21% | Q4 guided $427–437M  ➖ Cash flow pressure noted by analysts — worth monitoring next quarter → Cloud is the clear winner across the board → AI capex still accelerating — no signs of pullback → FCF compression across hyperscalers is the emerging risk → User growth cracks at $META worth watching → $VIAV quietly one of the best prints of the night
$GOOG https://t.co/aWt0S7Bvkr
$MU $MSFT $GOOG $TSLA $META Strong setups in this market. Leaders remain leaders for a reason, and healthy pullbacks often create the best opportunities. any meaningful pullback in quality names is a buying opportunity. Not financial advice — just sharing my view.
@Remzztrades $GOOG
Market traded mostly sideways today with limited movement, but leadership stayed strong in tech. Winners on the day: $NVDA $GOOG $MU $SNDK and $INTC. Semis saw some pullback after recent overbought conditions — healthy cooling rather than damage for now. Space names look like they may be trying to carve out a bottom, worth watching if momentum builds from here.
This is the week the AI trade either gets extended or gets questioned. $GOOG, $AMZN, $META, $MSFT all report Wednesday night. $AAPL Thursday. Five companies. One week. Combined market cap somewhere north of $14 trillion. The market isn't asking whether they beat revenue estimates. It's asking one question: is cloud capex still accelerating? Because the entire bottleneck thesis rests on this. If hyperscalers pull back on data center spend on $IREN, $NBIS, $WULF, $CIFR, $APLD even slightly, even in guidance language, EVERY f….. AI infrastructure name gets re-rated downward. Watch for: > Cloud revenue growth rate vs. prior quarter > Capex guidance language "accelerating" vs. "maintaining" vs. "moderating" > Any mention of compute shortages, power constraints, or data center lead times > OpenAI partnership commentary from Microsoft post-restructuring The tone of five earnings calls this week will set the direction for AI infrastructure for the next 6 months. This is the most IMPORTANT earnings week of 2026. -BP This is not financial advice, always DYOR.
$GOOG SOTP optionality underappreciated at the lows https://t.co/7gng0urn4P
$GOOG https://t.co/8bT9nkFk9f
$GOOG AI King 👑 “We’re not just a hyperscaler reselling other people’s technology. Our differentiation comes down to the fact that we own the IP, the model and the chips are ours.” “For every dollar of revenue, we’re not shipping 80 per cent of it to either a model or chip provider, which allows us to invest more.” “I don’t think the other players are building their own models, of any quality at least.” “They have a choice of what to buy. If we were not competitive in performance, in price, in quality, they would choose not to do so.” “Those AI providers depend on private capital markets, which are reaching a saturation point. If you’re going to go public, you can’t be lossmaking forever. And if you stay private, you cannot raise venture money forever.” “Over the next year to two you will see some shakeout in the market.” Whether “particular providers are going to make it or not largely comes down to the economics.” h/t @TMTBreakout
BIG TECH EARNINGS PREVIEW The most important week on Wall Street $GOOG | Rev: $107B | EPS: $2.67 → Google Cloud spotlight — 50%+ growth expected post $32B Wiz acquisition → Key question: Do AI search features grow the pie or shrink ad clicks? → Tariff pressure on retail advertisers + $40B Anthropic capex in focus → Wall St. consensus PT: $381 $AMZN | Rev: ~$177B | EPS: $1.65 → AWS growth: consensus 26% — but AI backlog could push it higher → $200B capex plan in 2026 dwarfs current free cash flow → Retail margins under pressure from import costs → Forward AWS guidance = the only number that matters $META | Rev: $55.6B → Can massive AI ad spend actually generate operating leverage? → Reality Labs still bleeding billions quarterly → WhatsApp + Threads monetization = long-term upside optionality → Risk: Chinese advertiser pullback on trade tensions $MSFT | Rev: $81.4B → Azure growth is the make-or-break metric → Any deceleration below 37% guidance = selloff trigger ⚠️ → Copilot enterprise adoption slower than expected → Annual capex doubling to $104B compressing cash flow margins $AAPL | Rev: $109.7B → Tim Cook resignation = succession narrative dominates 👀 → Services segment carrying earnings weight → Tariff hit: ~$900M this quarter — India production shift is the hedge → All eyes on June WWDC for AI monetization + Siri overhaul
👀 next week might be the most important week of 2026 for AI infrastructure investors. $MSFT, $GOOG, $AMZN, $META all report earnings between April 29 and May 1. combined, these four companies have publicly committed to over $700 billion in AI infrastructure capex this year. the market has priced the AI trade at record highs. $NVDA is peaking. everything is working. but here’s the thing nobody is saying out loud: all of this is priced on guidance that hasn’t been confirmed yet. next week’s earnings calls are not just about revenue and EPS. they are about whether hyperscaler capex guidance holds, increases, or the tail risk moderates even slightly. a single line from a Microsoft or Amazon CFO about slowing spend would send a wave through every AI infrastructure name in the market simultaneously. the reverse is also true, if all four reaffirm or raise capex targets, the AI trade gets a structural confirmation signal that justifies the valuations. this is asymmetric event risk for the sector. the BULL case: four consecutive guidance upgrades from the largest capital allocators in history. the infrastructure trade re-rates higher. the BEAR case: one company moderates language about 2027 capex. every AI data center, every GPU manufacturer, every power provider trades down on the same sentence. pay attention to the exact language. not just the numbers, the language. the capex confirmation window opens Tuesday. position accordingly. -BP Note: This is not financial advice, always DYOR.
$AMD — Advanced Micro Devices is the #1 alternative AI GPU play and the story is just getting started. 2025 was a defining year: full-year revenue hit $34.6B — up 34% YoY — with non-GAAP net income surging 26% to $6.8B and record non-GAAP EPS of $4.17. The engine is the Data Center segment — AMD expects data center AI revenues to grow at a CAGR of 80%+ over the next 3-5 years, with the MI450 Series and Helios rack-scale solutions driving demand across hyperscalers and sovereign AI buyers. The Helios platform is the game-changer: Helios systems featuring MI450 GPUs are expected to deliver rack-scale performance leadership beginning Q3 2026, followed by the MI500 Series in 2027. Customer wins are tier-1 — AMD’s OpenAI partnership has potential to generate $100B+ in revenue over coming years, while Oracle plans to deploy tens of thousands of AMD GPUs across OCI through 2027 and beyond. Risks are real: China export controls gutted $300M+ in revenue, and the gap before MI450 ships leaves AMD leaning on MI350 hardware mid-year. Next earnings drop May 5 — a critical catalyst. $AMD $NVDA $GOOG $AMZN $MU
5 AI Stocks. 1 Clear Winner for the Long Term. $CRDO | $MRVL | $MU | $GFS | $GOOG Here’s how they stack up 👇 $CRDO — Credo Technology The most asymmetric bet in AI infrastructure. → 201% YoY revenue growth in Q3 → ~70% gross margins, zero debt → AECs powering 5 of the world’s biggest hyperscalers → New acquisitions expanding into optical interconnects → TAM expanding to $10B+ as AI scale-out accelerates Still early innings. Institutions are just starting to notice. $MRVL — Marvell Technology The custom silicon kingmaker. → Data center = 74% of revenue, up 46% YoY → Custom ASIC revenue DOUBLED in FY2026 → FY2027 revenue guide raised to $11B → 1.6T interconnect ramp expected to be rapid → 51 analyst Buy ratings. Avg PT: ~$125 $MU — Micron Technology The HBM pure play. → Q1 FY2026: Revenue +57% YoY, EPS +167% YoY → HBM supply fully sold out through 2026 → Negotiating 2027 contracts NOW → Massive $200B global capacity buildout underway → Forward P/E: ~7x — dirt cheap for an AI compounder Cyclical risk is real. But this cycle has structural legs. $GFS — GlobalFoundries The specialty foundry play. → Focused on differentiated chips: auto, aerospace, IoT, 5G → EPS expected ~$1.89 in 2026 → Not riding the leading-edge wave — but defensive moat → Less volatility, less upside Solid for diversification. Not the alpha generator here. $GOOG — Alphabet The most underrated stock in the market right now. Most people see it as a search + cloud play. They’re missing the real story. 👇 The core business is firing: → Q4 2025 Revenue: $113.8B (+18% YoY) → Google Cloud: +48% YoY — $70B+ annualized run rate → 70%+ of Cloud customers now using AI tools → YouTube crossed $60B in annual revenue → $175–185B CapEx planned for 2026 → Gemini embedded across Search, Cloud & Workspace That’s what everyone knows. Here’s what they DON’T. The Hidden $234B Bombshell Alphabet is quietly sitting on TWO of the biggest IPOs of 2026: SpaceX: → Google invested $900M in SpaceX in 2015 → Alaska filing just confirmed: 6.11% stake as of end-2025 → SpaceX targeting $2T valuation IPO as early as June 2026 → Google’s stake = $100–122B at IPO price → A 100x+ return sitting silently on the balance sheet Anthropic: → Google holds an estimated ~14% stake in Anthropic → Anthropic just hit $30B annualized revenue — tripled from $9B last year → Latest round at $380B valuation (with $800B offers on the table) → Google’s Anthropic stake = ~$50B+ and climbing → Both IPOs expected Q4 2026 Combined hidden value: ~$234B The market hasn’t priced this in yet. 🤯 The rerating catalyst nobody’s talking about: Right now these stakes sit as opaque private holdings. Hard to model. Easy to ignore. The moment SpaceX lists in June → positions become liquid + mark-to-market. Institutions will have to reprice $GOOG overnight. You don’t need Alphabet to sell a single share. The IPO itself IS the catalyst. Not financial advice. DYOR.
The autonomous defense platform problem isn't compute. It isn't communication. It isn't even power, though $AMPX is solving that too. It's PERCEPTION. You cannot put an autonomous ground vehicle, port system, or maritime monitoring platform into operation without lidar that can tell the difference between a threat and a water buoy at 200 meters, in rain, in the dark. $OUST build solid-state digital lidar sensors. No moving parts. CMOS chip architecture. The same manufacturing process that drives smartphone camera cost curves down. Already qualified on autonomous vehicle stacks, defense perimeter systems, and port automation platforms. Supply chain: → silicon photonics wafer → Ouster digital sensor → perception module → autonomous defense/logistics platform → real-world operation The companies that qualified Ouster sensors TWO YEARS AGO cannot switch without restarting that process now, in 2026, when procurement urgency is highest. Two hard numbers: ~$1.5B market cap. $50 analyst high target (+86% implied upside). The obvious trade: the autonomous platform companies $TSLA $GOOG $ONDS $MBLY $AUR. Correct. Already crowded. The real trade: the sensor company at $1.5B that those platforms physically cannot function without. -BP Not financial advice. DYOR. Save this.
$GOOG if you missed earlier
The only thing $GOOG needs to fear and $META stealing search share.
AI Chip Race Heating Up $GOOG in talks with $MRVL to build custom AI inference chips. $MRVL +9% overnight, bucking market weakness. AI leaders are moving beyond software — owning hardware = better margins + scale advantage
HOW I WILL PLAY THE NEXT MONTHS AND WHAT I EXPECT: I want to touch on 5 important things: 1. First, I’m sad to see the lunch of $ASTS fail. I sold a while ago. “$Execution delays is a risks. Sold and took profit recently.” Still saddens me to see. 2. I see a lot of new concerns on US/Iran. Here’s my take and how I will play it: Overall I believe we have see the worst. I could be wrong. But usually when ceasefire and ‘talks’ have been somehow ongoing it’s very rare a full blown war will continue. I expect some volatility short-term. I’ll be DCA’en through if it plays out. Long-term I have NO concerns. US are on their way to a ‘goldilocks’ era. So many investments are being made INTO US. I expect inflation to rise short-term. Fall afterwards towards the goldilock-era for US where AI infrastructure will play out and dominate. Lastly. I see some concerns about ‘oh, but $SPY $SPX $QQQ are all back to ATH and topping. Yes. But MAG7 is not topping. $NVDA $GOOG $AMZN are close to touching Octobers high. But recently. $MSFT $AAPL $TSLA are far from it. Meaning the ‘top’ is not driven by small cap or MAG7. But the middle-layer of $SPYx / SP500. I’m not concerned. But expect more of a rotation to continue into risk-on - when US/Iran clears. 3. A couple of hours ago I released a FREE NEW extensive deep dive on $OUST. You should go read it. 4. I’m considering creating a FREE group-chat here on X. A community. What I expect of the group: This is not a buy/sell signal group. But a group to connect with like-minded. Analyzing the market, sharing ideas, research, insights, learnings and Go deep on finding gems together. There’s limited spots. If you want to join. Comment: “YES.” And just to be clear: I dont have a course or offer no paid services. 5. Based on 2) - I’ll sit tight in my long-term high conviction plays with ease and peace. Add on dips. Pure DCA. Meanwhile I’ll soon open up my short-term account again and begin some short-term swing trades in the timeframe of less than < 6 months. -BP. Please note: this is not financial advice.
SpaceX IPO – Simple Roadmap & Trade Setup Direct Beneficiaries (sympathy + sector momentum): $RKLB → launch + defense contracts $ASTS → satellite comms (high retail interest) $PL → geospatial data + analytics $LUNR → lunar + NASA exposure $RDW → space infrastructure + manufacturing These names move before and after IPO on narrative + capital rotation. Indirect / Hidden Leverage Plays: $GOOG → early investment could translate into $100B–$140B value unlock if IPO valuation expands $DXYZ → holds pre-IPO private shares (including SpaceX) → fastest public proxy for IPO speculation Small-Cap High Beta Plays (Momentum traders): $SATL $SIDU $SPIR $MNTS These tend to lag → then explode when retail chases the theme. This isn’t just an IPO — it’s a sector-wide catalyst. The real money is made by positioning before the listing, not chasing after. Space is becoming the next battleground after AI, nuclear, and quantum — and if this IPO hits, expect aggressive rotation + multi-week momentum across the entire space ecosystem.
$GOOG isn’t just the Google you know — it’s a stealth holding company sitting on $195–220B+ in two of the most anticipated IPOs in market history, while trading at value-stock multiples on its core business. As SpaceX and Anthropic approach their public debuts, every re-rating in their private valuations flows directly into Alphabet’s balance sheet. You don’t need to win the IPO lottery — just own the shareholder who already did. → SpaceX IPO at $1.75T = $110B+ gain crystallized on books → Anthropic IPO at $600–800B = $85–112B stake value → TPU/GCP revenue compound as Anthropic scales to $150B ARR by 2029 → Gemini + DeepMind = internal AI moat independent of either IPO → Waymo monetization still largely unpriced → Trading at only 27x forward P/E — cheap vs the asset base Not financial advice. DYOR.
Gemini integrates well with the committees existing tools $GOOG
$MU $GOOG 1/21/28 call adds working. https://t.co/PXfM17kP3k
Most investors are always chasing the last wave. The AI infrastructure cycle is playing out in layers — and each one is bigger than the last. Here’s the full roadmap: Wave 1: Semiconductors ✅ (Priced In) $NVDA. $AMD. $AVGO. The GPU arms race. Everyone knows this trade. Raw compute was the foundation. Most of the upside? Already captured. Wave 2: Memory & Storage ✅ (Confirming) More data. More inference. More throughput. Flash, DRAM, HBM all followed. $SNDK ’s recent move is the latest confirmation. The storage bottleneck is real — and the market is finally catching up. Wave 3: Photonics & Optical Networking 👀 (In Motion NOW) This is what most retail investors are still sleeping on. You cannot move AI workloads at scale with copper wire. Data centers need ultra-fast, low-latency interconnects — and photonics is the only answer. Silicon photonics is actively replacing copper-based communication inside and between hyperscaler campuses. The plays institutions are quietly accumulating: $AAOI — pure-play optical components, deep data center exposure $COHR — vertically integrated photonics at scale $LITE — transceivers powering the hyperscaler build-out $POET — integrated optical engines, early-stage, asymmetric upside $CIEN — backbone optical networking infrastructure $FN — precision optical manufacturing, best-in-class margins This wave is not coming. It is here. Wave 4: Power & Energy Infrastructure (Early Stage) AI doesn’t run on ambition. It runs on electricity. Data centers are projected to consume 8–10% of U.S. power by 2030. That is not a tailwind. That is a structural demand shock the grid is not prepared for. Nuclear is the only baseload solution that can sit next to a hyperscaler campus and deliver consistent, carbon-light power at scale. The plays: $CEG & $VST — utilities with nuclear-powered AI offtake contracts $CCJ — uranium supply, the fuel behind the revival $OKLO & $SMR — next-gen small modular reactors $VRT — liquid cooling and power management inside data centers The capex commitments from $MSFT, $AMZN , and $GOOG are already locked in. The power infrastructure just needs to catch up. This wave is early. That is the opportunity. Wave 5: Robotics 🤖 (Loading…) Once AI is trained, powered, and connected — it needs a body. Physical deployment into warehouses, factories, logistics, and healthcare. This is the final and potentially the largest layer of the entire cycle. Hardware-software integration is still 12–24 months from full ignition. But the smart money is already laying the groundwork quietly. The pattern is simple: Each layer enables the one after it. → Semis built the brain → Memory gave it recall → Photonics gave it nerves → Power gives it fuel → Robotics gives it hands The investors winning this decade are not chasing yesterday’s leader. They are identifying tomorrow’s bottleneck — and positioning before the crowd arrives. The question is not which wave already ran. The question is: which wave are YOU in front of? $AAOI $COHR $LITE $POET $CIEN $FN $CEG $VST $OKLO $SMR $CCJ $VRT DOYR , bookmark this and retweet for others.
Wouldn't waste my time using model cos that have cash flow problems. Anthro and OAI. Fool me once. $GOOG
Overnight markets flashing risk 👇 U.S. futures slipping while oil surges on fresh Middle East tensions and a potential Strait of Hormuz blockade. Energy ripping → $OXY +8% → $XOM & $CVX +4% Tech under pressure → $MU -4% → $AVGO & $TSM -3% → $NVDA -2%+ → $TSLA, $META, $GOOG also lower Same playbook: Geopolitical risk → Oil spikes → Energy rallies → Tech sells Headline-driven market — expect volatility and fast rotations.
Wall Street talks about the hyperscalers: $AMZN, $GOOG, $META, $MSFT. That is where the headlines are. But the money flows through the supply chain. Capex is tracking above $1 trillion this year. That is six times the level of 2022 Here is the full stack, sector by sector, of who actually gets paid: Power Infrastructure: $IREN, $CIFR, $NBIS, $WULF The compute layer requires power first. These are the companies building and owning the megawatt-scale facilities that hyperscalers cannot build fast enough themselves. Optical Networking: $AAOI, $COHR, $LITE, $POET GPU clusters are useless without the interconnects that move data between them at 800G and 1.6T speeds. This sector is capacity-constrained and just had its export inputs tightened by China this week. Space & Infrastructure: $RKLB, $ASTS, $PL, $SATL, $FLY, $ONDS, $KTOS Golden Dome. Autonomous systems. Satellite constellations. The government is funding the next generation of distributed compute and surveillance infrastructure from orbit. Critical Materials: $AXTI, $ALMU The raw substrate layer that the entire photonics stack sits on. Severely undersupplied. Almost zero retail coverage. Launch & Deployment: $RKLB, $ASTS Getting infrastructure into orbit requires reliable, affordable launch. One company owns this market. The public comp is scaling fast. Every sector on this list has either hyperscaler contract backing, government funding, or a physical supply constraint that makes demand inelastic. Save this for later. -BP Please note this is not financial advice.
"When the cloud became viable, people thought on-premise IT was dead overnight and every legacy company would collapse. Instead, Microsoft and Amazon just made a killing selling the transition" $MSFT $GOOG $AMZN
Know Your Charts, Know Your Edge. Most traders lose because they chase everything. The edge? Master a few names cold. $MSFT , $GOOG , $META , $MU , $AMZN and $SPY These aren’t random picks — they’re the most liquid, most-watched mega-caps on the market. High volume. Clean technicals. Levels that actually hold. When you know where $MU bounces, where $GOOG finds support, where $MSFT stalls before a breakout — you stop guessing and start executing. Key levels to lock in: → 200 DMA → Major horizontal support → Prior highs turned lows → Fibonacci retracement zones The setup doesn’t change. The stock comes to you. Depth over breadth. Trade fewer names. Know them cold. That’s where consistency lives. Not financial advice. DYOR.
Overnight markets are ripping 🔥 Ceasefire news easing geopolitical tensions has flipped sentiment fast — risk is back ON. 🚀 Tech leading: $TSLA, $AMD, $META +4% $NVDA, $GOOG +3% ₿ Bitcoin back above $72K — crypto names flying: $HOOD +7%, $MSTR / $COIN +5% 💾 Memory stocks strong: $MU, $SNDK +7% 🌏 Asia reacting big: $Nikkei +4%, $KOSPI +5% Momentum is building… this could turn into a massive global risk-on move.
Why $GOOG seemed late to AI
"By actively arming OpenAl's most dangerous competitor in the enterprise space, Google forces OpenAl to fight a grueling war on two fronts. This drains OpenAl's resources and protects Google's core, highly lucrative consumer search monopoly." $GOOG
$GOOG https://t.co/t5lLWLlpGo
Wow $META fail $GOOG invincible
$GOOG is 🐐
$GOOG https://t.co/kPxCO0P1wF
I would highlight $GOOG employee base is basically the same since ChatGPT's launch even though their revenue increased by ~$120 Billion. However, capex almost became 4x during this time. It's likely a good glimpse of the changing landscape of our future" - @borrowed_ideas
$GOOG won in AI
Smart $GOOG trying to reduce switching costs from ChatGPT.
Meanwhile if $GOOG search revs decline investors view it as under threat. And if Goog puts ads in AI results the user experience at OAI is relatively better (without them). Sticky wicket as they say. Private investors tolerate more risk than public. Now in size.
