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:
• What Is Google Gemini?
• The Road to Gemini
• Google Gemini Release Date
• Will This Be the New King of Advanced Chatbots?
• What Should You Do?
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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