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Google’s AI Bard: Exploring the Factual Error in Its First Public Demo

6min Read

Delve into the fascinating world of Google’s AI Bard, the good and messy parts alike. Uncover the truth behind such botched error and how emerging AI companies can avoid them.

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Google’s artificial intelligence (AI) chatbot, Bard, has experienced a rocky start after making a factual error during its first public demonstration. As a rival to OpenAI’s ChatGPT, Bard is set to become widely available to the public in the coming weeks. However, the Google AI Bard’s initial error has raised questions about its accuracy and reliability.

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In this article, we will decipher the key details surrounding the Google AI Bard error – the debut, the implications of its error, and the current state of AI chatbots in the tech industry. 

Google AI Bard’s introduction and demo error

Visual representation of Google AI Bard – Image via Pixabay

 During the first demonstration of Google’s AI chatbot Bard, the bot made a significant factual mistake. When asked about new discoveries from the James Webb Space Telescope (JWST), Bard provided three bullet points of information.

One of these bullets claimed that the telescope “took the very first pictures of a planet situated outside of our own solar system.” This statement turned out to be incorrect, as the first image of an exoplanet was taken in 2004, not by the JWST.

 Astronomers point out the mistake

 Prominent astronomers were quick to point out Bard’s error on social media. Astrophysicist Grant Tremblay tweeted that, while Bard is impressive, AI chatbots like ChatGPT and Bard have a tendency to confidently state incorrect information.

He highlighted that the first image of an exoplanet was actually captured by Chauvin et al. (2004) with the VLT/NACO using adaptive optics.

 The impact on Alphabet shares

 Following the publicized error, Alphabet’s shares slid as much as 9% during regular trading, with trading volumes nearly three times the 50-day moving average. This highlights the importance of accuracy and reliability in AI systems, especially when used in high-stakes applications like search engines and information retrieval.

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 How AI chatbots work and their limitations

 AI chatbots like Bard and ChatGPT are trained on vast amounts of text and analyze patterns to determine word sequences. However, they do not query a database of proven facts to answer questions. As a result, they can “hallucinate” and create false information.

 The problem of confidence in incorrect information

 A major issue with AI chatbots is their tendency to confidently state incorrect information as fact. This can be particularly problematic when these systems are used as search engines, where their answers are imbued with the authority of a would-be all-knowing machine.

 The importance of rigorous testing

 In light of Bard’s error, Google acknowledged the importance of a rigorous testing process. The company plans to combine external feedback with internal testing to ensure that Bard’s responses meet a high bar for quality, safety, and real-world information.

Depicting the Google AI Bard error – Image via Pixabay

 AI chatbot rivalry: Google’s Bard vs. Microsoft’s ChatGPT

 The recent announcements of Google’s Bard and Microsoft’s integration of ChatGPT into Bing highlight the growing rivalry between the two tech giants in the AI chatbot market.

 Microsoft’s early release of AI-powered Bing

 Microsoft announced the introduction of a new version of Bing and the Edge browser that will use an advanced version of the same AI that powers ChatGPT. This new integration is currently available in a limited preview, with users able to sign up for full access in the future.

 Google’s approach with Bard

 In contrast, Google has released Bard only to “trusted testers.” Google may claim that it is due to mistakes like the one encountered during Bard’s demo that they will conduct extensive testing before making the chatbot available to a broader audience.

Effect of AI rivalry on Bard’s product quality

The rivalry among AI models often drives developers to push the limits of innovation, but it can also lead to unforeseen shortcomings. The Google AI Bard error had been an eye-opening incident for many of its competitors and peers. OpenAI acknowledged the errors and considered them learning opportunities to improve Bard’s accuracy.

This incident highlights the need for thorough testing and ongoing development to ensure the quality and reliability of AI models, mitigating the impact of errors on their performance and maintaining public trust.

 Bard’s current status and future availability

 As of now, Bard is in a closed beta for testing, with greater public availability expected to arrive in the coming weeks. This timeline suggests that Google is taking a measured approach to the chatbot’s launch, ensuring that any potential errors are identified and addressed before the product’s full release.

 Google’s other product updates

 In addition to Bard, Google announced updates to several other products, including Google Lens, Google Translate, and Google Maps.

 Google Lens

 Google Lens will now allow users to search what they see in photos and videos across websites and apps they currently use. Additionally, this update enhances the utility of Google Lens as a visual search tool and offers new opportunities for users to discover and engage with content.

 Google Translate

 Google Translate will provide users with additional contextual translation choices, complete with explanations and multiple examples in the target language.

This feature aims to improve the overall quality and usefulness of translations, making it easier for users to understand and communicate in different languages.

 Google Maps

 Google Maps will now offer glanceable directions and views of places users want to visit using augmented reality. This update will enhance the user experience by providing more immersive, real-time information about locations and directions.

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 The future of AI chatbots

 As AI chatbots like Google’s Bard and Microsoft’s ChatGPT continue to evolve, it is crucial for developers and companies to prioritize accuracy and reliability. Rigorous testing, user feedback, and continuous improvements are essential to ensure that these systems provide users with trustworthy information and maintain their authority as information retrieval tools.

 Balancing convenience and accuracy

 The growing integration of AI chatbots into search engines and other applications reflects the increasing demand for convenient, natural language-based information access. However, striking the right balance between convenience and accuracy remains a challenge that developers must address to ensure the long-term success of these systems.

 The role of human oversight

 As AI chatbots become more advanced and integrated into various applications, the role of human oversight and moderation becomes increasingly important. While AI systems can be powerful tools for information retrieval, it is essential for human experts to monitor and review their outputs to maintain accuracy and trustworthiness.

An AI bot working in a futuristic setting – Image via Pixabay

 Final takeaway

 Google’s AI chatbot Bard may have experienced a rocky start, but its first public demo offers valuable lessons for the future development of AI systems. Ensuring accuracy, reliability, and rigorous testing are all essential components of a successful AI chatbot and will be critical factors in determining the long-term impact of these systems on the tech industry and the broader information ecosystem.

The Google AI Bard error can be witness to the fact that technological advancements and developments should not be rushed. As AI technology continues to advance, the challenge of balancing convenience with accuracy will remain a key consideration for developers and companies alike.



Prakriti is a Content Writer at AMBCrypto. She describes herself as a passionately creative individual, with a dash of strategic prowess. With over 3.5 years of experience in the field of content writing and marketing, she is dedicated to churning out top-notch content in domains like Crypto, Web 3.0, AI and contributing to quench the thirst for technical knowledge of her readers.
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