Post by riyasimla2000 on Oct 26, 2024 9:13:41 GMT
Transformer models have already become the basis for many modern services, such as LinkedIn, Netflix and Spotify. They allow you to personalize recommendations, create individual offers and anticipate user needs. One example of the use of this technology is the GPT chat, which is a generative model based on transformers. In fact, all these services use this very technology, offered by Google in the form of the Bert product. The eSputnik experience The eSputnik company also actively implements transformative models in its solutions. In particular, two years ago they presented a new version of the recommendation algorithm, which works on the basis of GPT. This was the most noticeable improvement in the company's 12 years of existence, and the results were not long in coming.
Read also: How new AI algorithms increase the effectiveness of wordpress web design agency marketing campaigns Impressive results thanks to new algorithms In different industries, transformer models give different effects, but always increase efficiency. For example, in the field of electronics, sales growth from the block of recommendations reached +40%. Other industries such as tools saw +20% growth, and the fashion and accessories industry tripled referral sales! Even pet products show a two-fold increase in sales thanks to referral blocks. What is a transformative model What is a transformative model and how does it differ from traditional models? The transformer model, unlike traditional algorithms, is able to take into account the context. She can understand the logic and sequence of relationships between goods.
While the traditional model simply "sees" product views and builds on that, the transformative model analyzes the overall context. Mechanism of operation of traditional algorithms and transformer models For example, if the traditional model sees that a user has viewed a bicycle, a water bottle, and sports gloves, it will simply suggest additional sports products. The transforming model will understand that this user is a cyclist and will offer a helmet or special clothing. Major improvements to the model Features of transformer models Adaptability to heterogeneous data. Transformers takes into account different types of data, such as product views, likes and reviews, which greatly improves the accuracy of recommendations. Easy integration of new product categories.
The model automatically adapts to new categories, without the need for intervention in business logic. Context processing. The model is able to take into account the sequence of events and their connection, which allows creating more accurate recommendations. One of the classic examples of the advantages of transformers is "cold start". If the traditional model needs some time to adapt to new products, the transformative model quickly picks up new data. For example, a new sneaker with an AID that was not available before will be taken into account and offered to users much faster. Transformer models better understand the context Read also: Path to growth: how AI technologies help PUMA Ukraine increase sales Benefits for eSputnik customers Thanks to the new transformative models, the company does not need to implement changes in business logic or configure scripts.
Read also: How new AI algorithms increase the effectiveness of wordpress web design agency marketing campaigns Impressive results thanks to new algorithms In different industries, transformer models give different effects, but always increase efficiency. For example, in the field of electronics, sales growth from the block of recommendations reached +40%. Other industries such as tools saw +20% growth, and the fashion and accessories industry tripled referral sales! Even pet products show a two-fold increase in sales thanks to referral blocks. What is a transformative model What is a transformative model and how does it differ from traditional models? The transformer model, unlike traditional algorithms, is able to take into account the context. She can understand the logic and sequence of relationships between goods.
While the traditional model simply "sees" product views and builds on that, the transformative model analyzes the overall context. Mechanism of operation of traditional algorithms and transformer models For example, if the traditional model sees that a user has viewed a bicycle, a water bottle, and sports gloves, it will simply suggest additional sports products. The transforming model will understand that this user is a cyclist and will offer a helmet or special clothing. Major improvements to the model Features of transformer models Adaptability to heterogeneous data. Transformers takes into account different types of data, such as product views, likes and reviews, which greatly improves the accuracy of recommendations. Easy integration of new product categories.
The model automatically adapts to new categories, without the need for intervention in business logic. Context processing. The model is able to take into account the sequence of events and their connection, which allows creating more accurate recommendations. One of the classic examples of the advantages of transformers is "cold start". If the traditional model needs some time to adapt to new products, the transformative model quickly picks up new data. For example, a new sneaker with an AID that was not available before will be taken into account and offered to users much faster. Transformer models better understand the context Read also: Path to growth: how AI technologies help PUMA Ukraine increase sales Benefits for eSputnik customers Thanks to the new transformative models, the company does not need to implement changes in business logic or configure scripts.