Google’s New AI is Going to Kill ChatGPT-4 | Comparative Guide

Google’s New AI is Going to Kill ChatGPT-4 | Comparative Guide

Gemini AI is Going to Kill ChatGPT-4

Google’s New AI is Going to Kill ChatGPT-4 | Comparative Guide

The recent release of Google’s Gemini has sparked fierce debate about whether it can dethrone ChatGPT, which boasts over 100 million monthly users. Initially, Google positioned Gemini’s text and image generation capabilities as its key differentiator. However, OpenAI’s recent integration of voice and image queries into ChatGPT has blurred the lines between the two models.

With OpenAI venturing into the multimodal arena and connecting ChatGPT to the internet, the most significant advantage for Gemini might lie in Google’s immense trove of proprietary training data. Access to information across Google Search, YouTube, Google Books, and Google Scholar could give Gemini a distinct edge in generating sophisticated insights and inferences. This advantage is further amplified by reports suggesting Gemini is trained on twice as many data points as GPT4.

Another key factor is the formidable partnership between the Google DeepMind and Brain teams. This alliance pits OpenAI against a world-class AI research team led by Google co-founder Sergey Brin and renowned AI experts. This team’s expertise in applying techniques like reinforcement learning and tree search – techniques used by AlphaGo to defeat a Go champion in 2016 – could play a crucial role in Gemini’s development and advancement.

Ultimately, the battle between Gemini and ChatGPT is a race for AI supremacy. While both models boast impressive capabilities, the availability of proprietary data and the strength of the research team behind Gemini might give Google the edge in this fascinating technological competition.

While Google’s new AI might be poised to dethrone ChatGPT-4, Sundar Pichai’s vision for the future of AI goes far beyond competition, aiming to unlock a world of innovation and positive impact. To Know More CLICK HERE

Comparision Of Gemini and ChatGPT-4

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FeatureGeminiChatGPT-4
Model typeLarge language model (LLM)LLM
Training data341GB text and code1.56T text and code
Parameters137B100B
Performance 79.4 BLEU score on WMT 2014 English-German translation
StrengthsFactual accuracy, knowledge base, reasoning abilityCreativity, humor, storytelling ability
WeaknessesCan be prone to factual errors, limited creativityCan be biased, may generate offensive content
ApplicationsQ&A, summarization, translation, code generationChatbots, creative writing, copywriting, marketing
AvailabilityOpen-sourceNot publicly available

Gemini VS ChatGPT-4 Which Is Better?

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Gemini and ChatGPT-4 both stand for the state-of-the-art in big language model development. Their skills will inevitably grow as they learn more and adapt, dissolving the difference between machine and human intellect. These two models are laying the groundwork for a society in which everyone has easy access to powerful language processing and information. The potential applications of AI are vast.

While OpenAI’s ChatGPT has garnered significant attention, Google’s latest AI, Gemini, boasts impressive performance. In a major development, Google claims the most powerful version of Gemini, Gemini Ultra, outperforms ChatGPT in 30 out of 32 academic benchmarks focused on reasoning and understanding.

Gemini Ultra’s prowess extends beyond ChatGPT. It achieved a remarkable 90% on the MMLU multitasking test, encompassing 57 diverse subjects like math, physics, law, medicine, and ethics. This score surpasses all other current AI models, including OpenAI’s GPT-4.

Even the less powerful version of Gemini, Gemini Pro, demonstrates its capabilities. It outperformed GPT-3.5, the LLM behind ChatGPT’s free-to-access version, on six out of eight tests. These impressive results highlight Gemini’s potential to significantly impact various fields.

TEXT

Capability

Benchmark                 Higher is better

Description

GPT-4API 

Gemini Ultra

 

General

MMLU

Representation of questions in 57 subjects (incl. STEM, humanities, and others)

86.4%

90.0%

Reasoning

HellaSwag

Commonsense reasoning for everyday tasks

95.3%

87.8%

 

DROP

Reading comprehension (F1 Score)

80.93%

82.4%

 

Big-Bench Hard

Diverse set of challenging tasks requiring multi-step reasoning

83.1%

83.6%

     

Math

MATH

Challenging math problems (incl. algebra, geometry, pre-calculus, and others)

52.9%

53.2%

 

GSM8K

Basic arithmetic manipulations (incl. Grade School math problems)

92.0%

94.4%

Code

Natural2Code

Python code generation. New held out dataset HumanEval-like, not leaked on the web

73.9%

74.9%

 

HumanEval

Python code generation

67.0%

74.4%

MULTIMODAL

Capability

Benchmark

Description

Gemini

GPT-4V

 

Image

MMMU

Multi-discipline college-level reasoning problems

59.40%

56.80%

Gemini Ultra (pixel only*)GPT-4V
 

VQAv2

Natural image understanding

77.80%

77.20%

Gemini Ultra (pixel only*)GPT-4V
     
 

TextVQA

OCR on natural images

82.30%

78.00%

Gemini Ultra (pixel only*)GPT-4V
 

DocVQA

Document understanding

90.90%

88.40%

Gemini Ultra (pixel only*)GPT-4V (pixel only)
 

Infographic VQA

Infographic understanding

80.30%

75.10%

Gemini Ultra (pixel only*)GPT-4V (pixel only)
 

MathVista

Mathematical reasoning in visual contexts

53.00%

49.90%

Gemini Ultra (pixel only*)GPT-4V

Video

VATEX

English video captioning

62.74-shot

56%

(CIDEr)Gemini UltraDeepMind Flamingo
 

Perception Test MCQA

Video question answering

54.70%

46.30%

Gemini UltraSeViLA

Audio

CoVoST 2 (21 languages)

Automatic speech translation

40.1Gemini Pro

29.10%

(BLEU score)
 

FLEURS (62 languages)

Automatic speech recognition

7.60%

17.60%

(based on word error rate, lower is better)

Conclusion

Gemini, with its combination of various talents, from handling multiple formats to generating text and images, coupled with Google’s massive data advantage, holds the potential to become the best large language model, surpassing even GPT-4.

The deciding factor in this “arms race” will likely be the size and quality of training data. Whoever possesses the richest and most extensive dataset will have a significant edge.

However, OpenAI’s Gobi, another next-generation contender, cannot be ignored. This begs the question: who will ultimately master the art of multimodal AI?

Is Gemini better than ChatGPT?

Does the latest Bard, powered by Gemini, live up to the expectations, though? There’s a catch, though: Google says that the “Ultra” version of Gemini is the only one that can outperform ChatGPT. According to preliminary reports, ChatGPT-4 is narrowly defeated by Ultra in several categories. That version won’t be available until later in 2024, though.

Gemini Pro is now accessible within Bard for free, giving users a chance to test out its sophisticated text-based features. User engagement is greatly enhanced by the combination of Gemini with Google’s Bard chatbot.

With the increased speed and efficiency of these processors, Gemini can handle more data and complete calculations more quickly. Five times the processing capability of GPT-4, Gemini has an astounding 16,384 TPUv5 chips.

It’s clear that Coinbase prevails over Gemini in this comparison and can provide you with higher-quality services.

It’s clear that Coinbase prevails over Gemini in this comparison and can provide you with higher-quality services.

The big language model is designed to function on a variety of platforms, including mobile devices and data centers. It is available in three sizes: Ultra, Pro, and Nano. It is automatically created audio.

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