Diving into the AI arena, Google’s latest marvel, Gemini Ultra, has officially entered the ring, aiming to dethrone the reigning champ, OpenAI’s GPT-4.
With whispers and waves of anticipation, the tech giant has finally unveiled what could be a game-changer in the world of large language models.
after extensive testing I’m here to spill the beans on whether Gemini Ultra lives up to its lofty promise of outshining GPT-4.
Is it merely hype, or has Google genuinely pulled off a feat that could reshape our digital interactions?
Stick around as we delve into the heart of this digital titan, dissecting its prowess and pitfalls, and ultimately, whether it’s worth your time and curiosity.
Rebranding Bard to Gemini :
Google has officially rebranded its Bard AI to Gemini, marking a significant shift in its approach to artificial intelligence. This rebranding signifies not just a change in name but also an upgrade in capabilities and features offered by Google’s AI.
Alongside the rebranding, Google introduced Gemini Advanced, which utilizes the Gemini Ultra model. This new model is touted as the most powerful version yet, surpassing the capabilities of its predecessor, Gemini Pro.
The Gemini Ultra model has been highlighted by Google’s DeepMind CEO as a potential “ChatGPT killer,” indicating its advanced capabilities and the company’s confidence in its performance against competitors like OpenAI’s GPT-4.
Now that we have access to Gemini Ultra, we’ll put it to the test to see if it truly lives up to the claims made by Demis Hassabis.. Is Gemini Ultra the formidable “ChatGPT killer” it’s touted to be?
Access and Subscription
How to Access Gemini Ultra
To discover what Gemini Ultra offers, head over to gemini.google.com/app. This is your portal to Google’s AI advancements, opening up a realm of sophisticated features that come with the Gemini era.
Gemini Ultra Pricing and Trial Period Details
To get into Gemini Advanced, which is powered by Gemini Ultra, you’ll need to upgrade your account. Google has set this upgrade at $20 a month.
But here’s the good part: you’re invited to enjoy Gemini Advanced for two months absolutely free. This trial lets you experience all that Gemini Advanced has to offer without dipping into your wallet.
Here’s how to get started:
- Click on the ‘Start trial’ button to initiate the process.
- Enter your payment details when prompted to unlock the free two-month trial.
- Enjoy exploring the advanced AI capabilities with Gemini Ultra, worry-free.
Global Availability
Optimization for English, Availability in 150 Countries
While Gemini Advanced is initially tailored for English speakers, its availability spans 150 countries. This wide reach ensures that you, along with a global audience, can access its capabilities.
App Availability and Future Language Support
Google has also rolled out a Gemini app for Android and iOS, initially for English speakers in the US. Plans are underway to add Japanese and Korean, with the goal to make English available globally, except in the UK, Switzerland, and the European Economic Area.
Keep an eye out for more languages and countries to be added, showcasing Google’s commitment to bringing Gemini Advanced to users everywhere.
Key Features : Gemini Ultra Vs ChatGpt 4
Performance and Speed :
Diving into Gemini Advanced, one thing that immediately stood out to me was the lightning-fast response speed. It’s like stepping from a bicycle onto a sports car, especially when you compare it to its predecessor, GPT-4. Playing around with Gemini Ultra, I was struck by how quickly it churned out answers.
It’s not just a tad faster; we’re talking about a speed that’s two to three times quicker than GPT-4, which is something I and many others have observed.
After testing it out, I can confidently say that Gemini Ultra doesn’t just edge out GPT-4 in terms of speed; it completely redefines expectations, placing itself in a whole new league.
Creativity : Comparison of Stories Generated by ChatGPT-4 and Gemini Advanced :
in our comparative analysis of AI storytelling, we tasked ChatGPT-4 and Gemini Advanced with crafting narratives from a thought-provoking prompt. The challenge was to write a short story about a software developer discovering a magical, ancient algorithm in legacy code capable of solving any coding issue.
The prompt aimed to test each AI’s creative flair, narrative construction, and the seamless blend of technical and fantastical elements. The stories generated by ChatGPT-4 and Gemini Advanced were evaluated for their quality, length, creativity, and the magical integration within a tech-driven storyline.
For readers interested in a direct comparison, we provide links to the original stories from both AIs.
Our concise comparison below reflects on these narratives, offering insights into the creative prowess of each AI model
Quality of Output:
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- ChatGPT-4: Offers a detailed, narrative-driven story with a focus on discovery and ethical considerations. The quality is high, with well-developed characters and a clear plot.
- Gemini Advanced: Presents a concise narrative with a strong focus on the mysterious and magical aspect of coding. The quality is equally high, but with a lean towards the mystical and the impact of sharing knowledge.
- Length:
- ChatGPT-4: Produces a longer, more detailed narrative that explores the protagonist’s journey and the algorithm’s impact in depth.
- Gemini Advanced: Offers a shorter, more focused narrative, emphasizing the pivotal discovery and the protagonist’s decision-making process.
- Creativity:
- ChatGPT-4: Shows creativity in blending technological elements with a storyline that examines the moral implications of using powerful, unknown algorithms.
- Gemini Advanced: Demonstrates creativity through the introduction of a magical algorithm, focusing on the transformative power of sharing knowledge and the community aspect of coding.
Problem Solving :
In our comparative analysis of AI capabilities, we’ve decided to utilize the same intriguing prompt that was highlighted in a comprehensive review by the AI Explained YouTube channel.
This prompt, “Today I own three cars, but last year I sold two cars. How many cars do I own today?”,
serves as a fascinating test to evaluate the problem-solving skills of the AI models in question. Our choice to use this prompt is inspired by its simplicity and the underlying complexity it introduces .
The Results :
In the provided results, we see a clear discrepancy between the two models’ approaches to the problem.
Gemini Advanced incorrectly deduces that if the user owned three cars and sold two last year, they would only own one car today. This response indicates a misunderstanding of the temporal aspect of the information provided.
On the other hand, ChatGPT-4 correctly interprets that the sale of the cars happened in the past and does not affect the current count. It rightly maintains that the user owns three cars today, as the action of selling cars occurred last year and has no bearing on the present situation.
This comparison reveals how each model processes temporal information and logical sequences differently, with ChatGPT demonstrating a correct understanding of the problem’s context and Gemini Advanced incorrectly applying past actions to the present scenario.
Coding Capabilities :
To test the coding capabilities of Gemini Ultra and GPT-4, you could provide them with a prompt that challenges them to interpret and generate code for a classic game. Here’s a coding task prompt you could use:
The Results :
Gemini Ultra’s Python Code:
Evaluating the provided code for the Snake game yields the following observations:
- Functionality: The code initializes with the Turtle graphics library, sets up the game board, and creates a stationary snake head and food item. However, it lacks the implementation of a main loop to keep the game running, necessary functions for updating the score, and snake body management, rendering the game non-functional.
- Efficiency: The code efficiently sets constants for game speed, screen size, and initializes game objects. Yet, without a working main loop or game logic, it’s incomplete.
- Readability and Comments: The code is well-structured and includes clear comments for setup and basic functions but falls short on implementing the full game logic.
- Correctness of Logic: The code correctly establishes the directional functions and collision detection with borders. However, it does not execute these functions due to the absence of a loop and event handling, which are critical for gameplay.
ChatGPT-4’s Python Code:
- Functionality: The code uses the Tkinter library and provides a fully functional game with a moving snake that responds to key presses, eats food, grows, and ends the game upon collision with the game boundaries or itself.
- Efficiency: The code is streamlined, using a class structure for the game, and contains all necessary functions for game operation within a single, cohesive unit.
- Readability and Comments: While the code lacks explicit comments, the use of descriptive function names and a clear structure makes the program easy to follow.
- Correctness of Logic: The logic for moving the snake, growing when eating food, and detecting game over conditions is correctly implemented and operates as expected.
In conclusion, ChatGPT-4’s code demonstrates a complete and functional Snake game, adhering to the prompt’s requirements and providing a playable experience. Gemini Ultra’s code, while it correctly begins the game setup, lacks the complete implementation required for a functional game.
Both sets of code have been linked in our GitHub repository for further examination and comparison. You can view the full code to see how each model tackled the task and the differences in their coding styles and capabilities.
Image Generation:
To assess the image generation prowess of each model, we employed a prompt designed to challenge their ability to conjure up detailed and imaginative visuals. The task was to create an image depicting a
The results were fascinating and distinct.
Gemini Ultra’s rendition takes us to a softer, more surreal interpretation. It’s as if the scene is from a dream or a concept artist’s canvas, blending technology and nature in a harmonious tableau that prioritizes mood over meticulous detail.
The resulting image has a Low quality, with the buildings and environment infused with a fantastical aura that might not be as crisp as DALL-E’s output but is compelling in its artistic merit.
In contrast, The DALL-E3 (ChatGPT-4) image presents a sharp, detailed cityscape that closely aligns with our futuristic vision. It boasts a high level of precision and a photorealistic quality that captures the prompt’s essence remarkably well.
when comparing the images produced by DALL-E 3 within ChatGPT-4 and those from Gemini Ultra as part of the Gemini Advanced , we observe a distinct edge in quality with DALL-E 3.
The image generated by ChatGPT-4’s DALL-E 3 showcases a higher level of detail, a more precise interpretation of the prompt, and a greater degree of realism.
The ability to vividly portray the bustling activity of a futuristic cityscape at dusk, complete with the nuances of light, shadow, and motion, highlights DALL-E 3’s advanced capabilities in creating images that closely align with complex, multifaceted prompts.
Gemini Ultra’s output, while creative and aesthetically pleasing, does not exhibit the same level of clarity or adherence to the specific details of the prompt. Therefore, for tasks requiring detailed and accurate visual representations, DALL-E 3 within ChatGPT-4 demonstrates superior performance.
Integration with Google Ecosystem
As we explore the integration of Gemini Ultra with the broader Google ecosystem, it’s clear that this connection offers unique advantages. For those deeply ingrained in Google’s suite of services, the ability to tie conversations and queries within Gemini to tools like Google Maps, YouTube, and Google Workspace is immensely valuable.
One of the standout features of Gemini Ultra is its web searching capability. Leveraging Google’s search engine, it can provide information that is both extensive and accurate.
This feature is particularly useful if your queries involve sifting through the vast ocean of online data. With Gemini, you’re essentially harnessing the search power of Google within your conversations, which could give it an edge over other models when it comes to pulling up the most relevant and up-to-date information.
The integration is not just about convenience; it’s about creating a seamless workflow where your AI assistant is as knowledgeable as Google’s search database. So, whether you’re asking about the likely winner of the Super Bowl or the forecasted weather for your next vacation, Gemini Ultra aims to provide answers that are both swift and reliable, backed by the most powerful search engine in the world.
Limitations and Potential for Improvement
- Problem Solving: Gemini Ultra has shown mixed results in logic and problem-solving tasks. While sometimes arriving at correct conclusions, it has also demonstrated lapses in understanding, as seen in tests where it failed to process a basic logical statement about car ownership.
- Coding: The model’s performance in coding tasks has been inconsistent. Some tests reveal an ability to generate complex code, but not without the occasional oversight that requires human correction.
- Image Generation: Although capable of producing images, Gemini Ultra’s fidelity to prompts varies, and it sometimes struggles to create visuals that align precisely with user requests, particularly when compared to the more accurate DALL-E 3 within ChatGPT-4.
- Image Understanding: Gemini Ultra has not consistently demonstrated strong image interpretation skills. It often misidentifies elements or misses crucial details in images, pointing to an area ripe for improvement.
another notable concern is the current inability to upload and interpret PDF documents directly within the platform.
This feature, which is available in other AI services like ChatGPT and Claud, is highly valued for its convenience and efficiency, particularly in professional and academic settings where PDFs are a common format for sharing and reviewing documents.
Conclusion: Is Switching from ChatGPT to Gemini Worth It?
Given Gemini Ultra’s impressive speed and its integration with Google’s ecosystem, it’s a strong contender in the AI space. However, ChatGPT currently offers a more reliable experience in logical reasoning, coding, and image understanding.
Switching between them depends on your specific needs and preferences. If speed and Google service synergy are top priorities, Gemini Ultra is worth exploring during its free trial period.
If you’re looking for stability and nuanced understanding, particularly in creative tasks, ChatGPT remains a solid choice. Ultimately, it’s not a clear-cut decision and may be best determined by personal trial and use.
Read More : Google Gemini vs ChatGPT: Who Wins? Full Analysis
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