Google has announced the phased rollout of its new ‘Gemini’ family of large language models with the Ultra version said to rival the abilities of OpenAI’s GPT-4.
What Is Gemini?
Gemini, which Google describes as its “newest and most capable” large language model (LLM) and representing a “new era” for AI, is a highly advanced and multimodal AI model. Gemini is a foundational model and not a product like a chatbot. This means it’s designed to be integrated into Google’s existing (and future) products such as its Bard chatbot and Google Search.
The Key Difference
The key difference to competing LLMs is Gemini’s native multimodality, which means it was built from the ground up to understand, process, combine, and generate different types of data seamlessly, i.e. text, code, audio, images, and video.
This approach differs from traditional multimodal models which often train separate components for different modalities and then stitch them together. As a result, Gemini can handle complex tasks involving various inputs more effectively than its predecessors, thereby making it particularly versatile and powerful.
Three Versions
Google has produced three versions of the Gemini model, each one optimised for specific tasks. These are:
– Gemini Ultra. This is the largest and most capable version of the model, designed for highly complex tasks. For example, Google reports that it excels in various benchmarks, outperforming existing models and even human experts in Massive Multitask Language Understanding (MMLU). Gemini Ultra is particularly strong in fields requiring advanced reasoning and understanding, such as mathematics, physics, history, law, medicine, and ethics.
– Gemini Pro. This model version is versatile and has been optimised for scaling across a broad range of tasks. It has, therefore, now been integrated into Google Bard to enhance its capabilities. This upgrade has reportedly improved Bard’s performance in understanding and summarising information, reasoning, coding, and planning.
– Gemini Nano. This version is the most efficient model, tailored for on-device tasks. Its efficiency makes it suitable for applications that require AI capabilities directly on mobile devices or other hardware with limited processing power.
Performance
In terms of performance, Gemini is reported to have shown exceptional results, surpassing state-of-the-art models in many areas. Google claims, for example that Gemini can outperform OpenAI’s GPT-4 platform (which powers ChatGPT) on 30 of the 32 widely-used academic benchmarks!
Gemini has demonstrated advanced capabilities in not just understanding and reasoning across different modalities but also in coding, being able to understand, explain, and generate high-quality code in multiple programming languages.
Adding To Google’s Search?
As expected, and intended, Google has been reported to be experimenting with integrating Gemini into its Search Generative Experience (SGE), where it has already shown improvements in speed and quality. This integration could have the potential for Gemini to enhance Google’s search capabilities significantly thereby upping the ante in the search engine market.
Downsides?
Although Gemini’s exceptional abilities point to a “new standard” being set (as described by Gartner’s Chirag Dekate), this kind of power is bound to come with risk and downsides. For example:
– Possible ethical and societal Impacts. AI systems with advanced reasoning capabilities could still make decisions or produce outputs that reflect biases present in their training data, leading to potential ethical issues and unfair representations in sensitive areas.
– Privacy concerns. The extensive data processing capabilities of Gemini could raise significant privacy concerns, especially regarding personal data misuse, and these concerns could increase as this type of model become more integrated into everyday technologies, e.g. Gemini Nano on devices.
– Misinformation and manipulation. Something this powerful and multimodal could have the ability to seamlessly create realistic fake content could be exploited for crime, spreading misinformation, or manipulating public opinion.
– Dependence and skill erosion. A really powerful multimodal model like Gemini could lead to an overreliance on AI which could lead to a decline in human skills and critical thinking abilities.
– Security risks. Powerful AI models like Gemini could become targets for cyberattacks. If compromised, they could be used for malicious purposes, such as generating harmful content or disrupting critical digital infrastructure.
– Economic impacts. The effects of AI-driven automation on employment, job displacement in certain sectors, and inequality are only likely to be increased by Gemini. As already stated, the Ultra version is very strong in areas like mathematics, physics, history, law, and medicine.
– Regulatory and control challenges. The rapid advancement and complexity of AI models like Gemini make it difficult for regulatory frameworks to keep pace.
– Unpredictable outcomes. The increasing complexity of AI LLMs can lead to less transparent and predictable decision-making processes, therefore, making it difficult to understand and manage these systems effectively.
OpenAI Challenger
Sam Altman, OpenAI’s CEO, has indicated that as early as next year, it could be launching its own new ultra-powerful AI products that could compete with Gemini. Open AI also has the backing of Microsoft (which is currently the subject of a CMA antitrust investigation).
What Does This Mean For Your Business?
With the rollout of Google’s Gemini AI, businesses appear to be on the cusp of a new era in AI. Gemini, with its versions Ultra, Pro, and Nano, is not just another large language model, but it represents a leap forward in AI’s ability to understand, process, and generate a multitude of data types, including text, code, audio, images, and video. This multimodal functionality is a key differentiator, setting it apart from existing models in a value-adding way.
For businesses already leveraging Google’s suite of products, the integration of Gemini could mean a significant boost in efficiency and capability. The enhanced Bard chatbot and Google Search, powered by Gemini, are likely to deliver more accurate, nuanced, and comprehensive results. This could transform how businesses handle data, engage with customers, and develop content.
Also, the advanced capabilities of Gemini, especially in its Ultra version, offer unparalleled opportunities in areas requiring deep analysis and reasoning, like market research, product development, and strategic planning. Its ability to outperform other models and even human experts in certain tasks could provide businesses with insights and solutions that were previously unattainable.
However, this power comes with challenges and responsibilities. For example, its power and multimodal capabilities could be effectively exploited by bad actors and the advanced data processing capabilities of Gemini could pose privacy and security risks if not managed carefully. Additionally, as AI technology advances rapidly in this way, staying compliant with evolving regulatory frameworks is crucial and businesses must navigate these changes responsibly to avoid legal and reputational risks. Also, with the EU only just compiling its own provisional AI bill (which won’t become law for at least 2 years), and OpenAI set to introduce its own next generation LLM in 2024 it seems that effective regulation in the AI market looks like being incredibly challenging and likely to lag considerably behind the technology.
The increasing economic impacts of AI-driven automation, particularly in employment, also warrant attention and businesses may be left with decisions such as how to reskill and redeploy their workforce to mitigate the effects of ultra-powerful LLMs and their AI chatbots eating into wider areas of human expertise.
Google’s Gemini, therefore, presents businesses with a wealth of opportunities for growth and innovation and yet, it also underscores the importance of a balanced approach in leveraging AI technology, and the need for regulation to keep up. As the AI landscape continues to evolve, businesses must remain adaptable, ethical, and vigilant to harness the full potential of AI while mitigating its risks. Gemini looks like being a disruptive competitive advantage for Google in the short term. The future competition in the AI market, with companies like OpenAI gearing up to introduce their own advanced models, indicates an exciting and challenging road ahead for businesses navigating the world of AI.
By Mike Knight
