Not Your Usual LLM: What Google AI Aims to Achieve with Gemini
With promises of groundbreaking capabilities in reasoning, code generation, and multimodal understanding, Google’s Gemini sparked a wave of interest in the tech world when it was announced in December 2023. The model was developed by Deepmind, a Google subsidiary focused on AI innovations, and seemed poised to revolutionize the AI landscape. However, the initial excitement has been tempered by a lukewarm reception. Let's dive in and explore the current state of Google’s ambitious AI project.
Google's newest AI in 90 seconds | Gemini
We’ve written an introduction to Google Gemini, including its model sizes and some initial comparisons to its competitor, OpenAI’s ChatGPT. Today, we’ll take a closer look at the advanced capabilities that piqued AI enthusiasts’ attention. Here’s a summary of Gemini’s top features:
- Native Multimodality: While other AI models might require separate training for different tasks (such as processing text, code, and images), Gemini can handle various formats seamlessly. This allows it to understand complex relationships between different types of information.
- Advanced Reasoning: Google AI highlighted that Gemini outperformed human experts on the MMLU (Massive Multitask Language Understanding) benchmark, which assesses an AI’s ability across various domains, including math, physics, history, law, and medicine. This suggests that Gemini’s capabilities extend beyond simple pattern recognition. It might possess abilities to reason through problems and draw logical conclusions, making it well-suited for tasks requiring deeper understanding.
- Direct Web Access: Unlike some AI models that rely on pre-loaded data, Gemini can directly access and process information from the web in real time through Google Search and other resources. This allows it to stay up-to-date and provide more accurate results.
- Integration with Google Workspace: As a Google product, Gemini could be tightly integrated with various Google Workspace tools like Gmail, Docs, and Drive. This seamless integration could significantly enhance user productivity.
How Google AI’s Gemini Has Been Received
The promise of what Gemini could do differently and better than its competitors initially created hype in the AI space, but the model hasn’t received the warmest of welcomes. The first major red flag came in the form of a viral video demonstrating Google Gemini’s multimodal skills, which was later revealed to have been partially staged. This raised questions about Google’s transparency and cast doubt on the true capabilities of the model. Gemini was also panned for producing inaccurate images, prompting Google to apologize and put a pause on the AI’s image generation of people.
Google AI opted for a limited developer release, prioritizing feedback from technical users over large-scale public access. This strategy may have allowed for refinement before wider adoption, but it created a sense of mystery surrounding the actual user experience. The gradual rollout of Gemini’s multimodal functionalities also left developers underwhelmed by what Gemini could really do. Reviews were mixed, with some developers impressed by Gemini’s potential and others remaining cautious due to the limited information available.
There’s also been varied feedback from the public, with some users reporting errors and hallucinations in Gemini’s responses and others declaring it their new preferred platform. It seems that Gemini’s performance differs across tasks. Many people have praised the tool as an aid in writing, but reviews suggest it’s not great with coding and image generation.
Developer Access to Gemini
There now seems to be a wait-and-see approach toward Gemini, and that includes how Gemini evolves and performs in the hands of developers. The AI is accessible via Google AI Studio and Google Cloud Vertex AI. Google has also released Gemma, a family of open-source models powered by the same research and tech as Gemini. If you’re looking to build and experiment with Gemini or the Gemma models, it’s best to have an AI PC that’s designed to handle your projects and workloads efficiently, like the Acer Swift X 14 laptop. Optimized for many AI apps, it also features next-gen processors that deliver enhanced performance, speed, and graphics.
For now, Gemini’s true capabilities and impact on the AI landscape remain unclear. Only time will tell if Google’s AI model can live up to its transformative potential and if the tech giant can truly be a worthy challenger in the AI world.
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About Micah Sulit: Micah is a writer and editor with a focus on lifestyle topics like tech, wellness, and travel. She loves writing while sipping an iced mocha in a cafe, preferably one in a foreign city. She's based in Manila, Philippines.
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