Why Google is Struggling to Catch up with PaLM 2 in Comparison to GPT-4

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Google has long been known for its search engine algorithm that can find almost anything on the internet. However, when it comes to developing natural language processing models, they seem to be falling behind in comparison to emerging technologies like PaLM 2 and GPT-4. In this blog post, we will explore why Google is struggling to catch up with PaLM 2 in particular, and how this could potentially impact the future of search and language processing technology.

Introduction

Google has been one of the leaders in Artificial Intelligence (AI) research and development for years. However, the recent emergence of PaLM 2, a new breakthrough in AI technology, has caused Google to struggle to catch up with its own brainchild, GPT-4. PaLM 2 is a language model that offers superior performance to GPT-4 in some tasks, which has led many to question why Google is struggling to compete. In this article, we will explore why Google is struggling to catch up with PaLM 2 in comparison to GPT-4.

PaLM 2 Vs. GPT-4 – The Battle for Supremacy

Google uses AI billion times in their I/O stream, but PaLM 2 is the answer to GPT-4. The 92-page paper that Google published on PaLM 2 suggests that it performs as well as GPT-4 on reasoning tasks. However, PaLM 2 has outfitted code-related tokens that make it hard to compare with GPT-4. In python coding tasks, PaLM 2 scores 88.4% with 100 tries, but only 37.6% with one try. GPT-4, on the other hand, is the best AI language model for zero-shot python coding tasks, scoring 67. Palm 2 comes in at number 7 with a score of 37.3 in python coding tasks. Google needs to add tools and run PaLM 2 a hundred times to approach GPT-4’s numbers.

PaLM 2 – The Features That Make It Stand Out

PaLM 2 beats GPT-4 on several metrics on several tests, but some things must still improve the results. The technology uses instruction tune variant chain of thought and self-consistency to improve results. Self-consistency means that they generate multiple responses and see which answer seems to be the most consistent across all the responses. Chain of thought is asking the model to think through its responses step by step. The AI tutors at Khan Academy use chain of thought to walk students through problem-solving, which has been met with fantastic results. However, Google is falling short of building something that’s like GPT-4 right out of the box.

Why Is Google Struggling to Catch Up with PaLM 2?

The answer to this question is simple: time and expertise. PaLM 2 was built on years of research and development, and it was the result of a collaboration of top-notch AI experts in Google’s team. GPT-4, on the other hand, is still in development, and the technology is yet to go through various tests before it’s released to the public. Therefore, there’s still much for Google to learn and adapt, considering that PaLM 2’s development has given the researchers a new perspective on how to tackle language modeling tasks.

Conclusion

In conclusion, it’s clear that PaLM 2 is the new groundbreaking technology posing a challenge for Google’s GPT-4. Despite the challenge, Google is not backing down, and it’s continuously looking for ways to catch up with PaLM 2. With time, it’s only a matter of time before Google catches up with PaLM 2 in functionality and performance. However, the level of expertise and investment poured into PaLM 2 development makes the technology a challenging and worthy competitor.

FAQS:

  1. What is PaLM 2, and how does it compare to GPT-4?
    PaLM 2 is a new language model that offers superior performance to GPT-4 in some tasks. This has led many to question why Google is struggling to compete.

  2. What features make PaLM 2 stand out?
    PaLM 2 uses instruction tune variant chain of thought and self-consistency to improve results. These features make PaLM 2 a worthy competitor to GPT-4.

  3. Why is Google struggling to catch up with PaLM 2?
    PaLM 2 was built on years of research and development by a team of top-notch AI experts. GPT-4, on the other hand, is still in development and is yet to go through various tests before it’s released to the public.

  4. Which AI language model is the best for python coding tasks?
    GPT-4 is the best AI language model for python coding tasks, scoring 67 in zero-shot python coding tasks.

  5. Will Google be able to catch up with PaLM 2?
    With time, it’s only a matter of time before Google catches up with PaLM 2 in functionality and performance. However, the level of expertise and investment poured into PaLM 2 development makes the technology a challenging and worthy competitor.

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