Opportunities, Pitfalls, and Strategies

In the realm of artificial intelligence, progress never comes from nowhere. Its evolution, indeed, is an accumulation of years of relentless pursuit and exceptional breakthroughs. One such disruption emerged in 2022, with the advent of Generative AI.

The story of AI’s evolution started with a focus on deep learning, a machine learning technique where layers of neural networks process data and make decisions.

Generative AI emerged as a game-changer in 2022. It has the potential to create new written, visual, and auditory content based on existing data or given prompts. With this emergence, the productivity race truly took off. Generative AI capabilities usually include diverse use cases such as content generation, summarization, code generation, and semantic search.

Elqano and Generative AI: Harnessing Power, Evading Pitfalls

At Elqano, we saw both the potential and the pitfalls of generative AI.

Instances such as the accidental leaking of sensitive data via ChatGPT at Samsung underscore the pressing issues of data confidentiality. In response, Samsung temporarily banned generative tools. However, this action does not solve the AI problems faced by companies as more and more generative tools will be introduced in the coming years.

Prompt sensibility is another hurdle. Bad prompts can be incomplete, vague, or misleading, which can lead to undesirable results. Meanwhile, a good prompt provides relevant information and clear instructions.

Moreover, we must consider ‘model hallucination.’ This phenomenon occurs when the AI model combines unrelated or inaccurate information from its training data or misinterprets the user’s query, resulting in fictional or incorrect information. It is crucial to verify AI-generated responses to avoid such issues.

Strategies for Safe Integration and Effective Use of Generative AI

At Elqano, we developed an approach to avoid these pitfalls and benefit from generative AI.

At the core of our philosophy is a pragmatic approach that prioritizes customer relations. This ethos serves as the guiding principle for our internal R&D team that specializes in Machine Learning and Natural Language Processing (ML/NLP).

Our main focus: A Secure Environment. Our algorithm is hosted on an Azure server in our client’s cloud, ensuring data confidentiality.

In addition to these strategies, it is essential to think about the process to avoid misinformation, identify the right partnerships, and understand the underlying technology.

Now, what Role Can the Generative AI Play in Knowledge Management

A short reminder about knowledge management, what does it mean?

Knowledge Management (KM) is a multidisciplinary approach that makes the best use of an organization’s knowledge.

It encompasses creating, sharing, using, and managing the organization’s knowledge and information.

Generative AI can significantly enhance KM through various use cases, including:

  • Summarizing, gathering, and reconstructing information
  • Creating intelligent knowledge bases
  • Extracting knowledge
  • Performing topic modeling and automated documentation
  • Reviewing and optimizing content
  • Curating data automatically
  • Performing semantic searches and smart document analyses
  • Recognizing sensitive content
  • Referencing source content
  • Enabling business intelligence, trend identification, and sentiment analysis
  • Detecting anomalies
  • Generating knowledge graphs and multilingual content

Our next step: Integrating Generative AI to Improve Elqano’s Solutions

Elqano aims to combine the best of both worlds: our philosophy of security, control, and human-centric approach, with the power of AI and Generative AI. We are integrating advanced features that tap into the power of Generative AI.

These include:

Refining Collaboration with “Automated Drafts of Answers”

Currently, Elqano’s robust functionality is rooted in fostering internal expertise within an organization.

When questions are posed by collaborators, our system identifies the most knowledgeable internal expert in that specific field by analyzing document indexation. This expedites the information-sharing process, ensuring questions are directed to the right people without delay.

As we move forward, we aim to integrate the capabilities of Generative AI to further streamline this process.

The new feature, “Automated Drafts of Answers”, will produce preliminary responses to the posed questions by leveraging the AI’s understanding of the indexed documents and the organization’s collective knowledge.

These AI-generated drafts do not replace the human experts but rather provide them with a foundation to build upon.

Experts can then review, modify, validate, or dismiss the proposed answers. This not only accelerates response times but also alleviates the workload on experts by providing them a head start in crafting their responses.

In addition, we are setting a new benchmark for data validity. Contrasting with Large Language Models like ChatGPT, which typically utilize public and non-verified data, our generative AI operates on expert-validated data drawn from internally verified sources. This unique approach guarantees a higher level of data security and the reliability of the AI experience we offer.

By innovating and continuously refining these features, we aim to provide an unparalleled user experience that marries safety, control, and the immense potential of AI and Generative AI.

The Journey Continues

The journey to harness the full potential of generative AI in knowledge management is ongoing. But with the right strategies, tools, and philosophies, we believe we can transform the way organizations manage and utilize their most valuable resource: knowledge.

As we embark on this exciting journey, we are grateful for your continued support and look forward to exploring the endless possibilities of generative AI together.