OpenAI vs CaztonAI

Global AI Keynotes: CEO of Cazton delivered keynotes for Global AI Developer Days in Fall 2022 in Europe, United States and Latin America. The keynote compared the AI offerings of AWS, Azure and GCP. The demo included multiple programming languages, including Node.js, Python and the latest .NET (C#) framework.
OpenAI offerings include GPT-3, an AI language model that can generate human-like text, and DALL-E, an AI image generation tool.
CaztonAI makes it possible to create customized AI models for our clients. These models can be used offline, online or in hybrid mode. These models can also be used with any of the OpenAI offerings.
Microsoft and Cazton: We work closely with OpenAI, Azure OpenAI and many other Microsoft teams. Thanks to Microsoft for providing us very early access to critical technologies. We are fortunate to have been working on GPT-3 since 2020, a couple years before ChatGPT was launched.
Top clients: At Cazton, we help Fortune 500, large, mid-size and startup companies with Big Data and AI development, deployment (MLOps), consulting, recruiting services and hands-on training services. Our clients include Microsoft, Broadcom, Thomson Reuters, Bank of America, Macquarie, Dell and more.

ChatGPT is the fastest product in history to have acquired more than a million customers in just five days. Generative AI or GANs (Generative Adversarial Network) is a type of artificial intelligence that generates new content, such as text, images, or music, based on a set of input data. GANs have made it possible for machines to mimic human creativity. Before Generative AI, most models were used for processing and analyzing pre-existing data. However, now they can be used to create something entirely new. This opens up infinite use cases in all business domains to incorporate AI.

However, while OpenAI is great, every company using it will need customizations based on their use cases. In a pay as you go model, the most frustrating part is paying for something you may not even use. In some cases, accuracies in image generation are lower than 5%. Imagine, paying $100 when you only got $5 worth of value. We can help with creating an extremely cost effective solution, which is fully customized to your needs.

OpenAI has demonstrated the power of AI and has brought AI closer to human like performance. In fact, in some cases, it can beat a human. Some examples are:

Text completion: OpenAI can generate text completion based on any input text prompt. While some humans may outperform OpenAI in quality, it's almost impossible for a human to compete in terms of speed. This is true for many different use cases such as content or code generation, summarization, expansion, conversation, creative writing and style transfer, etc.
Image-generation: Simple based on a text prompt, the three major use cases in image generation are:
- New image generation.
- Editing an existing image.
- And creating multiple different variations of an existing image.

Learn more about our OpenAI offerings.

While everything we do applies to all AI use cases, for the purpose of demonstration, we will only use image generation. OpenAI DALL-E is a generic AI model for image generation and it's great for creating realistic images and art from a description in natural language. However, in some cases, we may need to customize the model for our needs. So, we used this prompt, "Create a close-up headshot of a beautiful female model with long, flowing hair and a soft, natural makeup look." (1)

OpenAI: We use DALL-E and the results are the following four pictures (Results: Jan 15, 2023

Prior to this, we had seen a recurring known issue in OpenAI DALL-E images. It wasn't the best at creating headshots, hands, feet and other body parts. Here are some examples of images produced using natural language prompts in 2022 (zoom in to see hands and faces):
CaztonAI: We built a completely offline model and customized it specifically for headshots and got the following image based on the same prompts shared above:
- CaztonAI model has the following advantages over OpenAI:
  - Free: We are only paying for hardware resources. The model can be run offline with no access to the internet and doesn't not use any other third party. So, we do not pay any fees for the generation of the pictures.
  - Customized: This is just one-use case. However, imagine doing this for text, image, video and/or audio generation for social media posts and fully customized to your domain: healthcare, airlines, manufacturing, banking, e-commerce, tech, fintech etc. Customization can be done for the fully offline model or the hybrid model (using the generic OpenAI model and adding a customized model to the pipeline).
  - Compliance: For many customers offline model is the only option given their compliance needs.
  - No data sharing: The good news with this approach is that internal company data can be used wherever it's deemed fit.
- Note: We are a tech services company. We can build this for you.
OpenAI and CaztonAI hybrid: Then we used OpenAI variations for one of the pictures created by CaztonAI.

We prefer the hybrid approach for many reasons:
- Cost effective: Why pay for pictures we can't even use? This is the first criticism of a GAN. In many cases, even after multiple iterations, the results are unusable. So, the benefit of the customized model is to produce free images. Once we know which ones we like, we can leverage OpenAI to create variations. While this option is not free, it's overall better value.
- Higher quality: One major benefit is getting overall better-quality results.
- Better prompts: We can also use OpenAI text completion to generate better prompts and also use other offerings such as code completion for other use cases within the company.
- Fast: OpenAI results are fast. Once the offline model provides what we want, variations appear in less than a minute. Results are near real time and may be real-time in future.
- Larger use case: Remember, while we can help customize models, having a base model like GPT-3 or GPT-4 (to be released) for text is a huge advantage. While our model is specific and lot smaller, it works great for the specific use case. However, the generic OpenAI model opens up unlimited possibilities and we recommend using it for all relevant use cases.

Note: We can help create a fully automated solution all the way from development of the model, integration with OpenAI, MLOps (Machine Learning Operations) and scaling the model as per the needs. We can also help create enterprise grade applications: Web, mobile and tablets based (both thick client; help deploy it to cloud, multi-cloud, on-premises and hybrid cloud environments. How about integrating all this with your existing applications? Yes, we can help with that.

Azure OpenAI service helps us leverage OpenAI services powered by Azure. Here are some notable reasons to use Azure OpenAI service:

Large pre-trained AI models: We can use all models offered by OpenAI. These are models that are large (100GB or more) and can be used with API calls and integrate with existing applications.
Customization: We can easily add customizations and fine tune the AI models based on your data and hyperparameters.
Ethical AI: Microsoft has years of experience in creating responsible AI solutions. This is a huge value add as it detects and mitigates harmful use of AI.
Security: Microsoft invests more than $1 billion on just cybersecurity research and development annually. They also employ more than 3500 security experts. Azure OpenAI service supports role-based access security.

Our team of experts is extremely fortunate to work with top companies all over the world. We have an added advantage of creating best practices after witnessing what works and what doesn't work in the industry. We can help you with the full-development life cycle of your products from initial consulting, development, testing, automation, deployment and scale in an on-premises, multi-cloud or hybrid environment.

OpenAI and Azure OpenAI: We can help create models that are completely proprietary and owned by our clients: both offline and online. We can help integrate OpenAI or Azure OpenAI service wherever needed. We can also help with creating hybrid solutions.
Technology stack: We can help create top AI solutions with incredible user experience. We work with the right AI stack using top technologies, frameworks, and libraries that suit the talent pool of your organization. This includes OpenAI, Azure OpenAI, Semantic Kernel, Pinecone, Azure AI Search, FAISS, ChromaDB, Redis, Weaviate, Stable Diffusion, PyTorch, TensorFlow, Keras, Apache Spark, Scikit-learn, Microsoft Cognitive Toolkit, Theano, Caffe, Torch, Kafka, Hadoop, Spark, Ignite, and/or others.
MLOPs: We help with MLOps; develop models, optimize them for production, deploy and scale them. We help create a CI/CD environment and make your company automation-first.
Best practices: Introduce best practices into the DNA of your team by delivering top quality machine learning (ML) and deep learning (DL) models and then training your team.
Customized AI Solutions - The Future of Business Efficiency: Develop enterprise apps or augment existing apps with real time ML/DL models. This includes Web apps, iOS, Android, Windows, Electron.js app.

Notes:

The results displayed above are based on the queries made on or before January 15, 2023.
This is usually for our enterprise customers (large, medium and startup businesses) and the terms and conditions are underlined in the Master Services Agreement and/or the Statement of Work. We will work with customers and customize it based on the agreement.