Blog - Arkavian

Why George R.R. Martins’s Generative AI Lawsuit Will Cost Authors Even If They Win

AI made a big splash this year as the next big thing in technology. Now that AI is famous, it’s the target of a lawsuit over copyright infringement.

On the 19th of September, George R.R. Martin, the Author’s Guild and a handful of other authors filed a lawsuit against OpenAI, creators of ChatGPT. This follows other lawsuits such as one headlined by Sarah Silverman (which also targeted Meta). Between these two lawsuits, the authors allege that OpenAI’s ChatGPT and Meta’s LLaMA were trained on datasets containing illegally acquired copies of the plaintiffs’ works. Their lawsuit claims the books were illegally acquired from pirate websites and that they didn’t consent to the use of their copyrighted work as training material.

Why Diversity and Inclusion are Keys to AI Startup Success

Artificial Intelligence (AI) is no longer the stuff of science fiction; it has become part of everyday life. In 2022 alone, AI startups received $52.1 billion in funding from 3,396 venture capital deals. Investment figures like this are a strong indicator that AI has great potential to transform our everyday lives.

Rapid growth, however, comes with challenges. In the case of AI, an increasingly pertinent concern is the issue of AI bias. The tech industry has long struggled with diversity and inclusion. According to a 2019 Wired survey, Silicon Valley still suffers from imbalances, with the combined population of Black, Hispanic, and Indigenous individuals making up only 5% of the workforce. In 2023, a staggering 83% of tech executives are white, and only 37% of tech companies have women on their boards. This striking lack of representation extends to AI, where it’s estimated that 78% of global professionals possessing AI skills are male, resulting in a significant gender gap in the field.

Training your AI with images is missing a dimension, video is better

Deepfake videos are becoming easier than ever to make these days, thanks to software advancements that produce better images. Technology is constantly improving, so we can reasonably expect even more mind-blowing advancements in the near future.

But you don’t have to wait around for the next big breakthrough to occur. You can make better deepfakes today with the tools that are already available to you. It’s pretty simple, really: Instead of relying on still photos for training data, use the higher-quality data that videos provide to train your machine learning (ML) model.

So what makes video a superior training tool for AI?

AI Data Collection is Too Hard to do Ethically

All AI models require training data — and most developers get their data unethically. Everyone seems to be doing it: OpenAI was recently hit with multiple lawsuits (more) claiming the company stole internet data to train its popular ChatGPT tool. And Stability AI, the creator of the well-known Stable Diffusion tool, is being sued by Getty Images for copyright infringement for using millions of images without the proper licensing.

These cases are still in the courts, but one thing is certain now: the amount of data required to train a model like ChatGPT is huge — much larger than the amount of data available for most AI developers. Yet most publicly available datasets are licensed for non-commercial use only. That means developers can’t (ethically) use that data to train an AI model if the final product is part of a commercial endeavor.

AI is inconsistent and you have to adapt

Ask anyone on the street what they think about AI, and you’ll probably hear that they’re concerned. That’s to be expected since AI is blowing up today’s headlines, and not always in a good way.

For instance, one thing on many people’s minds is how AI will affect their jobs. That’s a valid fear. After all, technology has changed how we work before. Look at what happened after the industrial revolution and the rise of the personal computer in the 1980s. An estimated 3.5 million jobs disappeared and entire industries went out of existence due to computing and the internet.

The Limits of AI: Why Not Every Problem Can Be Solved with Machine Learning

There’s no denying that AI is a powerful tool. It has revolutionized the way we interact with technology, giving birth to intelligent virtual assistants, self-driving cars, and language processing tools. Some view it as a solution for all the world’s ailments, while others call it a curse that will bring down society as we know it.

In reality, however, it’s not that clear-cut.

The Race for AI Dominance is Fueling an International Arms Race

Read the news on any given day and you’ll see media firestorms about the dangers of AI and fearmongering over robots being developed for warfare. Simultaneously, countries are diving headfirst into AI development and new software is emerging daily. The hustle for AI dominance has our heart rate rapidly rising, reminiscent of the nuclear arms race of the twentieth century.

Why Open Source AI Projects Need a Code of Ethics

The reason AI development has made such impressive strides lately is largely due to the use of open source software. This isn’t just some niche trend — everyone’s using open source AI, from programmers to academics to everyday users.

But here’s the thing: with great power comes great responsibility. Now that AI is everywhere, it’s time to think not just about what it can do, but what it should do. Suddenly, there are endless options, and there is little oversight.

Google is Right to Fear Open Source AI

You wouldn’t expect a behemoth like Google, which has its hands in almost every aspect of technology, to even care about open source and open core technology. But it turns out, it does care. And it’s afraid. Very afraid.

Deepfakes Don’t Use GANs

Deepfakes are everywhere these days, from Tom Cruise TikTok impersonations to fake video of former president Donald Trump resisting arrest. Because the AI engine behind deepfakes is relatively complex and technical, there is a fair amount of misinformation about how these videos are created.