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Gold’s Gleam: Caution Amid The Rally

Gold prices are surging, with the SPDR Gold Shares (GLD) fund up about 11% in 2025 and returns climbing roughly 42% over the past year. Gold futures, too, are on the rise—up around 10% year-to-date and 36% higher than last year. By contrast, the S&P 500 has barely moved in 2025, gaining only 1.5%, and has risen 17% over the past year.

Yet, as the allure of the precious metal intensifies, seasoned investors are urging restraint. Certified financial planner Lee Baker of Claris Financial Advisors recalls, “I didn’t get any calls from clients about gold a year ago. Now, I get them regularly.” He cites Warren Buffett’s timeless advice: “Be cautious when others are greedy, and be greedy when others are fearful.” Baker warns that while the current fervor is tempting, the typical investor should limit gold allocation to no more than 3% of a diversified portfolio—lest they fall into the classic trap of buying high and selling low.

Why are gold prices on the rise? The answer lies in its enduring reputation as a safe haven during turbulent times. Investors flock to gold amid uncertainty, with recent US sanctions against Russia acting as a turbocharger for returns. These sanctions have spurred central banks, particularly in China, to boost their gold purchases instead of U.S. Treasury bonds, aiming to safeguard their reserves from potential geopolitical strife. Moreover, many see gold as a hedge against inflation, even though the data supporting that view remains mixed.

Samir Samana, senior global market strategist at Wells Fargo Investment Institute, notes, “In times of real crisis, bonds have shone brighter than gold.” His perspective underscores that while gold may shine during periods of high uncertainty, its rally might be unsustainable without a prolonged crisis.

For investors, the takeaway is clear: while gold’s current surge offers attractive returns, caution is paramount. As the market faces potential headwinds, following Buffett’s contrarian wisdom may help avoid the pitfalls of an overheated market. In the world of investing, where timing is everything, it’s not just about chasing returns—it’s about staying disciplined when the herd runs wild.

Meta Unveils 816 Billion-Parameter AI Model For Mac, But It Requires 1TB Of RAM

Meta has introduced what it describes as the most capable open-weight AI model available in the United States, making a strategic bet on Apple’s Mac ecosystem. The release reflects the company’s ambition to strengthen its position in open AI while bringing advanced models into professional development and creative workflows.

A Powerful Model With High Hardware Requirements

Called Muse Spark Open, the model has 816 billion parameters and a context window of 1 million tokens. Meta said benchmark results published on Thursday show it outperforming other widely used open-weight systems across key evaluations.

Natively multimodal, Muse Spark Open is designed for complex coding and agentic tasks, extending beyond conventional chatbot use. However, local deployment requires substantial computing power. According to Engadget, the model needs at least 1TB of RAM, with the best performance expected on a Mac Studio equipped with Apple’s M5 Ultra chip. These requirements may limit local use to developers and organisations with access to high-end hardware.

Built For Real-World Development

Meta has paired Muse Spark Open with Muse Code, its AI coding terminal, and tested it across agentic workflows. In one project, the model helped develop a Mastodon client, handling bug fixes, new features and the build process.

The company also deployed the model in DaVinci Resolve, the professional video-editing platform, where it reviewed and cropped footage. These examples demonstrate Meta’s aim to position open-weight AI as a tool for practical production work, from software development to creative tasks, rather than just research demonstrations.

The Strategic Case For Open-Weight AI

Open-weight models give developers and organisations greater flexibility to customise AI, integrate it into internal tools and build specialised workflows. Depending on deployment, they can also reduce costs and provide more control over infrastructure than relying entirely on proprietary services.

However, access to model weights does not eliminate the cost of running advanced AI. Muse Spark Open’s reported memory requirements could make API access a more practical option for many developers than local deployment.

Expanding Access Beyond Mac Hardware

Meta is making Muse Spark Open available through multiple API platforms, allowing developers to use the model without running it on their own machines. This broadens access beyond users with high-end Mac hardware while retaining the option of local deployment for those able to support it.

The release combines Meta’s push to strengthen its position in the open-weight AI ecosystem with a focus on professional users. Wider adoption will depend on the model’s performance, practical usefulness and the resources required to run it.

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