The UK -based technology company SECQAI announced that it has developed the world’s first quantum large language model (QLLM). According to the company’s statements, this new model significantly increases problem solving capabilities and calculation efficiency by combining artificial intelligence and quantum cognition.

SECQAI aims to integrate quantum cognition into traditional artificial intelligence models, to make language processing processes more efficient and to start a new era in solving complex problems. In this context, the company states that it develops a quantum simulator and quantum attention mechanism with a gradient -based learning system and carries artificial intelligence models to an advanced level.

It will be used to develop drugs and materials

Rahul Tyangi, the founder and CEO of the company, said that this development could revolutionize various industries by increasing the interaction between artificial intelligence and quantum cognition. TYYGİ stressed that this technology can be ground in many sectors such as finance, drug development, cyber security and semiconductor design. QLLM will enter a special beta test with certain partners this month. In this process, the practical applications of the model will be tested and the performance will be evaluated.

According to the transferred, the model will be able to strengthen the security protocols by discovering hidden patterns in encryption algorithms. In addition, the model can be used effectively in areas such as risk analysis and fraud detection in the financial sector. The ability to quickly and accurately analyze large volume financial data can ensure that markets are more safe and transparent.

However, what QLLM can do is not limited to these. The model can process complex simulations efficiently to optimize semiconductor designs, while it can make it possible to make real -time decisions in robotics through advanced problem solving methodologies.

On the other hand, there are some restrictions on this technology. Since the cost of quantum infrastructure is quite high, every company is very difficult to adopt this technology. In addition, the need for a large amount of data for the model to work effectively, can bring some difficulties in data access.