Artwork

محتوای ارائه شده توسط TechTarget Editorial. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط TechTarget Editorial یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
Player FM - برنامه پادکست
با برنامه Player FM !

AWS GenAI strategy based on multimodel ecosystem, plus Titan, Q and Bedrock

21:35
 
اشتراک گذاری
 

Manage episode 428993308 series 3493557
محتوای ارائه شده توسط TechTarget Editorial. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط TechTarget Editorial یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

AWS is quietly building a generative AI ecosystem in which its customers can use many large language models from different vendors, or choose to employ the tech giant's own models, Q personal assistants, GenAI platforms and Trainium and Inferentia AI chips.

AWS says it has more than130,000 partners, and hundreds of thousands of AWS customers use AWS AI and machine learning services.

The tech giant provides not only the GenAI tools, but also the cloud infrastructure that undergirds GenAI deployment in enterprises.

"We believe that there's no one model that's going to meet all the customer use cases," said Rohan Karmarkar, managing director of partner solutions architecture at AWS, on the Targeting AI podcast from TechTarget Editorial. "And if the customers want to really unlock the value, they might use different models or a combination of different models for the same use case."

Customers find and deploy the LLMs on Amazon Bedrock, the tech giant's GenAI platform. The models are from leading GenAI vendors such as Anthropic, AI21 Labs, Cohere, Meta, Mistral and Stability AI, and also include models from AWS' Titan line.

Karmarkar said AWS differentiates itself from its hyperscaler competitors, which all have their own GenAI systems, with an array of tooling needed to implement GenAI applications as well as AI GPUs from AI hardware giant Nvidia and AWS' own custom silicon infrastructure.

AWS also prides itself on its security technology and GenAI competency system that pre-vets and validates partners' competencies in putting GenAI to work for enterprise applications.

The tech giant is also agnostic on the question of proprietary versus open source and open models, a big debate in the GenAI world at the moment.

"There's no one decision criteria. I don't think we are pushing one [model] over another," Karmarkar said. "We're seeing a lot of customers using Anthropic, the Claude 3 model, which has got some of the best performance out there in the industry."

"It's not an open source model, but we've also seen customers use Mistral and [Meta] Llama, which have much more openness," he added.

Shaun Sutner is senior news director for TechTarget Editorial's information management team, driving

coverage of artificial intelligence, unified communications, analytics and data management technologies. He is a veteran journalist with more than 35 years of news experience. Esther Ajao is a TechTarget Editorial news writer and podcast host covering artificial intelligence software and systems. They co-host the Targeting AI podcast.

  continue reading

34 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 428993308 series 3493557
محتوای ارائه شده توسط TechTarget Editorial. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط TechTarget Editorial یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

AWS is quietly building a generative AI ecosystem in which its customers can use many large language models from different vendors, or choose to employ the tech giant's own models, Q personal assistants, GenAI platforms and Trainium and Inferentia AI chips.

AWS says it has more than130,000 partners, and hundreds of thousands of AWS customers use AWS AI and machine learning services.

The tech giant provides not only the GenAI tools, but also the cloud infrastructure that undergirds GenAI deployment in enterprises.

"We believe that there's no one model that's going to meet all the customer use cases," said Rohan Karmarkar, managing director of partner solutions architecture at AWS, on the Targeting AI podcast from TechTarget Editorial. "And if the customers want to really unlock the value, they might use different models or a combination of different models for the same use case."

Customers find and deploy the LLMs on Amazon Bedrock, the tech giant's GenAI platform. The models are from leading GenAI vendors such as Anthropic, AI21 Labs, Cohere, Meta, Mistral and Stability AI, and also include models from AWS' Titan line.

Karmarkar said AWS differentiates itself from its hyperscaler competitors, which all have their own GenAI systems, with an array of tooling needed to implement GenAI applications as well as AI GPUs from AI hardware giant Nvidia and AWS' own custom silicon infrastructure.

AWS also prides itself on its security technology and GenAI competency system that pre-vets and validates partners' competencies in putting GenAI to work for enterprise applications.

The tech giant is also agnostic on the question of proprietary versus open source and open models, a big debate in the GenAI world at the moment.

"There's no one decision criteria. I don't think we are pushing one [model] over another," Karmarkar said. "We're seeing a lot of customers using Anthropic, the Claude 3 model, which has got some of the best performance out there in the industry."

"It's not an open source model, but we've also seen customers use Mistral and [Meta] Llama, which have much more openness," he added.

Shaun Sutner is senior news director for TechTarget Editorial's information management team, driving

coverage of artificial intelligence, unified communications, analytics and data management technologies. He is a veteran journalist with more than 35 years of news experience. Esther Ajao is a TechTarget Editorial news writer and podcast host covering artificial intelligence software and systems. They co-host the Targeting AI podcast.

  continue reading

34 قسمت

Wszystkie odcinki

×
 
Loading …

به Player FM خوش آمدید!

Player FM در سراسر وب را برای یافتن پادکست های با کیفیت اسکن می کند تا همین الان لذت ببرید. این بهترین برنامه ی پادکست است که در اندروید، آیفون و وب کار می کند. ثبت نام کنید تا اشتراک های شما در بین دستگاه های مختلف همگام سازی شود.

 

راهنمای مرجع سریع