DeepSeek Introduces Engram Technology

 

DeepSeek reveals a new secret: Smart memory dramatically boosts AI efficiency

Modern AI models possess enormous capabilities, yet they still suffer from a fundamental problem that most users may not expect.This is waste. Despite training AI models on a huge amount of online content, they still deal with simple concepts as if they are seeing them for the first time.

Imagine an employee working in a huge library who, whenever asked for a well-known book, re-examines the catalog page by page to locate it, instead of simply remembering where it is. This behavior is similar to what current artificial intelligence models do, reprocessing familiar concepts each time, resulting in a significant and unnecessary waste of energy and computational power..

This is where innovation comes in.DeepSeekThe one called Engram, which offers a radical solution to this problem, is a super-powerful intelligent memory system that allows the model to find and instantly retrieve common meanings, which is exactly what the human mind does, thus increasing efficiency and significantly raising the level of thinking and reasoning.

 

First conclusion: Artificial intelligence wastes billions of operations on obvious things.

The main problem that cameEngram's solution is that AI models treat familiar information as if it were new every time. Instead of directly recognizing common concepts, they deconstruct and analyze them from scratch, much like a student who has to read the definition of a simple word from the dictionary every time they hear it, even if they have used it hundreds of times before.

He worksAn engram acts as a time-saving memory, storing readily available meanings for recurring patterns, allowing the model to access them directly without being bogged down in troubles or burdening the deep neural network with routine tasks. The result: a greater focus on genuine thinking.

 

Second conclusion: The ideal brain for artificial intelligence is a combination of thinking and memory.

innovationDeepSeek is not just about adding memory; it came to find the right balance. Most modern models rely on what is called an "expert mix," where only the specialized parts, and not the entire model, are activated for the task.

She did  DeepSeek conducted several experiments and found that allocating 20 to 25% of the model's additional memory capacity is the optimal balance. This is because excessive memory can impair the ability to think deeply, while insufficient memory leads to the model wasting energy on reconstructing simple or intuitive concepts.

Thus,DeepSeek offers a practical recipe for designing AI models to be more efficient in the future.

 

Third conclusion: Better memory means deeper thinking

The biggest surprise she presentedDeepSeek, through the innovation of Engram, was not only improving the model's performance in information retrieval, but there was also a clear increase in the model's logical, mathematical, and programming skills.

The reason is that traditional models consume the first few layers in processing repetitive details. However, withIn Engram, the first layers get rid of this burden, allowing the deeper layers to focus on analysis, reasoning, and solving complex problems.

In other words, the model becomes "deeper" and faster, as if the model has acquired additional layers without increasing its actual size..

 

Fourth conclusion: Exceptional performance in handling long texts

He appearsEngram has a remarkable advantage, especially when dealing with long documents. This advantage is evident in tasks that require finding specific information within a huge amount of text. This process is known as looking for a needle in a haystack.

Thanks to this technology, smart memory handles the processing of recurring patterns, enabling the model to focus on ideas, the relationships between them, and the overall context. This leads to a significant leap in the accuracy of comprehension and tracking across long texts..

 

Fifth conclusion: Massive memory without loss of speed

One of the most important featuresEngram is a very practical and scalable solution. DeepSeek has proven that adding massive memory modules does not result in a noticeable slowdown in performance.

In experimentsIn DeepSeek, a massive memory layer was loaded onto the regular CPU memory instead of the graphics processor, but the loss of processing speed was only less than 3%.

This means that AI models can be supplied with very large amounts of memory without high cost or annoying slowdowns.In speed

 

Conclusion

It formsEngram represents a paradigm shift in the way artificial intelligence systems are developed. It goes beyond simply increasing the size of models as the sole solution, emphasizing that innovation in structure and design—inspired by the workings of the human brain—can be more impactful and effective. Memory is no longer merely a storehouse of information; it has become a fundamental element that enables the model to access deeper levels of reasoning and analysis.