AWS has increased prices for reserved AI GPU capacity by around 20%, highlighting the growing shortage of high bandwidth memory and advanced chips. As demand outpaces supply, AI development costs are rising, making large scale model training and deployment more expensive.
Anthropic’s reported 1.4 GW Australian AI tender signals a major investment opportunity, but also a harder sovereignty question: will Australia and the Global South build capability inside this frontier infrastructure, or remain dependent on foreign chips, models, permissions and inference margins?
At midyear, the AI race has become a contest for global power. Energy, chips, cybersecurity, capital markets and state intervention now shape who controls the inference economy, who pays for it, and who is left exposed in the next industrial order of machines, markets and sovereignty to come ahead.
It’s no secret that businesses around the world are adopting AI and automation, with a study from IBM showing roughly 30% of IT professionals already relying on new AI and automation tools.
But is anyone really surprised? Studies already show that AI can boost worker productivity by as much as 14%. So why don’t we all just stop while it’s still a fair fight and let AI take over everything?
Almost one-in-four companies are adopting AI because of labor or skills shortages, and 30% of global IT professionals say employees at their organization are already saving time with new AI and automation software/tools. - IBM
Well some companies have taken that line of thinking to heart. An entertaining article by The Verge was published recently, and shows what seems to be a seller on Amazon forgetting to check an automated ChatGPT plugin before publishing it’s ‘work’:
Amazon responded to The Verge saying:
We work hard to provide a trustworthy shopping experience for customers, including requiring third-party sellers to provide accurate, informative product listings. We have removed the listings in question and are further enhancing our systems. - Amazon spokesperson Maria Boschetti
This isn't just a one-time thing; it seems like there's a trend of AI-created content causing problems on online marketplaces, and also X (formerly Twitter):
Despite the removal of the products, this mishap highlights the risks of using AI and automation unchecked. It’s unfortunate that Bethesda Game Studios couldn’t read this article before replying to lots of negative reviews on their latest game ‘Starfield’.
Customer feedback and interaction is often considered essential in business, and gathering feedback from your audience can serve invaluable to improving the product. However, many have speculated that Bethesda may have used a bot to respond to the massive amount of negative reviews they got on steam, with a Youtuber even attempting to recreate the review responses with his own prompts.
Bethesda’s hilarious response to bad Starfield reviews #gaming #bethesda #starfield pic.twitter.com/LussZAPqjE— Busch League Gaming (@BuschLeagueGMNG) January 13, 2024
And it’s not hard to see why. Below are two different responses from Bethesda:
Four paragraphs elicit a large response from Bethesda.
A single word labelled as a bad review gets an almost identical response as above.
Whilst not impossible to be human written, it’s hard to believe the same team would apply such a similar amount of effort in replying to a 4 paragraph review (review and response 1) as they would with one that simply says “midfield” (review and response 2) (a play on the name starfield). If Bethesda wanted to damage their reputation they certainly picked the right method.
So, a couple of companies got it wrong, but that still doesn’t make AI boosted productivity any less tempting - just make sure your customers don’t know. Unless you should? A recent study at MIT discovered that sometimes AI generated content is in fact received better than human generated content.
So, should companies keep it under wraps or should they take artificial intelligence and automation in their stride and embrace it fully and publicly? Well, the verdict’s still out but stay tuned as I’m sure we’ll see more example of companies getting it wrong, AND right in the not so distant future.
AWS has increased prices for reserved AI GPU capacity by around 20%, highlighting the growing shortage of high bandwidth memory and advanced chips. As demand outpaces supply, AI development costs are rising, making large scale model training and deployment more expensive.
The memory war exposes AI’s harder truth: power now sits in fabs, wafers, export licences and trusted supply. Apple, Micron, Nvidia, China, South Korea and Japan are no longer fighting over chips alone, but over dependence, pricing and the pace of intelligence itself across global markets, in 2026.
AI’s memory bottleneck is now reshaping the chip war. Apple’s search for Chinese supply, Micron’s pricing power, South Korea’s expansion and Nvidia’s HBM demand expose a harder truth: the AI boom is becoming a test of cost, sovereignty and global dependence across every device and data centres now.
Broadcom’s $35 billion AI XPV Platform with Apollo and Blackstone signals that frontier AI growth is now constrained by power, silicon and data center capacity, not algorithms, pulling private equity, energy policy and infrastructure regulation into the core of the AI race.
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