Google’s “Project Genie” and the rise of AI agents share a core logic: they kill off incumbents. This impacts gaming stocks like Roblox, Unity, TTWO, and triggers a killing spree in SaaS by enabling new virtual world interactions and disrupting to-B software. 2
Nvidia’s massive $100 billion investment plan in OpenAI has stalled. Jensen Huang reportedly cites concerns over increased competition from Google and Anthropic, plus OpenAI’s “lack of discipline.” This is a significant shift. 5
ASML CEO warns: AI model training faces an impending energy crisis. Without major power efficiency gains, future frontier AI models could consume the world’s entire energy supply. Models trained in 2027 may require $100 billion+ compute clusters to function. 10
The AI economy is driven by three fundamental inputs: Compute (GPUs), Memory (HBM), and implied software/data. Nvidia still leads in compute, but AMD is a credible second source. Custom silicon from Google ($GOOGL) and Amazon ($AMZN) is gaining serious traction as hyperscalers push ASICs. 13
AI bots are now dubbed AI agents. Their emerging social platforms, like Moltbook, signal a progression towards a “Skynet” future. 16
The AI agent era will rapidly transform data like the Epstein files into easily searchable knowledge bases. This will enable effortless public inquiry and visualize relationships of powerful figures, initiating a collective “demystification” of elites. 19
AI scaling is bottlenecked by a critical memory problem. Memory supply (teal line) remains flat, while model size (purple line) grows exponentially. This starves GPUs for data, severely limiting their utilization. Boosting GPU efficiency requires memory breakthroughs. 23
Frequent, casual sightings of the Tesla Cybercab, despite visible imperfections like misaligned scissor doors, indicate its proximity to mass production. 15
Stanley Druckenmiller’s 2023 observation about copper being “the tightest position I’ve ever studied” is validated by the AI economy’s massive power infrastructure buildout. Every viable AI path depends heavily on copper, further tightening supply. Initiated a starter position for copper exposure. 18
Google ($GOOG) has flipped from the cheapest Maggy 7 stock (forward P/E) last year to the most expensive currently. It is the only Maggy 7 trading at all-time highs (ATHs), while others are off their peaks. Upcoming earnings this Wednesday imply a +/- 6.5% move. 22
Retail investors with limited capital often get trapped chasing high-growth or meme stocks, frequently losing principal. Instead, focus on accumulating wealth through dollar-cost averaging (DCA) and long-term investing. Consistent DCA over years can build substantial capital and returns. 29
For investors averse to market volatility, dollar-cost averaging (DCA) into ETFs and integrating them into a portfolio offers a simpler, less stressful approach to US stock investing. This strategy eliminates the need for constant monitoring and fear. 30