At the moment, the hottest issue in the technology world is AIGC.
Generative AI AIGC is an important symbol of the era of artificial intelligence 1.0 entering the 2.0 era. Based on GPT and Diffusion Models dissipation models, it has swept all walks of life in a short period of time, bringing disruptive technologies to the entire human society, and has also quickly spawned a number of new unicorn companies such as OpenAI, Anthropic, MidJourney, and Stability AI.
Matt Wood, Vice President of Global Product at Amazon Web Services
According to Matt Wood, vice president of global product at Amazon Web Services, generative AI is reshaping all walks of life, "Generative AI can unlock innovation beyond traditional boundaries, pushing us into uncharted territory, far beyond the original boundaries." It's very exciting. ”
Take the smart painting software MidJourney, for example, whose vivid generative images can reach the point of being fake. After using MidJourney to help generate a movie atmosphere map, director Lu Chuan sincerely said that the effect of AI in 15 seconds is more powerful than a one-month work made by a professional poster company.
And that's just the tip of the iceberg for generative AI applications. In fact, the new products and models brought by AIGC are emerging one after another, with unlimited potential and opportunities. Chen Xiaojian, general manager of Amazon Web Services Greater China product department, believes that due to the trend of generative AI, we will see more and more new opportunities.
Computing power challenges and solutions
The opportunity and potential of generative AI is already in front of us, so it is not so easy to actually achieve it and make high-quality applications, because there are several hurdles to cross.
The first thing to bear the brunt is computing power. It is a clear fact that artificial intelligence cannot develop to the extent it is today if it is not supported by strong computing power. Computing power is the foundation and prerequisite for artificial intelligence.
Chen Xiaojian, General Manager of Amazon Web Services Greater China Product Department
Chen Xiaojian said that the wave of AI innovation has brought about an explosion in the demand for computing resources, "Developers need more cost-effective software and hardware solutions to cope with the shortage of computing resources. At the same time, cloud services also need to provide fast and efficient elastic resources. In addition, cloud services need to further lower the threshold for use so that customers can quickly get started. ”
Amazon Web Services' treasure chest has a wealth of treasures that can help developers. In response to the shortage of computing power, Amazon Web Services can provide comprehensive and in-depth infrastructure capabilities, including Intel, AMD, NVIDIA, and self-developed CPU and acceleration chip products.
In the self-developed chip camp, the new fifth-generation Nitro improves performance per watt by 40%, achieving lightweight virtualization and hardware-level encryption. The general-purpose processor Graviton3 based on the ARM architecture, the machine learning training chip Trainium, and the machine learning inference chip Inferentia have all brought multiple increases in data throughput and significant cost reductions.
For elastic resource provision, Amazon Web Services provides more than 600 different computing instances to build a rich and flexible computing instance resource in the form of building blocks to meet the requirements of various computing powers. Weta Digital, the visual effects development company for Avatar 2, has significantly improved its development efficiency after using Amazon Web Services' machine learning services.
In response to the problem of simplifying computing power applications that customers are generally concerned about, Amazon Web Services is constantly exploring how to maximize the elasticity, agility, and pay-as-you-go features of the cloud, and promote cloud services to become serverless, so as to help customers minimize O&M work, increase business agility, and better cope with various business uncertainties.
Model services for easy onboarding
The computing power problem is solved, and the next step is the problem of building a large model. Matt Wood believes that unlocking the value of generative AI requires providing access to best-in-class base models, providing a secure and private environment to customize models, and finding opportunities to enhance the experience.
Amazon Web Services provides targeted policies for each.
Amazon Bedrock is the easiest way to build and scale generative AI applications using the underlying model, lowering the barrier to entry for all developers. Allows users to access base models from AI21 Labs, Anthropic, Stability AI, and Amazon through APIs.
The Amazon Titan Model Library enables secure and private model tuning, "which users can optimize and fine-tune very securely and privately," says Matt Wood.
If you need to improve the efficiency of code generation, then Amazon CodeWhisperer is an ideal tool. It is based on machine learning, supports 15 different programming languages, and is free for individual users.
Build a cloud-native data strategy
Data is the raw material and foundation of AI, and it is especially important for generative AI and large models. How to manage and harness this huge amount of data has always been a challenge. Amazon Web Services' cloud-native strategy effectively solves this challenge.
Amazon Web Services has launched 15 purpose-built cloud-hosted database services to provide perfectly matched data services for various user scenarios, which can fully meet the needs of today and the future.
Amazon Web Services has a vision of Zero-ETL that aims to enable seamless data transformation and invocation without users writing a single line of code. This easy integration, connecting all your data, greatly reduces the complexity of data management.
Building end-to-end data governance is also part of your data strategy. Data governance accelerates and secures the flow of data. Matt Wood mentioned that with Amazon DataZone, a new data management service, administrators and data asset managers can manage and govern data access using granular control tools to ensure that data access occurs under the right permissions and the right context.
epilogue
Chen Xiaojian emphasized that the highly secure and reliable cloud infrastructure provided by Amazon Web Services allows innovation to reach every corner quickly. "Amazon Web Services has more than 200 services ranging from compute, storage, and networking to machine learning and quantum technologies, providing users with comprehensive support."
In the era of AIGC, Amazon Web Services has also opened treasure chests for enterprises and developers, which are full of magic treasure weapons, which can greatly help the development of data management and AIGC-related applications.
As Matt Wood envisions, Amazon Web Services always wants to make promising and exciting technologies available to everyone. "We believe that when we look back next year, we have reached the point of rapid explosion, with endless inventions and applications."