Canada Always Chickens Out….Why You Need Gold and Crypto…IBM Deploys First Quantum Computer Outside the U.S. Why It Matters…..Google Convinces OpenAI to Use TPU Chips in Win Against Nvidia…..New Molecule Could Shrink Data Centers to Postage Stamps
Looks like Canada chickened out this time 👀
— #Markets & Mayhem (#@Mayhem4Markets)
11:43 AM • Jun 30, 2025
Markets are in a grind higher mode for risk sentiment. In our view, fundamentals have become incrementally more positive - progress on trade talks, Fed comments in the dovish direction, geopolitics no longer a driver with oil below $65 and supportive seasonals. However, positioning is less supportive than before with some long positions being built. On balance, we see the environment as constructive for risky assets. But with positioning moving to the long side, we do not see a sharp rally but a slow grind higher in risky assets.
The U.S. equity market has surged to record highs, driven by AI-led megacap momentum, passive flow mechanics, and a sentiment shift from fear to FOMO. However, this strength masks growing fragility beneath the surface. Labour market data is flashing early warning signs: while initial claims remain low, continuing claims have broken above a two-year ceiling, suggesting rising re-employment friction.
I agree with Jefferies here, expect a slow grind higher but watch the data for signs of weakness. The wild card there though is the Fed, if Trump gets them to lower rates to 1% then we could see a massive rally.
What’s going on in the Stablecoin, Tokenization, Crypto world is huge. Two things happened yesterday…..
BREAKING: Tom Lee has been appointed chairman on the board of directors for Bitmine, a Bitcoin miner.
Today they announced a $250M private placement to implement buying Ethereum for their $ETH treasury.
$BMNR, the public stock for Bitmine, is up 48% in the pre-markets.
Tom
— #amit (#@amitisinvesting)
12:29 PM • Jun 30, 2025
and…….
Robinhood's shifting retail investing
$HOOD just announced:
- The first-ever private stock tokens in the EU, starting with SpaceX & OpenAI
- $ETH & $SOL staking
- Pre-IPO stock trading for private companies
- Own chain (where you basically become a bank)
- Tokenized assets— #Anastasiia Bobeshko🇺🇦 (#@anabobeshko)
6:11 PM • Jun 30, 2025
🚨🇺🇸 ROBINHOOD BOSS SAYS OPENAI STOCK JUST WENT FULL CRYPTO
Robinhood pulled off a private trade of OpenAI shares using crypto tokens on Arbitrum, moving exactly 2,304.84 tokens that anyone can now see on the blockchain.
This isn’t some meme coin stunt - it’s real equity
— #Mario Nawfal (#@MarioNawfal)
10:00 PM • Jun 30, 2025
Not sure yet how this all plays out. Could crytpo treasury companies be the next dot com bust? Sure.
Historically, shell companies would publish a press release stating their entry into the newest hottest space to drum up excitement in their shares. The crypto treasury model has the tangible allure of real money being invested, but the insiders are getting shares at a fraction of the price the public is paying. The offerings are disclosed and filed with the SEC, but the public does not care (or care to look). The public demand for the small float is insatiable for a few days, then those insider shares become effective to sell and the stock melts. P.T. Barnum would be having a field day in this environment
I do think you will eventually see everything tokenized.
Wow…….
TRUMP JUST NOW:
WITHOUT SUBSIDIES FROM THE US GOVERNMENT, ELON WOULD CLOSE UP SHOP & HEAD BACK TO SOUTH AFRICA
OH BOY
— #amit (#@amitisinvesting)
4:57 AM • Jul 1, 2025
JPMORGAN REITERATES UNDERWEIGHT RATING ON $TSLA, PT $115
Analyst comments: "Based on our checks, the softer demand for Tesla vehicles evident in 1Q results appears to have continued into 2Q, such that we now expect the rate of year-over-year decline in deliveries to accelerate
— #Wall St Engine (#@wallstengine)
6:27 AM • Jul 1, 2025
🔥 HEAT Formula Playbook: Themes
Which is why you need Gold and Crypto in your portfolio….
DEFENSIVE ROTATION BENEATH THE SURFACE: Utilities and gold/silver futures are outperforming—both up ~25% YTD—despite the equity rally. This rotation into defensive and haven assets suggests that investors are hedging against macro risk, even as indices rise. It could; be argues that crypto’s rebound (Bitcoin >$100K, Coinbase +130%) reflects growing risk taking /speculative appetite, but this could also a search for alternatives amid fiscal and currency concerns.
🔥 HEAT Formula Playbook: Themes
Quantum computing has the potential to be more powerful than AI, but nobody seems to have any idea when it will be available for commercial use. IBM is one of our core holdings because I believe that they have the potential to be one of the leaders, they just need to execute. So this article caught my eye…….
I had GPT take a deep dive…..
1. What the News Means 🌍
IBM just installed its Quantum System Two in Japan, powered by the new Heron processor, marking a major milestone in global quantum expansion .
It’s the first non-U.S. deployment, signaling IBM’s intent to lead globally.
The machine pairs classical supercomputer Fugaku with quantum processors, enabling hybrid computing for optimization and chemistry workloads barrons.com.
2. Expert View: Proximity to Workable Quantum
IBM Management continues to target a fault-tolerant quantum computer by 2029—a system that can correct its own errors and provide reliable results
Analyst forecasts suggest error rates and circuit depth are improving, making useful quantum computing feasible within the next 2–5 years, with broader utility models following by 2029–2032 .
My view: Hybrid quantum-classical systems (like the IBM-Fugaku model) will see commercial pilot use by 2027–2029, with fully fault-tolerant machines usable at scale around 2030–2033.
3. Market-Sized Winners – Ranked 1–10
Company | Reason for Win | Score |
|---|---|---|
IBM (IBM) | Leader in quantum hardware, global deployments, hybrid systems, roadmap discipline. | 9 |
Google (GOOGL) | Pushed quantum advantage in 2019; expanding hardware and algorithms R&D. | 8 |
Microsoft (MSFT) | Developing modular, error-correcting qubit systems (Topological), integrated with Azure Quantum. | 8 |
IonQ (IONQ) | Pure-play trapped-ion qubit specialist; accessible via cloud and customer focus. | 7.5 |
Rigetti (RGTI) | Developing hybrid quantum-classical platform with superconducting qubits. | 7 |
Honeywell / Quantinuum | Strong trapped-ion systems with growing enterprise partnerships. | 7 |
4. Potential Losers – Quantum Imitators
Classical HPC vendors who lag in quantum integration risk reduced relevance.
Crypto/mining hardware firms may see diminished demand as quantum reshapes certain computation markets.
Early-stage quantum startups lacking scale or IP risk being eclipsed by hardware leaders like IBM, Google, and IonQ.
5. Strategic Takeaways
IBM’s hardware momentum solidifies its lead and suggests it’s the temporal frontrunner in quantum commercialization.
The 2029 roadmap is credible—meaning the firm could reach breakthrough capability within the next 4–5 years.
Hybrid computing pilots from 2027–2029 offer an actionable window for early use cases in optimization and pharma.
Diversified exposure across market leaders is key—IBM and Microsoft provide hardware/platform breadth, IonQ brings focused upsides on qubit gains.
🔍 Bottom Line
IBM’s global deployment is far more than PR—it’s a tangible step toward commercial quantum utility. We’re now in phase two: from theoretical to applied hybrid processing within ~3–5 years. Full-scale, fault-tolerant quantum computing remains a 10-year frontier.
Buy into licensed hardware bets: IBM, IonQ, Microsoft—these should lead quantum-led innovation portfolios.
Avoid high-risk clones and irrelevant tech players that fail to align infrastructure with quantum-era computing needs.
🔥 HEAT Formula Playbook: Themes
I think NVDA is the clear winner when it comes to AI, so any article that potentially dents their virtual monopoly is going to catch my eye……
OPENAI TAPS GOOGLE $GOOGL TPUs FOR CHATGPT, NOW USING GOOGLE’S CHIPS INSTEAD OF NVIDIA’S $NVDA!
MASSIVELY BULLISH FOR THE GOOGS!
— #Dividend Dude (#@DividendDude_X)
8:20 PM • Jun 27, 2025
I had GPT break this down and see what implications there were, if any……
🔍 What’s Changed?
OpenAI, long reliant on NVIDIA GPUs, has begun renting Google’s TPUs via Google Cloud to run ChatGPT and other inference workloads—marking the first significant use of non-NVIDIA AI chips by OpenAI .
Purpose: Lower costs and diversify away from NVIDIA & Microsoft data center dependence .
Limitations: OpenAI isn’t using Google’s top-tier TPUs (reserved in‑house), but early model TPU v5p/v6/v7 units are in use .
✅ Impact on the Key Players
1. Google (GOOGL) – Positive
Strategic Cloud Move: Validates Google Cloud’s TPU positioning, boosts credibility with marquee customers like OpenAI and Apple .
Competitive Edge: Directly challenges NVIDIA’s GPU dominance; Silicon differentiation in high-value AI workloads.
Financial Upside: Increased TPU rental income and share of AI‑cloud spend.
Score: 9/10
2. NVIDIA (NVDA) – Slight Pressure, but Not a Disruption
Market Share Shift: Losing some inference volume, but OpenAI still trains with NVIDIA, and Google isn’t offering its best silicon yet.
Pricing Power: NVIDIA’s GPUs still dominate for performance flexibility. TPUs’ narrow use cases mean share losses may be limited short-term.
Long-Term Risk: If TPU performance improves and Google opens more capacities, it could chip away at mid- to long-term dominance.
Score: 7/10
⚖️ Verdict: Net Change?
This is a strategic win for Google, and a mildly negative signal for NVIDIA, but it doesn’t turn the AI-chip market upside down.
Google: Moves from internal-only to external cloud differentiation, expanding their commercial reach.
NVIDIA: Remains dominant—TPUs lack the flexibility and ecosystem of CUDA GPUs today, keeping NVDA in control of high-end workloads.
💡 Expert Insight
🟢 Google Cloud gets a shot in the arm—TPUs gain real-world validation from OpenAI, opening the door to further enterprise adoption.
⚠️ NVIDIA should not be counted out. Their GPU dominance persists, with CUDA lock-in and unmatched performance versatility.
🚨 Watch TPUs' trajectory closely: Performance improvements in TPU v7 or broader access could signal more serious competition for NVIDIA in inference workloads.
🏁 Market strategy: Still a Buy on NVIDIA & Google—they are key infrastructure players, but expect Google to gradually chip away if TPU continues scaling.
📈 Long-Term View
Short-Term (6–12 months): NVIDIA remains dominant; Google gets strong cloud platform recognition.
Medium-Term (1–3 years): Expect competitive tension as Nvidia defends markets, Google expands TPU reach.
Long-Term (3–5 years): Dual-supplier environment could emerge. Watch fragmentation, pricing pressure, and ecosystem lock-in.
🔢 Ratings
Company | Short-Term | Medium-Term | Long-Term |
|---|---|---|---|
8/10 | 9/10 | 9/10 | |
NVIDIA | 9/10 | 8/10 | 8/10 |
Bottom Line: This TPU news is a positive for Google, giving them AI-hardware credibility and revenue upside. It’s a slight headwind for NVIDIA, but not a game-changer—yet. Continued TPU performance gains and broader access could shift that narrative. For now, both remain essential bets in the AI infrastructure ecosystem.
🔥 HEAT Formula Playbook: Themes
This tweet caught my eye. All of the analysis we are doing in AI assumes the starting point is today’s technology, but suppose we make a breakthrough like this? In this case maybe we don’t need massive data centers…..
🚨🇦🇺 NEW MOLECULE COULD SHRINK DATA CENTERS TO POSTAGE STAMPS
Move over SSDs - scientists have cooked up a single-molecule magnet that might someday store 3 terabytes of data per square centimeter, cramming 40,000 “Dark Side of the Moon” CDs or half a million TikToks into a
— #Mario Nawfal (#@MarioNawfal)
9:20 PM • Jun 28, 2025
I had GPT look for public companies that could benefit from this technology…
🧬 TL;DR: “1-Dy” Could Be the Moore’s Law Moment for Storage
Scientists have developed a single-molecule magnet (SMM) using a new dysprosium-based compound called 1-Dy, capable of holding magnetic memory up to –173°C, a significant leap above prior SMMs that failed at –193°C.
Why it matters:
🔹 3 terabytes per square centimeter = 100× current SSD density
🔹 Could shrink AI data centers to the size of a closet
🔹 Massive implications for edge AI, quantum computing, biotech, and defense
📦 What’s the Core Innovation?
SMMs (Single-Molecule Magnets) store data magnetically at the molecular level—like a magnetic hard drive, but atom-scale.
The 1-Dy molecule resists “bit flipping”, meaning it can hold its state (0 or 1) stably at relatively high cryogenic temperatures.
Up to –173°C = progress. While still cryogenic, this is much more manageable than –193°C+ needed before.
🧠 What Could This Enable?
Stamp-sized drives with 100× capacity of today’s SSDs
3 TB per cm² is orders of magnitude denser than NAND flash.
Massive implications for AI training, which is I/O bound as much as compute-bound.
Cryogenic compute/storage convergence
Quantum computing already uses cryo environments; this aligns perfectly.
Hybrid quantum + molecular storage architectures may emerge.
Radically decentralized AI
Imagine LLMs like GPT-4o running entirely on edge devices with molecule-scale storage.
💼 Are There Investable Public Players?
No one owns this molecule yet—this is lab-stage tech, not commercially viable at scale. But here’s who could benefit or dominate if it matures over 5–10 years:
🏆 Potential Winners – Ranked (1–10)
Company | Why It Matters | Score |
|---|---|---|
IBM (IBM) | Deep in cryogenic research, quantum-classical hybrid compute; strong material science labs | 9 |
Western Digital (WDC) | Top storage player; already exploring HAMR and molecular-scale innovations | 8 |
Seagate (STX) | Has funded molecular-scale storage R&D, leader in ultra-dense magnetic storage | 8 |
Micron (MU) | May integrate this tech downstream if commercialized via new storage class memory | 7 |
Applied Materials (AMAT) | Would likely supply fabrication tools if molecule-based memory becomes manufacturable | 7 |
ASML (ASML) | If lithography adapts to molecular storage scale, ASML stands to benefit | 7 |
Intel (INTC) | Historically backed novel storage via Optane and quantum R&D; possible resurgence play | 6.5 |
Google (GOOGL) / Amazon (AMZN) | Would be massive end users for AI training; likely to acquire or partner early | 6 |
Oxford Instruments (UK) | Cryogenics & quantum lab tools; small-cap pick-and-shovel supplier | 6 |
📉 Possible Losers
Company | Why at Risk | Score |
|---|---|---|
Legacy NAND SSD vendors | May lose pricing power as new density frontier opens | 🟥 Risk |
Commodity DRAM suppliers | If molecule-scale memory cannibalizes RAM in AI workloads | 🟥 Risk |
Large Data Center REITs | If data centers shrink dramatically, physical footprint demand may soften | 🟥 Watch |
🧭 Strategic View
This is a "file away and track" moonshot, but the implications are real if progress continues:
📈 5–10 year horizon — commercial viability depends on improving the operating temperature to room temp or ~0°C.
🧬 Bet on the picks and shovels — IBM, Seagate, AMAT, ASML are best positioned to either develop, adopt, or supply the ecosystem.
🛠️ Buy exposure to quantum + storage convergence, especially IBM and cryogenic-enabling firms.
Final Word:
This discovery is not priced into the market. If single-molecule memory hits even 20–30% of its potential, the AI infrastructure stack will be rebuilt from the bottom up. Think of this as the NAND flash of the post-silicon era.
Before You Go Some Ways I Can Help
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Tuttle Wealth Management: Your Wealth Unschackled
Advanced HEAT Insights: Matt’s Inner Circle, Your Financial Edge
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