Welcome to Nofinity

In this episode of Bankless, David Hoffman speaks with Mo Jalil and Oscar Thorne, co‑founders of ETH Systems – a new spin‑off from the Ethereum Foundation focused on Ethereum, institutions, and privacy.

• Ethereum is a great neutral base layer, but without built‑in privacy, institutions cannot use it.
• Institutions need confidentiality for their business and must remain compliant – both require cryptography.
• Currently they use private networks because public blockchains lack privacy, even though Ethereum offers deep liquidity and new business opportunities.

• Mo Jalil has a traditional finance background (Goldman Sachs, hedge funds) and led APAC BD at the Ethereum Foundation. He realized institutions need privacy to use public Ethereum.
• Oscar Thorne has been in crypto for ~10 years, focusing on privacy and protocol design (Status, R&D labs). He wrote a book on proof systems and built client‑side proving tooling.
• Together they started the Institutional Privacy Task Force at the EF, now spun out as ETH Systems.

• Interdealer compression: A tier‑1 investment bank wants to net trades without an expensive third party – this requires privacy on a shared state like Ethereum.
• Multi‑party private payments: Some jurisdictions require sender, receiver, auditor, and government as participants. This couldn’t be done privately and performantly for years – ETH Systems found a solution.
• Massive scale: One project could roll out to an entire country with tens of millions of users.

• Many current solutions are bespoke because institutions have specific legal and business needs.
• The goal is to extract generic building blocks that become open‑source libraries and a reusable stack.
• ETH Systems follows a two‑track approach: business‑driven (directly helping institutions) and open‑source (strengthening the whole Ethereum ecosystem).

• ETH Systems is a for‑profit company – necessary for sustainable funding and to be a trusted counterparty for institutions.
• Demand is massive and inbound – institutions reach out because they see DeFi’s potential but need privacy and compliance.
• Engagements take 18–24 months, so first products are still in development.

• Financial infrastructure should run invisibly on blockchain: users can trade global stocks without revealing their identity, yet enjoy all DeFi benefits (ownership, transferability, verifiability).
• Privacy means selective disclosure – aggregates like TVL or trading volume remain visible, while individual transactions stay private.
• The bridge between cypherpunks and institutions is narrower than expected: both want censorship resistance, security, and openness – they just speak different languages.

• DeFi protocols should be open to adaptation – ETH Systems seeks collaboration to modify products for institutional users.
• Open‑source contributions are welcome: the team regularly publishes write‑ups and market maps; contributors benefit from high attention from banks.
• More mutual understanding is needed between developers and traditional finance – a continuous feedback loop is essential.

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The speaker explains why first-principles thinking is the ultimate "cheat code" for life. Using examples like Elon Musk (landing rockets) and Toyota (just-in-time production), he shows how successful people break conventions. He then presents a 4-step framework and demonstrates how to use AI to amplify this process.

• Goal: Break a problem into its smallest components – without offering solutions or assumptions.
• Example: To start a YouTube channel, you only need a phone and a story – not necessarily a studio.
• AI Prompt: Have the AI act as a "first-principles analyst" that only decomposes, not advises.

• Goal: Distinguish between facts and inherited assumptions.
• Example: Tesla questioned the combustion engine – and sparked a revolution.
• AI Prompt: The AI as a "skeptical red-team analyst" uncovers hidden assumptions.

• Goal: Create new combinations from existing building blocks – like music from 12 notes.
• AI Prompt: Let the AI search millions of combinations at scale.

• Goal: Let the real world decide – with minimal cost.
• Example: James Dyson built 5,127 prototypes before perfecting the bagless vacuum.
• AI Prompt: The AI as a "skeptical scientist" designs the cheapest, fastest test.

• AI models tend to default to conventional answers. You must force them to apply first-principles thinking.
• The provided prompts (following the AIM framework: Actor, Input, Mission) ensure AI doesn't just suggest solutions but thinks step by step.

• It’s not about being right all the time – it’s about quickly learning why you were wrong.
• Even a success rate of just 2% can change your life if that one hit lands.
• “You don’t need 100 wins – you only need one.”

In this episode of Huberman Lab Essentials, Dr. Chris Palmer explores the intimate connection between diet and mental health. He shares his personal journey: after curing his own metabolic syndrome with the Atkins diet, he noticed dramatic improvements in mood, energy, and sleep. As a psychiatrist, he began using the ketogenic diet for treatment-resistant patients, with remarkable results – including a man with schizoaffective disorder whose hallucinations and delusions vanished.

• Mitochondria are key: they regulate neurotransmitters (serotonin, dopamine), hormones (cortisol), inflammation, and even neurotransmitter release.
• The ketogenic diet stimulates two crucial processes:
  • Mitophagy – clearing old, defective mitochondria
  • Mitochondrial biogenesis – creating new, healthy mitochondria
• This explains why the diet works not only for epilepsy (known since 1921) but also for mental disorders.

• For mild mood issues or burnout, simply reducing carbohydrates (eliminating ultra-processed foods) can help.
• For serious mental illness (depression, bipolar disorder, schizophrenia), the ketogenic diet should be done under medical supervision.
• Ketone levels:
  • For depression: ≥ 0.8 mmol/L
  • For psychosis/bipolar: ≥ 1.5 mmol/L
• Never stop medications on your own – the diet may enhance their effects and require adjustments.

Dr. Palmer emphasizes that nutrition is a powerful yet underutilized tool in psychiatry, and large-scale randomized controlled trials are currently underway.

The speaker updates his Value Investing Quadrant for the second half of 2026. The quadrant plots reward (x-axis) and risk (y-axis), with the ideal investment being high reward and low risk (bottom left corner). The following stocks are discussed:

• Risk: Very high, as it is a bet on Elon Musk and unlikely to ever be profitable.
• Reward: Very low. Placed at the bottom left.

• Risk: Now high from a price perspective. Stock rose from 560 to 1,500, P/E ratio now 57.
• Reward: Too expensive for value investing. Only interesting if the bubble bursts.

• Yield: ~5% (10-year at 4.7%).
• Risk: High due to inflation, national debt, and money printing.

• Return: Long-term ~6%.
• Risk: Very low. The speaker would sell now but considers it a solid long-term hold.

• Dividend yield 5%, trees growing. Interesting for income investors.

• Currently fairly valued for an 8% return. The speaker awaits a pullback for a better entry.

• Fairly valued for a 10% return. Optimistic due to AI growth.

• Sideways for 13 years despite company growth. Potential 10% return.

• Stock surged (from 25). Dividend yield now 4%, return potential reduced.

• Stock up 38%. Growth driven by AI partnerships (OpenAI), considered riskier now.

• Growth slowed from 25% to 19%, but still a 19% grower.

• Stock at 2,000, good results, but credit risks.

The speaker emphasizes that investors should choose based on risk tolerance and goals. He is building a diversified portfolio on his research platform.