By guest author: Nielo Wait, VRZ Champions LinkedIn: https://www.linkedin.com/in/nielo/ YouTube: Slopfiction Caveat: These ideas were articulated with the assistance of artificial intelligence — barely legal em dashes and all. Two AIs walk into a bar. Bartender: “Sorry, we don’t serve minors.” As the western AI begins to litigate, the eastern AI forks the bartender, open-sources the quantized version, and shouts, "The next round is on me!" USA, run by lawyers, is trying to legislate its way into AI dominance. China, run by engineers, is shipping fast, hard-coding its own vision of what AI should be. Both are building futures. But the difference in approach is already warping the GenAI landscape — and who gets to shape it. That’s the frame: GenAI isn’t good or bad. It’s just barely legal . Not in the smirking, R-rated LoRa sense. In the sense that the rulebook doesn’t exist yet, the court cases are unresolved, the ethics are wea...
In the world of machine learning, the mention of “deep learning” brings to mind intricate architectures and mind-boggling complexities. But we don't always need huge, super-complex neural networks with hundreds of layers to solve our machine learning problems. So-called “shallow networks” remain relevant for several reasons. Not all problems demand the complexity of deep networks. Shallow networks are computationally more efficient, faster to train, and easier to interpret. They shine in tasks where a simpler model can deliver accurate results. This makes them a valuable tool in the toolbox of machine learning. In this post, we'll have a look at their unique strengths and applications. What are neural networks? Firstly, let’s have a look at neural networks in general (i.e. regardless of whether they are deep or shallow). Neural networks are the backbone of modern machine learning. As the name suggests, they are...