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
| Feature | Gemini | ChatGPT-4 |
| Model type | Large language model (LLM) | LLM |
| Training data | 341GB text and code | 1.56T text and code |
| Parameters | 137B | 100B |
| Performance | 79.4 BLEU score on WMT 2014 English-German translation | |
| Strengths | Factual accuracy, knowledge base, reasoning ability | Creativity, humor, storytelling ability |
| Weaknesses | Can be prone to factual errors, limited creativity | Can be biased, may generate offensive content |
| Applications | Q&A, summarization, translation, code generation | Chatbots, creative writing, copywriting, marketing |
| Availability | Open-source | Not publicly available |
Gemini VS ChatGPT-4 Which Is Better?
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 Ultra | DeepMind Flamingo | ||
Perception Test MCQA | Video question answering | 54.70% | 46.30% | |
| Gemini Ultra | SeViLA | |||
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?
faq 's
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.
Is Bard Gemini free?
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.
Is Gemini better than GPT 4?
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.
What is better than Gemini?
It’s clear that Coinbase prevails over Gemini in this comparison and can provide you with higher-quality services.
What is better than Gemini?
It’s clear that Coinbase prevails over Gemini in this comparison and can provide you with higher-quality services.
Is Google Gemini an LLM?
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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