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Home CV Talks What is Google Gemini? Top Facts and Uses to Know in 2024

What is Google Gemini? Top Facts and Uses to Know in 2024

Dec 21, 2023 1.3K Reads

Ever since the release of the new AI model, Google Gemini by the search engine and IT giant Google, the domain of artificial intelligence has yet again stirred up conversations about this latest release. The claims by Google about the novel and unique features brought forth in this new AI model have made it a major contender outshining other existing AI models. 

The nuances of this model and its features, uses and applications are still a mystery to many owing to the recency of its release. But here, we have delved into the various features and applications that Google Gemini brings to the access of users as well as evaluate certain key concerns that arise with the novel features and developments it brings forth. 

What is Google Gemini?

On 6 December 2023, almost a year after the release of the AI chatbot Chat GPT that took the world by storm, Google released the “most capable and general model it has ever built”. Google Gemini is a collaborative model engineered by the Google Research team along with the Google DeepMind unit. 

Unlike the vast majority of AI tools and bots that are being developed by AI engineers, Google Gemini is an artificial intelligence model that can be integrated in and rolled out on a number of AI tools and devices as well. Google Gemini is a multimodal AI model that is capable of gathering information and efficiently processing and analysing it in a number of formats simultaneously, a characteristic intrinsically different from the current existing models that are either trained efficiently in one domain or analyse multiple modes of inputs at a superficial level successively.

Introducing Gemini

Google Gemini is a generalised AI model not only capable of gathering inputs in multiple formats but also performing a variety of functions efficiently, unlike AI tools and bots programmed to perform only a particular domain of functions. 

Top Advanced Features of Google Gemini

Google claims that Gemini, unlike other artificially intelligent models, comes closest to (and manages to surpass in some cases) the human intelligence in its holistic nature. It is being claimed by Google as being efficient in its functioning across data centres to mobile devices. 

Here are a few of the top features that Google Gemini brings to the table with its advanced engineering and data designing. 

  • High Flexibility: One of the primary distinguishing features of Gemini is that it is one of the most flexible AI models introduced by Google that is suitable for integration and roll-out in a majority of domains ranging from data centres to interconnected devices to chatbots and other AI tools. Gemini as a model can put to effective use its detailed engineering and programmed intelligence to work effectively on a diverse number of platforms.
  • Natively Multimodal: Google Gemini is a novel and pioneering AI model in that it is designed from “bottom-up”, i.e. from the ground level of programming to be multimodal in nature. Human intelligence is holistic by nature, as it can evaluate and carefully analyse multiple modes of information (vis. a. vis. visuals, text, sound etc.) to derive insights from them, an aspect existing AI tools aren’t adept at mimicking. However, Google Gemini is trained from its grassroot programming to be able to assess and analyse inputs in multiple formats (text, visual, audio, motion etc.) to use it for effective reasoning. This is starkly in contrast with the existing models of AI that are trained to separate multimodal content to analyse them separately and further combine those analyses. Google Gemini starts interpreting and reasoning with information in the multimodal format itself. 
  • High Adaptability: Google Gemini is an adaptive AI model that has immense capacities for performing nuanced tasks and smartly adjusts its functioning with respect to the device or service platform it is working with, e.g. on Google Pixel devices versus on Google Bard. 
  • Outperforming Human Intelligence: One of the prime reasons for Google Gemini to have stirred strong discourses in the technological front is its outperformance of human intelligence. Trained to display sophisticated and advanced reasoning much similar to that exhibited by well-trained experts in various fields, Google Gemini was the first AI model that outperformed humans on massive multitask language understanding (MMLU) with a score of 90%. 
  • Nuanced Knowledge/Abilities in Multiple Domains: Google Gemini is capable of performing a number of tasks across various ranges with advanced expertise, a feature missing in many prominent existing AI models as well. It can effectively perform a number of tasks in domains related to advanced reasoning and problem-solving, coding, multimodal analysis, mathematical problem-solving, coding and development and so on. Moreover, the scores achieved by the model on tasks of these domains exemplify stellar performances akin to those exhibited by experts in these fields. As per statistics released by Google, Gemini has exceeded the current state-of-the-art results on 30 out of 32 widely-used academic benchmarks used in large language model (LLM) research and development.
  • Available Sizes: Currently, the model is available in 3 sizes based on the complexity of tasks they are designed to handle. The current first version of Google Gemini is available for testing and integration in three sizes, Gemini Ultra, Gemini Pro and Gemini Nano. 

Top Features of Google Gemini

What are the Applications of Google Gemini?

Google has created Gemini to work on 3 different scalable sizes depending upon the complexity of functions that these sizes have been programmed to be capable of performing. Currently, the following three sizes of Gemini have been released by Google for use in the first version of the model:

  • Gemini Ultra: The Ultra model of Gemini is the most nuanced and largest model created to address advanced and highly complex tasks with ease.  
  • Gemini Pro: The Pro model of Gemini is designed to exhibit efficient multitasking abilities. For instance, it has been designed to effectively carry out and scale a wide range of tasks with expert knowledge and deftness.  
  • Gemini Nano: This size has been designed keeping in mind the size and range of tasks performed on devices such as android devices. Thus, Nano is a comparatively smaller range model designed for efficient performance on devices. 

Available Sizes for Google Gemini 

Currently, Google is executing the application of Gemini by effectively integrating it with a variety of Google services and tools like Google Bard (the AI chatbot by Google), Google Pixel devices etc. The use of Gemini is being provided by Google in the following domains: 

  • Google Bard: Google Bard, since the release of Gemini, is integrating the Pro version in the fine-tuned manner into the Bard services. Moreover, in 2024, Google Bard Advanced is to be launched that would integrate the full potential of Gemini in its reasoning, planning and understanding. The current model, while available in English, is being developed to work equally well in other languages. 
  • Google Pixel Devices: Google is already working on integrating Gemini features into its Google Pixel android devices, with Pixel 8 all set to integrate Gemini Nano in services like summarisation on voice recording applications, “Smart Reply” for messaging applications such as Whatsapp and so on. 
  • Google AI Studio: From December 13, 2023, Google AI Studio and Google Cloud Vertex AI would allow for the Gemini API to be visible on the platform for programming and building using its services. 
  • Gemini Ultra: Google has announced that while it is occupied with nuanced pilot testing and further development of the Gemini Ultra model, it shall release a version of Ultra early in 2024 for use by select Beta users and enterprises. Upon further programming based on reinforcement learning from human feedback (RLHF), the model is expected to be released for use by all users including developers and enterprises. 

Thus, it can be seen that Google has created a seamless transition pipeline for the integration of Gemini as its new and most advanced AI model into the various services and products by Google. Gemini is being claimed by Google as being its largest and most transformative generative AI model as of yet, set to alter the +face of artificial intelligence and its application in the modern world. 

Key Ways to Access Google Gemini

Key Concerns Related to Google Gemini

As is the case with any newly released AI model, Gemini is under the scrutiny of users as well as experts for a number of key concerns that it might face or the implications its usage can have in the future. 

Here we have highlighted a few of the prominent concerns that are being raised since the release of Gemini about its implications.

  • Security and Cyber Well-Being of Users: This is one of the primary concerns that has also been identified by the Google Deepmind Team. Gemini being designed as a multimodal model, it can be tough for it to assess the threat, offence or risk. For instance, while the imagerial input offered to the model may not be threatening, the combined inputs provided through image, text and audio may carry some threatening or offensive undertones. This concern is being acknowledged by Google as its team is working on engineering nuanced protection and safety evaluations for the model and examining the role of adversarial testing techniques to provide a safeguard for the users’ well-being. 
  • Threats to the Society: Google Gemini, owing to its complex programming, is highly advanced in the domain of scientific and mathematical reasoning. Its multimodal functioning also makes it highly adept at analysing and providing scientific and mathematically well-reasoned solutions to complex problems. This has raised prominent questions about the potential risk this model can harbour by providing risky and dangerous solutions, such as nuclear and physics-related solutions for inputs and prompts. However, thet team at Google is working towards creating multilayered safeguards for user well-being and safety which would prevent Gemini from providing solutions to inputs that carry potentially harmful implications for the society or humanity. 
  • Impact on Human Employability: A common concern associated with any artificially intelligent software or tool is its implications for humans. Similarly, with the majorly transformative skills and expertise of Gemini, which goes as far as exceeding human intelligence on certain parameters, has raised significant concerns on its impact on the employability of humans across a range of industries and career domains. Gemini’s abilities for coding, creation, analysis, reasoning and more make it suitable for efficient use in not only the IT, finance or similar sectors but is also expected to contribute to significant scientific breakthroughs, all of which raise the important question about how it would impact the role of human intelligence in professional activities. 

  Thus, while Gemini is being lauded for its capabilities and advanced features for performing various activities and outperforming humans on a number of tasks, concerns about the long-term implications of such an AI model are pertinent areas to focus upon as well. The implications that such models can have on humans at an individual as well as societal level need to be taken into consideration before their widespread deployment to ensure that human services and skills don’t turn obsolete. 

Concluding Note: Is Gemini the New Big Name in AI?

On the basis of the performance reports of Gemini released by Google as well as the vision with which Gemini was created, it can be said that the future of Gemini and artificial intelligence across the globe is awaiting a boom and complete transformation. The Gemini model is especially designed to come as close as possible to the holistic and integrative nature of human intelligence and can be a major driving force in analysis and breakthroughs in the endeavours towards maximising the well-being of humankind.

FAQs (Frequently Asked Questions)

Google Gemini is an AI model that has been created by Google with certain unique and advanced features such as multimodal functioning, complex programming and so on. It is one of the first AI models that has outperformed humans on  massive multitask language understanding (MMLU) tasks.

No, Google Gemini is not an application or software, it is an AI-based model that can be integrated with other functions and applications to provide smart services. 

Google Gemini is currently being offered in fine-tuned versions on Google Bard, which can be accessed through a mobile phone. So if you are using Google’s AI chatbot, Bard, on your mobile phone, you can use Gemini on your cell phone. Additionally, Gemini services are being provided by Google on its android devices–Google Pixel 8 phones, so if you have or plan to purchase Pixel cell phones then you can make full use of various Gemini services on your phone.

Google Gemini cannot be directly used by a user since it is not an AI bot, tool or software. Rather, it is a model that is integrated into the very services and other AI tools such as Google Bard, Google API, Google AI Studio or Google Pixel devices. So, if you want to use Gemini, you can use it through Pixel phones or through the AI Studio of Google or Bard.

While the Pro and Nano versions are being fine-tuned and offered for services in Bard and Pixel as of now, the full functionalities and features of Gemini are expected to be available for use from early 2024. 

While OpenAI’s Chat GPT caused quite a stir upon its release in December 2022, it is based on GPT Model 3, which is less advanced than Google Gemini, a highly complex and advanced multimodal AI model. Moreover, while Chat GPT is an AI chatbot capable of performing only a certain range of tasks, Gemini is an integrative model that can perform a large variety of tasks across a range of domains with deftness. 

Gemini is an advanced AI model created by the collaborative efforts of Google, Google Research Team, and Google Deepmind. 

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