VENDORiQ: Google Launches Gemma and Brings Gemini to More Products

Uncover how Google's Gemma and Gemini are revolutionising AI development, making it more accessible and cost-effective for businesses and developers.

The Latest

March 2024: Google announced the availability of Gemma on Google Cloud, which allows customising and building with Gemma models in Vertex AI and running them on Google Kubernetes Engine (GKE). Gemini for Workspace was also launched via two plans: Gemini Business for USD20 monthly, limited to 1,000 actions per user per month; and Gemini Enterprise (formerly Duet AI for Workspace Enterprise) for USD30 monthly, with no usage limit and the capability to translate captions in 100+ language pairs in AI-powered meetings.

Why It’s Important

IBRS believes that this Google launch will spur more vendors to develop smaller-sized AI models, which require lower resource requirements and can be trained and fine-tuned using readily available computing resources. This is driven by the need to eliminate massive, specialised infrastructure typically needed for larger models like LaMDA or Megatron-Turing NLG. Organisations can better leverage existing infrastructure for AI development and deployment. This should further increase cost-effectiveness and efficiency through significantly less computational power requirements that make it deployable on standard hardware like laptops and workstations.

The release of Gemini Enterprise signifies Google’s intensified efforts to compete in the burgeoning generative AI market. While Microsoft’s early entry with ChatGPT and its successful enterprise offering established it as a leader, Google aims to catch up by leveraging the advanced capabilities of Gemini. While details about Gemini’s specific capabilities are limited, it’s likely designed to address the limitations identified in Bard and potentially surpass the functionalities of ChatGPT in certain areas. Google is paving the way for a future where AI benefits a broader spectrum of developers and users.

Who’s Impacted

  • CEO
  • AI developers
  • IT teams

What’s Next?

  • Analyse internal workflows and business processes to identify tasks suitable for Gemma’s capabilities.
  • Collaborate with internal development teams to explore the potential integration of Gemma into existing applications or workflows, considering factors like data security, user experience, and ongoing maintenance.

Related IBRS Advisory

1. VENDORiQ: Google’s Gemini Pro and Imagen 2 to be Deployed on Samsung S24 Series

2. VENDORiQ: Google’s AI Hype Hides a Bigger Problem

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