**Introduction to Deep Gram AI**

Deep Gram is a cutting-edge Artificial Intelligence (AI) model that specializes in summarizing audio and video content. Our AI is trained on a data set that we gathered and labeled ourselves, allowing it to become an expert in its field. In this article, we will delve into the features and capabilities of Deep Gram, including summarization, language detection, entity detection, diarization, topic detection, and more.

**Summarization Feature**

Our AI's summarization feature is a Domain-Specific Language Model (DSLM) that can listen to any audio or video and write a synopsis. We built, trained, and fine-tuned this model in-house on the data set we gathered and labeled ourselves. The result is an AI that can produce high-quality summaries with accuracy. In the demo, our AI wrote a summary of the video "Between Two Ferns" with Zach Efron, which was compared to a manual summary written by us.

**Topic Detection and Entity Detection**

Deep Gram's topic detection feature allows it to identify the major subjects discussed in the audio or video content. The model also includes an entity detection system that extracts people, places, names, and other relevant information from the content. In the demo, our AI tried its best to write a bullet point list of the major topics discussed in the "Between Two Ferns" video.

**Entity Detection**

The entity detection feature is particularly useful for identifying specific individuals mentioned in the content. Our model was able to extract the name of Steve Jobs from the transcript and even make a humorous comment about him looking like Zach Galifianakis after waking up from a 15-year nap. Entity detection can also be used to identify places, organizations, and other entities mentioned in the content.

**Language Detection**

Deep Gram's language detection feature can determine the language of the audio or video content. In the demo, our model correctly detected that the content was in English (en). This feature is useful for understanding the original intent and context of the content.

**Limitations of Deep Gram AI**

While Deep Gram AI has made significant progress in its capabilities, there are still limitations to be aware of. Like other AI models, it can mishear words or struggle with nuances of human language. In the demo, our model had trouble transcribing Zach Galifianakis's last name upon their first attempt.

**Technical Details**

The code for Deep Gram is open-sourced and available for developers who want to build on top of its capabilities. The front-end work was relatively simple, but the real meat of the technology lies in the code that calls the AI model. This code is available in the link provided in the description.

**Practical Applications**

Deep Gram's AI has a wide range of practical applications, from content creation to transcription services for individuals and enterprises. Our users have built entire websites with their voices, created wearable art that responds to voice commands, and even hooked up our AI to Stable Diffusion to create realistic art. With the ability to record live transcriptions in real-time, Deep Gram's AI can be used to create live subtitles or transcribe podcasts on the fly.

**Conclusion**

Deep Gram AI is a powerful tool for anyone looking to work with audio or video content. Its summarization feature, topic detection, entity detection, and language detection capabilities make it an invaluable resource for content creators and consumers alike. Whether you're a student looking for a way to summarize lectures, a business wanting to transcribe meetings, or simply someone who wants to create art with their voice, Deep Gram has something to offer. Sign up for Deep Gram today to take advantage of its free transcription service and unlock the full potential of your audio data.

"WEBVTTKind: captionsLanguage: enif you're a YouTuber a podcaster or if you're a fan of YouTube videos and podcasts you gotta check this out we recently used AI to build this demo Link in the description that transcribes any YouTube video summarizes it detects the major topics discussed and more today we'll discuss how you can use it how it works and how you can build something like it ready let's go thank you all right so first things first here's the demo follow the link in the description and you'll see this page here you'll enter the link to any YouTube video you want whether it's a podcast a sketch an interview a tutorial or anything else today I'm going to be using an episode of Zach galifianakis's series between two ferns so once I enter that link I'm going to be directed to this page this page asks me what I want the AI to do so smart format up here tells the AI not only to transcribe the video but also to make that transcription pretty you know by adding proper punctuation knowing when to use numerals to represent numbers instead of words and so on and so forth I'll check that box and now I'm also going to check the summarization box over here so that the AI not only transcribes our video but also summarizes it like a spark notes or a cliff note synopsis up next I'm going to click on the topic detection and entity detection boxes so that we can get a list of the major subject discussed as well as a list of the people places and data discussed utterances and paragraphs is just another additional layer of formatting to make the transcription pretty and I'll also turn on language detection just to demonstrate it this will identify the dominant language spoken in the video which is particularly useful if you're doing research and you stumble across a video in a foreign language that you just can't pinpoint our AI models will be able to tell you exactly what language is being spoken finally I'll check the diarization box by checking this box I'm going to tell the AI to label every word with its speaker that way we know who said what you know instead of a transcript that looks like this we'll get a transcript that looks like this but all right enough talking about the features let's see them in action now that I've checked every box I just click get results down here and boom results the first thing we'll see down here is a speaker labeled transcript so we know who said what here speaker zero is Zach elephanakis and speaker one is David Letterman good thanks I know I was just watching I would just watch the color bars in the national anthem as you can see the AI transcribed the whole video but that's not all my favorite feature here is the summarization our new summarization feature is a dslm also known as a domain-specific language model basically in the same way that doctors choose specializations AI can specialize as well and this AI specializes in summarizing we built trained and fine-tuned this model in-house on a data set that we gathered and labeled ourselves and the result is an AI that can listen to any audio or in this case watch a YouTube video and then write a synopsis here for this example our AI wrote The Following summary and for comparison here's a summary that I wrote of the video note that the AI summary and my own summary have some pretty close similarities even some word for word phrases in there up next we have topic detection and entity detection long story short the AI tried to the best of its ability to write a bullet point list of the major subjects discussed in the video meanwhile entity detection extracts the people places names and so on that were discussed as well for example the name Steve Jobs was mentioned did you just wake up from a 15-year nap you look like Steve Jobs now okay and so was Santa Claus welcome to another edition of Between Two Ferns I'm your host sac alphanakis my guest today is Santa Claus with an eating disorder thank you very much for inviting me I appreciate it finally the language detected was en which is computer speak for English and if you'd like to see the request that was sent to the server that hosts the AI you can click on this tab now it's important to discuss a couple limitations of these AI models much like how chat GPT hallucinates or how AI image generators have a tough time with fingers sometimes transcription models mishear words in the same way that humans do for example our model had trouble transcribing Zach galifianakis's name as we can see here in the transcription and here in the entity detection tab but I'll give the AI a little bit of leeway here since even most humans can't transcribe galifianakis's last name upon their first attempt now if you're curious as to how this demo works you can click up here to see the code a good chunk of it is front end work but the real meat is in the code that calls the AI you can find that here long story short all of these features summarization language detection any detection diarization topic detection and so forth are all available in the Deep gram API out of the box seriously if you look in the code the most complicated part of building this app is creating the front-end components and buttons meanwhile all it takes to utilize an AI is a single function call here that's it this is the line of code that tells the Deep gram AI to parse the audio the only parameters you need are one the audio you want to transcribe and analyze and two a list of the buttons that the user clicked like whether or not they want the model to do summarization that's how simple it is to use deep grams AI all you need to do is sign up to create an API key and from that point on it's just one line of code two parameters and a partridge and a pear tree as in all you need to do is sign up create an API key and you'll be able to apply transcription diarization summarization topic detection and much more to any audio you desire whether that's your podcast or your videos or even recorded Zoom meetings from work old voicemails and so forth whether you're an individual or an Enterprise you wouldn't be the first course to use deep gram to make the most of your audio data our users have built entire websites with their voices driven cars with their voice created live real-life subtitles to wear and even hooked up our AI to stable diffusion to create art like the art that you're currently seeing on screen not to mention if you want to create live transcriptions in real time you can do that as well whether you want to record yourself live or if you want to tap into a live radio feed like we did here with BBC but long story short whether you're a content creator or an avid content consumer like me this demo is linked in the description and if you want to build anything with our specialized audio expert AI models sign up for deep gram and you'll receive up to 45 000 minutes of free transcription that's 200 worth for 750 hours or 31 days straight worth of audio we'd love to see what demos you come up with now if you like this video leave a like down below if you have any questions feel free to chat with us in the comments section and as always follow deep web for more AI content foreignif you're a YouTuber a podcaster or if you're a fan of YouTube videos and podcasts you gotta check this out we recently used AI to build this demo Link in the description that transcribes any YouTube video summarizes it detects the major topics discussed and more today we'll discuss how you can use it how it works and how you can build something like it ready let's go thank you all right so first things first here's the demo follow the link in the description and you'll see this page here you'll enter the link to any YouTube video you want whether it's a podcast a sketch an interview a tutorial or anything else today I'm going to be using an episode of Zach galifianakis's series between two ferns so once I enter that link I'm going to be directed to this page this page asks me what I want the AI to do so smart format up here tells the AI not only to transcribe the video but also to make that transcription pretty you know by adding proper punctuation knowing when to use numerals to represent numbers instead of words and so on and so forth I'll check that box and now I'm also going to check the summarization box over here so that the AI not only transcribes our video but also summarizes it like a spark notes or a cliff note synopsis up next I'm going to click on the topic detection and entity detection boxes so that we can get a list of the major subject discussed as well as a list of the people places and data discussed utterances and paragraphs is just another additional layer of formatting to make the transcription pretty and I'll also turn on language detection just to demonstrate it this will identify the dominant language spoken in the video which is particularly useful if you're doing research and you stumble across a video in a foreign language that you just can't pinpoint our AI models will be able to tell you exactly what language is being spoken finally I'll check the diarization box by checking this box I'm going to tell the AI to label every word with its speaker that way we know who said what you know instead of a transcript that looks like this we'll get a transcript that looks like this but all right enough talking about the features let's see them in action now that I've checked every box I just click get results down here and boom results the first thing we'll see down here is a speaker labeled transcript so we know who said what here speaker zero is Zach elephanakis and speaker one is David Letterman good thanks I know I was just watching I would just watch the color bars in the national anthem as you can see the AI transcribed the whole video but that's not all my favorite feature here is the summarization our new summarization feature is a dslm also known as a domain-specific language model basically in the same way that doctors choose specializations AI can specialize as well and this AI specializes in summarizing we built trained and fine-tuned this model in-house on a data set that we gathered and labeled ourselves and the result is an AI that can listen to any audio or in this case watch a YouTube video and then write a synopsis here for this example our AI wrote The Following summary and for comparison here's a summary that I wrote of the video note that the AI summary and my own summary have some pretty close similarities even some word for word phrases in there up next we have topic detection and entity detection long story short the AI tried to the best of its ability to write a bullet point list of the major subjects discussed in the video meanwhile entity detection extracts the people places names and so on that were discussed as well for example the name Steve Jobs was mentioned did you just wake up from a 15-year nap you look like Steve Jobs now okay and so was Santa Claus welcome to another edition of Between Two Ferns I'm your host sac alphanakis my guest today is Santa Claus with an eating disorder thank you very much for inviting me I appreciate it finally the language detected was en which is computer speak for English and if you'd like to see the request that was sent to the server that hosts the AI you can click on this tab now it's important to discuss a couple limitations of these AI models much like how chat GPT hallucinates or how AI image generators have a tough time with fingers sometimes transcription models mishear words in the same way that humans do for example our model had trouble transcribing Zach galifianakis's name as we can see here in the transcription and here in the entity detection tab but I'll give the AI a little bit of leeway here since even most humans can't transcribe galifianakis's last name upon their first attempt now if you're curious as to how this demo works you can click up here to see the code a good chunk of it is front end work but the real meat is in the code that calls the AI you can find that here long story short all of these features summarization language detection any detection diarization topic detection and so forth are all available in the Deep gram API out of the box seriously if you look in the code the most complicated part of building this app is creating the front-end components and buttons meanwhile all it takes to utilize an AI is a single function call here that's it this is the line of code that tells the Deep gram AI to parse the audio the only parameters you need are one the audio you want to transcribe and analyze and two a list of the buttons that the user clicked like whether or not they want the model to do summarization that's how simple it is to use deep grams AI all you need to do is sign up to create an API key and from that point on it's just one line of code two parameters and a partridge and a pear tree as in all you need to do is sign up create an API key and you'll be able to apply transcription diarization summarization topic detection and much more to any audio you desire whether that's your podcast or your videos or even recorded Zoom meetings from work old voicemails and so forth whether you're an individual or an Enterprise you wouldn't be the first course to use deep gram to make the most of your audio data our users have built entire websites with their voices driven cars with their voice created live real-life subtitles to wear and even hooked up our AI to stable diffusion to create art like the art that you're currently seeing on screen not to mention if you want to create live transcriptions in real time you can do that as well whether you want to record yourself live or if you want to tap into a live radio feed like we did here with BBC but long story short whether you're a content creator or an avid content consumer like me this demo is linked in the description and if you want to build anything with our specialized audio expert AI models sign up for deep gram and you'll receive up to 45 000 minutes of free transcription that's 200 worth for 750 hours or 31 days straight worth of audio we'd love to see what demos you come up with now if you like this video leave a like down below if you have any questions feel free to chat with us in the comments section and as always follow deep web for more AI content foreign\n"