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Google Gemini: What we know so far
Published: September 29, 2023
Rebekah Carter
The LLM arms race is on. Every tech leader, from Meta to Microsoft, is now going all-in on generative AI and innovative tech. Google Gemini, announced at the Google I/O developer conference in May 2023, is one of the most recent AI solutions set to transform the marketplace.
Announced just after Google shared its decision to combine its DeepMind and Brain AI labs to create a brand-new research team (Google DeepMind), Gemini represents Google’s focus on increased AI investment. The solution follows the launch of Bard, Duet AI, and Google’s PaLM 2 LLM.
Though the technology is “still in training,” according to Google, it could have the power to transcend OpenAI’s position in the AI marketplace. Google notes the solution, trained to be “multimodal” from the ground up, already demonstrates exceptional performance.
Here’s everything you need to know about the AI technology.
Google Gemini is one of the most recent additions to Google’s AI-focused digital roadmap. Built to become Google’s “flagship AI,” Gemini is designed for highly efficient tool and API integrations and consists of a “group of large AI models” rather than just one LLM.
Though details about the technology remain scarce, Google’s announcement in May suggests the service will take a similar approach to GPT-4’s model architecture, offering access to various capabilities. Moreover, Google has indicated that, like PaLM 2, when Gemini becomes fully available, it will be provided in multiple sizes and forms.
Reportedly, Google Gemini can generate images and text, thanks to training, including video transcripts from YouTube. It’s also rumored to have fantastic coding abilities. Like Microsoft’s strategy with Copilot, Google will gradually integrate Gemini into all its products, including the Bard Chatbot and Google Workspace.
Additionally, later this year, Google says Gemini will be available for developers to access through the Google Cloud. Google’s Chief Scientist, Jeffrey Dean, said the next-gen multimodal model would utilize “Pathways,” Google’s AI infrastructure, to enable scaling and customization.
Though some industry analysts have suggested Google Gemini will be released later this year, not much has been revealed about the model’s capabilities.
The solution uses an architecture combining a multimodal encoder and decoder, meaning users can input various prompts (from text to voice and imagery) and receive relevant responses. According to an anonymous source involved with the project, the AI will not just “compete” with solutions like ChatGPT but surpass other tools.
Initially, Google will focus on developing a multifunctional product that produces images and text. However, eventually, you may be able to use the same solution to analyze flowcharts, control software, or create code. Used alongside Google’s productivity and communication tools, the solution also has the potential to improve employee efficiency and creativity significantly.
CEO of DeepMind, Demis Hassabis, said that techniques from AlphaGo, such as tree search and advanced reinforcement learning, could give Gemini advanced abilities for problem-solving and intelligent reasoning. Additionally, he noted Gemini might use memory to fact-check sources against Google Search and improved reinforcement learning to reduce hallucinated content.
Google Gemini isn’t the first time we’ve seen Google experimenting with AI and large language models. After ChatGPT became widely available, Google, like many competitors, jumped into action to create its own models. The AI-powered chatbot Bard is one example.
While Bard is a bot very similar in style to ChatGPT, capable of creating responses to natural language inputs, Gemini is set to be the AI framework that underpins this technology. It’s currently being developed by several Google Brain and Deepmind team members, including Sergey Brin, Paul Barham, and Tom Henningan.
Google is a next-generation foundation model that will strengthen the functionality of Google’s other AI tools while also allowing developers and enterprises to create their own solutions.
Due to the lack of information on Google Gemini’s capabilities, you might assume the tool will be very similar to many other large language models. However, some analysts, such as “SemiAnalysis”, suggest the tool may outperform existing models like GPT-4.
For instance, Gemini is more adaptable than OpenAI’s service. It can handle various kinds of data and tasks without comprehensive fine-tuning. Plus, it can learn from numerous domains and data sets without restriction from labels or predefined categories.
Moreover, thanks to its advanced reinforcement learning capabilities, Gemini is highly creative. It can generate novel outputs, going beyond the insights it can gain from training data. Moreover, Gemini isn’t limited to a single modality. It can offer a range of outputs in different formats.
SemiAnalysis says this tool is five times more powerful than the most advanced GPT-4 solutions on the market. They also suggest that the solution could be 20 times more powerful within a few years than ChatGPT.
As tech giants continue to enter the generative AI and LLM playing field, the top question on many people’s minds is: “Will it outperform ChatGPT?” The answer to this question remains uncertain. For now, we know that GPT-4, the technology powering the latest version of ChatGPT, is a little different from Gemini in various ways.
GPT-4 boasts 1 trillion parameters and can understand and generate natural language. This makes it exceptionally powerful for text data tasks. However, Gemini, developed by Google, is a multi-modal intelligence network. It can handle various types of data and jobs simultaneously, processing text, images, audio, video, 3D models, and graphs.
This could mean Google Gemini is more versatile than GPT-4 and ChatGPT. Additionally, it’s worth noting that Google’s extensive access to a vast array of proprietary training data ensures the company can continue to enhance the service going forward.
Google Gemini can process data from various services, including Google Search, Google Books, YouTube, and Google Scholar. This could give the model a distinct edge over other models.
Of course, it’s also important to mention that OpenAI isn’t the only AI company Google needs to outperform going forward. Meta is also working on an AI model, according to some reports, and may soon launch a new LLM to potentially de-throne OpenAI.
Already, Meta announced the release of their Llama 2 open-source AI model in partnership with Microsoft, so it seems likely that the company will continue to progress in this landscape.
Google Gemini AI will gradually roll out into the various AI tools and services that Google offers in the months ahead.
However, it’s not currently available to access and customize on a massive scale. According to Google, they’re still working on fine-tuning and rigorously testing the model for safety. This is crucial when companies are becoming more concerned about the ethics and transparency of AI large language models.
When the model meets Google’s high standards, the team says the technology will be available in various sizes and tuned for different capabilities.
Companies can access packages like those available for PaLM 2, with unique options for smaller and larger businesses.
Though we’ll have to wait and see just how powerful Google Gemini is, it could change interactive AI as we know it. Google’s incredible research team and AI experts certainly have the skills to create a solution that brings generative AI to billions of people and use cases.
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