BlueOcean, a brand intelligence platform, used Anthropic's Claude 3 models (Haiku and Opus) via Amazon Bedrock to consolidate four separate API calls into a single, more efficient one, resulting in over 50% cost reduction.

Boyner uses Azure OpenAI Service and Azure Machine Learning to analyze data faster and generate product descriptions automatically from product photos.

National Bank of Greece built an AI-powered document processing solution using Azure AI Document Intelligence. They analyzed 50 million pages to create a comprehensive dataset and employed Azure Cognitive Services for Greek language recognition, integrating the solution into six customer-facing digital banking applications. This implementation automates document categorization and data extraction, streamlining both customer service and regulatory processes.

Torrens University used Microsoft Azure OpenAI to analyze and standardize over 1,200 courses and 60,000 web pages, improving and standardizing all course curriculums on one intuitive platform, MyLearn.

Lamini, an all-in-one LLM platform for enterprises to build open LLMs on proprietary data, uses Mistral-7B as one of the most popular open base models. Lamini enables Fortune 1000 customers across various industries to tune and deploy models in production efficiently, even on AMD GPUs with performance parity to NVIDIA GPUs. Mistral-7B's ease of use and high-quality results help customers move from proof-of-concept to production, deploying proprietary LLMs effectively.

Sarvam AI specializes in developing AI solutions for Indic languages. They developed a Hindi Large Language Model by extending Meta's Llama 2 in partnership with AI4bharat. The model aims to deliver GPT-3.5-like performance on Indic languages under compute and data constraints, achieving high performance on a frugal budget.

BenevolentAI, a UK-based TechBio company, leverages Claude to speed up data generation and annotation by orders of magnitude, while maintaining high-quality results. This supports the company's efforts in drug discovery and research, significantly enhancing their data processing capabilities.

Mendel has developed Hypercube, an AI platform that integrates Meta Llama 2-based LLM for natural language processing on clinical data. Hypercube uses a hypergraph semantic layer and the proprietary Eloquent language to enable querying and retrieving clinical information for applications like trial matching and patient cohorting. Llama 2 assists in converting natural language queries into Eloquent, bridging the gap for users unfamiliar with the query language.

Mayo Clinic uses Meta's Llama 2 to develop RadOnc-GPT, a specialized large language model for radiation oncology. RadOnc-GPT is fine-tuned on patient records and deployed locally to ensure data security. It supports a chatbot that answers routine post-radiotherapy questions, reducing nurses’ and clinicians’ workloads and improving treatment decision-making speed, accuracy, and quality. Future developments include predicting patient outcomes and expanding clinical tasks, enhancing operational efficiency and patient care.

Aive, an AI platform for video post-production, leverages Meta's Llama 3 to automate video summarization and smart clipping. By analyzing long-form content, Aive creates concise, engaging video formats optimized for platforms like Facebook and Instagram. This integration helps brands like LVMH, L'Oréal, and Stellantis streamline video workflows, reduce costs, and maximize content impact across channels within a secure and scalable AI environment.

Meditron, a suite of open-source large multimodal foundation models tailored for the medical field, leverages Meta's Llama 2 and 3 to assist with clinical decision-making and diagnosis in low-resource settings. Developed by researchers at EPFL and Yale School of Medicine in collaboration with humanitarian organizations like the International Committee of the Red Cross, Meditron provides evidence-based, contextually aware recommendations and diagnostic support. It automates tasks such as generating treatment regimens, determining radiation modalities, and assigning diagnostic codes, thereby enhancing clinical efficiency and improving patient outcomes. With over 30,000 downloads and top performance on medical benchmarks, Meditron democratizes access to advanced medical AI tools, enabling equitable healthcare innovation in underserved regions.

Fortune partnered with Accenture to develop Fortune Analytics, an AI-powered tool designed to analyze over 20 years of Fortune 500 and Global 500 financial data and related articles. This tool allows users to generate visualizations and receive ChatGPT-style responses, making data-driven insights more accessible. The platform is set to launch in beta on June 4, 2024, and aims to enhance enterprise decision-making by providing easy access to financial data and journalism archives.

Paradigm uses OpenAI’s GPT-4 API to evaluate clinical trial data sets, significantly improving the speed, accuracy, and cost of patient screening. By replacing traditional models with GPT-4, Paradigm achieved a 90% reduction in clinician time spent on model validation and a 10% increase in accuracy. This allows faster, more equitable access to clinical trials, especially for underserved patients with unstructured medical data.

NOAA and USAID are among the U.S. government agencies using Google Cloud AI to unlock critical data insights to streamline operations and improve mission outcomes — all with an emphasis on responsible AI.

NOAA and USAID are among the U.S. government agencies using Google Cloud AI to unlock critical data insights to streamline operations and improve mission outcomes — all with an emphasis on responsible AI.

Kinaxis and Dematic are building data-driven supply chains to address logistics use cases including scenario modeling, planning, operations management, and automation.

Kinaxis and Dematic are building data-driven supply chains to address logistics use cases including scenario modeling, planning, operations management, and automation.

Spotify leveraged Dataflow for large-scale generation of ML podcast previews, and they plan to keep pushing the boundaries of what’s possible with data engineering and data science to build better experiences for their customers and creators.

Mistral AI will use Google Cloud's AI-optimized infrastructure to further test, build, and scale up its LLMs, all while benefiting from Google Cloud's security and privacy standards.

Anthropic has partnered with Google Cloud to offer its family of Claude 3 models on Vertex AI — providing organizations with more model options for intelligence, speed, cost-efficiency, and vision for enterprise use cases.

Cox 2M, the commercial IoT division of Cox Communications, is able to make smarter, faster business decisions using AI-powered analytics.

Essential AI, a developer of enterprise AI solutions, is using Google Cloud’s AI-optimized TPU v5p accelerator chips to train its own AI models.

Broward County, Florida, and Southern California Edison are using geospatial capabilities and AI to improve infrastructure planning and monitoring, generate new insights, and create regional resilience for communities facing climate challenges today and tomorrow.

Woven – Toyota's investment in the future of mobility — is partnering with Google to leverage vast amounts of data and AI to enable autonomous driving, supported by thousands of ML workloads on Google Cloud’s AI Hypercomputer. This has resulted in 50% total-cost-of-ownership savings to support automated driving.

Mayo Clinic has given thousands of its scientific researchers access to 50 petabytes worth of clinical data through Vertex AI search, accelerating information retrieval across multiple languages.

MSCI uses machine learning with Vertex AI, BigQuery and Cloud Run to enrich its datasets to help our clients gain insight into around 1 million asset locations to help manage climate-related risks.

Orange operates in 26 countries where local data must be kept in each country. They are using AI on Google Distributed Cloud to improve network performance and deliver super-responsive translation capabilities.

Broward County, Florida, and Southern California Edison are using geospatial capabilities and AI to improve infrastructure planning and monitoring, generate new insights, and create regional resilience for communities facing climate challenges today and tomorrow.

Hugging Face is collaborating with Google across open science, open source, cloud, and hardware to enable companies to build their own AI with the latest open models from Hugging Face and Google Cloud hardware and software.

Kakao Brain, part of Korean technology company Kakao Group, has built a large-scale AI language model that is the largest Korean language-specific LLM in the market, with 66 billion parameters. They’ve also developed a text-to-image generator called Karlo.