Smart Diversification & Intel Bounces Back

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The S&P 500 is up for eight consecutive weeks. The ‘magnificent seven’s’ profits in Quarter 1 were 63% higher than last year. The other 493 companies still increased profits by 17%. What’s next for the stock market? Can it continue despite higher interest rates? A possible peace deal in the Middle East might lower oil prices and send markets into higher positive territory. Nigel Green deVere, CEO, explains.

Ensure that, from an investor’s perspective, you have diversification. Why? Because the world can change. Despite AI continuing to grow and opportunities in the energy sector, gold, and fixed returns, volatile markets are the new normal.

 “That is why smart diversification is always the best investment.”- Nigel Green.

Smart diversification means talking to a financial adviser and looking for the best opportunities and then diversifying sectors and asset classes. This allows for a robust portfolio that can earn you money in the future.

Heading into the second half of the year, we see new ‘Uber’ IPO listings. SpaceX will be listing soon, and Anthropic and OpenAI are likely to follow. Could the magnificent 7 become a magnificent 10?

Watch Nigel’s full video here.

Intel, a company that seemed doomed last year, has struggled to keep up with competitors in the AI race. Forward to 2026, and the chipmaker’s shares have risen 225%. Why? There are talks of an agreement to supply Apple with chips, a tie-up with Musk’s ‘Terafab’ project and some significant supply deals with cloud customers.

The AI boom has been focused on graphics processing units (GPUs), which are used for training large AI models. Intel’s biggest push was its CPU components that anchored servers and PCs.

AI training models rely on GPUs, but once the model is built and put to work answering questions, a phase of inference takes place – (when AI ‘agents’ start performing tasks on their own), CPUs do more of the coordinating. We see a move back to CPUs for established AI models.

Training setups might run eight GPUs for every CPU, Inference runs around 4 to one, and agentic work might even out the balance. As AI models develop, the need for CPUs will increase.

Please note, the above is for educational purposes only and does not constitute advice. You should always contact your adviser for a personal consultation.

* No liability can be accepted for any actions taken or refrained from being taken, as a result of reading the above.

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