GERASOFTContactAI / ML
INTEGRATION &
DEVELOPMENT
Generative AI - Custom Models
Who we are
Artifical Intelligence Developers
We help businesses uncover unique opportunities where AI could be used to stay ahead of their competition, or bring their existing visions to life by integrating AI into their specific use case.
Services
Generative AI Integration
We integrate with Large Language Models (LLMs), like ChatGPT, Claude, and LLaMA to help automate manual processes, provide personalised content, or Stable Diffusion and DALL-E to generate custom assets.
Prompt
Engineering
Just as humans, AI can do more harm than good, or it can be useful when provided with good examples, proper training and the right instructions. With our expertise in AI, we know how to get the desired results.
Development of Custom AI Models
For more specialised use cases, or large datasets custom deep learning models are the most efficient by being flexible, powerful, and cost-effective. We choose the right model for you, train and test it, and retrain when needed.
Generative AI
OpenAI's ChatGPT is one of the most advanced language models, capable of interpreting, processing, and generating human-like text based on input. It offers different models that vary in speed, quality, and price.
Meta's LLaMA is the most advanced true open-source language model, allowing for extensive community contributions and customization. LLaMA is highly trainable, enabling developers to fine-tune it for specific applications.
Anthropic's Claude is a major ChatGPT rival. Like other advanced AI models, it's capable of understanding text, and replying with relevant content, but while it's subjective, it's considered the most human like model.
OpenAI's DALL-E is an advanced image generation model. It can generate images from text descriptions in various styles, including realistic, fantasy, abstract, and more.
Stability AI's Stable Diffusion is a cutting-edge image generation model. It's open-source nature allowed it to grow rapidly through community contributions because of its flexibility and extensive customisation.
Custom AI Models
Simple one layer machine learning models like logistic and linear regression are most suitable for simpler datasets due to their fast and cost effective trainability and exectution.
For more complex datasets, we incorporate deep hidden layers to enable the model to capture advanced patterns. With no theoretical limits on the number of layers and parameters, deep neural networks offer great flexibility.
Imagine trying to predict the price of a stock in the next minute. It's not just the current price that matters, but also the previous prices. RNNs are useful for sequential data where the previous points influence the next one.
CNNs excel in image processing tasks, such as recognizing objects in photos, classifying images, and facial recognition. They are ideal for any application involving visual data.
Transformers are powerful for handling text and language tasks. They are used in applications like translating languages, summarising text, and analysing sentiments, giving different weight to relevant parts via attention.
Why AI?
The power of AI is that it understands unstructured data. While a computer program needs specific instructions, and clean data to operate, AI can interpret different languages and tones to provide personalised content.
Example use cases
Review summarisation
A very good demonstration of AI's power is how it can take thousands of reviews, and summarise the main points of the reviews. Before AI, people had to parse through all the reviews to get the same result.
Personalised learning
People learn in different ways, and want to know different topics. Previously, they either took a whole class, read a whole book, or hire a tutor. With personalised AI learn, people can learn how, when, and what they want.
Business analysis
We made use of AI to provide personalised blog content by gathering a short business description based on their website content from their URL, approximating their target audience, and generate content they may like.
Incident resolution
While it takes a long time for developers to parse through hundreds of error messages from different sources, AI can read all of them, and make connections between the sequence of errors to find the root of the issue in seconds.