• The video analyzes how US markets historically react to different midterm outcomes – without political bias.
• Currently there is a Republican trifecta; prediction markets favor a Democratic majority in the House and Senate.

• Best scenario since 1953: Democratic president with Republican Congress (median annualized return ~20%).
• Republican trifecta also positive: avg 13.3%, median 13.6%.
• Worst scenario: Republican president with fully Democratic Congress – avg 4.9%, median 4.0% (but returns remain positive: 12-month avg 4%).
• Including data back to 1928, the Great Depression skews results for divided regimes.
• Trifectas (Republican or Democratic) have historically performed similarly well (avg 9.8% vs. 9.0%; median 12.4% vs. 11.3%).

• Democratic trifectas also saw severe bear markets (e.g., 1937: -39%, 2008: -38.5%).
• Republican regimes show more extremes and higher volatility (e.g., 1987, 2020).
• The return distribution shows that lower averages are not just due to a few outliers.

• Trump's second term so far closely resembles his first (S&P 500 ~26% vs. ~20% after normalization).
• It currently outperforms Biden's term, which was in a bear market at this point.
• Bitcoin: Returns under Trump II and Biden are significantly lower than under Trump I and Obama II – likely due to macroeconomic issues (inflation, labor market).

• Highest Sharpe ratio: Lyndon B. Johnson (1.96), followed by Roosevelt (1945) and Clinton.
• Worst Sharpe ratio: Nixon's second term (-1.6).
• Heatmaps and Z-score charts visualize returns and risk by congressional composition.

• Historical data provide guidance, not guarantees. Uncertainty about the election outcome weighs on markets – polls can be wrong (see Brazil).

On October 29, 2025, Binance – the world's largest crypto exchange – fell victim to the largest hack in history (crypto and beyond). North Korea stole roughly $6.3–6.4 billion from Binance hot wallets across multiple blockchains, almost a quarter of the country's annual GDP.

• Entry vector: A compromised laptop of a DevOps engineer (according to Binance). Binance later said there were additional points of breach.
• No private keys: The attackers did not obtain private keys but manipulated Binance's signing infrastructure – like using a bank's pen to sign checks without opening the vault.
• EIP-7702: On Ethereum, they used a novel technique: they pre-signed 50 transactions with different nonces. One of them converted the hot wallet into a smart account controlled by an attacker smart contract, sweeping all assets.
• Automation: New deposits were immediately drained as they arrived.
• Multiple chains affected: Ethereum, Bitcoin, Tron, Solana, XRP, etc. – indicating compromised infrastructure, not individual keys.
• Pre-hack tests: About 3 weeks earlier, attackers tested the EIP-7702 method using Tornado Cash-funded wallets.

• Swift freezes: Tether, Circle, Arbitrum Security Council and others froze nearly half the funds (~$3 billion). This is unprecedented – after the Bybit hack, initially less than 3% was frozen.
• Criticism: Circle and Tether's fast response was likely linked to their business relationship with Binance.
• Laundering and DeFi: The hackers used DeFi, including ThorChain, losing up to 10% on some swaps due to liquidity issues. MEV searchers earned ~$50 million.
• Aave freeze: Aave froze markets to prevent the use of stolen stablecoins.

• ThorChain became a major laundering channel for North Korea. In previous TraderTrader hacks, over 99% of daily volume came from laundering.
• FBI warning: FBI, Secret Service and IRS named ThorChain directly, urging node operators to block transactions with stolen funds.
• Centralization: ThorChain can be halted within minutes by a few node operators; becoming a node operator requires community approval – not very decentralized, according to Pablo.
• Controversial statements: JP Thor was quoted with a new Aston Martin helicopter with a DPRK flag, and argued North Korea might use the money to feed children – widely criticized as absurd and ignorant of the regime's reality.

• TraderTrader is a subgroup of North Korea's RGB (Reconnaissance General Bureau), responsible for major crypto hacks – from Ronin to Bybit and now Binance.
• Name origin: Trojanized trading apps as malware decoys in fake job interviews.
• Many subgroups: "Lazarus" has become a catch-all; different units have different TTPs.
• AI & automation: Laundering is highly automated; AI likely plays a role, though not confirmed.

• Operational security is the weakest link – not smart contract bugs. ~90% of crypto organizations lack real OpSec expertise.
• Deploy EDR (Endpoint Detection and Response) e.g., CrowdStrike (~$150/year). Most infiltrations start on a laptop.
• Education: Leaders, security and compliance teams must understand the threat landscape (North Korea, TraderTrader etc.).
• Industry stance: The industry must stop enabling mass laundering. Decentralization and permissionlessness should not become excuses to fund dictatorships.
• Outlook: North Korea now holds more ETH than the Ethereum Foundation – a sad milestone.

Key takeaway: This hack was not a single exploit but a failure of operational security. The industry must prioritize OpSec before the next billion-dollar loss.

• The Financial Times reported that OpenAI's annualized revenue is not $70 billion, but around $50 billion.
• This $20 billion gap caused a sell-off in Nvidia, CoreWeave, SoftBank, and Oracle stocks.

• Anthropic uses gross revenue (including cloud partner share), while OpenAI uses net revenue. To compare them, the market added the partner share back to OpenAI's number, creating the $70 billion estimate.
• OpenAI never officially confirmed that figure, yet it was priced into contracts and valuations across the industry.

• Internal plans show $856 billion in compute and infrastructure spending by 2030.
• Major contracts: $300 billion with Oracle (starting 2027), up to $250 billion with Microsoft Azure.
• Projected revenue for 2026 is only $36 billion – the commitments equal nearly 24 years of current revenue.
• Cumulative free cash flow from 2026 to 2030 is forecast at −$278 billion.

• Nearly all construction is funded through private credit: GPU-backed loans, project finance, and bonds.
• Companies like Oracle ($156B debt), CoreWeave ($52B debt), and SoftBank ($40B bridge loan + junk bonds) are deeply leveraged.
• Lenders are betting that OpenAI's revenue will grow fast enough to cover the bills.

• OpenAI has raised massive capital ($122B in March, another $30B now being negotiated), but the gap between revenue and spending remains enormous.
• The entire AI infrastructure market faces a critical test: Can OpenAI deliver on expectations, or is a painful correction ahead?

The author reviews six S&P 500 stocks with unusual investment stories: a utility, a spin-off, AI infrastructure, a SpaceX stake, a software/financial services name, and an ETF provider. Core message: timing and risk-reward matter; most names are fair-to-expensive, and genuinely cheap opportunities are scarce.

• Pinnacle West (PNW) – utility: Dividend yield 3.49%, P/E 20, growth 5–6% annually through 2030; Arizona growth and data centers support demand. $10B investment over 4 years. More attractive at recession/cyclical lows, not during euphoria.
• Solventum (SOLV) – 3M spin-off: P/E 11, profitable healthcare segments (surgical, dental, health IT). Spin-offs often carry debt/legacy issues and forced-selling pressure; interesting but currently too complicated.
• Generac (GNRC) – AI “picks and shovels”: Backup power for data centers; backlog $1.6B, industrial growth ~30%; Amazon contract potentially $8B. EPS ~9, P/E 20; 2028 EPS estimate 16 → 50%+ upside. A lower-risk way to play AI than direct AI bets.
• EchoStar (ECHO) – SpaceX at a discount? Spectrum sale to AT&T for $23B; owns 2% of SpaceX, split-adjusted entry at $42, stock around $90. UBS target $156 (~60% upside), but little value without SpaceX; risky, only for SpaceX believers.
• Gen Digital (GEN) – cheap but problematic: P/E 14, dividend 2%, $8B debt; brands Norton/Avast. Management appears more focused on survival than sustainable value creation.
• Invesco (IVZ) – valuation gap: P/E 10 vs. market ~30; benefits from rising markets and ETF assets. Fairly valued but reveals market risk: if the bubble bursts, 50–70% downside is possible, similar to the broader market.

• Textron: too cyclical/risky.
• J.M. Smucker: cheap but no clear catalyst.
• Allegiant: fairly valued compounder, not a bargain.
• GoDaddy: risky, high churn and stock-based compensation.
• Avery Dennison: solid but expected returns too low.
• FedEx Freight: spin-off with financial engineering.
• REIT, Tyler Technologies, Hasbro: unattractive or fairly valued.

None of the ideas is clear deep value; the most interesting stories are Generac (AI infrastructure) and EchoStar (discounted SpaceX exposure), each with clear risks. The author stresses: buy when sentiment is poor, not when the story is obvious and priced in.

• A study in Nature Aging from Dr. George Church’s lab (Harvard Medical School/Wyss Institute) reported that a single gene, the RNA splicing factor SRSF1, extended median lifespan in aged female mice by 14 % (108 days; from 778 to 886 days).
• SRSF1 likely improves RNA splicing fidelity and protein homeostasis without forcing cells into an embryonic state.

• The Yamanaka cocktail (Oct4, Sox2, Klf4, c-Myc) can reset cell age but risks loss of cell identity and teratomas.
• SRSF1 does not push cells toward pluripotency; it targets how cells edit their RNA messages.
• Major caveat: SRSF1 is a well-documented proto-oncogene; increased activity can help cancer cells escape cell death.

• A transcriptomic clock of 292 genes was trained on 133 human skin fibroblast lines (donors aged 1–96); 89 candidate genes were tested.
• SRSF1 was the most consistent hit; its baseline expression naturally declines with age.
• In fibroblasts from older donors (55, 65, 79 years), modeled rejuvenation reached 16 years, but with an ±9.5-year error margin.
• DNA methylation clocks were mixed; senescence markers were mixed (beta-galactosidase down, p16 unchanged); DNA damage markers were not significantly reduced.
• Crucially, cell identity was preserved, and pluripotency markers (Oct4, Sox2, Nanog) remained silent.

• An AAV8 vector carried mouse SRSF1 under a Tet-On switch, activated by doxycycline.
• Female mice received the vector at day 561 and induction at day 606; n=19 (10 treated, 9 controls).
• Median survival: 778 vs. 886 days.
• Caveats: female mice only; controls lived below the typical 850–900 days for C57BL/6; small exploratory cohort; individual physical performance measures were not significant after correction.
• Frailty: modeled score rose 44 % slower; onset of persistent frailty was delayed by about 123 days in the relevant subset.
• Liver: optimized DNA methylation clock showed −0.5 years, other clocks showed no significant difference; no histological reversal of liver fibrosis.
• Dosing mattered: high continuous SRSF1 expression did not help; only moderate pulsed induction supported survival.

• Shift Biosciences shared a 2025 preprint on SB000, a single-gene candidate that reset epigenetic clocks in fibroblasts (Horvath-2013 −7.4 years; Dunedin Pace −0.132), but reported no survival data.
• The Church lab disclosed SRSF1’s sequence, pathways, and survival curves, filed patents, and founded Regulus Bio.
• AAV cargo limit: about 4.7 kb; SRSF1’s coding sequence is about 747 bp, so it fits with regulatory switches. But systemic AAV doses carry liver toxicity; Tet-On requires prolonged doxycycline with microbiome and mitochondrial risks.
• Life Biosciences ER-100 (AAV2, OSK, glaucoma) reported in 2026 that the first 3 patients tolerated 56 days of doxycycline induction; this says little about systemic safety.
• There are no human trials of SRSF1; because of its proto-oncogene risk, long toxicology studies would be needed. Realistically, future use would likely target localized tissues, not systemic longevity.

• SRSF1 is an important proof of concept for single-gene rejuvenation via RNA splicing.
• The open question is whether its repair benefits can be separated from its oncogenic risk.

David Hoffman (Bankless) interviews Zach Williamson (Aztec) about the competition to become the "private Ethereum." Zach asserts that Aztec is the only smart-contract chain without backdoors or viewing keys – unlike many rivals that rely on centralized provers or compliance hooks.

• Most projects take shortcuts: they introduce third parties to verify transactions, enabling censorship and surveillance.
• Aztec takes the harder path: full decentralization and formal verification (Stage-2 rollup from day one).

• AI-driven attacks make every public transaction exploitable – data can be analyzed and abused.
• Aztec enables applications impossible on public chains: e.g., private KYC (ZK Passport), private lending, or tokenization of real-world assets with compliance.

• Current tools: zk.money (private transfers), Nolo (wallet), Nyx (private DeFi/yield).
• Aztec Tiara upgrade (2026): halved proof times, soft finality in 6–12 seconds, more formal verification.
• 2027 goals: real-time proving, 5-minute hard finality (with tipping option), cheaper provers.

• New users: try zk.money or visit aztec.network.
• Institutions: Aztec is a neutral network – they can add viewing keys at the app layer if desired.

“Privacy wins not as a feature, but as a requirement for applications that cannot exist otherwise.” – Zach Williamson