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Overview– Google Gemini 1.0 Ultra Review – A Quick Review
Are you looking for Google Gemini 1.0 Ultra Review? You’re in the right place. Let’s begin. The race to create top-notch AI chatbots is heating up, and Google’s latest entry, Gemini 1.0 Ultra, is really making waves. Formerly known as Google Bard, Gemini has undergone some big improvements. It now has a friendlier interface, can handle much longer queries (1,000 times longer!), and delivers better coding results. At $19.99 a month for the Advanced version, Gemini is priced similarly to competitors like ChatGPT Plus and Microsoft Copilot Pro (which both charge $20 per month), but it stands out as the most capable and visually appealing chatbot we’ve tried. Here we bring you the pros and cos before we go deep in to the review
Pros:
- Stunning visual representations and polished presentations.
- Ensured no copyrighted characters were included in image assessments.
- Achieved outstanding outcomes in our travel planning evaluations.
- Enjoy a complimentary 60-day trial of Gemini Advanced.
Cons
- Image generation can be inconsistent.
- Local event searches yielded generic outcomes.
- Noticed some language refinement opportunities during code reviews.
What Is Google Gemini 1.0 Ultra?
Gemini, like ChatGPT and Microsoft Copilot, is a large language model (LLM). You can ask Gemini questions or make requests, and it sifts through loads of data to give you answers in complete sentences that sound human. The version I used was Gemini 1.0 Ultra, a significant upgrade from the previous PaLM2 model. To put it in perspective, Google’s previous LLM Bard could handle around 1,000 tokens per request, while ChatGPT 4.0 can manage up to 128,000. But Gemini 1.0 Ultra, and later 1.5 Pro, can handle one million and 10 million, respectively. This means you can put much more text into one request, allowing for more detail and longer input/output for coding, image creation, and more.
Google Gemini 1.0 Ultra Price
Just like OpenAI, Google offers its chatbot in two versions: free and premium. Anyone with a Google account can use Gemini, but Gemini Advanced requires a $20 monthly subscription, similar to ChatGPT Plus and Microsoft Copilot Pro. Right now, Google is offering a 60-day free trial of Gemini Advanced before charging your card.
With the subscription, you get access to Google’s most capable model, 1.0 Ultra, while the free version uses the 1.0 Pro model, better suited for everyday needs. The differences between these models’ capabilities are vast and complex, as you might expect from machine learning.
There’s also a developer-focused model called Gemini 1.5 Pro, released to the public on April 9th, and Gemini 1.0 Nano, designed to work offline without internet. Neither 1.5 Pro nor 1.0 Nano is available to the public yet, but I’ll be testing them as soon as they are. All the testing mentioned below is based on the latest Gemini 1.0 Ultra model.
How To You Use Google Gemini?
You can find Google Gemini at gemini.google.com. To use it, you’ll need a Google account, either personal or through Workspace. It’s a separate website from the main Google.com search page, so remember to visit it directly. Gemini doesn’t have a mobile app yet, but you can access it on a mobile browser.
The interface is simple, mainly focused on a chat function. As you type in prompts, Gemini responds with sometimes lengthy answers. You can ask follow-up questions too. At the top-right corner, there’s a small menu with options like Dark Theme, Help, FAQ, Reset Chat, and See History.
If you’re already using Chrome, Gemini is a good choice as your default chatbot. It also works on Edge.
Gemini’s free version works in 250 countries, while Gemini Advanced is available in over 180.
Google’s AI -Still in Progress
Gemini Ultra boasts more power than its predecessor and even claims superiority over GPT 4.0, which runs ChatGPT. Both OpenAI and Google keep their models under wraps, so the public has limited insight into them.
Google describes Gemini as an “experiment.” A small disclaimer below the chat function warns that Gemini might show inaccurate or offensive content not reflecting Google’s views. However, Google continues to invest in it, recently giving it the ability to enhance its logic and reasoning by executing code independently. The “experiment” label mainly serves as a heads-up that Google won’t be responsible for nonsensical or unethical responses from Gemini.
Though I won’t go into all the details from the linked story, the main point is that Gemini’s image generation had some serious issues. It would sometimes overcorrect, like depicting the Founding Fathers of America as black or Native American men. For example, when asked to show vanilla ice cream, it would only return images of chocolate as you can see in the image below.
Comparison of Image Generation and Story Context: Gemini 1.0 Ultra vs. ChatGPT 4.0
In my first test, I pushed the boundaries of language models (LLMs) by challenging them with complex prompts. I wanted to see how well they could generate multiple images based on natural language instructions.
The results were amusing yet sometimes off the mark. While tools like Gemini are great for basic design tasks, they struggle with more nuanced prompts. For instance, one prompt asking for a twist on aliens resulted in a comic strip featuring aliens and something resembling a Xenomorph from Alien.
There’s also a growing discussion about copyright issues in AI-generated content. For example, a recent experiment with SoraAI led to concerns about copyright infringement when it unexpectedly included SpongeBob SquarePants imagery in response to a prompt about a mermaid and a crab.
Gemini’s results were less coherent, often producing bizarre images like a distorted cat. While it’s clear that LLMs understand the basics of prompts, they sometimes struggle with coherence and may inadvertently infringe copyrights.
Until legal issues surrounding AI-generated content are resolved, caution is advised when using these tools for public-facing or commercial purposes. It’s an exciting technology, but we need clarity on copyright and ownership before fully embracing it for creative projects.
Image Recognition Benchmark: Gemini 1.0 Ultra vs. ChatGPT 4.0
Recently, both GPT and Gemini upgraded their Language Models (LLMs) to recognize and understand images, opening up new possibilities for users. One playful experiment involved testing their comprehension by presenting them with a picture of a server farm, which was actually an image of themselves at work.
The results were impressive, with both LLMs accurately describing the contents of the image, achieving a precision level of 99%. However, the fun twist was that neither of them recognized that they were looking at a picture of themselves generating the response.
This playful test showcased the advanced capabilities of these LLMs in image recognition and understanding, while also highlighting the humorous aspect of their limitations.
How Does Google Gemini 1.0 Ultra Handle Creative Writing?
When it comes to creative writing, AI like LLMs often struggle with crafting surprising twists. While humans can sense when a twist is coming due to our collective knowledge of media tropes, AI has difficulty grasping concepts like “surprise” and “misdirection,” often leading to predictable results.
So, when asked to give a new twist on the classic tale of Little Red Riding Hood, Gemini didn’t quite hit the mark. It ended up revealing the twist too early in a lengthy story, falling short of the surprise factor. While the story was more detailed and action-packed compared to ChatGPT’s, it still missed the mark on delivering a satisfying twist.
Similarly, ChatGPT attempted a twist by portraying the Wolf as a guardian of the forest but stumbled in executing a second twist. Both AI models struggled to produce truly original and innovative storytelling, relying instead on familiar TV tropes that might not hold up to scrutiny from discerning audiences.
This test underscores that AI still has a long way to go before it can truly rival human creativity in writing. While these models may raise concerns among writers and creatives, they’re far from replacing the genuine innovation and originality that humans bring to storytelling.
Coding With Google Gemini 1.0 Ultra
Google Gemini 1.0 Ultra offers robust support for coding in multiple programming languages, making it a popular choice among developers. It helps with tasks like debugging, explaining code issues, and even generating small programs for users to utilize. Unlike ChatGPT, Gemini goes further by allowing exports to platforms like Google Colab and Replit for Python, enhancing its versatility.
However, Google advises caution when using the generated code, emphasizing that Gemini is still in the experimental stage. Users are responsible for verifying and testing the code for errors and vulnerabilities before relying on it. While code can be easier to fact-check compared to text, it’s essential to ensure its accuracy by running and testing it.
In a test to evaluate Gemini’s coding capabilities, we asked Gemini to identify the flaw in the following code which is crafted to deceive the compiler by making it believe that an object of type A is actually of type B, when it’s not truly the case.
Although Gemini provided a comprehensive response, it failed to address certain instructions crucial for avoiding Undefined Behavior (UB). This indicates a gap in understanding or an oversight on Gemini’s part.
Conversely, ChatGPT 4.0 delivered a nearly accurate response, albeit lacking some technical terminology for added clarity.
Shopping and Entertainment With Gemini 1.0 Ultra
When it comes to using the web for research, I find Gemini more helpful than ChatGPT, especially for finding information about local businesses. Gemini seems to excel in this area, likely due to access to extensive datasets.
I suspect that the difference in accuracy and usefulness between Gemini and ChatGPT may be because there are fewer user-submitted reviews for local businesses on Microsoft Bing compared to Google.
For example, we conducted a search on Copilot and it showed only 58 user reviews from TripAdvisor, while Google provided over 750 reviews covering various aspects like pricing, reservations, and more.
Now, onto the test. I wanted to see how well Gemini and GPT could find local veterinarians specializing in exotic animals to help with my injured iguana.
Google’s presentation of the data is impressive, showing maps, helpful links, and star ratings directly in the window. Please refer above image for the results we got in google. On the other hand, GPT also provided detailed results, including phone numbers and specific information about the iguana request. Overall, GPT slightly outperformed Gemini in contextualization and helpfulness, especially by including the Colorado Exotic Animal Hospital.
Next, I asked both Bard and ChatGPT for recommendations on what to do in Boulder, Colorado, this weekend. GPT provided highly specific events, whereas Gemini returned more generic suggestions like a Film Festival and live music at BOCO Cider. These recommendations lacked specificity and failed to capture the unique essence of Boulder.
Travel Planning With Gemini 1.0 Ultra
Another useful application of chatbots is in travel planning and tourism. With their ability to contextualize requests, you can customize your conversations much like you would with a travel agent in person.
In this case, Gemini excelled by providing highly specific and tailored results, while GPT only offered vague answers that didn’t take into account the context clues about interests.
When I asked GPT to look at hotels and flights for preferred travel dates, its lack of current datasets was evident. It struggled to find prices for a single hotel and advised me to check regularly for flight deals on sites like KAYAK. Meanwhile, Gemini not only provided a breakdown of prices, times, and potential layovers for flights but also embedded Google Flights data directly into the window. Similarly, it offered hotel options with embedded images, rates, and star ratings.
GPT 4.0’s recommendations fell short, suggesting a hotel far over budget and ignoring context clues. In vacation planning, Gemini clearly outperformed GPT in contextual understanding, data retrieval, presentation, accuracy, and overall helpfulness.
Gemini, labeled as an “experiment” by Google, comes with a disclaimer warning of potential inaccuracies or offensive information. Despite ongoing improvements, there are still areas where Gemini falls short, such as image generation overcorrections. However, Google is transparent about the limitations, and users are encouraged to exercise discretion.
Performance Testing: Google Gemini 1.0 Ultra vs. ChatGPT 4.0
I used the chatbot benchmarking feature on the Chat.lmsys website to compare the performance of the latest models of ChatGPT 4.0 and Google Gemini 1.0 Ultra directly.
For the same code evaluation task, I asked Gemini to debug the code provided. ChatGPT 4.0 responded first, taking 41 seconds and generating 357 words. Gemini 1.0 Ultra followed closely behind, taking 46 seconds and producing 459 words. While ChatGPT’s coding answer was slightly more accurate, the differences were minimal. Gemini’s result had some verbiage missteps in one part, leading to the variance in results.
Google Takes a Huge Step Forward With Gemini Ultra 1.0
Gemini offers a compelling glimpse into Google’s vision for AI chatbots in the modern era. With a user-friendly interface and the ability to handle longer requests, Gemini Ultra is a joy to use. Its accurate results and few misses on coding tests make it stand out. Plus, it hasn’t violated any copyright laws so far. Overall, Gemini is the most user-friendly and accurate chatbot we’ve tested, earning it our Editors’ Choice award.
