Generative AI and On-Premise LLMs for Enterprise

The work of large language models explained in simple terms: Large language models (LLMs) are artificial intelligence (AI) models that are designed to understand and generate natural language by using a combination of statistical analysis and machine learning algorithms. They use natural language processing (NLP) algorithms and language modelling to process and generate text. They are trained on vast amounts of data to learn the patterns, structures, and nuances of language.

When generating text, the model predicts the probability of the next word based on the preceding words. It then selects the word with the highest probability and adds it to the sequence, imitating human language.

By leveraging the capabilities of large language models, enterprises can streamline their operations and improve their overall efficiency.

Among the top applications of LLMs in the Enterprise are document search chatbot, personalised employee training, routine automation, and data analysis.

To implement LLM for your company, you need to find a reliable provider that specialises in developing generative AI solutions for enterprise settings. It is important to consider factors such as on-premise deployment, language support, and security.

Tovie AI has been certified with IBM Cloud and adheres to the strictest security standards in the financial sector. Currently supporting over 30 languages, Tovie AI is a versatile solution that can effectively assist a diverse range of company employees and customers.

To tailor foundation language models like GPT for your business, there are three main techniques:

• Domain-Specific Training Data: training the model on data specific to your industry or business
• Fine-Tuning: training the model on a smaller dataset that is specific to your use case
• Customisation: modifying the model architecture, adding additional training data, or adjusting the model's hyperparameters

By using these techniques, businesses can customise GPT to improve the accuracy and relevance of the model's predictions for their specific needs.

Generative AI functions by first undergoing a comprehensive training phase using a large dataset specific to the desired content. Following this, it enters the generation phase where it creates fresh content, improving with each cycle of feedback. Distinctively, this technology learns from existing data and produces new, analogous yet novel content, creating wide-ranging utility across numerous domains.

Yes. By deploying LLMs on-premises in your private cloud, you can leverage the incredible power they provide and keep full control over how your data is handled, stored, and managed.