What Is Google Gemini and When You Could See It Released
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What is Google Gemini? Defining Google Gemini AI
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.
What is Google Gemini? The Basics
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.
What Can Google Gemini Do?
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.
What is the Difference Between Gemini and Bard?
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.
Google Gemini: Performance Insights
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.
Is Gemini Better 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.
How do I Access Gemini AI?
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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Google’s stakes in the artificial intelligence (AI) space just got higher with the imminent release of Gemini, its most advanced large language model (LLM) yet. With Gemini, the search titan hopes to surpass OpenAI’s GPT-4 model with multimodal learning, the ability to execute more human-like tasks and be one step closer to artificial general intelligence (AGI).
Here’s what we’ll cover in this Google Gemini news article:
While Gemini’s performance is yet to be seen by the general public, Google has given access to select companies to try out this new LLM. How does this hold up to Google Gemini competitors? Let’s find out.
What Is Google Gemini?
Hinted as Google’s answer to GPT-4, Gemini is not just a “combination of scale, but also innovations,” according to Demis Hassabis, CEO and Co-Founder of Google DeepMind, a Google subsidiary dedicated to AI research and creator of Google Gemini.
This LLM is based on DeepMind’s previous multimodal models, such as the Flamingo and PaLM 2, to create its own interactive AI and further the frontiers of natural language processing. (NLP) And if you think that GPT-3’s model is large, with more than 170 billion parameters, Gemini is expected to exceed it in size to become the largest language model to date.
Google Gemini Features
Aside from being the largest language model, though, there are several Google Gemini features that you should look forward to based on recent reports. Here are some of them:
• Series of models: Hassabis said that we should think of Gemini as “individual models of different sizes,” which means this new platform can serve tasks of any size, depending on the use case.
• Multimodal learning: Gemini’s AI infrastructure has “several improvements” on top of Google DeepMind’s previous multimodal models, allowing it to learn and produce texts and images at the very least.
• Problem-solving and reasoning: Google’s new LLM also touts reinforcement learning to solve the problem of hallucination and information inaccuracy typically found in Google Gemini competitors like ChatGPT.
• Fact-checking and memory: Google Search as a tool is built into Gemini’s AI infrastructure to get better accuracy in generated content. Furthermore, Gemini will also use “episodic memory banks” to store and retrieve data, allowing it to build on and expand its knowledge base as it learns.
These features give us a peek into Gemini’s performance over other AI personal assistants and applications like ChatGPT and Bard. We can expect better interactive AI infrastructure and more accurate, relevant user results.
The Road to Gemini
Google’s latest developments in the AI space shouldn’t come as a surprise. Even before the rise of GPT-3, Google had been quietly building its own AI infrastructure to address users’ needs.
In 2018, Google unveiled Duplex – a voice-based AI assistant that could make phone calls and restaurant reservations on the user’s behalf. Beyond this, Google also launched BERT in October 2019 to improve natural language understanding (NLU) for search queries.
Google also made a lot of steps in recent months to improve its existing LLMs and interactive AI capabilities:
• Search Generative Experience (SGE): This is the company’s take on an AI search companion that summarizes user content while bringing traffic to the publisher’s website content.
• Google Bard: Bard is Google’s conversational AI utilizing a chat interface to answer questions, give topic summaries and even create poems
• Responsible AI with Anthropic: Google invested $300 million to double down in its mission for a safer, more ethical use of generative AI.
Gemini looks like the peak of Google’s efforts and is easily the company’s largest language model to date. This improvement in scale isn’t just for show as well. According to Hassibis, they reduced the error rate from 10% to only 1%, which is a massive improvement.
Google Gemini Release Date
All this Google Gemini news wouldn’t be complete without a date, so when should you expect to see it?
Unfortunately, we can’t give a solid number yet, but it might probably be available by the end of 2023, according to The Information. In fact, the search engine company has already greenlit Gemini access to some developers, and you’ll soon see its beta release in Google’s Vertex AI platform.
Will This Be the New King of Advanced Chatbots?
While multimodal learning and interaction are not new, these Google Gemini features position the LLM as a rival to OpenAI’s GPT models and other AI alternatives in the market. Let’s look at how Gemini measures up to its biggest competitors.
1. AI Personal Assistants
If you’re using advanced chatbots like Google Bard, Claude or ChatGPT, you’re also using their underlying language models. You can use these tools to create Amazon ads, Facebook or just to get advice. They’re also able to answer questions and help with decision-making.
What makes Gemini’s performance unique is its multimodal models, allowing users to generate different types of content, such as:
• Texts
• Images
• Charts
• Other data types
Furthermore, you’ll also enjoy conversing with a model that can plan, remember and reason. This means you can assign more human-like tasks to Gemini and expect it to deliver.
2. GPT-4
Currently a paid service, GPT-4 is the closest of all Google Gemini competitors at the moment. It’s robust, multimodal and “stable,” according to OpenAI. Right now, you can try GPT-4 with ChatGPT Plus, giving you a glimpse of its text-based capability. You can create blogs, pay-per-click (PPC) content and customer service conversations with the help of GPT-4.
But how is Gemini different?
Its seamless integration with Google Search sets it apart from GPT-4, which still requires the activation of plugins to generate relevant, timely content.
For Gemini, fact-checking and reinforcement learning are already built into its engine, allowing for more accurate generated content. While we’re not sure about its other multimodal capabilities, we can expect that it will be on par with GPT-4 at the very least.
3. Bing Chat
Google’s latest developments should also be compared with its nearest competitor in the search engine space – Bing.
The Microsoft-led company also has its version of an AI search companion called Bing Chat, a fusion of Bing Search and ChatGPT. Basically, you can access Bing’s search engine power while in a conversational interface akin to OpenAI’s ChatGPT.
It’s also multimodal in that you can generate images with a prompt. (Read more: Bing Image Creator Tool)
While OpenAI’s technology powers Bing Chat, Gemini is a brand-new LLM that will be used across Google’s AI-powered services.
4. Llama 2
Meta, Facebook’s parent company, has also released (a.k.a. leaked) its own LLM called Llama 2. Unlike other AI personal assistants, including Gemini, Llama 2 is open-source. This means end-users have the power to modify its elements based on their specific use cases.
Being open-source has advantages in encouraging collaboration and innovation among developers. However, there is also a risk of malicious actors taking advantage of the technology.
Gemini is a closed-source LLM, bringing added security while trading off customizability. The question of which model is better ultimately boils down to preference.
What Should You Do?
Any AI and Google enthusiast should welcome this Google Gemini news. After all, you’ll finally have a conversational AI tech that goes toe-to-toe with OpenAI.
For now, though, all you have to do is sit and wait as the select few developers tinker their way around Google Gemini. You can still access some of Google’s experimental features through Google Labs. All you have to do is join the waitlist to try out the following features
• Project IDX
• Magic Compose
• Search Generative Experience
• Duet AI
• MusicLM
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