ThoughtSpot Boosts Data Accessibility with GPT-3 Integration

With ThoughtSpot’s generative AI entry, you can query your data using natural language to get text or a graph back, as appropriate. This is useful for exploring and understanding how your data behaves.

By using AI, Thoughtspot is able to turn plain language queries into SQL behind the scenes and deliver an answer. This allows the company to analyze large data sets in a more efficient way and ultimately make better decisions.

Over the past few years, Google has been working on a new search engine which will be based off of machine learning anda vast amount of data. The project is known as GPT-3, and it has already started rolling out to a select few users. The idea behind GPT-3 is that users can enter a query and get an answer right away without having to sift through pages of results.

Initially, ThoughtSpot aimed to create their own large language model in order to provide users with the most accurate and flexible intent-driven interface. However, when the public Large Language Model capabilities became available, they took advantage of it and delivered a platform that is both highly accurate and flexible. Because of this innovation, ThoughtSpot has become one of the leaders in this field.

The ChatGPT technology falls under the category of artificial intelligence, which has been traditionally viewed as being very unreliable in delivering accurate results. However, Thoughtspot takes advantage of the GPT-3 API to help translate the natural language into SQL and also adds its own layer to make sure that only one answer is delivered. This helps ensure that data is returned as accurately as possible, even in cases where it may not be 100% accurate.

Large language models can provide great accuracy for business computing, but making them trustworthy for data queries is a major game changer. Nair’s company has developed a different software stack to achieve this trust at scale, which has been successful in large companies.

The feedback loop allows the company to quickly and easily fix any erroneous data, ensuring that their algorithms are always as accurate as possible. This helps to ensure that customers receive the best possible service, and that the company remains competitive in the market.

Users can change the way they measure something by editing the query, and this feedback is used to fine-tune future answers. For example, users may want to measure how busy a place is by counting the number of people in it, or they may want to gauge how big something is by measuring its length or width. This flexibility makes it easy for users to get an accurate perspective on what’s happening around them.

ThoughtSpot’s AI capabilities not only help users ask complex questions and retrieve personalized answers, but also help data experts build customized data models for their source data. This is something that is especially important for companies as they attempt to grow and understand their customer base.

With today’s launch of a private beta of the new integration with GPT-3, Atlassian is opening up access to its vibrant community of developers, testers and administrators. Atlassian’s aim is to provide an easy way for everyone on the team to collaborate and share information quickly and easily.

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Zara Khan

Zara Khan is a seasoned investigative journalist with a focus on social justice issues. She has won numerous awards for her groundbreaking reporting and has a reputation for fearlessly exposing wrongdoing.

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