Google Gemini: The AI model by Google

Author(s): Manika Nagpal

Originally published on Towards AI.

Google’s launch of Gemini, proclaimed as a groundbreaking AI model and their most potent yet, signals a continued surge in AI advancements. Despite AI's exceptional year since ChatGPT’s debut, the momentum shows no signs of slowing. OpenAI’s surprise at ChatGPT’s impact initially led to apprehension due to its wide capabilities, prompting calls for caution. However, with Google’s aggressive move, unveiling Bard earlier and now Gemini, the landscape is shifting.

Gemini is apparently a new AI designed to compete with OpenAI. At first, people were excited by its impressive performance and flashy demo. But as experts looked closer, they found issues. The demo exaggerated what Gemini could do, and comparisons with existing AI showed it might not be as groundbreaking as thought. Still, Gemini stands out for its ability to understand different types of content. Despite some confusion, it could become a strong rival to other AI models, even though its full impact and release date are still uncertain.

Dive into more such exciting deets of Google Gemini with me in this blog!

Google Gemini is multimodal

PaLM 2, also known as Pathways Language Model 2, serves as Google’s fundamental technology fueling AI capabilities across its extensive range of offerings. This encompasses Google Cloud services, Gmail, Google Workspace, hardware like Pixel smartphones and Nest thermostats, and notably, the renowned AI chatbot Bard. Gemini marks a significant leap in AI evolution, distinct from Google’s PaLM 2. While PaLM 2 fuels Google’s extensive suite, Gemini stands out as a multimodal marvel, transcending conventional AI boundaries.

Sundar Pichai, unveiling Gemini amid its developmental phase, emphasized its core difference. “Gemini was created from the ground up to be multimodal,” he asserted. Multimodal AI, often misunderstood merely as adaptable to various content types, holds a deeper meaning for Google.

During Alphabet’s Q3 2023 earnings on October 24, Pichai hinted at the profound impact of this multimodal venture. “We’re laying the foundation for the next-generation series of models, rolling out throughout 2024,” he disclosed. The fervent pace of innovation underlines Google’s commitment to pioneering AI advancements.

GPT-4 vs Google Gemini

Gemini encompasses a range of models — Gemini Ultra, Gemini Pro, and Gemini Nano — each tailored for specific functions and computational power. It’s a natively multimodal AI, designed to seamlessly process text, images, audio, and code. In contrast, GPT-4 from OpenAI, the latest in the Generative Pre-trained Transformer series, is renowned for generating human-like text and handling text and image inputs.

The comparison between Gemini and GPT-4 reveals their strengths across various benchmarks. Gemini Ultra showcases prowess in diverse areas: from mathematics to code generation, image and video understanding, and audio processing. It excels in multi-discipline reasoning but slightly trails in certain areas like commonsense reasoning compared to GPT-4.

Gemini’s standout feature lies in its native multimodal capabilities, covering audio and video in addition to text and images, setting it apart from GPT-4. Integrated into Google Bard and tailored for different platforms, Gemini offers a versatile, powerful AI experience. Conversely, GPT-4’s dominance in language processing finds extensive use in content creation, translation, and education.

Both models — Gemini and GPT-4 — present distinct strengths, making the choice contingent upon specific task requirements. Gemini’s multimodal edge and integration within Google’s ecosystem make it a robust choice for audio and video processing, while GPT-4 shines in text-based AI tasks. As AI progresses, the potential and applications of these models are poised to expand, heralding an exciting phase in artificial intelligence.

Lastly, Gemini stands out due to its developer accessibility, unlike other models like ChatGPT. Pichai emphasized its efficiency with tools and APIs, showing Google’s intent to empower developers. Early access leaks revealed Gemini’s integration into MakerSuite, unveiling its multimodal capabilities for code generation, NLP apps, text, and object recognition.

How can Organizations benefit from Google Gemini?

Organizations can immensely benefit from Google’s Gemini- a multifaceted AI model designed for versatile integration and application. Its multimodal nature, capable of comprehending text, code, images, audio, and video, mirrors human-like perception and interpretation, enhancing its usability across various sectors.

Gemini’s integration into Google’s unified AI stack unlocks numerous opportunities. It synergizes with Google Cloud’s scalable infrastructure, offering leading-edge AI-optimized resources for training and deploying models, now inclusive of Gemini. The model’s flexibility spans from data centers to mobile devices, catering to varied computational needs.

Moreover, Gemini amplifies the Vertex AI platform, empowering developers to craft innovative agents spanning text, code, images, and video. With tools for customization, fine-tuning, and augmentation, Vertex AI harnesses Gemini’s potential, enabling comprehensive agent management and deployment.

The expansion of Duet AI, Google’s collaborative AI platform, incorporates Gemini’s capabilities across developer tools and security operations. It facilitates faster coding and enhanced troubleshooting and aids cybersecurity responses, accelerating threat detection and remediation.

Gemini’s addition propels advancements across Google’s AI technology stack. Cloud TPU advancements, like TPU v5p and AI Hypercomputer, cater to the escalating demands of GenAI models, ensuring high-performance and cost-efficiency. Furthermore, Google’s commitment to expanding indemnification and competitive pricing makes Gemini accessible to a broader spectrum of organizations.

Google’s comprehensive AI innovations, integrated with Gemini, pave the way for AI-powered advancements across industries. They offer unparalleled opportunities for organizations to revolutionize digital transformations, fostering the creation and adoption of advanced GenAI agents.

If you are interested in exploring the working of such AI innovations, we highly recommend you explore Large Language Models with the help of websites like Kaggle, ProjectPro, GitHub, etc.

Hope that was a fun info session on Google Gemini!

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Published via Towards AI