Recently, the artificial intelligence community has been awestruck by the success of OpenAI’s GPT-4 and Google’s BERT (Bidirectional Encoder Representations from Transformers) in head-to-head comparison. GPT-4 is a natural language processing (NLP) system that can generate natural-sounding text, while BERT utilizes deep learning technologies to better comprehend context. Following close behind them is another Google technology, BARD (Bidirectional Attention from Representations for Discourse), which is a submodule of BERT.
In three recently conducted tests, both GPT-4 and BERT achieved surprisingly high scores in all categories, and the performance of BARD lagged behind that of its rivals. It is worth noting that BARD has been developed specifically for domain-specific tasks, such as short-answer questions, question-answering for specific scenarios and other in-context tasks. Despite its purpose-built design optimized for applications with limited context, it appears that BARD’s performance falls behind the other two technologies. I
In the first test, GPT-4 and BERT both achieved a score of 92% on the Stanford QA (natural language question-answers) challenge. BARD scored considerably lower at 69%. The second test was specially designed by Google to evaluate domain-specific applications. On this test, GPT-4 outperformed BERT by a slight margin with a score of 92%, while BARD scored 81%. In the third test, a popular test called SQuAD, GPT-4 scored 91% and BERT came in a close second at 89%. BARD again scored considerably lower at 72%.
It is clear from these tests that BARD is lagging behind its rivals in the current AI landscape. While BARD was developed by Google to better handle domain-specific tasks, it seems that it is simply not performing up to its potential. However, Google should not lose hope on BARD yet, as more research and advancement can certainly help it to improve both its performance and its ability to handle domain-specific tasks.
Google is committed to further advancing AI research, so it is likely that BARD will eventually catch up with the leaders in the field. With continued investment and development, BARD could eventually become a formidable player in the AI industry.
