The $67 billion power grab signals the next BIG opportunity in AI investing
A new record was created on Wall Street last week. Not by a technology company, chipmaker or an AI startup. Instead, it came from the power industry.
Read MoreSouth African Investor
Three AI stocks to watch in 2026: The companies getting rich from AI – without building a single model
Almost every AI conversation eventually gets to the models – ChatGPT, Gemini, Claude, Grok. That’s where the public attention goes. That’s what gets the headlines.
But behind every one of those models is a layer of infrastructure that most investors never think about: the networks that move the data, the pipes connecting the processors, and the teams cleaning and labelling the training data that makes the intelligence possible in the first place.
These are the picks-and-shovels of the AI gold rush. And right now, three companies operating in this space are posting numbers that are genuinely hard to ignore.
Xi, Trump and the Thucydides Trap
“Can China and the United States overcome the so-called Thucydides Trap and create a new paradigm of major-country relations?”
That question is not neutral. It is not diplomatic small talk. It is a frame. And once you understand the frame, the entire relationship, and everything that comes out of Beijing this week looks very different.
After 59 Years, the UAE just walked out on OPEC. Here’s why it matters…
Recently the United Arab Emirates (UAE) did something that would have seemed almost unthinkable a year ago. After 59 years of membership – since Abu Dhabi joined the cartel in 1967 – the UAE announced it is leaving OPEC, effective May 1.
Read MoreCould Cerebras looming IPO “Out-Chip” Nvidia
Cerebras Systems. Founded in 2015 in Sunnyvale, California, Cerebras was built by a team of semiconductor veterans – several of whom held senior engineering roles at AMD, Nvidia’s biggest GPU rival. From day one, they set out to solve a problem that had been quietly frustrating the AI world for years: standard chips, no matter how powerful, are small. AI models are enormous. And making thousands of small chips talk to each other quickly enough to train or run a cutting-edge model is messy, expensive, and slow.
Their answer wasn’t to make a better version of what already existed. It was to throw out the rulebook entirely.
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