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Artificial Intelligence

Google Gemini - The Most Sophisticated Multimodal AI

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Google introduces its latest innovation, Gemini, as a multimodal AI developed by the Google DeepMind team. Here is the information.

Google introduces its latest innovation, Gemini, as a multimodal AI from the Google DeepMind team. Claimed to be the most advanced AI based on benchmarking against competitors. Here is the information.

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Key Takeaways
  • Google Introduces Gemini as the Latest and Most Advanced AI Model Developed by the Google DeepMind Team.

  • Gemini becomes a multimodal AI that can understand various types of prompts simultaneously such as text and images, text and audio, and code.

  • There are three versions of Gemini available, each with its capabilities.

  • Currently, Gemini is still in the development stage and will be released globally in 2024.


In its latest post, Google has introduced Gemini, its newest and most powerful artificial intelligence (AI) model. Learn what Gemini is, all its versions, capabilities, and how to use it here.

 

What is Gemini?

Google Gemini is a set of large multimodal language models developed by Google DeepMind. Gemini is the successor to LaMDA and PaLM 2 and is claimed to be the most powerful large language model.

Gemini has multimodal understanding and generation capabilities. This means that Gemini can process and generate content in various formats, including text, code, images, and videos. This ability allows Gemini to perform various complex tasks.

Developed by the leading team at Google DeepMind under the visionary leadership of Demis Hassabis, Gemini is evidence of Google's commitment to remain a forefront company in AI.

Various Versions of Gemini

In Gemini 1.0, there are currently three versions, each with its capabilities and advantages. Here's a review of each.

 

1. Gemini Ultra

Gemini Ultra is the most advanced version of Gemini, with 1.5 trillion parameters. This version has the most superior multimodal understanding and generation capabilities and can be used for various complex tasks such as:

  • Answering questions with in-depth understanding, even for complex questions.
  • Translating languages more accurately and naturally.
  • Generating creative content, such as poetry, stories, or code.

 

2. Gemini Pro

Gemini Pro is a lower version of Gemini Ultra with 500 billion parameters. This version has similar capabilities to Gemini Ultra but with lower performance. Gemini Pro can be used for various tasks, such as:

  • Answering questions with good understanding.
  • Translating languages quite accurately.
  • Generating creative content that is quite engaging.

 

3. Gemini Nano

Gemini Nano is the smallest version of Gemini, with 100 billion parameters. This version has more limited capabilities but can still be used for various tasks, such as:

  • Answering questions with a decent understanding.
  • Translating languages is fairly accurate.
  • Generating relatively simple creative content.

 

In the context of large language models, parameters are numbers used to represent relationships between various concepts and words.

 

Next-Generation Abilities

Gemini is still in development but has the potential to change various aspects of its users' digital lives. As reported by Google, they will introduce the next generation of Gemini with enhanced capabilities. Here are some improvements to Gemini:

  • More sophisticated reasoning: Gemini is expected to have more sophisticated reasoning abilities. This means Gemini will be able to better understand the relationships between various concepts and words, making more accurate inferences and conclusions.
  • Understanding text, images, audio, and more: Gemini can currently understand text, images, and audio. However, in the future, Gemini is expected to better understand various types of data.
  • Advanced coding: Gemini can currently generate code, but in the future, Gemini is expected to generate more complex and efficient code. For example, Gemini will be able to produce more modular code, making it easier to modify and fix.

 

Security and Accountability Assurance

Google is committed to making Gemini a responsible large language model. To achieve this, Google implements various steps, including:

  • Internal evaluation: Ensuring that at every stage of development, there is a consideration of risks and their handling.
  • Regular monitoring and evaluation: Google regularly monitors and evaluates the performance of Gemini to ensure that this model does not produce harmful, biased, or discriminatory content.
  • Potential risk research: Google conducts research to identify biases and toxicity such as cyber-offense and other crucial issues.
  • Collaboration with external experts: To identify Gemini blind spots, Google collaborates with external experts to ensure that this technology operates under policies.

 

Using Gemini

Gemini is currently in the development stage and is only available to a select few Google users. Google plans to release Gemini to the public in 2024.

Currently, Gemini 1.0 is being rolled out on some Google products such as Bard, Pixel 8 Pro, and some experiments on SGE. As for Google Cloud Vertex AI, the Gemini Pro API will be available on December 13th to facilitate developers and other customers.


Article Source

As a dedicated news provider, we are committed to accuracy and reliability. We go the extra mile by attaching credible sources to support the data and information we present.

  1. Google DeepMind: “Gemini Era” https://deepmind.google/technologies/gemini/#introduction 
  2. Google Blog: "Introducing Gemini: our largest and most capable AI model" https://blog.google/technology/ai/google-gemini-ai/ 
  3. Google for Developers: "How it’s Made: Interacting with Gemini through multimodal prompting" https://developers.googleblog.com/2023/12/how-its-made-gemini-multimodal-prompting.html

Disclaimer: All news published by cmlabs has undergone a strict verification and data processing process based on the cmlabs News Publication Guidelines. However, the data or core news we write may undergo changes, reductions, or additions. Consequently, cmlabs assumes no liability for any losses or damages that may arise from the use of this information. We encourage readers to conduct additional verification before making decisions based on the information written on this page.

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Tati Khumairoh

Tati Khumairoh

An experienced content writer who is eager in creating engaging and impactful written pieces across various industries. Using SEO approach to deliver high-quality content that captivates readers.

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