We are excited to announce a new limited video series featuring innovations across Azure AI Language. In this video series, you will hear from subject matter experts (SMEs) that will take us through how you can use features powered by Azure OpenAI’s GPT models and others, to build the next-generation applications with generative AI. This video series will also feature new product announcements, customer stories and more; everything that we believe is important for our customers to stay updated on with the service.
With the recent announcements around Azure OpenAI Service this year, you might be wondering how we are thinking about embedding the GPT models across Azure AI services. You may have seen our announcement from earlier this year on how we embedded GPT models to power auto-labeling of entities in Named Entity Recognition. Now, Rena Liu, a product manager on the Azure AI team, walks us through how you can use it in the Azure AI Language Studio.
Similarly, you may have seen our blog post announcing general availability of document and conversation in Azure AI Language. Watch this video where Yanling shows how customers can get concise summaries of long-form documents, agent-customer conversations in call centers and more using task-optimized models powered by Azure OpenAI. Developers building such capabilities for call centers and customer support centers will find this to be extremely effective (in terms of output quality) along with accelerated time-to-value on insights that they are looking to derive from such documents and conversations.
Next, if you are building applications for call centers to transcribe speech, analyze sentiments, redact PII and summarize conversations between call center agents and customers, check out this video with Peyton offers a step-by-step guide using Azure AI Speech and Azure AI Language.
Finally (for now), if you are a developer building healthcare applications, you might have come across our Text Analytics for health offering. In this video, Rena logs into the Azure AI Language Studio to show exactly how you can build your app using Text Analytics for health.
We look forward to engaging with customers on this new Azure AI Language series. For these and more videos that we hope to publish over time, please head over the (979) Azure AI Language Services - YouTube video series on Microsoft Developers YouTube channel or Azure AI Language Series show on Microsoft Learn. Please subscribe to the series to get first-hand experience on exciting new skills in Azure AI Language.
Hello. Not going to be mean here but I think you're releasing too many voices for English (US). Maybe you should release voices for other languages such as Chinese, French, German, or something else.
Yes, in relation to images animation, for instance; may it be possible to apply generative models with Reinforcement Learning / CNNs through simple tools of NPL?
Thanks for your comment AMateos91! To answer your questions about from OpenAI to implement RL via generative models coded by NPL, could you please elaborate a little bit more to help me understand more about the context of your question?
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We are excited to announce a new limited video series featuring innovations across Azure AI Language. In this video series, you will hear from subject matter experts (SMEs) that will take us through how you can use features powered by Azure OpenAI’s GPT models and others, to build the next-generation applications with generative AI. This video series will also feature new product announcements, customer stories and more; everything that we believe is important for our customers to stay updated on with the service.
\n
\n
With the recent announcements around Azure OpenAI Service this year, you might be wondering how we are thinking about embedding the GPT models across Azure AI services. You may have seen our announcement from earlier this year on how we embedded GPT models to power auto-labeling of entities in Named Entity Recognition. Now, Rena Liu, a product manager on the Azure AI team, walks us through how you can use it in the Azure AI Language Studio.
\n
\n\n
\n
Similarly, you may have seen our blog post announcing general availability of document and conversation in Azure AI Language. Watch this video where Yanling shows how customers can get concise summaries of long-form documents, agent-customer conversations in call centers and more using task-optimized models powered by Azure OpenAI. Developers building such capabilities for call centers and customer support centers will find this to be extremely effective (in terms of output quality) along with accelerated time-to-value on insights that they are looking to derive from such documents and conversations.
\n
\n\n
\n
Next, if you are building applications for call centers to transcribe speech, analyze sentiments, redact PII and summarize conversations between call center agents and customers, check out this video with Peyton offers a step-by-step guide using Azure AI Speech and Azure AI Language.
\n
\n\n
\n
Finally (for now), if you are a developer building healthcare applications, you might have come across our Text Analytics for health offering. In this video, Rena logs into the Azure AI Language Studio to show exactly how you can build your app using Text Analytics for health.
\n
\n\n
\n
We look forward to engaging with customers on this new Azure AI Language series. For these and more videos that we hope to publish over time, please head over the (979) Azure AI Language Services - YouTube video series on Microsoft Developers YouTube channel or Azure AI Language Series show on Microsoft Learn. Please subscribe to the series to get first-hand experience on exciting new skills in Azure AI Language.
","body@stringLength":"5017","rawBody":"
We are excited to announce a new limited video series featuring innovations across Azure AI Language. In this video series, you will hear from subject matter experts (SMEs) that will take us through how you can use features powered by Azure OpenAI’s GPT models and others, to build the next-generation applications with generative AI. This video series will also feature new product announcements, customer stories and more; everything that we believe is important for our customers to stay updated on with the service.
\n
\n
With the recent announcements around Azure OpenAI Service this year, you might be wondering how we are thinking about embedding the GPT models across Azure AI services. You may have seen our announcement from earlier this year on how we embedded GPT models to power auto-labeling of entities in Named Entity Recognition. Now, Rena Liu, a product manager on the Azure AI team, walks us through how you can use it in the Azure AI Language Studio.
\n
\n\n
\n
Similarly, you may have seen our blog post announcing general availability of document and conversation in Azure AI Language. Watch this video where Yanling shows how customers can get concise summaries of long-form documents, agent-customer conversations in call centers and more using task-optimized models powered by Azure OpenAI. Developers building such capabilities for call centers and customer support centers will find this to be extremely effective (in terms of output quality) along with accelerated time-to-value on insights that they are looking to derive from such documents and conversations.
\n
\n\n
\n
Next, if you are building applications for call centers to transcribe speech, analyze sentiments, redact PII and summarize conversations between call center agents and customers, check out this video with Peyton offers a step-by-step guide using Azure AI Speech and Azure AI Language.
\n
\n\n
\n
Finally (for now), if you are a developer building healthcare applications, you might have come across our Text Analytics for health offering. In this video, Rena logs into the Azure AI Language Studio to show exactly how you can build your app using Text Analytics for health.
\n
\n\n
\n
We look forward to engaging with customers on this new Azure AI Language series. For these and more videos that we hope to publish over time, please head over the (979) Azure AI Language Services - YouTube video series on Microsoft Developers YouTube channel or Azure AI Language Series show on Microsoft Learn. Please subscribe to the series to get first-hand experience on exciting new skills in Azure AI Language.
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Hello. Not going to be mean here but I think you're releasing too many voices for English (US). Maybe you should release voices for other languages such as Chinese, French, German, or something else.
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Thanks a million! Do more on various services and how to apply them in real life scenarios!
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Yes, in relation to images animation, for instance; may it be possible to apply generative models with Reinforcement Learning / CNNs through simple tools of NPL?
Thanks!
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Thanks for your comment AMateos91! To answer your questions about from OpenAI to implement RL via generative models coded by NPL, could you please elaborate a little bit more to help me understand more about the context of your question?
\n
\n
Thanks!
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By the way, why not from OpenAI to implement RL (CNNs) via generative models coded by NPL?
Will it be even commercial on the own platform?
Thanks and best!
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By the way, why not from OpenAI to implement RL (CNNs) via generative models coded by NPL?
Will it be even commercial on the own platform?
Thanks and best!
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Thank you so much! So thrilling and useful!
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