Welcome to Nofinity

• On May 27, 2026, the head of the NYSE operator called Hyperliquid bigger than NASDAQ – a decentralized perpetual futures exchange on its own Layer 1 blockchain.
• In 18 months, it grew from an unknown crypto exchange to a top-10 asset with an all-time high of ~$74 (+199% YTD).

• Spot ETFs: 21Shares (THYP) and Bitwise (BHYP) pulled in over $136M in 13 trading sessions – 3.5x faster than Solana ETFs (on a market cap-adjusted basis).
• Goldman Sachs: Liquidated XRP, Solana, and reduced Ethereum positions, buying a NASDAQ-listed treasury vehicle (small position but signal).
• A16Z (unconfirmed): Accumulated 3.9M Hype (~$192M) since mid-April, partly staking – indicating long-term hold.
• Hyperliquid Strategies (PRR): A publicly traded company (former biotech) holding 20M Hype; board includes Bob Diamond (ex-CEO of Barclays). Joining Russell 3000 on June 26 – forced buying from passive funds.

• 97-99% of trading fees feed an automated fund that continuously buys Hype, removing ~14% of circulating supply annually.
• Over $1.3B in cumulative buybacks.
• Issue: Buybacks are volume-dependent – Q3 2025: $316.8M, Q4: $255M, Q1 2026: $192.3M (39% decline while price rose).

• On June 6, ~9.92M Hype ($714M) unlock for insiders – equal to >10 months of buyback capacity.
• The buyback engine cannot mechanically absorb this supply, risking price drop.

• Oracle Failure: On May 28, the synthetic SpaceX perpetual crashed 45% due to a faulty oracle feed. Such failures could escalate as HIP3 markets (40% of volume) grow.
• Governance: Only 27-30 validators, closed-source core software – even Grayscale flagged auditability risks in a bullish report.
• Short Squeeze: 56% of open interest was short; the rally was partly fueled by forced liquidations, not genuine conviction.

• Hyperliquid is a real cash machine, but its buyback engine only works in a bull market. The upcoming unlock and reflexive risks (oracle, governance) could severely impact price.
• Question: Are institutions smart money or are they providing exit liquidity for insiders before the supply cliff?

1. Monitor quarterly buyback figures – if they keep falling, the flywheel reverses.
2. Track the $714M unlock on June 6.
3. Watch PRR's premium to its underlying Hype – when it compresses, leverage works downward.
4. RSI is ~77 – overbought territory.
5. Self-custody reduces custodial risk compared to ETF wrappers.

• The speaker analyzes historical Bitcoin price patterns in so-called "midterm years" (e.g., 2014, 2018, 2022) and compares them to the current situation in 2026.
• July has often been a relief month after a sharp drop in June. Statistically, July in midterm cycles has frequently shown positive returns (2026: +10.5%, 2022: +20%, 2018: +38%).

• The overlay of year-to-date returns for 2026 and 2018 shows striking similarities.
• In 2018, the July relief was followed by a renewed weakness as early as August. In 2022, the next downturn only began in mid-August.
• Reaching the bear market resistance band or the 200-day moving average is uncertain – neither was reached after the June low in 2022, while 2018 did reach the resistance band.

• A key indicator is the rise in the 10-year US bond yield – in previous cycles (2023, 2022, 2018), rising yields coincided with falling Bitcoin prices.
• The yield is showing an upward trend again, which could point to a correction in the latter part of Q3.

• Historically, August and September have often been negative in midterm years (2022: -15% in August, 2018: negative in August/September).
• The likelihood of a renewed weakness phase within the next two to three weeks is high.
• The speaker recommends not trying to time the exact bottom, but instead using a dollar-cost averaging (DCA) strategy.
• A cyclical bottom is expected around November 2026.

• Reminder of the ITC conference (November 20–22 in Miami) with a price increase coming soon.
• Call to subscribe to the channel.

Markets are weak, AI is getting hit, but the future lies in physical assets and capital efficiency. This video analyzes who is winning the CAPEX race for artificial general intelligence (AGI) – and it turns out Tesla and SpaceX, despite their relatively low spending, could come out ahead.

Why CAPEX Matters Now

• Compute scale requires massive infrastructure: power, cooling, data centers, solar, batteries.
• Physical footprint is essential to scale robots, cyber cabs, and other technologies.
• Vertical integration is key: companies like Tesla control the entire supply chain – "from sand to satellites." This gives them a massive advantage.

The Numbers Compared

• Hyperscalers (Meta, Microsoft, Amazon, Google) will spend $750 billion by 2026 on cloud server farms – but not on humanoid robots or cyber cabs.
• Tesla spends only $25 billion – that's just 4% of hyperscaler spending. But this money goes into concrete, physical AGI projects.

Tesla's and SpaceX's Physical Projects (a selection)

• Tesla Cyber Cab Factory: Produces up to 120 units per day.
• Optimus Factory (Fremont): Builds 1 million humanoid robots per year.
• Austin Terrafab: Capacity for 10 million Optimus robots annually.
• Tesla Advanced AI Chip Fab (Austin): In-house chip production before the massive Terrafab facility goes online.
• Tesla Cortex Clusters: Supercomputers with hundreds of thousands of AI training chips for autonomous driving and Optimus.
• 4680 Battery Expansion (Nevada): High-volume cell production for Cyber Cabs, Semis, Cyber Trucks.
• Tesla Mega Factory (China & Houston): Gigantic energy storage systems.
• 100 GW Solar Factory (Texas): Fully vertically integrated solar cell production.
• Lithium Refinery (Corpus Christi): Largest lithium refinery in North America ensures battery-grade quality.
• SpaceX Starbase: Building multiple Starships simultaneously – aiming for multiple launches per day.
• Gigafactory for Space: 11 million square feet for solar cells, satellites, and orbital data centers.

Why Tesla's Approach is Superior

• Efficiency: Elon Musk builds a data center in 122 days – others take 2-3 years.
• Return on Invest (ROI): Experienced investor Ron Baron notes Tesla generates $15 billion profit on a $7 billion Gigafactory investment – a return of over 200% per year.
• Market Potential: Musk estimates the Optimus market at $30 trillion, Robo-Taxis at $10 trillion, and Terrafab at $10 trillion. A potential $100 trillion valuation for the Tesla-SpaceX combination.

The Decisive Difference

While hyperscalers pour money into cloud infrastructure and software, Tesla builds physical AGI assets with direct, massive ROI. The future belongs to physical intelligence: robots that work 20 hours a day, never get sick, and reduce human labor costs to $1 per hour. The data flywheel effect means all robots instantly learn any new skill – unprecedented progress.

Conclusion: Absolute CAPEX figures are irrelevant – what matters is the return on invested capital. Tesla and SpaceX are building the physical foundation for the AGI future, offering asymmetric profit potential. The world will change radically by 2030 – be prepared.

Mojmir Hlinka and Mario Lochner analyze the recent slump in AI and semiconductor stocks. Hlinka emphasizes: Markets are not logical, but psychological. After extreme gains, massive profit-taking set in – despite stellar earnings (e.g., Infineon 25% above estimates). The crash is a historic bear trap, not a trend reversal. The AI revolution is still in its infancy. Investors should not panic-sell but stay disciplined.

• No perfect timing: Nobody can call the exact top or bottom. Only buy back to original allocation (e.g., increase from 5% to 10%, not overweight).
• AI stocks belong as a mix in balanced or dynamic portfolios, not as a core holding.
• Sector rotation: Money flows from chips to software (e.g., Microsoft +10% after earnings).
• Beware of crash prophets: Historically they were rarely right (Dotcom, Lehman). Long-term investors fare better.

• Fed keeps rates not because of inflation, but to give Trump time to lower oil prices. Recent US inflation data were good.
• Iran conflict: Hlinka was wrong about a quick end. Oil prices are volatile. As soon as calm returns, markets could surge.
• Digital Euro: Hlinka warns of bureaucracy and loss of freedom – unlike Switzerland, which has enshrined cash in its constitution.

• Gold is searching for its investment identity. Physical gold („chocolate bar“) provides security, and its low volatility is a virtue.
• Nestlé is structurally weak: missed opportunities with the strong franc, baby food scandal, many clients reject the stock. Danone is the better alternative.

„Stay calm. Nothing has happened. Markets are psychological; the biggest mistake is not investing at all.“ – Mojmir Hlinka

Ethereum is often underestimated, but there are five strong reasons why it remains dominant and poised for long-term growth.

• Ethereum leads with 11,000 active developers, ahead of Solana.
• Milestone: 1 million lifetime developers, 232,000 active in the last 12 months.
• Major TradFi names build on Ethereum: Robinhood (its own L2), JPMorgan (money market funds), Franklin Templeton ($1.6B fund), BlackRock (BUIDL – #1 tokenized treasury with $2.5B).
• Ethereum holds 44% of the tokenized RWA market.

• Nearly 50% of the $300B+ stablecoin market resides on Ethereum.
• Highest TVL among smart contract chains: $41B (8x Solana’s $4.9B).
• L2s like Arbitrum, Optimism, Base, and Robinhood Chain keep capital within the ecosystem.
• ETH is the preferred DeFi collateral (lending, perpetuals, staking).

• US spot Ethereum ETFs saw net inflows > $300M in July 2025. BlackRock’s iShares ETF drives >80% of daily flows.
• Staking ETFs (Rex/Osprey, Grayscale, BlackRock) let institutions earn yield without running validators.
• 67 Ethereum treasury companies hold >8.2M ETH (6.8% of supply). Bitmain alone owns 5.5M ETH.
• Organizations like Etherealize (co-founded by ex-Ethereum lead Danny Ryan) and Ethereum Institutional push Wall Street adoption.

• Staking yield of 2.65% turns ETH into a bond/dividend-like asset.
• Bitmain earned $45.7M quarterly from staking (98% of revenue); projected $284M annualized.
• Unlike Bitcoin (no native staking), Ethereum provides steady income even during price stagnation – attractive for corporate treasuries.

• Glamsterdam (H2 2026) – biggest upgrade since The Merge:
  • EIP-732 (EPBS): Decentralizes block production, removes relays.
  • EIP-7928 (BALLs): Parallel transaction execution → lower fees & higher throughput.
• Hegata (also H2 2026) with EIP-7805 (Fossil): Censorship resistance via forced inclusion lists.
• Future EIPs on account abstraction (pay fees in stablecoins) and Verkle Trees (lower node storage) boost scalability & decentralization.

• ETH/USD: +23% in three weeks; ETH/BTC ratio recovering and testing the 200-day MA.
• Analysts: Standard Chartered forecasts $4,000 year-end; Citi sees $2,240.
• RSI/MACD hint at overbought conditions; volume remains moderate. Still, fundamentals suggest a sustained rally is possible.

Bottom line: Despite recent underperformance, Ethereum’s developer activity, institutional demand, capital dominance, staking yields, and upcoming upgrades create a powerful foundation. A breakout above $4,000 and new all-time highs are realistic if market conditions and upgrades align.

Summary follows...

How to Use AI Agents to Automate 99% of Your Life

This video demonstrates how to build four simple AI agents based on a "4 Cs" framework to make daily life more efficient, requiring no technical skills.

1. Coordination: Prioritization and Time Management

• Problem: Average 117 emails/day, interruptions every 2 minutes (275 times daily). Attention is fragmented.
• Solution: A coordination agent managing emails and calendar.
  • Email Agent: Connect Gmail; sort emails into "urgent", "informational", and "ignore"; draft replies in your style, but don't send without approval.
  • Calendar Agent: Connect Google Calendar; compare schedule with urgent emails, highlight conflicts and prep time.
• Key Insight: Don't delegate immediately! First make work visible, then efficient, then automatic. Gradually hand over responsibility.

2. Creativity: Turning Ideas into Tangible Output

• Principle: You remain the director and make decisions. The agent assembles rough notes into a final product.
• Example: Creating a PowerPoint presentation.
  • Create a folder with notes; agent builds an 8-10 slide real PPT file.
  • Asks clarifying questions; style templates can be saved as a "skill" and reused.
• Key Takeaway: If you are clear, AI multiplies your clarity. If you are confused, AI multiplies the confusion.

3. Clarity: Understanding Complex Documents

• Two Modes: Telescope (gathering info from many sources) and Microscope (deep diving into one document).
• Telescope Example: Researching a company before signing a contract (web, emails, documents).
• Microscope Example: Analyzing a contract. Instead of a simple summary:
  • Identify key terms (fees, deadlines, exclusions, risks).
  • Create a five-column table: "What the contract says", "Plain English meaning", "Why it matters", "Risk level", "Questions to ask".
• Important Note: Do not upload sensitive data (financial, medical).

4. Coaching: Preparing for Important Conversations

• Goal: Practice for job interviews, negotiations, pitches – your first rehearsal should not be in the critical room.
• Structure:
  1. Add context (company background, job description, resume).
  2. Give the agent a role (e.g., skeptical hiring manager).
  3. Practice in voice mode – like a real conversation.
  4. After the talk: Role switch – agent becomes a coach providing feedback (weaknesses, improved answers).
  5. Increase intensity: Simulate a tougher persona (e.g., startup CEO).
• Output: A one-page prep card with key points.

• AI will change jobs but not replace them – it creates new opportunities.
• The real contest is about things machines cannot own: attention, creativity, clarity, and judgment.
• Use the machines, but don't become one.