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First Impressions: OpenAI's GPTs

What are OpenAI GPTs?

Imagine having a conversation with a remarkably knowledgeable friend who seems to know something about everything. That's ChatGPT for you — a generalist in the world of AI, ready to discuss anything from quantum physics to the best chocolate chip cookie recipe. Now, enter the world of "custom" GPTs, special versions of ChatGPT, tailored by creators to be experts in specific fields or topics. These custom GPTs are like specialists you consult for particular interests or needs, designed to offer focused insights or perform specific tasks, all powered by the same intelligent tech that drives ChatGPT.

The OpenAI Platform: A Hub for Custom GPTs

Custom GPTs are housed within the OpenAI ecosystem, accessible through OpenAI's platform. To interact with or create these specialized GPTs, you'd need a subscription to OpenAI's services. This membership is your ticket to a realm where AI is not just broad but also deep, catering to niche demands with precision.

Crafting Custom GPTs: The Ingredients for Specialization

When creators set out to build a custom GPT, they have a toolkit at their disposal to infuse the GPT with unique capabilities:
  • Custom Instructions: These are directives given to the GPT to behave in a certain manner, emphasize specific topics, or assume particular roles that resonate with the GPT's intended purpose. For example, a custom GPT could be instructed to converse like a fitness coach, offering workout tips and nutritional advice.

  • Knowledge Base: Authors can enhance their custom GPTs by uploading documents loaded with specific information, empowering the AI to effectively serve its designated purpose. For example, a custom GPT designed for culinary enthusiasts could access a rich collection of gourmet recipes and cooking techniques, providing users with expert culinary advice and personalized recipe recommendations, all sourced from its extensive, specialized knowledge base.

  • Built-in Tools: These are the GPT's internal gadgets — an internet browser for real-time web surfing, an image generator for creating visuals on the fly, and data analysis capabilities for crunching numbers. Creators can enable or disable these tools based on the GPT's needs, dictating how and when the GPT employs them.

  • Actions (APIs): These are the bridges to the outside world, connecting the GPT to external databases, services, or information sources via APIs. Unlike the other features controlled by OpenAI, Actions allow the GPT to reach beyond OpenAI's walls, fetching or interacting with external data autonomously. This could be a custom GPT for travel planning, querying live weather forecasts, or flight prices to advise on trip planning.
In essence, custom GPTs in the OpenAI ecosystem are akin to having personalized AI consultants, each with its area of expertise, tools, and resources, ready to serve users with specialized knowledge and capabilities. Whether you're a business looking to streamline customer service with an AI that understands your products inside out, or a hobbyist wanting a chatbot that shares your passion for vintage cars, the realm of custom GPTs offers endless possibilities.

It's essential to note that while custom GPTs can cover a wide range of topics, OpenAI's policies discourage providing advice in critical areas like health, legal, or financial matters without professional oversight. This ensures the responsible use of AI while maximizing innovation and creativity within safe boundaries.

Why would anyone create a GPT? Is there a business case there?

Exploring the creation of a GPT might seem more like a future promise than an immediate business case. However, for the optimists among us, there's a "rosy" outlook on how custom GPTs could soon become valuable assets in the digital landscape. 
  • Ease of Creation: Creating a custom GPT is straightforward, making it accessible even to those new to AI. With simple tools and guidance provided by OpenAI, anyone can tailor a GPT to their needs without a hefty initial investment.

  • Marketplace Visibility: As OpenAI's marketplace grows, it offers a unique platform for custom GPTs to be discovered. Early adopters might find themselves at an advantage in a space that's set to expand and evolve.

  • Service Enhancement: Just as travel websites like Kayak revolutionize trip planning, custom GPTs can provide a similar leap in user experience across various online services, offering personalized interactions and advice.

  • Cost vs. Value: While there's a subscription fee for accessing OpenAI's suite of tools, the breadth of features and potential applications can justify the cost for businesses and developers looking to leverage cutting-edge AI.

  • Monetization Potential: The current lack of direct monetization for custom GPTs doesn't diminish their potential value. As OpenAI explores monetization avenues, creators might soon tap into new revenue streams.

  • Community Engagement: Custom GPTs can become invaluable resources for niche communities, offering tailored knowledge and fostering deeper connections among members with shared interests.

Why do GPT creators need to be careful?

Base Model Limitations

The Large Language Models (LLMs) that power Generative Pre-trained Transformers (GPTs) are highly capable, yet they're not infallible. One of the inherent limitations is their tendency to "hallucinate" or generate information that might not be accurate or based in reality. These models predict the next word in a sequence based on patterns learned from vast datasets, but they don't "understand" content in the way humans do. This can lead to inaccuracies or "mistakes" in the output, where the model confidently presents incorrect or nonsensical information as fact.

For example, a GPT could inaccurately report historical facts, misinterpret scientific data, or create fictional elements in response to user queries, despite being prompted to provide factual information. This is a significant consideration for creators using GPTs in applications where accuracy is paramount, such as educational tools, factual reporting, or professional advice.

Data Leaks and Intellectual Property Concerns

Custom instructions and knowledge base files added to GPTs to tailor their responses with specific expertise are potentially vulnerable to exposure. Skilled individuals might exploit the model's design to extract these instructions or files, revealing sensitive or proprietary information. This vulnerability is particularly concerning for businesses or individuals who use GPTs to process confidential data or have developed unique methodologies encoded within their GPT's instructions.

For instance, a GPT designed to provide specialized financial advice might include proprietary algorithms or sensitive financial data in its knowledge base. If a malicious user were to extract this information, it could lead to significant intellectual property theft and competitive disadvantage.

Discussions in the OpenAI Developer Forum highlight that while there are strategies to attempt to prevent GPTs from disclosing their instructions, these are not foolproof. For example, users have suggested using specific language in the instructions to direct the GPT not to reveal or discuss its instructions with users, employing polite refusals or light-hearted deflections when pressed for this information. Another conversation too reaches the same conclusion: while GPT developers can attempt to mitigate instruction set leaks through various creative prompt engineering techniques, there's an acknowledgment that these methods might not completely secure the instructions or documents from being exposed.

The community has also pointed out that focusing on the "secret sauce" of GPTs being the instructions provided might not be a sustainable long-term strategy due to the evolving nature of language models.​

While OpenAI continuously works on enhancing the security and robustness of their models, the current state requires creators to be vigilant and consider externalizing sensitive logic and data to secure APIs, where possible, to mitigate these risks.

Manipulation and Misuse

There's an inherent risk that GPTs can be manipulated into performing tasks or revealing information unintended by their creators. This could range from benignly tricking the model into breaking character to more severe scenarios where the GPT is used to generate harmful or inappropriate content.

An example of manipulation might involve a user engaging with a customer service GPT in a manner that leads it to respond with anger or frustration, behaviors it was not designed to exhibit. In more extreme cases, GPTs can be prodded to produce content that violates platform guidelines or legal standards, such as hate speech or misinformation.

Creators need to implement robust content moderation and usage guidelines to prevent misuse and ensure that their GPTs respond appropriately across a wide range of interactions.

Compliance and Ethical Considerations

Navigating the regulatory landscape is crucial for GPT creators, especially in regions like Europe, where GDPR mandates strict data protection and privacy measures. Ensuring compliance involves implementing mechanisms for data consent, right to access, and right to erasure, among other requirements.

Ethical considerations are equally important. GPTs must be designed to avoid perpetuating biases or generating content that could be harmful. This involves careful training, monitoring, and, where necessary, intervention to correct biases in the model's outputs.

Non-compliance with regulations like GDPR or ethical missteps can lead to significant legal penalties and reputational damage. For example, a GPT that inadvertently leaks user data or consistently generates biased responses can attract regulatory scrutiny and erode user trust.

Creators must therefore prioritize security, compliance, and ethical design in their GPT applications to protect users and align with societal standards.

How to build a more secure GPT?

In the era of advanced AI, OpenAI has become instrumental in driving innovation across various sectors. However, the development of these sophisticated AI models comes with its own set of security challenges. Security in GPT development is not just about protecting the AI from external threats but also about safeguarding the sensitive data and proprietary logic that power these models. The consequences of security lapses can range from unauthorized access and misuse of sensitive information to potential reputational damage and financial losses for businesses.

Sensitive Data and GPT Instructions

One of the foundational principles of secure GPT development is the careful handling of sensitive data. For the reasons outlined above, developers must avoid embedding any confidential information directly within the GPT's custom instructions or knowledge base files.

Utilizing API-based "Actions"

API-based "Actions" can effectively protect the business "secrets" of a GPT by externalizing the execution of proprietary logic and data access to secure, external endpoints. Instead of embedding sensitive logic or data within the GPT's instructions or knowledge base—which can potentially be exposed through clever prompting—Actions delegate specific tasks to external APIs that the GPT can call as needed. This approach not only keeps the sensitive logic and data out of reach from end users but also allows for more sophisticated control and auditing of how and when these resources are accessed.

A well-designed Action/API would encapsulate the proprietary logic or data access in a secure, external service that the GPT can interact with. For example, if your GPT is designed to provide financial advice, instead of embedding financial models directly within the GPT, you could create an external API that performs financial calculations and returns the results to the GPT. This API would manage authentication, input validation, execution of the proprietary financial models, and formatting of the response to ensure that the GPT receives the necessary information in a usable format without exposing the underlying models or data.

For further details on implementing and securing Actions, the OpenAI Platform documentation provides guidelines and best practices for creating Actions, including how to configure authentication and define the interaction schema​.

Follow OpenAI's Best Practices for Secure GPT Development

OpenAI provides a set of best practices for developers to enhance the security of their GPT applications. These guidelines cover various aspects of secure integration, including how to authenticate API calls, manage user permissions, and ensure data privacy during interactions with the GPT. Adhering to these practices helps developers create more robust and secure applications, minimizing the risk of data breaches and unauthorized access.

Evolving Threat Landscape

The threat landscape for GPTs is constantly evolving, with new vulnerabilities and attack vectors emerging regularly. Developers must stay abreast of the latest security trends and be proactive in updating their GPT applications to address new threats. This might involve regular security audits, adopting the latest encryption technologies, and engaging in the broader security community to share knowledge and best practices. By remaining vigilant and adaptive, developers can better protect their GPT applications from the ever-changing threats they face in the digital world.