AI at Any Cost? This Video is a much watch!

Watch the video here: (you really should)

Firstly apologies, it’s been over 6 months since my last blog post. I’ve been absolutely flat out delivering AI projects and training with a brilliant range of clients, so my socials took a back seat for a while.

But this week, something popped up on my feed that completely stopped me in my tracks. Despite being 17 minutes long this video stole my complete attention for that time. It looks into Elon Musk’s xAI project in Memphis and let’s just say, it hit a few chords with me.

This isn’t a promo piece or a shiny launch. It’s a genuinely uncomfortable but necessary look at what unchecked AI development can really look like in the real world. And if you’re working with or around AI (which let’s face it, most of us are), I’d really encourage you to take the time to watch it.

Some of the takeaways that resonated with me were:

1. An AI arms race is well underway, and the environment is the casualty

One of the key takeaways from the video is just how fast the global race for AI dominance is moving and how environmental considerations are being left in the dust.

We’re talking about huge supercomputing sites that use enough energy to power entire cities, being built at record pace. And when it comes to carbon emissions or pollution? Not a lot of transparency. Not a lot of accountability.

The Memphis site is powered by dozens of gas turbines, reportedly running without permits or pollution controls. Local residents are raising serious health concerns and there’s a strong sense that no one is really listening.

2. Musk is playing catch-up, and he’s not hiding it

Elon Musk is quite open about the fact that he was late to the AI game. According to the film, he made the decision that the only way to compete with companies like OpenAI was to build his own supercomputer and quickly.

And it seems that "speed at all costs" became the operating model. The usual checks and balances, especially around local engagement or environmental planning, appear to have been skipped. It's a case study in moving fast and breaking... well, pretty much every rule.

3. US regulators are supporting AI growth, even at the expense of the planet

One of the more surprising parts of the documentary is hearing from the head of the US Environmental Protection Agency. They suggest that supporting AI growth is part of the agency’s mission.

That raises some big questions. If the EPA is now backing rapid AI expansion, even when it involves industrial-scale fossil fuel use and little oversight, what does that mean for communities on the ground? Who’s actually protecting the public interest?

4. Political support is making this possible

The film highlights how the political climate has played a big part in enabling this kind of build. Cuts to EPA funding (Instigated by Musk!) and a deregulatory agenda have made it far easier for large tech-led projects to push through, even in communities that are already vulnerable to pollution and underinvestment.

South Memphis is the example used in the film, but it clearly wont be the last.

Why This Matters for Businesses Using AI

At Embrace AI Training, we spend a lot of time helping businesses adopt AI in a practical, ethical, and sustainable way. We don’t just talk about prompts and productivity. We also talk about:

• When not to use AI

• The energy demands of large language models

• Whether AI is really adding value to a task or just being used because it can

This film is a clear example of what happens when those questions aren’t asked. A large-scale project goes ahead, unchecked. The people living nearby pay the price. And the AI arms race rolls on.

The image below is from a slide on our course. If you a re old enough to understand it then it won't need any explanation. For those of you who have no idea, check out the film "It's a Mad Mad Mad Mad World!"

Final Thoughts

Yes, the video is long. And yes, it’s heavy in parts. But if you're serious about building or using AI responsibly, it’s one of the most important things you could watch this month.

It gives you a front-row seat to what’s happening right now in the world of AI infrastructure. Not five years from now. Not in theory. Today.

And it leaves you with one very clear question:

Just because we can build it, should we?