Google Gemini AI : An AI with Many Talents

Google Unveils Gemini: A Versatile, Multifaceted AI

Introduction to Google Gemini AI ?

We are talking about Google Gemini, which is a research product of Google DeepMind. Since Gemini comes from DeepMind, we should first discuss Google DeepMind before diving into Gemini. Google DeepMind is a leading AI research lab based in London that was acquired by Google in 2014. DeepMind has assembled a talented team of researchers seeking to create artificial general intelligence (AGI). Now that we have provided background on DeepMind, let’s deep dive into Google Gemini, which is one of DeepMind ‘s latest research innovations. Gemini demonstrates DeepMind’s continued progress in developing AI systems that can learn continuously.

What is Google Gemini ?

Google Gemini can understand and connect information across text, images, video, audio, and code. It is the state-of-the-art performance & most capable general model by Google DeepMind. It is the most flexible model & different from other ai chatbots such as Microsoft bing, ChatGPT, Claude & others.  

First version of Gemini i.e gemini 1.0 comes in there different sizes & those are

• Gemini Ultra — The largest and most capable model for highly complex tasks.
• Gemini Pro — The best model for scaling across a wide range of tasks.
• Gemini Nano — The most efficient model for on-device tasks.

The researchers tested Gemini on 32 different challenges related to language, math, science, history and more. Gemini did better than any other AI on 30 of the 32 challenges! This shows it is very smart across different subjects.

One test called MMLU asks very hard questions on 57 different topics like math, medicine, physics and ethics. Gemini scored higher than even human experts on this test! It shows Gemini can understand and think through difficult problems across many fields of knowledge. The researchers also taught Gemini to take its time to reason through tricky questions before answering. This helped Gemini get a lot more answers right compared to just going with its first guess.

Overall, the tests show Google’s Gemini can understand and solve problems in many areas better than previous AI systems. It is a very impressive achievement in making smarter and more capable AI!

Difference Between Google Gemini Vs ChatGPT 4:

• MMLU: This stands for Massive Multitask Language Understanding. It’s basically a test of how well a language model can answer questions on a bunch of different topics. Gemini got 90%, while ChatGPT 4 got 86.4%. So, Gemini is a bit better at answering questions in general.
• Big Bench Hard: This is a test of how well a language model can do reasoning tasks. It’s kind of like a word problem test, but for computers. Gemini got 83.6%, while ChatGPT 4 got 83.1%. So, they’re pretty close on this one.
• DROP: This stands for Diagnostic Reading Comprehension Over Paragraphs. It’s a test of how well a language model can understand what it reads. Gemini got 82.4%, while ChatGPT 4 got 80.9%. So, Gemini is a little bit better at reading comprehension.
• HellaSwag: This is a test of how well a language model can do commonsense reasoning. It’s kind of like asking your friend for advice on what to do in a weird situation. ChatGPT 4 actually beat Gemini on this one, with 95.3% to Gemini’s 87.8%. So, ChatGPT 4 is a bit better at understanding everyday situations.
• Math: This section has two tests. GSM8K tests basic arithmetic, and MATH tests more challenging math problems. Gemini beat ChatGPT 4 on GSM8K (94.4% to 92.0%), but ChatGPT 4 did a little bit better on MATH (52.9% to 53.2%). So, they’re pretty close on math overall, with Gemini being slightly better at basic math and ChatGPT 4 being slightly better at harder math problems.
• Code: This section also has two tests. HumanEval tests how well a language model can generate Python code, and Natural2Code is a similar test but on a different dataset. Gemini beat ChatGPT 4 on both of these tests (74.4% to 67.0% on HumanEval and 74.9% to 73.9% on Natural2Code). So, Gemini is better at generating Python code.

Types of Google Gemini:

1. Ultra: Think of Ultra like a superhero of computers. It’s super strong and can do really hard jobs, like creating different types of cool writing – poems, computer code, stories, music, emails, and even answering really tough questions. But, here’s the catch – it needs a lot of computer power to do its magic.
2. Pro: Meet the Pro model – it’s like a superhero’s sidekick. Not as strong as Ultra, but still really good at many things. It can create different kinds of cool writing and answer your questions in a smart way, all while using less computer power than Ultra. It works on big computers or servers.
3. Nano: Now, imagine Nano as the little helper for your phone. It’s the smallest superhero, perfect for tasks that your phone can handle on its own without needing the internet. Nano can understand and answer basic questions, but it’s not as fancy as the bigger superheroes. It’s like having a tiny wizard in your pocket!

Main Features:

• Gemini can generate code based on different inputs you give it.
• Gemini can generate text and images, combined.
• Gemini can reason visually across languages.

How to access google gemini ai ?

Unfortunately, directly using Google Gemini in its full form currently isn’t possible for most people. The  more powerful versions (Pro and Ultra) are still under development and mainly used within Google products and services like Bard. However, there are ways to experience some capabilities of Gemini indirectly:

1. Bard:  Bard, the platform you’re interacting with now, utilizes the Pro version of Gemini, allowing it to understand your questions and requests better and generate more informative and creative responses. So, by interacting with Bard, you’re already experiencing a taste of Gemini’s power. You can upload an image and provide a prompt based on the image to get an answer.
2. Smartphone Features: The Nano version of Gemini powers some features on specific Google Pixel devices, such as:
   • Summarize in Recorder: This feature, available on Pixel 8 Pro, uses Nano to automatically generate summaries of your voice recordings.
   • Smart Reply in Gboard: Nano helps power this keyboard feature on some Pixel devices, suggesting relevant and concise replies to messages.
3. Future Availability: Google plans to gradually make Gemini more accessible in the future. Keep an eye out for announcements about potential public trials or integrations into existing Google products and services.

Limitations of Google Gemini ai

Google Gemini is a super smart computer friend, but it’s still learning and growing. Right now, you can’t use it by itself, but you can see what it can do on platforms like Bard and some special phone features. It’s getting better, and one day, more people will be able to use it. But, like all cool things, Gemini has some things it’s not great at yet:

• It’s still learning: Gemini is in the early stages, and only a few versions are out, like Ultra, Pro, and Nano. So, not everyone can use it just yet.
• Lack of Common Sense: Being an AI tool often lack common sense reasoning. It may misinterpret information or make decisions that seem logical based on patterns in the data but don’t align with human understanding.
• Watch out for fairness: Gemini, like all smart tools, can sometimes be a bit unfair or make mistakes. It’s important to use all kinds of information when teaching it so it understands everyone.
• Privacy Concerns: Google Gemini or other AI chatbots often requires access to large amounts of data to function effectively. This raises concerns about privacy, as individuals may be uncomfortable with the collection and use of their personal information
• Ethical Dilemmas: As Google Gemini becomes more advanced, ethical concerns arise. Questions about how Google Gemini should be used, who is responsible for its actions, and the potential misuse of its powerful technologies are subjects of ongoing debate.

Conclusion:

Google’s new AI system Gemini represents a major advance in multifaceted intelligence. With its ability to understand and connect information across text, images, audio and more, Gemini scored higher than previous state-of-the-art AI models and even human experts on a range of benchmarks testing various skills.

The different Gemini models balance performance and practicality, enabling complex reasoning as well as basic on-device use. While still an ongoing research project, Gemini demonstrates Google’s ambition to develop safer, more capable AI that can assist people in new ways. The future capabilities of systems like Gemini remain to be seen, but its well-rounded intelligence could drive transformative applications across many fields. For now, we await more open testing and insight to better understand the strengths and limitations of Google’s promising new AI achievement. For now, we await more open testing and insight to better understand the strengths and limitations of Google’s promising new AI achievement.

If you don’t know how to use Google Bard, read the complete blog here for guidance –