A record 89% of Americans now say the U.S. government is full of corruption
Source: Hedgeye, Gallup
Steve Jobs built the foundation.
Tim Cook expanded it into an ecosystem. Which era had the bigger impact? Source: Apple Club
Indians are buying more Gold for Investment than for Jewellery
First time since 2020 Source: Patterns
Junk bonds are pricing in perfection.
High-yield spreads have fallen to just 2.66% above US Treasuries—close to their tightest level in years and roughly half the historical average. That leaves almost no margin for error. Yet the labor market is slowing, fiscal deficits remain near 6% of GDP, and economic risks are building. Credit markets often crack before equities notice. At a 2.66% spread, investors are receiving very little compensation for default and liquidity risk. If spreads widen, financial conditions could tighten quickly—and stocks may feel the impact soon after. Source: Kurt S. Altrichter, CRPS®
Just didn't
Nike $NKE is getting removed from the S&P 100 after 18 years as the stock crashes 79% in the last 5 years. Source: Trend Spider
The US Treasury could buy back over $34 BILLION of its own debt in September alone.
This week alone carries up to $14.5 BILLION in capacity, with the program doubling in size on September 9. The 30-year yield sits near a 20-year high, with the government now spending over $1 TRILLION a year just on interest. Treasury Secretary Bessent insists the goal is liquidity, not controlling yields, saying "I have not bought anything yet." Source: coinbureau
Welcome to the AGI era.
That's how OpenAI's Greg Brockman closed the GPT-6 Astra launch. The headlines: → Trained on 100,000+ GPUs at Stargate, Texas → Claims the lead in coding, science, reasoning and cybersecurity → Works inside software: spreadsheets, 3D worlds, circuit boards, tax forms → First model to hit OpenAI's "Critical" cyber threshold — access restricted via Daybreak → Priced at 2.5x GPT-5.6 Why this matters for AI hardware & memory chips: 1) 100k GPUs for one model = the compute race is accelerating, not plateauing. 2) Agentic models that build, reason and act burn far more inference tokens. Inference = sustained demand for HBM and DRAM, not one-off training spend. 3) 2.5x pricing shows customers will pay for capability → hyperscaler capex stays funded. The picks-and-shovels trade remains alive and well.
AI’s next bottleneck isn’t chips. It’s the town hall.
26 US data-center projects were blocked in Q1 2026—nearly as many as the 31 blocked during all of last year. And the resistance is accelerating: • 166 projects faced local opposition • 49 additional projects were delayed • Roughly $130 billion of AI infrastructure is now stalled Markets focus on GPUs, electricity and financing. But the real constraint may be community approval. Noise. Water consumption. Electricity demand. Land use. Local disruption. The AI buildout may be global in ambition—but every data center must still win approval locally. Any forecast assuming a smooth infrastructure ramp may be far too optimistic. Source: Kurt S. Altrichter, CRPS®
