Microsoft’s enhancement of Azure AI capabilities through its new AI model-as-a-service offering a significant step forward in the world of artificial intelligence. Microsoft has made strides in expanding its AI offerings, including the introduction of Meta’s Llama 2 running in Models as a Service and the preview of GPT-4 Turbo with Vision. This move not only enhances the versatility of Azure AI but also represents a shift in how AI’s potential is conceptualized, with a greater emphasis on generative AI and multimodal application development.
One of the key enhancements to Azure AI is the availability of Meta’s Llama 2 running in Models as a Service. This addition provides users with a powerful tool for generating diverse and imaginative content, opening up new possibilities for AI application development. The Llama 2 model, renowned for its performance in language tasks, can now be seamlessly integrated into various applications, enhancing their capabilities and offering more flexibility to developers.
Alongside Llama 2, Microsoft has also unveiled the preview of GPT-4 Turbo with Vision, an advanced generative AI model. This model is designed to produce high-quality content and facilitate multimodal application development, combining the power of natural language processing with computer vision. The inclusion of GPT-4 Turbo with Vision in Azure AI signifies Microsoft’s commitment to pushing the boundaries of AI technology, offering users the ability to create more sophisticated and versatile applications.
Microsoft AI model-as-a-service
In addition to these new models, Microsoft has also expanded the Azure AI model catalog with the addition of more models such as the Phi 2 Small Language Model (SLM). This move aligns with Microsoft’s aim to provide a comprehensive selection of AI models to Azure AI, giving customers more choice and flexibility to meet their specific needs. The expanded catalog allows users to select from a wider range of models, each with their unique strengths and capabilities, thereby enhancing the versatility of Azure AI.
To assist users in selecting the most suitable model for their needs, Azure AI Studio offers a model benchmarking and evaluation subsystem. This feature allows users to review and compare the performance of various AI models, providing quality metrics for Azure OpenAI Service models and Llama 2 models. By simplifying the model selection process, Azure AI Studio makes it easier for users to leverage the full potential of Azure AI.
Here are a selection of the AI models available in Microsoft Azure AI model-as-a-service
Phi-2. is a small language model (SLM) from Microsoft with 2.7 billion parameters. Phi-2 shows the power of SLMs, and exhibits dramatic improvements in reasoning capabilities and safety measures compared to Phi-1-5, while maintaining its relatively small size compared to other transformers in the industry. With the right fine-tuning and customization, these SLMs are incredibly powerful tools for applications both on the cloud and on the edge.
DeciLM. Introducing DeciLM-7B, a decoder-only text generation model with an impressive 7.04 billion parameters, licensed under Apache 2.0. Not only is DeciLM-7B the most accurate 7B base model to date, but it also surpasses several models in its class.
DeciDiffussion. DeciDiffusion 1.0 is a diffusion-based text-to-image generation model. While it maintains foundational architecture elements from Stable Diffusion, such as the Variational Autoencoder (VAE) and CLIP’s pre-trained Text Encoder, DeciDiffusion introduces significant enhancements. The primary innovation is the substitution of U-Net with the more efficient U-Net-NAS, a design pioneered by Deci. This novel component streamlines the model by reducing the number of parameters, leading to superior computational efficiency.
DeciCoder. 1B is a 1 billion parameter decoder-only code completion model trained on the Python, Java, and JavaScript subsets of Starcoder Training Dataset. The model uses Grouped Query Attention and has a context window of 2048 tokens. It was trained using a Fill-in-the-Middle training objective. The model’s architecture was generated by Deci’s proprietary Neural Architecture Search-based technology, AutoNAC.
Orca 2. Like Phi-2, Orca 2 from Microsoft explores the capabilities of smaller LMs (on the order of 10 billion parameters or less). With Orca 2, shows that improved training signals and methods can empower smaller language models to achieve enhanced reasoning abilities, which are typically found only in much larger language models. Orca 2 significantly surpasses models of similar size (including the original Orca model) and attains performance levels similar to or better than models 5-10 times larger, as assessed on complex tasks that test advanced reasoning abilities in zero-shot settings.
Mixtral 8x7b. Mixtral has a similar architecture as Mistral 7B but is comprised of 8 expert models in one from a technique called Mixture of Experts (MoE). Mixtral decodes at the speed of a 12B parameter-dense model even though it contains 4x the number of effective parameters.
These enhancements to Azure AI are already being put to good use by global law firm Dentons. The firm is using Azure AI to implement Azure OpenAI Service models, including GPT-4 and Meta’s Llama 2, into its generative AI application. With these models, Dentons is able to summarize legal contracts and extract key parts from documents, resulting in significant time savings. This practical application of Azure AI models illustrates their potential to transform various industries by automating complex tasks and improving efficiency.
“Through the incorporation of a lease report generator, into our fleetAI system, developed with Microsoft Azure’s Open AI service, we have revolutionized a time-consuming task that previously took 4 hours, reducing it to just 5 minutes,” said Sam Chen, Legal AI Adoption Manager for Dentons (UKIME). “This significant time saving enables our legal professionals to concentrate on more strategic tasks, thereby enhancing client service and underscoring our dedication to innovation.”
Microsoft’s enhancement of Azure AI capabilities through new models and services represents a significant advancement in the field of AI. By introducing powerful new models like Meta’s Llama 2 and GPT-4 Turbo with Vision, and expanding the Azure AI model catalog, Microsoft is providing users with more choice and flexibility, and paving the way for more innovative and imaginative applications of AI.
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