Month: Apr 2025

The Troubling Rise of Artificial Intelligence: A Mirror of Modern Ideologies

Artificial intelligence is becoming increasingly prevalent, no longer confined to science fiction. In some industries it may just enhance minor aspects, but in others, it is replacing processes. AI programs today can generate realistic deep-fake videos, simulate voices, create images, write essays, and even compose poems or songs.

While these creations are (mostly) not yet indistinguishable from reality, they are convincing enough to deceive many. Major companies are integrating AI into their operations, often at the expense of human jobs. Customer support has been partially replaced by chat bots. Websites are now flooded with AI-generated articles, and the likes of X are full of bots that use AI to repost a summary just to farm engagement. 

The influence of AI on our future is undeniable. Even this blog was partially written by AI. I stole a transcript from a YouTube video that made some good points, and turned it into a blog using AI. Deleted some parts, rewrote others, shuffled paragraphs around, and mixed in some of my own opinion and information from other sources. 

One thing to always keep in mind is how the creator’s ideas can then become a bias in the algorithms. This was seen in Google’s Gemini, which severely favoured political correctness over accuracy.

Like many discovered weaknesses, it is exploited by people for humorous effect. People asked Gemini to make an image of the Pope or a World War II German Soldier and they got a dark skinned version. Even the founders of Google were turned into Asians. The bias was so extreme, that the only reliable way to get white people was to ask AI to generate absurd racial stereotypes which would then be switched for a white person. This could be abused by asking for a person doing a mild stereotype and it would instinctively choose to draw a dark-skinned person whereas a non-biassed algorithm might have just defaulted to white.

So using Gemini, you couldn’t get a historically accurate image of most people, and could only create images of white people if it was in jest.

It was so bad that you couldn’t even ask for white actors, because that isn’t inclusive. But you can ask for only black, because that is inclusive.

When it comes to impersonating celebrities, it seemed to make out that it cannot impersonate people in the case that the person held right-wing views or provided controversial opinions, but then it had no problem with left-wing opinions.

In a now deleted tweet, there was a thread about the creator of Gemini posting several tweets about left-wing politics, systematic racism, and white privilege. All the usual phrases of woke activists.

Young people in particular will use AI for information, potentially at the expense of critical thinking. As AI becomes more integrated into education, media, and social platforms, it has the power to influence societal narratives, political opinions, and perceptions of history. This raises questions about the ethical responsibilities of AI developers and the potential consequences of unchecked technological influence. Prominent figures like Elon Musk have voiced such concerns.

As AI continues to be a prominent part of our lives, it’s important to understand any underlying bias, and any limitations of what it can and cannot do.

AI-Generated Games: Cutting Through the Hype

I watched this video and found it incredibly interesting.

Explaining the Rise of AI Generated ‘Games’ | AI and Games #78

One fascinating development has been AI-generated game simulations—models trained to generate video game frames based on existing gameplay footage. These systems often resemble playable versions of classic titles like Minecraft or Doom, but in reality, they’re more akin to interactive videos than fully functioning games.

While visually impressive, these AI-generated experiences are fundamentally limited. They operate by predicting the next frame, rather than running a dynamic game engine. This means they perform well under predictable conditions—opening doors, shooting enemies—but can quickly “hallucinate” inconsistencies when a player moves unpredictably, leading to bizarre visual errors.

Despite their novel appeal, these AI-driven simulations are not the future of gaming. The attention they’ve received is largely driven by press releases from AI companies eager to position themselves at the forefront of technological innovation. While these projects highlight advancements in AI model sophistication, they’re far from replacing traditional game engines.

There are three key reasons why these systems are unlikely to make a lasting impact on game development:

1. Consistency Issues

   These AI models generate frames based on prior footage, rather than maintaining a persistent world state. This can result in sudden shifts in location or enemies appearing out of nowhere, making gameplay unpredictable and unreliable.

2. Data and Hardware Limitations

   Training these models requires vast amounts of gameplay data—often spanning years of recorded footage. Additionally, the immense computational power makes them incredibly resource-intensive and requires a prohibitively expensive graphics card. While players love running Doom on unconventional devices, this AI-driven Doom may be the most expensive version yet.

3. Game Stability and Evolution  

   Unlike traditional game engines, these AI models depend on static, unchanging titles for training. They can’t adapt to evolving game mechanics or updates, making them ill-suited for modern game development, which often sees drastic iteration throughout production. Old games like Doom, or the more recent Bleeding Edge have ceased development, making them good choices for this research.

As these AI-generated game simulations continue to emerge, it’s important to approach them with a degree of skepticism. While industry figures like Phil Spencer and Satya Nadella may speculate on AI’s role in game preservation, the real question is: what do the creators of these systems say? The truth is, they aren’t making bold claims about AI reshaping game development—because they understand the inherent limitations.

Video game creation and development remain largely unaffected by these experimental AI-driven projects. Even as generative AI becomes a hot topic, separating hype from reality is crucial. These systems don’t threaten traditional gaming, but they do provide a fascinating glimpse into AI’s capabilities—and its current shortcomings.

Rebase Debate

I’ve written a few blogs about debating issues with the Team Lead. Another argument we had was about the use of Git Rebasing. The blog will be quite long if I go into the detail of what this means, but:

  • Git is a type of source control
  • Source control allows you to see the changes with the date/time they occurred
  • You can create a “branch”, make your changes, then merge many changes at once into the “main” branch.
  • There’s a concept of “merge” which basically keeps the timestamps they were originally made
  • There’s another concept of “rebase” which creates new commits, so changes the timestamps like they have just been made.

This new team always rebase, and end up rebasing as they are developing in their branch. A well-known rule is that if multiple developers are working on the same branch, you cannot rebase it without causing problems to your team members.

I raised this as a potential issue because I saw many upcoming items we need to work on that need multiple developers working on a feature, or needing to work from a shared branch. The Team Lead dismissed because he has apparently never had problems working with rebase before.

As I forewarned, I got hit:

  1. Jay creates folder A with many files
  2. I branch from his changes
  3. Jay moves all those files to folder B
  4. rebases
  5. I then rebase my branch. Git can’t see the move because the history is rewritten. It keeps folder A with the old files and treats them as mine. It adds folder B with Jay’s edited files.

Later on, the Team Lead was hit with something similar.

Team Lead
rebased fine for me
 
Team Lead 
hmm this is fucking me up now
i rebased onto jay's branch which went fine
 
Me
but now there is duplicates all over the shop
 
Team Lead
now i'm trying to rebase onto develop but it's trying to apply jay's commit to it too
 
Andrew
he rebased his branch again
before merging into develop
 
Team Lead 
but it should recognise that my branch starts at my first commit though shouldn't it
 
Andrew
not if you rebased onto his before he rebased again
you just have to drop any of his commits
 
Team Lead 
ah right, not come across that before but makes sense

So if you have multiple developers working in the same branch, you should not rebase once commits have been synced by one or more team members. Rewriting the commit history means Git cannot sync new changes because it sees everything as a new commit.