The jobs report was a barnburner. Nonfarm payrolls increased by 172,000 versus expectations for 88,000, while prior months were revised higher by 93,000. Wage growth came in at roughly 0.3%. Yet the market sold off. In our view, the market is misreading the signal. It is assuming that stronger than expected employment and growth will cause a an acceleration in inflation. History would suggest otherwise. Productivity growth is running near 3%, while unit labor costs are hovering around 0.5%. Those are not the hallmarks of an inflationary boom. They are the hallmarks of healthy, productivity-driven growth that will lower inflation. Meanwhile, the yield curve continues to flatten despite a roughly 55% increase in oil prices year-over-year based on a three month moving average. In past cycles, an energy shock of this magnitude steepened the yield curve when the Federal Reserve was accommodating it. Instead, the bond market appears to be discounting something much more powerful: the deflationary impact of technological innovation, particularly artificial intelligence, which is beginning to increase productivity across broad swaths of the economy. If tensions with Iran ease and oil prices retreat, we believe inflation could move into negative territory before year-end. In our view, the Fed made a historic policy error when it raised rates aggressively into what was largely a supply-driven inflation shock in 2022. We do not believe the next generation of monetary policymakers will be eager to repeat that mistake. Notably, gold peaked on the day Kevin Warsh was appointed. The inflation trade may already be behind us. If our research is correct, the next phase of this cycle could be characterized by accelerating growth, declining inflation, falling interest rates, and a strengthening U.S. dollar. That combination would create a remarkably supportive backdrop for innovation-led equities and the technologies driving the next productivity boom. I discuss this framework in greater detail in this month’s episode of In The Know.
Tesla FSD (Supervised) is now officially available in 11 countries!
• U.S.
• Canada
• Mexico
• Puerto Rico
• The Netherlands
• Australia
• New Zealand
• South Korea
• China
• Lithuania
• Estonia (new)
Eventually, most of this map will be blue.
This is the first time we're seeing the latest generation Boston Dynamics Atlas in motion.
- Features 56 DoF, with 360° rotation in key joints
- 6.2 ft tall, weighs 198 lb (90 kg)
- Operating temperature: -20° to 40°C
- IP67 dust and water protection
- Only two unique actuators to minimize cost and complexity
- A Limb can be swapped in less than 5 min.
Halter announced today the launch of direct-to-satellite connectivity using SpaceX's @Starlink for its smart cattle collars, a world-first that removes the need for cell towers or on-ranch infrastructure.
"Using Starlink enables ranchers to manage cattle anywhere they can see the sky. Combined with a suite of new tools for reproduction, animal behavior, and precision pasture management, the release significantly expands what is possible for cattle ranch management.
Beef ranchers in remote and rugged regions that were limited by connectivity can now turn to virtual fencing to run more productive and sustainable operations - at a time when they face rising fuel costs, labor shortages, and an aging workforce pressures."
Halter’s internal modeling estimates direct-to-satellite capability expands coverage of the U.S beef cattle market by 2.5x. Until now, Halter’s solar-powered, GPS-enabled collars relied on Halter’s proprietary long-range radio towers. With direct-to-satellite, the collars can communicate via Starlink, eliminating ground infrastructure entirely.
Happy coding! Opus 4.7 is a significant step up. To get the most out of it, take the time to adjust your workflow to take advantage of Claude running for longer & being more agentic. It feels like a nice improvement with old workflows, and a significant leap once you take the time to adjust.
Btw, if Anthropic had any way to ship this, they would. Trained AI models are the fastest depreciating asset in history. GPT-4 cost $100M to train 2 years ago and now it's worth less than Qwen3.5-27B ($1M). Sending the FOMO back, clock is ticking boys. @DarioAmodei@bcherny