- DataRobot announces enhanced integrations and accelerators with Google’s Gemini models.
- Clients can access LLM blueprint strategies for 150+ models, including Gemini models, optimizing AI applications for diverse use cases.
- New solution accelerators, Mistral 7N and Llama 2, alongside support for Vertex AI Model Garden, empower AI practitioners.
- Success stories include Inchcape’s 50% reduction in model training time and Keller Williams’ 15% productivity increase.
- Google Cloud’s inclusion in the DataRobot Partner Ecosystem strengthens the AI landscape with an open platform approach.
Main AI News:
DataRobot, a prominent player in the AI lifecycle domain, has unveiled enhanced integrations and accelerators in collaboration with Google’s Gemini models. This strategic move aims to empower organizations with rapid AI deployment capabilities, ensuring immediate business impact.
This deepening partnership builds upon the earlier joint initiative between DataRobot and Google Cloud to expedite the adoption of generative AI solutions. Now, clients can avail themselves of the following benefits:
- Comprehensive LLM blueprint strategies encompassing over 150 models from Model Garden, including Gemini models. Leveraging DataRobot’s LLM playground, equipped with top-tier foundation models, facilitates the development of AI applications tailored to diverse use cases, all while guaranteeing visibility and performance.
- Introduction of new solution accelerators. DataRobot’s AI Accelerators portfolio now encompasses Mistral 7N and Llama 2, alongside robust support for Vertex AI Model Garden. These offerings empower AI practitioners with expansive, adaptable, and industry-specific LLMs, facilitating accelerated solution development.
Notable successes among DataRobot’s clientele include:
- Inchcape, a leading global automotive distributor, achieved a 50% reduction in model training time, coupled with an 8.1% cost reduction.
- Keller Williams witnessed a 15% increase in productivity through a generative AI-powered Learning Hub tailored to their vast network of over 187,000 real estate agents worldwide.
- Gannett/USA Today Network embraces generative AI solutions with confidence, backed by best-in-class AI guardrails and human oversight.
Arvind Thinagarajan, VP of Data Science & Analytics at Gannett/USA Today Network, expressed, “Using the DataRobot AI Platform, we’ve automated many steps in the pipeline for hundreds of models. The synergy between Google Cloud and DataRobot helps us create a comprehensive solution for developing, deploying and managing models.”
Ritika Suri, Director of Technology Partners at Google Cloud, highlighted, “By collaborating with partners like DataRobot, we empower organizations with innovative AI solutions tailored to their enterprise needs. Leveraging Google Cloud’s robust Gemini-powered infrastructure alongside DataRobot’s full AI lifecycle platform, we enable users to accelerate their AI journey and drive significant business impact.”
Raj Ramanujam, SVP of Global Channel/Tech Alliances at DataRobot, affirmed, “We’re dedicated to equipping our customers with world-class tools to confidently navigate the AI landscape. Deepening our partnership with Google Cloud underscores our commitment to accelerating AI adoption and maximizing investments in Google Cloud.”
Google Cloud’s inclusion in DataRobot Partner Ecosystem further strengthens the initiative to streamline the AI landscape with an open platform approach. This ecosystem facilitates seamless integration of cutting-edge AI technology, cloud infrastructure, and applications within the DataRobot AI Platform, enhancing governance across the AI lifecycle.
Conclusion:
The deepened collaboration between DataRobot and Google Cloud signifies a significant stride towards empowering organizations with advanced AI solutions. With enhanced integrations and accelerators, clients can harness the power of Gemini models to optimize AI applications, driving tangible business impact. This partnership reinforces the trend of collaboration in the AI market, emphasizing the importance of open platforms and ecosystem alliances in accelerating AI adoption across industries.
