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Recently, at the Amazon Cloud Technology Generative AI Builders Conference, Chen Xiaojian, general manager of Amazon Cloud Technology Greater China Product Department, mentioned that Amazon Cloud Technology is focusing on application scenarios, tools and infrastructure, data bases, and AI native These five levels of application construction and generative AI services continue to help enterprises and developers fully unleash the potential of generative AI.
With the large-scale surge in data, abundant and highly scalable computing power and the continuous improvement of machine learning model capabilities, generative AI has become a hot topic in various industries, and companies are thinking about how to innovate with the help of generative AI technology. business and quickly gain a competitive advantage.
"Generative AI is not just about big models. Today, when we talk about generative AI, most people are talking about basic models, and the entire generative AI application is like an iceberg floating on the sea, exposed on the surface of the sea. The tip of the iceberg that most people can see above is like a basic model, and at the bottom of the glacier, a large number of services other than the basic model are also needed to support it, such as acceleration chips, databases, data analysis, data security services, etc. Amazon Cloud Technology provides a complete end-to-end generative AI technology stack, from the bottom acceleration layer such as acceleration chips and storage optimization, to the middle layer model building tools and services, to the top layer generative AI related applications, each All levels are continuing to innovate to meet the different needs of customers," said Chen Xiaojian.
According to the Generative AI Productivity Frontier Technology Report released by McKinsey Consulting in June 2023, about 3/4 of the economic benefits brought by generative AI technology come from four main functions: marketing and sales, product and R&D , software engineering and customer operations, these four functions are also the main force in the current use of generative AI applications. Amazon Cloud Technology believes that the business value it brings to enterprises in typical application scenarios mainly includes three aspects: enhancing customer experience, improving employee productivity and creativity, and optimizing business processes.
Among the many basic models, how to conveniently and securely choose the basic model that is most suitable for its own business scenario is a challenge that every enterprise faces when building generative AI applications.
In this regard, Amazon Cloud Technology officially launched Amazon Bedrock. This service is combined with Amazon SageMaker Jumpstart to help enterprises with different needs for basic models to easily and safely choose basic models.
For enterprises, data is the key to transforming general artificial intelligence into AI-generated models that understand the business and customers. In terms of data base, Amazon Cloud Technology provides specially built databases for application scenarios such as user personal information, session information management, and private domain knowledge base in the field of generative AI. For the vector data that needs to be processed by Retrieval Augment Generation (RAG), Amazon Cloud Technology has added vector database functions to Amazon OpenSearch Service, Amazon Aurora PostgreSQL, and Amazon RDS for PostgreSQL. Enterprises can use these functions to store and search their machines. Embeddings, used in translation and generative AI applications, allow vectors to be co-located with the data. In addition, the Amazon DataZone data governance service provided by Amazon Cloud Technology can discover, access, share and manage large-scale data across organizational boundaries, and reduce the heavy workload of internal members when accessing data and using analysis tools.
Amazon Cloud Technology believes that programming will be one of the areas where generative AI technology will be rapidly applied. In response, Amazon launched Amazon CodeWhisperer, which can be used in the advanced options of the basic model to generate code suggestions in real time, fundamentally improving developer productivity. Recently, Amazon also launched the Amazon Whisperer customization function, which can generate better code suggestions than before, allowing CodeWhisperer code suggestions to be safely customized using private code libraries. These private code libraries can cover internal APIs, databases, best practices, architectural patterns, etc. .
It is reported that Amazon Cloud Technology has helped 1,000 small and medium-sized enterprises and startups quickly realize generative AI innovation through out-of-the-box generative AI services and tools, empowering 100,000 Chinese developers.
Chen Xiaojian mentioned, “Developing generative AI applications is a systematic project full of challenges, and it is not a simple splicing of products and services. Therefore, how to accelerate the commercialization of customers’ final applications, in addition to Amazon’s own resources, we It is also necessary to build a strong partner ecosystem, and work with them to help solve various technical problems in the construction of generative AI applications and accelerate application implementation. In addition to cloud services, we also provide solution architects, product technical experts, artificial intelligence Multiple resources such as experiments, data labs, rapid prototyping teams, professional service teams, training and certification departments jointly help customers succeed. At the same time, we also work with ecological partners and start-up circles to build a complete system of generative AI to further assist generative AI. The implementation of technology."
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