What is DEEPSEEK AI and Why it is so overhyped and biased?

The world went nuts over this new Chinese AI model called Deepseek things are going to accelerate even more it’s a big deal because now China is officially a major player in the world of AI, which is going to change things fast. What makes this AI special is that it has a kind of “thinking” ability, meaning it’s better at understanding and making decisions, kind of like how humans think. Today, we’re going to talk about Deepseek and Deepseek R1. We’ll explain why people are making a bigger deal out of it than they should and we’ll also check if it’s actually biased in any way.

DeepSeek is a machine learning algorithm is about taking a complex model that might be too slow or complicated to use, and simplifying it so it works faster and more efficiently, while still keeping its smartness and accuracy.

Here’s an analogy:

Let’s say you have a super-smart robot (the complex model), but it’s really big and slow, like a huge computer. Now, you want to create a smaller robot that can still do all the same tasks but way faster and doesn’t need so much power. It is the process of teaching this smaller robot to copy the behavior of the bigger one, so it works well without all the extra weight

DeepSeek is a type of AI that was made in China, and like other AI models created in specific countries, it has certain rules or limits about what it can talk about. For example, it’s designed not to discuss things that could be sensitive or controversial, especially topics related to the Chinese government.

While this might be done to keep things safe or to follow the country’s laws, it also creates a problem. By avoiding certain subjects, DeepSeek might only show part of the picture and leave out important information. So, instead of giving a full, balanced view, the AI might hide some answers or only show information that fits within these rules, which can show how things really are.

In simpler terms, it’s like if someone tells a story but leaves out certain parts—you get a version of the story, but not the whole truth.

So, if you ask anything about China’s controversy, you won’t get an answer.

One of the biggest problems with fixing bias in AI models like DeepSeek is that we don’t know exactly how they work. The people who create these models don’t always share the full details about how they were trained, what information they were fed, or how they decide what to include or leave out.

It’s like having a mystery box. We don’t know what’s inside or how it was put together. So, if the AI shows some bias or gives unfair answers, it’s really hard to figure out exactly why or where it came from.

Without knowing all the details, it’s tough to fix the issues, hold the creators responsible, or make sure the AI is fair to everyone.

To fix bias in AI models like DeepSeek, we need to take several important steps:

1. Diverse Training Data: We need to make sure the AI learns from lots of different voices and experiences, especially from groups that have been left out in the past. This helps the AI understand everyone, not just one type of person.
2. Transparency and Clear Explanations: We also need the people who build AI to be open about how they do it—like how they train it and what data they use. If we know more about how the AI works, it’s easier to spot and fix any unfairness.
3. Finding and Fixing Bias: Researchers are working on ways to find and fix bias in AI, but this is still a work in progress. We need to keep improving these methods so the AI can be fairer over time.
4. Clear Rules and Ethics: We also need rules and guidelines to make sure AI is used responsibly. This helps ensure that people are held accountable for making sure the AI is fair and doesn’t harm anyone.

Bias in AI is a tricky problem, and solving it isn’t easy. But by working together—researchers, developers, government, and the public—we can build AI that works well for everyone, not just a few.

DeepSeek, incorporates safety measures designed to prevent the generation of harmful or biased content. However, these measures are not foolproof. Research has shown that can still generate biased outputs, highlighting the need for continuous improvement and more robust safety protocols. This is an ongoing arms race, with researchers constantly trying to stay ahead of the evolving capabilities of these models.

The world has never seen a piece of technology adopted at the pace of AI. Many AI companies have rapidly grown into critical infrastructure providers without the security frameworks that typically accompany such widespread adoptions. As AI becomes deeply integrated into businesses worldwide, the industry must recognize the risks of handling sensitive data and enforce security practices on par with those required for public cloud providers and major infrastructure providers.

DeepSeek explained: Everything you need to know