This increasing demand for energy is putting pressure on the transmission capacity of the electrical grid and the availability of data centers equipped to handle the power needs, causing voltage

Developing large AI models necessitates substantial computing capacity; for instance, training GPT-4 was reported to consume more electricity than what 5,000 average U.S. homes use in a year.

What I Read This Week… AI firms in the U.S. are encountering limitations in the electrical grid as their demand for computing power exceeds current power and data center resources. What’s happening?

company alone. Essentially, by investing in an index of 500 stocks, you might be predominantly investing in just 10, with the remaining 490 merely as a

However, as a select few stocks begin to dominate those indices, the associated risks increase rather than decrease. If there aren't limits on how much any single stock can contribute to the index, it

Many everyday Americans invest in S&P 500 index ETFs largely due to Buffett's endorsement. They’ve been led to believe that these funds offer low costs and diversification among the top 500 companies

This situation requires urgent attention, or it could lead to a major crisis. Why is that?

Test

Woah! Nice work!

It’s wild to consider that Deepseek is pricing Deepseek V3 at $0.28/1M output. This model is reportedly the second best non-reasoning model, following only Gemini 1206 in benchmark assessments.

to significant fallout among those companies, as they may struggle to make enough revenue to cover their incurred costs.

Take a look at the current pricing for "intelligence," which is low and rapidly decreasing. Numerous companies are set to pour tens of billions into the competition for AI offerings to the public.

The deflationary effects of technology can easily be overlooked—especially during the current AI investment boom—but they are consistently present.