Draft:AI Wrapper

An AI wrapper (or LLM Wrapper) is commonly defined as either:

An AI wrapper (or LLM Wrapper) is commonly defined as either:

  • in a technical sense, a software layer that sits between the user and an AI model, or
  • in a broader sense, the services or applications themselves that are available or distributed to businesses or private users that make use of (or at-least largely base on) the latter.

Purposes

  • making AI more usable and effective for specific tasks.
    • Instead of having users interact directly with an AI model's raw API or its official website, wrappers handle the Formatting of user inputs, structuring AI outputs in a useful way, enhancing AI capabilities with additional logic or integrations (pipeline?)

example: company-internal AI-powered assistant instead of generic AI chatbot:

  • Uses proprietary data to provide more accurate responses, (context, pre-prompting, custom GPTs?)
  • Integrates with internal tools like CRMs and knowledge bases, (agentic AI?)
  • Follows specific workflows tailored to business needs (propromted)

Functionality

  • API

Example

Criticism

Limitations and Security Concerns

Because of their functionality of generating text, based on probability, LLMs and wrappers thereof are prone to inaccurate responses

Security Concerns

Main article: Prompt injection

https://shieldbase.ai/blog/innovation-beyond-llm-wrapper

Scalability and Maintenance

The accuracy and performance of AI-powered results worsen, when the volume of queries or complexity of use cases increase. Also, frequent updates to the ground-lying models can break existing wrappers, which can lead to maintenance problems.

Domain-Specific Accuracy

Clankers perform bad in specialized industries where domain knowledge is critical (healthcare, finance, or legal). Fine-tuning alone may not be sufficient.

Ethical and Bias Concerns

Pre-trained models, can inherit biases present in their training data.

Prominent Examples

Perplexity AI, a AI search engine uses large language models and real-time web search capabilities, to provide responses based on current Internet content, citing sources used. Its real-time search engine is called Sonar and is based on Meta's open-source Llama. A free public version is available, while a paid Pro subscription offers access to more advanced language models and additional features.

https://thenewstack.io/more-than-an-openai-wrapper-perplexity-pivots-to-open-source/

https://analyticsindiamag.com/global-tech/perplexity-ai-is-destroying-the-llm-wrapper-myth

See also

References

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