Optimizing LLM Selection: Navigating Hallucinations with Teneo

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In today’s rapidly advancing world, managing and understanding human language has become increasingly critical. Large Language Models (LLMs) have emerged as powerful tools for tackling this challenge but have a drawback in the form of hallucinations. With a wide variety of LLMs available, determining the best choice while managing LLM hallucinations can be daunting. The answer lies in the unparalleled capabilities of Teneo, a platform that enables businesses to orchestrate advanced Generative AI solutions with ease. In this article, we will explore the challenges of LLM hallucinations and highlight why Teneo is the ideal solution for effectively addressing them.

Decoding LLM Hallucinations: What They Are and Why They Matter

It is essential to understand what LLM hallucinations are. LLMs such as LLaMa or GPT-4 generate outputs that, while coherent and grammatically accurate, contain factually incorrect or nonsensical information, essentially creating their version of the truth.

Case Study: Google’s Bard AI and the Financial Impact of Hallucinations

LLM hallucinations are common and can be found in every LLM, causing not just embarrassing but having potential financial impact. One example in early in 2023 was Google’s Bard AI gave the wrong answer to a question about the James Webb telescope, causing a drop in Alphabet’s (Google’s parent company) stock price.

Evaluating LLMs: The Hallucination Index and Its Insights

Understanding the power of LLMs but aware of the risks of hallucination, which LLM should you use to reduce the risk of creating an AI assistant that hallucinates? Galileo, a data quality platform, has released a LLM hallucination index that scores the most well-known LLMs and how prone they are to hallucination, based on the following scenarios:

  • Q&A with RAG
  • Q&A without RAG
  • Long-Form Text Generation

Comparing LLMs in Q&A Scenarios: RAG and Non-RAG Analysis

Retrieval-Augmented Generation (RAG) represents a blended method that incorporates aspects of retrieval-based data and generative knowledge derived from the LLM. For this, Galileo found that GPT-3.5-turbo was the most cost-effective LLM. Adding that: “While GPT-4-0613 performed the best, the faster and more affordable GPT-3.5-turbo-0613/-1106 models performed nearly identically”.

For Q&A without RAG, the highest scorer was once again GPT-4, “Open AI’s GPT-4 performed the best and was least likely to hallucinate for Question & Answer without RAG”. While for the open-source models, Meta’s largest model, Llama 2 (70b), performed best.

Long-Form Text Generation: Identifying Cost-Efficient LLMs

While GPT-4 remained on top, Llama-2-70b-chat, and gpt-3.5-turbo-1106 emerged as strong contenders for being the most cost-efficient.

Choosing the Right LLM: Balancing Performance and Cost

Reading the LLM hallucination index, you will quickly discover that depending on your use-case you will be recommended a different LLM. While GPT-4 is the winner of the three task types, thus being the strongest LLM to pick, it is not recommended.

Why GPT-4 Leads but May Not Always Be the Best LLM Choice

There could be several reasons why GPT-4 is not recommended for every option. One big reason is that GPT-4 might not be cost-effective, especially for individuals or small businesses.

Integrating Teneo: Enhancing LLM Efficiency and Reducing Costs

Luckily, using any LLM with Teneo could help you reduce costs up to 98% significantly by:

  • Caching the responses, and not prompting your LLM when asked the same question.
  • Shortening and reducing the number of tokens used on your prompt.
  • Using Teneo Inquire to collect data (PII anonymized) on previous sessions and optimize the behaviour from your LLMs.
  • Controlling each input and output sent to and from LLMs.

Reduce your LLM costs with Teneo – Explore FrugalGPT Solutions

The Teneo Advantage: Seamless Integration and Customization

In addition of full control over your LLMs, Teneo introduces the following elements to your Generative AI solution:

  1. Enhanced Language Understanding: Teneo’s advanced language understanding capabilities allow it to accurately identify and process hallucinations, even when they present in complex or ambiguous language patterns. This precision is crucial for ensuring that individuals experiencing hallucinations receive the appropriate assistance and support.
  2. Personalized Responses: Teneo’s ability to generate personalized responses based on an individual’s unique experiences and circumstances sets it apart from other LLMs. This customization is particularly important when dealing with LLM hallucinations, as it allows for a tailored approach that addresses the specific needs of each user.
  3. Seamless Integration: Teneo’s seamless integration with existing systems and platforms enables businesses to enhance LLM applications that can effectively manage LLM hallucinations without requiring significant infrastructure changes. This adaptability ensures that Teneo can be easily implemented in a variety of settings, from healthcare to customer service.

The Future of LLMs: Teneo as the Solution to Hallucination Challenges

In conclusion, addressing LLM hallucinations is of paramount importance. As the demand for LLMs and their processing capabilities continues to grow, Teneo stands out as the prime candidate to tackle this phenomenon. Boasting Natural Language Understanding, Adaptive Answers, seamless integration, and a user-friendly interface, Teneo represents the ideal and cost-effective solution for businesses seeking an LLM capable of successfully navigating the complexities of hallucinations. Do not let LLM hallucinations go unaddressed – harness the power of Teneo today.

Ready to tackle LLM hallucinations with Teneo? Contact Us for a tailored solution.

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