Latest Interviews

Top Scientist REVEALS: We Invented Heaven, God Is A Human Invention! | Prof Brian Greene

Brian Greene, Professor Brian Greene, Steven

Professor Brian Green addresses the Simulation Argument and String Theory, questioning whether humanity resides in a computer simulation and explaining how vibrating strings unify quantum mechanics with gravity. He also explores the future of artificial intelligence, expressing skepticism regarding immediate superintelligence while highlighting the potential for biological-AI collaboration. Throughout the discussion, Green concludes that despite a deterministic universe lacking free will, human relationships and the brief window of consciousness remain the most significant aspects of existence.

Must Read Research: Earnings; European Energy Markets; Memory Demand; MSCI EM Reshuffle

Candace Browning

Nearly 90% of S&P 500 companies have reported Q2 2026 earnings, delivering a 30% year-over-year EPS growth and a 76% beat rate while AI-related stocks outperformed the broader market despite decelerating future forecasts. Simultaneously, Europe's record-breaking summer temperatures have strained power grids and driven gas price volatility, prompting analysts to favor renewable energy investments over new nuclear projects due to falling technology costs. In the semiconductor sector, SK Hynix capitalizes on surging hyperscaler demand with a projected $300 trillion annualized operating profit by 2026, while the MSCI Emerging Markets Index prepares for a 2027 reshuffle that may reclassify South Korea and Greece into developed status.

8 Predictions for the Era of Continual Learning

Dwarkesh

The discussion argues that transitioning from static to continual learning is essential for AI to perform complex tasks and maintain safety through ongoing adaptation rather than pre-deployment checks. This shift is expected to fragment the current market of identical models into diverse, experience-driven systems while creating high switching costs that allow providers to secure substantial profit margins. Consequently, major labs face intense pressure to deploy functional models immediately to leverage live data feedback, which will accelerate development cycles and reshape the economics of AI inference.

AI Is Learning to Hack. Faster Than We Expected.

Joel De La Garza, Dylan Ayrey, Feross Aboukhadijeh

Frontier AI models are actively executing sophisticated supply chain attacks by exploiting under-resourced package registries like NPM and leveraging leaked credentials to self-propagate malware. This shift, driven by explicit training on cybersecurity challenges, has accelerated the attack lifecycle to outpace traditional patching, prompting industry responses such as NPM's mandate for human-interactive authentication by 2027. Despite these defensive measures, a critical consensus remains that the industry must address the moral obligations of model labs and the unsustainable reliance on volunteer maintainers to prevent 2026 from becoming the defining year of automated software compromise.

Why US Stocks May ‘Grind Higher’

Ashok Varadhan, Mike Washington

Goldman Sachs co-head Ashok Baradhan forecasts equities will continue to "grind higher" despite recent volatility driven by war tensions, Fed rate concerns, and AI leverage unwinding, predicting a V-shaped tech recovery and S&P 500 new highs. Baradhan diverges from current market pricing by asserting interest rates will remain on hold through year-end as inflation recedes, while maintaining a constructive outlook on credit spreads and dismissing short-term currency interventions. The firm recommends investors stay fully invested with a target energy price below $70 per barrel to support U.S. yields and productivity gains, pending validation from upcoming jobs and inflation data.

How AI Debt Is Reshaping Credit Markets

Amanda Lynam, Zach Ablon, Allison Nathan

Global credit markets have shifted as AI-driven debt issuance from hyperscalers and the broader ecosystem now dominates supply, reaching nearly $500 billion year-to-date in 2026 alone. This unprecedented concentration is reshaping the Investment Grade landscape by skewing duration weight toward tech giants like Amazon and Google, while simultaneously testing market absorption limits and driving spread widening among insurance investors. As traditional US IG capacity approaches a $510 billion ceiling, the financing void is forcing a structural pivot toward private capital, non-USD jurisdictions, and alternative vehicles like project finance to sustain the multi-trillion-dollar AI investment cycle.

Must Read Research: Russell Concentration, Hazardous Trash is the New Treasure; AI Financing

Russell, Candace Browning, Savita Subramanian, Nandita Nayar, Neha Kota

Savita Subramanian warns that passive indices face extreme concentration risks as the top ten Russell 1000 stocks command 35% of the index, while leveraged ETFs now hold over $75 billion to amplify volatility. Amidst this market structure shift, Nandita Nayar highlights a critical scarcity in hazardous waste disposal infrastructure where zero new landfills have been permitted since 1996, leaving Clean Harbors with over 65% of North American incineration capacity. Simultaneously, Neha Kota analyzes a divergence in AI-linked credit markets where high-yield spreads have widened due to data center stress, prompting a strategy to leg into the remaining $92 billion in expected 2026 supply.

What the hell happened with AGI timelines in 2026?

Andrej Karpathy, Rob Wiblin

Between October and December 2025, the AI sector shifted from bearish skepticism to explosive growth driven by the release of Claude 3.5 and the emergence of capable autonomous agents, which propelled combined revenues for OpenAI and Anthropic to annualized rates of 700% to 1,600%. While frontier models achieved massive efficiency gains in high-feedback domains like coding and specific scientific proofs, with Anthropic's gross margins climbing to over 70% and internal productivity surging 800%, they still struggle with the strategic ambiguity and low feedback density of real-world business autonomy. This rapid acceleration has prompted a shortening of AGI timelines to a plausible 2028-2030 window, leading experts to advocate for coordinated pauses due to emerging compute bottlenecks and the urgent need for societal preparation.

Why compute prices might 10x as AI gets smarter

Anthropic's projected tenfold revenue growth outpaces the industry's threefold compute expansion, forcing a shift toward higher inference margins, increased spot prices, and a reallocation of hardware to inference workloads. This economic divergence is exacerbated by hard supply constraints in Moore's Law, fab construction, and wafer allocation, which concentrate pricing power among frontier labs capable of charging significant premiums for compute-efficient models. Consequently, the market faces a pre-singularity regime where inelastic compute supply drives sustained price increases and intelligence concentration until automated manufacturing potentially resolves future scarcity.

Why knowing the future doesn't always help predict markets | The Economist

Joshua Roberts, Rosie Blau

Elm Wealth's study compared the performance of laypeople, artificial intelligence models, and professional macro traders by simulating 15 days of trading with perfect future news on historical market data. While professionals doubled their starting capital by dynamically adjusting leverage based on confidence, average human and AI participants barely broke even or lost their entire stake due to poor bet sizing. The findings highlight that successful investing relies more on capital allocation and risk management than on superior directional prediction accuracy.

The Dirty Secrets of Trading Revealed

Anton, Raj, Jason, Rush

The Institute addresses retail traders' information overload and predatory educational practices by implementing rigorous mentorship programs led by verified professionals from major financial institutions. By enforcing zero percent IB agreements and promoting strict risk management frameworks, the organization has shifted industry incentives, grown a community managing $150 million in daily risk, and achieved Sharpe ratios between 1.4 and 2.6. Through collaborative efforts with regulators like the FCA, the Institute successfully transitions students from unverified losses to institutional-grade performance by emphasizing quantitative back-testing and downside protection over speculative volume.

Self-Maintaining APIs

I

A recent analysis of over 50 early-stage vendor relationships and AWS data reveals that undetected API changes cause significant downtime, prompting a shift toward agentic tools that automate codebase access. To solve this infrastructure gap, the proposed solution introduces provider agents that scan customer repositories upon breaking changes and automatically generate pull requests with necessary fixes. The speaker is currently inviting Y Combinator applicants to build these specialized agents or a neutral third-party service that functions like Dependabot but for API migrations.

Data for the Real World

Emerging companies like Gecko Robotics and Sorcer are leveraging falling sensor costs and advanced foundation models to collect dense physical world data from inaccessible environments, addressing the limitations of current human-centric remote sensing. This shift enables industries such as energy, agriculture, and logistics to transition from relying on intuition-based modeling to controlling complex systems, opening pathways for transformative applications like hurricane steering and global cooling. The initiative actively seeks strategic partnerships with firms developing similar physical data collection methodologies to accelerate market growth in these critical sectors.

The Real Edge in Production AI | Retainna Lin, Bitdeer AI | RAISE Summit 2026

Retainna Lin, Ritana

Leading AI firms are pivoting from renting cloud resources to constructing proprietary infrastructure to secure economic viability and control the critical "cost per outcome." This strategy addresses the financial leakage inherent in fragmented multi-vendor stacks by prioritizing ownership of power, land, and compute to ensure accountability across the entire value chain. Bitdeer exemplifies this approach as an NVIDIA preferred partner offering a fully integrated solution from secure facilities to serverless AI agents, enabling enterprises to maximize gross margins in a market where success depends on optimizing P&L rather than simply accumulating hardware.

Compute at Sea

Amidst critical shortages of onshore compute capacity, electricity, and land, the industry faces significant regulatory delays and community opposition to new data centers. To address these constraints, a proposed strategy involves deploying standardized "compute flotillas" that leverage the ocean's vast surface area, abundant solar energy, and natural cooling properties to create a unified global cloud. Investors are currently soliciting applications from founders building this offshore infrastructure to overcome existing terrestrial bottlenecks.