Leading the way in the race for large language models is Google’s Gemini AI

World AI Championship Chat GPT vs Google cOVER

Google’s latest offering, Gemini, is causing quite a stir in the large language model (LLM) arena thanks to its remarkable performance. Gemini beat Microsoft’s Bard and OpenAI’s GPT-4 in a set of benchmarks on a range of tasks, such as text summarization, question answering, and code development.

Improved Results on Important Benchmarks

 

Handling intricate reasoning tasks is one of Gemini’s most remarkable performance features. Gemini performed 82% accurately in a benchmark test measuring multi-step thinking abilities, while GPT-4 and Bard scored 75% and 70%, respectively. This implies that Gemini is more adept at deriving conclusions by recognizing the connections between several bits of information.

When it came to jobs requiring factual accuracy, Gemini also did well. Gemini scored 91% accurately in a benchmark that assessed summaries of factual subjects, while GPT-4 and Bard scored 88% and 85%, respectively. This implies that Gemini is more adept at finding and utilizing trustworthy information, which is beneficial for assignments like producing research papers or news stories.

An Emphasis on Transparency and Explainability

 

Gemini sets itself apart in part because of its emphasis on explainability and transparency. Gemini can explain its reasoning process, in contrast to certain other LLMs that may provide results that are hard to grasp. Users will find it simpler to trust Gemini’s findings and comprehend how it arrived at its conclusions as a result.

“A Google AI representative stated, “We think it’s important for LLMs to be understandable as well as powerful.” “Gemini’s focus on explainability is a step in that direction.”

Gemini will be released gradually. While Google’s chatbot Bard began utilizing a modified version of the language model last week, Gemini Pro went on sale to the general public. Additionally, Gemini Nano is integrated into several features of Google’s Pixel 8 Pro smartphone. The public still cannot use Gemini Ultra at this time. Google claims that only a small number of developers, partners, and security and liability experts have access to it, and that it is still undergoing security testing. Nonetheless, the plan is to release Gemini Ultra to the general public through Bard Advanced in the early months of 2019.

Microsoft has now refuted Google’s assertions that Gemini Ultra can outperform GPT-4 by having GPT-4 rerun the tests with marginally different prompts or inputs. In November, a group of Microsoft researchers published a study on a tool they termed Medprompt, which combines many approaches to improve the way prompts are fed into language models. You’ve probably observed that when you slightly alter the text, ChatGPT’s answers or Bing’s image creator’s output look slightly different. The premise of Medprompt is similar, but far more sophisticated.

gemini_medprompt

(image/Microsoft)

In some of the thirty tests Google had previously highlighted, Microsoft was able to enable GPT-4 to outperform Gemini Ultra by utilizing Medprompt. One such test was the MMLU test, where GPT-4 employing Medprompt inputs was able to achieve a score of 90.10 percent. It is unclear which language model will take the lead in the future. It’s far from over in the struggle for the AI throne.

The Future of LLMs

Gemini’s outstanding performance indicates that LLMs are getting more powerful and clever all the time. This has given rise to conjecture over the possible effects of LLMs on a variety of sectors, including customer service, education, and healthcare.

Although LLMs are still in their infancy, it is clear that they have the power to completely alter the way we work and live. It will be intriguing to see how LLMs are used to some of the most important problems facing humanity as they continue to advance.

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