Autor: da Agency

Introducing Phi-3: Redefining what’s possible with SLMs

We are excited to introduce Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks. This release expands the selection of high-quality models for customers, offering more practical choices as they compose and build generative AI applications.

Starting today, Phi-3-mini, a 3.8B language model is available on Microsoft Azure AI Studio, Hugging Face, and Ollama. 

Phi-3-mini is available in two context-length variants—4K and 128K tokens. It is the first model in its class to support a context window of up to 128K tokens, with little impact on quality.

It is instruction-tuned, meaning that it’s trained to follow different types of instructions reflecting how people normally communicate. This ensures the model is ready to use out-of-the-box.

It is available on Azure AI to take advantage of the deploy-eval-finetune toolchain, and is available on Ollama for developers to run locally on their laptops.

It has been optimized for ONNX Runtime with support for Windows DirectML along with cross-platform support across graphics processing unit (GPU), CPU, and even mobile hardware.

It is also available as an NVIDIA NIM microservice with a standard API interface that can be deployed anywhere. And has been optimized for NVIDIA GPUs. 

In the coming weeks, additional models will be added to Phi-3 family to offer customers even more flexibility across the quality-cost curve. Phi-3-small (7B) and Phi-3-medium (14B) will be available in the Azure AI model catalog and other model gardens shortly.   

Microsoft continues to offer the best models across the quality-cost curve and today’s Phi-3 release expands the selection of models with state-of-the-art small models.

Azure AI Studio

Phi-3-mini is now available

Explore the release

Groundbreaking performance at a small size 

Phi-3 models significantly outperform language models of the same and larger sizes on key benchmarks (see benchmark numbers below, higher is better). Phi-3-mini does better than models twice its size, and Phi-3-small and Phi-3-medium outperform much larger models, including GPT-3.5T.  

All reported numbers are produced with the same pipeline to ensure that the numbers are comparable. As a result, these numbers may differ from other published numbers due to slight differences in the evaluation methodology. More details on benchmarks are provided in our technical paper. 

Note: Phi-3 models do not perform as well on factual knowledge benchmarks (such as TriviaQA) as the smaller model size results in less capacity to retain facts. 

Safety-first model design 

Responsible ai principles

Learn about our approach

Phi-3 models were developed in accordance with the Microsoft Responsible AI Standard, which is a company-wide set of requirements based on the following six principles: accountability, transparency, fairness, reliability and safety, privacy and security, and inclusiveness. Phi-3 models underwent rigorous safety measurement and evaluation, red-teaming, sensitive use review, and adherence to security guidance to help ensure that these models are responsibly developed, tested, and deployed in alignment with Microsoft’s standards and best practices.  

Building on our prior work with Phi models (“Textbooks Are All You Need”), Phi-3 models are also trained using high-quality data. They were further improved with extensive safety post-training, including reinforcement learning from human feedback (RLHF), automated testing and evaluations across dozens of harm categories, and manual red-teaming. Our approach to safety training and evaluations are detailed in our technical paper, and we outline recommended uses and limitations in the model cards. See the model card collection. 

Unlocking new capabilities 

Microsoft’s experience shipping copilots and enabling customers to transform their businesses with generative AI using Azure AI has highlighted the growing need for different-size models across the quality-cost curve for different tasks. Small language models, like Phi-3, are especially great for: 

Resource constrained environments including on-device and offline inference scenarios.

Latency bound scenarios where fast response times are critical.

Cost constrained use cases, particularly those with simpler tasks.

For more on small language models, see our Microsoft Source Blog.

Thanks to their smaller size, Phi-3 models can be used in compute-limited inference environments. Phi-3-mini, in particular, can be used on-device, especially when further optimized with ONNX Runtime for cross-platform availability. The smaller size of Phi-3 models also makes fine-tuning or customization easier and more affordable. In addition, their lower computational needs make them a lower cost option with much better latency. The longer context window enables taking in and reasoning over large text content—documents, web pages, code, and more. Phi-3-mini demonstrates strong reasoning and logic capabilities, making it a good candidate for analytical tasks. 

Customers are already building solutions with Phi-3. One example where Phi-3 is already demonstrating value is in agriculture, where internet might not be readily accessible. Powerful small models like Phi-3 along with Microsoft copilot templates are available to farmers at the point of need and provide the additional benefit of running at reduced cost, making AI technologies even more accessible.  

ITC, a leading business conglomerate based in India, is leveraging Phi-3 as part of their continued collaboration with Microsoft on the copilot for Krishi Mitra, a farmer-facing app that reaches over a million farmers.

“Our goal with the Krishi Mitra copilot is to improve efficiency while maintaining the accuracy of a large language model. We are excited to partner with Microsoft on using fine-tuned versions of Phi-3 to meet both our goals—efficiency and accuracy!”   
Saif Naik, Head of Technology, ITCMAARS

Originating in Microsoft Research, Phi models have been broadly used, with Phi-2 downloaded over 2 million times. The Phi series of models have achieved remarkable performance with strategic data curation and innovative scaling. Starting with Phi-1, a model used for Python coding, to Phi-1.5, enhancing reasoning and understanding, and then to Phi-2, a 2.7 billion-parameter model outperforming those up to 25 times its size in language comprehension.1 Each iteration has leveraged high-quality training data and knowledge transfer techniques to challenge conventional scaling laws. 

Get started today 

To experience Phi-3 for yourself, start with playing with the model on Azure AI Playground. You can also find the model on the Hugging Chat playground. Start building with and customizing Phi-3 for your scenarios using the Azure AI Studio. Join us to learn more about Phi-3 during a special live stream of the AI Show.  

1 Microsoft Research Blog, Phi-2: The surprising power of small language models, December 12, 2023.
The post Introducing Phi-3: Redefining what’s possible with SLMs appeared first on Azure Blog.
Quelle: Azure

Cloud Cultures, Part 7: Creating balance in a digital world through precision and mindfulness in Japan

Innovate. Connect. Cultivate.

The Cloud Cultures series is an exploration of the intersection between cloud innovation and culture across the globe.

‘Mottainai,’ an idea deeply rooted in Japanese culture, is a call to respect resources and avoid waste. It goes beyond mere frugality; it’s an inherent recognition of the value of each item. I saw this ideology reflected everywhere during my trip to Japan for this episode of Cloud Cultures—in the transportation system, in my interactions with shop owners, even in the movements of a master sushi chef (or itamae) that I watched over the bar at an Omakase restaurant.

The same approach is applied to Japan’s technological innovations. While innovation is often associated with monumental breakthroughs or flashy advancements, I found that in Japan, innovation thrives in the simplest forms. It’s a philosophy woven into the Japanese way of life—a reverence for simplicity, mindfulness, and the intrinsic value of everything around us. Using the principles of precision and mindfulness, we can bridge the gaps between technology, design, and craftmanship.

Japan invents with intention

I started my latest Cloud Culture adventure in the Shinagawa district of Tokyo, wandering through narrow streets and sampling local specialties before meeting with Takeshi Numoto, Executive Vice President and Chief Marketing Officer at Microsoft. He’s a Japanese native and expert in ordering delicious meals—needless to say, I was thrilled to cohost this episode with Takeshi. We walked to an Omakase restaurant where we discussed the formalities of Japanese business culture. After sharing some baked oysters prepared with a culinary torch, I went to learn about one of Japan’s most renowned innovations: the railway system.

West Japan Railway Company prioritizes safety and innovation

For the 20 billion passengers riding trains in Japan each year, confidence in the precision and quality of the railway system is key. With over thirty-five years of operation and an impeccable safety record with five million daily users, West Japan Railway Company (JR-West) embodies responsibility, prioritizing safety while envisioning the future of train technology. On Takeshi’s advice, I met with a member of the local Microsoft team, Toshie Ninomiya, Managing Executive Officer of Microsoft Japan. Together, we had the opportunity to sit down with Okuda Hideo, Director and Executive Officer of Digital Solution Headquarters of JR-West, and his team.

During the pandemic, JR-West experienced an 89% decline in passengers. This created a sense of urgency—and ultimately, demanded a mindset shift. They pivoted their business strategy from filling as many seats as possible to curating a unique, personal experience for their riders. With their customers in mind, JR-West implemented cloud and AI solutions to become a more data-driven company. Now, they store customer transport and purchase data on the cloud, which can be analyzed to unlock insights that enable better customer experiences.

After our visit with JR-West, it became clear to me why Japan’s railway system is recognized worldwide. Through meticulous attention to detail and data-driven insights, JR-West ensures that their services exceed customer expectations while maintaining impeccable standards of efficiency and safety.

Sony Group uses cloud technology to embrace AI

While Toshie and I learned how JR-West uses AI to benefit their customers, Takeshi visited Sony headquarters to meet up with an old friend, Tsuyoshi Kodera, Executive Vice President, CDO and CIO of Sony Corporation.

In 1946, with only 190,000 yen and a team of 20 employees, Masaru Ibuka founded Sony with a vision of “establishing an ideal factory that stresses a spirit of freedom and open mindedness that will, through technology, contribute to Japanese culture.” Reflecting Sony’s unwavering commitment to pushing boundaries and achieving the unprecedented, the company has consistently introduced groundbreaking products, often claiming the titles of ‘Japan’s first’ and ‘world’s first.’

Throughout our journey, we were reminded of the importance of collaboration and balance. Beyond their partnership with Microsoft, Sony has expanded their AI strategies in exceptional ways. For example, they’ve implemented new autofocus capabilities in their cameras, implemented AI throughout their factory manufacturing lines, and even incorporated it in their famous Gran Turismo series on PlayStation. Sony is looking toward the future of AI and cloud capabilities to create deeper experiences, build lifelong customers, and help democratize innovative technologies.

NISSIN FOODS Group modernizes with AI to improve efficiency and productivity

For our final stop, Toshie and I visited the CUPNOODLES MUSEUM in Yokohama to meet with NISSIN FOODS Group’s Chief Information Officer, Toshihiro Narita, and discuss how the company is fusing together cloud computing and shaping future food trends.

Since launching the world’s first instant noodles, NISSIN FOODS Group’s vision has remained consistent: contribute to society and the earth by gratifying people everywhere with pleasures and delights food can provide. And despite not being a traditional tech company, NISSIN FOODS Group is embracing digital transformation wholeheartedly.

As part of its program to support sustainable growth, NISSIN FOODS Group aims to improve labor productivity through efficiency. To this end, they’ve implemented various initiatives to improve in-office productivity. This includes migrating to the cloud using Microsoft 365 to adopt a remote work-enabled environment and improve cybersecurity hygiene to continuously maintain the health of the company’s IT estate. Cloud and AI technologies are helping NISSIN FOODS Group’s employees be more productive, giving them more time back to focus on creative work, and in turn, create new food cultures.

After enjoying our custom CUPNOODLES from the My CUPNOODLES Factory, Toshie and I had a chance to reflect on the unique approach NISSIN FOODS Group is taking. They are showcasing how every company can encourage innovation by modernizing with cloud technology, while staying true to their roots. From CUPNOODLES to cutting-edge food tech, innovation knows no bounds in Japan, offering a flavorful glimpse into the future of both technology and gastronomy.

Building a future that embraces tradition

From digital invention to food accessibility and revolutionizing transportation, Japan continues to evolve with a focus on precision and mindfulness. I see a culture that blends tradition and innovation, forging a future that honors heritage while embracing progress. Inspired by the incredible sights and smells of my journey—not to mention the insightful leaders I’ve met along the way—I carry with me a renewed perspective on how we can build a digital world rooted in intentionality and craftsmanship.

Cloud Cultures

Check out the other blogs in this series, from Mexico to Malaysia, and more

Read now

Learn more

Watch more Cloud Cultures episodes

Find the Azure geography that meets your needs

Learn more about Microsoft customers in Japan

Discover about how Microsoft is investing in AI in Japan

The post Cloud Cultures, Part 7: Creating balance in a digital world through precision and mindfulness in Japan appeared first on Azure Blog.
Quelle: Azure