r/TechGawker

Just as US-EU trade tensions seemed to be cooling, a new flashpoint has arrived.

Trump has threatened a 100% tariff on any country imposing a digital services tax on American companies, and made clear it would supersede any existing trade agreements. This comes less than two weeks after the EU approved a deal designed to cut tariffs on US goods.

The tactic has worked before. Canada repealed its 3% digital services tax after a similar ultimatum to keep trade negotiations alive.

But the EU is a different beast. France already has a DST in place and has previously said it won't bow to US pressure. Germany and Belgium are planning their own versions. The core disagreement, whether large American tech companies pay enough tax on European revenue, has been running for years with no resolution in sight.

For ecommerce sellers operating across borders, this isn't abstract. A 100% tariff on goods from major EU trading partners means higher sourcing costs, more expensive imports, and consumers on both sides paying more for everything.

A few things worth discussing:

Do you think EU countries will back down the way Canada did, or is this a different situation entirely? If these tariffs do go into effect, which product categories do you think get hit hardest?

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In this episode, we follow the money—literally. Who's funding the lab-meat revolution? Who benefits from the push toward synthetic and modified food systems? And what does Bill Gates' massive portfolio of bets on "fake food" tell us about where the food industry is headed?
We examine the corporate networks, venture capital flows, and policy influence behind lab-grown meat, plant-based alternatives, and genetically modified food technologies. We look at who's investing, what they stand to gain, and what it means for food sovereignty, agricultural workers, and your plate.
Topics covered:

Bill Gates' food tech investments and portfolio strategy
Lab-grown meat companies: funding, timeline, and profit models
Synthetic biology and the corporate push for food system transformation
The intersection of tech billionaires, agriculture, and policy
Food sovereignty vs. corporate food control
What this infrastructure means for consumers in practice

SOURCES & FURTHER READING: https://youtu.be/urEy-MdU7Vs?si=uM4RAgljP2hbfMRO, https://youtu.be/7XvHnW\_XT18?si=N7XWoiK2F4Qw\_lcO, https://youtu.be/KZKkS6aFlpw?si=R-1mUiErX4xVEFjW, https://youtu.be/RZqYSkoQ-xg?si=82sdQxmPxHQMF2YM, https://youtu.be/Y0lsLnXX4U8?si=qB\_IgVSVOUv8uvb, https://youtu.be/Gn9z1FgHC-8?si=4LDFDbVf6\_V7tlTX, https://youtu.be/\_ce0IpCi8\_k?si=xY0tFGvAq18Gfz90, https://youtu.be/b9iADoVjZ1w?si=HKBKuMQhUK-X0p8J, https://youtube.com/shorts/mV8KsV-FP4c?si=QLxGsxun-7zoqMTZ,

The tech industry is quietly facing a massive financial reality check regarding artificial intelligence. Ed Zitron recently went on CNBC and laid out the bear case for companies like OpenAI and Anthropic, essentially calling the current landscape a hardware based business model disguised as software innovation. The core problem is that these generative models are incredibly expensive to run and they lack a clear path to profitability because enterprise customers are not seeing a return on investment. Instead of creating efficient software, these companies are basically encouraging users to burn through compute tokens to justify their astronomical valuations.

Here are the key takeaways from the financial breakdown:

• Massive cash burn: OpenAI reportedly burned through over $20 billion in 2025 alone.
• No enterprise value: CEOs across the sector are starting to admit that businesses cannot accurately measure ROI from these models due to inherent unreliability.
• The Oracle warning: Oracle is currently building over 7 gigawatts of data center capacity for a single AI customer, but they openly acknowledge the risk of nonpayment if the AI startup bubble pops.
• Obscured growth: Major tech giants are allegedly masking their own AI revenue failures by conflating it with the natural growth of their other established cloud services.

Even if the software side of the AI boom turns out to be a massive miscalculation, the physical infrastructure being built right now is very real and requires a staggering amount of raw materials. Hyper-scalers are locking down gigawatts of power, which fundamentally requires immense physical resources for grid expansion and data center construction. In the context of this domestic infrastructure buildout, Gunnison Copper (OTC: GCUMF) is advancing an in-situ copper recovery project in Arizona that aims to supply the base metals required for these large scale power and electrification demands. Whether the AI bubble bursts or not, the demand for the physical hardware and the power grid upgrades to support it is already locked in by these massive capital expenditure commitments.