Generative AI is taking the world by storm, making heads turn in various industries and businesses. As a seasoned observer of the field for over a decade, I must say it's impressive to see the strides that have been made.
At vPhrase, we have been at the forefront of using generative AI to create commercial data-to-text insights for the last eight years. Our goal has always been to generate insights from data in a language that business users can easily comprehend and act on.
Although the use of generative AI in data-to-text insight technology holds significant potential to revolutionize the way businesses analyze and interpret data, it is crucial to note that human oversight remains necessary to ensure the accuracy and relevance of the generated insights.
But let's be real, crafting concise and clear insights from data has been a giant task for us and many other companies. We've tried every trick in the book, but it's the advances in generative AI that have really turned the game around.
By leveraging ChatGPT, we at vPhrase have been able to develop technology that automates the process of generating insights from data. This has not only saved businesses valuable time and resources but also eliminated the limitations that other Generative AI has been facing. Talk about a win-win!
Let's have a look at how Pharazor leverages ChatGPT and remove the limitations by offering Enterprises more control over their data and insight generation process.
Limitations of Generative AI like ChatGPT for Enterprise BI
Many companies are hesitant to adopt AI in their Enterprise Business Intelligence due to concerns about the reliability of the insights generated by AI algorithms.
Since these models work with mathematical probabilities, they can sometimes render inaccurate insights due to potential issues with incomplete or inaccurate data, which could lead to significant financial and reputational consequences if acted upon.
To avoid these risks, companies tend to be cautious and verify the accuracy and reliability of AI-generated insights before relying on them. Contextual understanding and data privacy are also concerns that companies must address before embracing AI in Enterprise BI.
Factually incorrect generated content by AI
In the context of AI, hallucinations refer to the potential for AI algorithms to generate false or misleading insights based on incomplete or inaccurate data.
AI hallucinations occur when an algorithm generates an output that is not based on actual patterns or relationships in the data but instead on noise or random chance.
Problems faced by Enterprise BI due to Hallucinations
Hallucinations in AI-generated content can lead to a range of potential problems, including inaccurate or biased reporting, incorrect conclusions, and reputational damage.
Suppose an AI system is used to identify fraudulent transactions in a financial institution's system. The system might be trained on a large dataset of previous fraudulent transactions, but if the dataset is biased, the AI system might start to hallucinate fraudulent patterns in legitimate transactions, leading to false positives and unnecessary alerts.
For example, the AI system might flag a transaction as suspicious because it contains a certain pattern that was present in previous fraudulent transactions, even though the current transaction is actually legitimate.
How Phrazor leverages ChatGPT's potential to resolve hallucination by AI
Phrazor is an innovative platform that leverages the power of machine learning algorithms and domain-specific rules to generate high-quality written content, including reports, summaries, and articles.
To ensure accuracy and reliability, we have developed a unique feature that empowers our users to edit the variations generated by ChatGPT, identify any errors or biases, and correct them before publishing.
This feature mitigates the risk of inaccurate or misleading insights and enables our users to have greater confidence in the quality of the insight they produce.
Our users have the assurance that the content published is authentic, as it is only the variations selected and approved by them that are made available to their intended audience. With this powerful tool at their disposal, our users can unlock new insights and gain deeper understanding while upholding the highest standards of quality and accuracy.
To do this, users would need to edit the output generated by LLMs in the above step and can also provide feedback to our algorithms which are continually refined and updated.
While other generative AI systems may have the potential for hallucinations, Phrazor's ability to allow users to control and tweek the generated insights gives enterprises confidence and trust, which is lacking in other generative AI tools.
Importance of data security using AI
As more organizations consider implementing ChatGPT to generate valuable language-based insights, the issue of data privacy looms large. Sharing data over the public internet raises concerns for many companies, who may be uncomfortable with the potential risks involved, or subject to regulatory requirements regarding the sharing of personally identifiable information (PII) or financial data.
This creates a delicate balancing act for organizations, where they must navigate the potential benefits of innovation while ensuring compliance with legal and ethical obligations. As such, the question of how to leverage the power of ChatGPT while maintaining the security and privacy of sensitive data is a crucial one, requiring careful consideration and analysis of potential risks and benefits. With the right approach, however, organizations can harness the potential of ChatGPT to drive transformative insights and unlock new opportunities for growth and success.
Phrazor has been using a large language model and working with enterprise data for a long time now. We have been leveraging these public models by anonymizing PII, redacting sensitive data, and masking important information before sharing data with any cognitive service like ChatGPT. This process does not affect the quality or coherence of generated insights.
Phrazor also adheres to industry best practices for data protection, such as compliance with the EU's General Data Protection Regulation (GDPR) and the Payment Card Industry Data Security Standard (PCI DSS).
Understanding Contexts in Language Generation
Every enterprise faces unique challenges that require specific solutions. However, when using ChatGPT, many AI practitioners and engineers struggle to convey their business context effectively, resulting in less relevant language output.
While ChatGPT may be useful in a generic setting, it may not align with internal strategy or provide relevant insights. To address this, Phrazor allows users to define business scenarios and interpretations, giving them greater control over the ChatGPT generated output.
Let's take an example here to understand more about this scenario:
Company ACME has decided to cut on sales effort in Europe since it is not profitable and want to allocate the budget of marketing spend in that region to other potential places.
When chatGPT or any other Generative AI tool encounters sales drop in Europe it will generate an insight saying your profits are down due to sales drop in Europe without taking into account that Europe was negatively affecting profits.
To control this, Phrazor allows users to specify the business context for the decision such that the AI would take into account the specific context of the region and the company's goals and generate insights based on it.
This will help to ensure that the generated insights are relevant and actionable. Additionally, the tool should be able to identify patterns and trends in the data that may not be immediately apparent, allowing the company to make informed decisions.
By leveraging this, companies can generate valuable insights aligned with their goals that can inform decision-making and help drive long-term success.
In conclusion, while both Phrazor Generative AI and other AI driven tools offer unique benefits for generating content, Phrazor stands out for its ability to generate highly specific and structured insights using ChatGPT on top of its robust system.
As AI continues to evolve, the future of AI in business intelligence is promising. The technology will continue to improve, making content creation faster, easier, and more efficient than ever before.
We encourage readers to explore the capabilities of Phrazor Generative AI using ChatGPT further and see firsthand the benefits it can offer for content creation. As we move towards a more AI-driven world, it is exciting to imagine the possibilities and opportunities that lie ahead.