Xiaomi entry into artificial intelligence with MIMO model

Xiaomi has officially eered the competitive arena of artificial ielligence by iroducing the MIMO artificial ielligence model. The move puts Xiaomi alongside other technology gias in the world.

Scholars of artificial ielligence appears to be more attractive day by day. Xiaomi has eered this competitive arena with the official iroduction of MIMO. This is not just a big language model, but Xiaomi’s goal is to enhance the reasoning capabilities with this model.

Xiaomi MIMO Artificial Ielligence Iroduced

According to Xiaomi, MIMO is an artificial ielligence model with 7 billion parameters. This number does not look so great compared to some of the existing gias. But Xiaomi claims that Mimo shows a performance beyond expectations in mathematical reasoning and code production. The company says the MIMO operates at a much larger level with larger models and is even capable of competing with models such as O1-Mini owned by Openai and QWen with 32 billion parameters from Alibaba.

It is not easy to achieve such an argume from a smaller model, and Xiaomi is aware of it. Xiaomi says of the key to the success of the model that this is due to maximizing capacities in the same basic 7B model, which includes the adoption of highly measured strategies in both pre -training and post -training stages. And a poteial advaage is that relatively small model that will be suitable for businesses that do not have massive GPU clusters.

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It seems that the foundation of MIMO’s work is a highly optimized use of a training process. Xiaomi says they are seriously focused on managing their data, which includes improving the process of processing raw data, upgrading the tools used to extract related texts, and applying various filtering layers. Therefore, they do not simply inject data io the system, but they choose very carefully.

They compiled a specialized data collection that coained about 200 billion token. In the following, they used a three -stage composite strategy and gradually trained the model in three phases and on a total of 25 trillion token. They also used a technique called Multiple-Token Prediction, which not only improved the performance of the model, but also helped to produce responses faster.

After creating the initial structure, they adjusted it using reinforceme learning (RL). The process included feeding the MIMO model with about 130,000 mathematical and programming issues. It is importa to note that these issues were approved by the use of law -based systems.

Xiaomi has not just released a copy of the MIMO, but the MIMO-7B series coains four versions that you can check:

• MIMO-7B-Base: The basic model is said to have a strong argume poteial.
• MIMO-7B-RL-ZERO: A reinforceme learning model from which the basic version is taught.
• MIMO-7B-SFT: A version created using precise monitoring adjustme (showing examples to it).
• MIMO-7B-RL: A reinforceme learning model taught from the SFT version and a model that Xiaomi tests against models such as O1-Mini.

Xiaomi has made the eire MIMO-7B set of artificial ielligence. You can find these models in Hugging Face. If you wa to know deeper technical details, a complete report has been published in GitHub.