Why your brand should invest in its own LLM


Large language models can fundamentally transform how your brand interacts with its audiences, ensuring that all communication—both internal and external—is consistently on-brand and aligned with your strategic objectives. Investing in your own model allows for fine-tuning to reflect your brand’s unique voice, terminology, and values. This can help you deliver personalised customer experiences and maintain cohesive communication to strengthen your brand identity and improve engagement across all touchpoints.

Should you use publicly open models like OpenAI’s GPTs?
It’s a crucial decision to make: should you opt for a readily available solution like the trainable GPTs from OpenAI, or invest in building your own language model from the ground up? This choice isn’t just about the immediate ease of integration; it’s about considering the long-term strategic benefits and challenges for your brand. Here are some key factors to consider:

1. Data Control and Privacy
With your own language model, you can ensure that all data handling happens within your control and complies with strict privacy laws like GDPR. This control is essential when dealing with sensitive customer information, which may not be securely managed by public models.

2. Achieving a Custom Model
While public models like OpenAI’s GPTs are general-purpose and adaptable, even extensive training on specific data does not allow these models to alter their core structure, limiting their effectiveness in specialised scenarios. In contrast, a custom model built from the ground up can integrate seamlessly with your existing systems and cater precisely to your brand’s unique requirements.

3. Competitive Edge
Owning a unique model can significantly differentiate your brand in the market. It enables you to offer innovative features that set you apart from competitors relying on generic, public tools.

4. Strategic Independence
Building and owning a language model perfectly aligns with your long-term business strategies, offering your brand the agility to adapt quickly to new market trends without depending on third-party development timelines.

How to go about developing your own LLM?
If you are looking to develop your own language models with minimal technical overhead, several platforms offer robust, ready-to-use solutions that can be deployed on-premises. Here are some accessible options:

1. Hugging Face Transformers

This platform provides a vast array of pre-trained models that are easy to customise and deploy. Hugging Face also offers simple interfaces for training and fine-tuning models, making it a great starting point for companies without deep AI expertise.

What’s special about Hugging Face is that it offers a plethora of NLP tools that can be used to analyse customer sentiment, automate customer service responses, and personalise marketing messages.

2. Amazon Web Services (AWS)

AWS stands out as a premier choice for brands looking to develop their own language models. With tools like Amazon Q for custom model creation and Amazon Bedrock for scaling, AWS offers a robust and comprehensive suite of solutions. Their powerful infrastructure, with advanced GPUs and custom chips like Trainium and Inferentia, ensures efficient and cost-effective development.

    Additionally, AWS provides services such as SageMaker, which simplifies the entire machine learning process, and the Nitro System for enhanced performance and security. By leveraging AWS’s advanced tools and infrastructure, businesses can confidently build, train, and deploy their own language models, driving innovation and growth.

    3. RapidMiner

    While RapidMiner is primarily a data science platform, it can be used in content creation by analysing trends and generating insights from data, which can inform content topics and strategies. It offers an intuitive, graphical interface that simplifies the process of building, training, and deploying machine learning models. It’s well-suited for teams that prefer a visual approach to model development and require a tool that integrates easily with existing data sources.

    RapidMiner is particularly effective for analysing customer data and deriving insights that can inform marketing strategies. It can help you segment customers based on their behaviour, predict churn, and optimise marketing campaigns through predictive analytics.

    4. Microsoft Azure Machine Learning

    For brands with a preference for Microsoft environments, Azure Machine Learning provides a comprehensive suite of machine learning tools that facilitate the building, training, and deploying of models directly within the Microsoft ecosystem. It supports on-premises deployment, which is crucial for maintaining data privacy and security.

    From a marketing perspective, Azure Machine Learning can analyse user data to predict trends and personalize content recommendations. While it doesn’t generate content directly, it can help you understand which types of content are most likely to succeed with your audiences, allowing you to create more effective and targeted content.

    Azure Machine Learning can also be leveraged to create custom models that predict customer preferences and behaviour, enabling more targeted marketing efforts. It integrates well with other Microsoft products that might already be in use, such as Dynamics 365 for Sales or Microsoft 365, enhancing the workflow across marketing and sales teams.

    5. IBM Watson

    IBM Watson offers an array of AI services, including language understanding, which can be tailored and deployed within an organisation’s private infrastructure. Watson’s tools are designed to be accessible, allowing non-specialists to develop powerful models tailored to their specific needs.

    IBM Watson excels in areas like tone analysis and personality insights, which can enhance content personalisation. Watson can help create content that matches the emotional tone and style preferred by your target audience. In addition, Watson’s language capabilities can be used to develop more nuanced and engaging content, such as personalised customer communications and adaptive marketing messages.

    If you need advice and guidance about setting up your brand’s own LLM, speak to our experts today.

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