Deepseeking: The Market
I have completely eliminated the need for Bloomberg terminals and analysts—unless they are truly exceptional, which is extremely rare. Even when you do find such analysts, the problem is that they often haven’t leveraged or scaled their capabilities with AI, which drastically reduces their productivity.
Simply put, I have integrated both the creative and analytical aspects of my mind—combining liberal arts and STEM—to create a powerful blend of memetic scale and real-world execution, sometimes in mere seconds.
For example, running your own local LLM on a MacBook M4 Max, combined with a plethora of data feeds and analyzed through my unique perspective, is an absolute game changer.
To elaborate, an LLM achieves higher levels of reasoning and accuracy as you increase its available RAM and computational resources.
This is why I mentioned that, in the future, even the consumer electronics space will become highly technocratic and classist, as one will quite literally be able to purchase a smarter computer. A closed-end iteration that seamlessly “just works” will stand in contrast to open-source “smart” devices, which will likely be exported from the manufacturing base of Ningbo—where DeepSeek is located and undoubtedly in talks with manufacturers to facilitate this.
Overall, the level of precision and intricacy required to “out-algo the algo” while maintaining discretion was considered impossible just a few years ago.
DeepSeeking: The InTrilligence of Apple
The third biggest story on Monday was Apple's positive performance in the market. But what drove this green movement? One key factor may be Apple's CAPEX allocation, which hasn't been heavily concentrated in LLMs. This aligns with what I learned months ago from an Apple executive, who revealed - before it was widely known - that Apple lacked substantial…