Daniel McCarthy’s Post

New: VinceAI 100+ Templates 🏅 GPT-40 is a step towards much more natural human-computer interaction-it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. available now: vinceai.io 🏆 #vinceai #aigenerative

We’re kick-starting 2024 with a revolution in real-time ASR and Speech Intelligence.
🔥   Real-time, live, instant, low-latency. Faster to read and more reliable than my linkedin posts. 🔎   Whatever you call it, the transcription and use of audio ‘in the moment’ is here, and has now reached a point where the accuracy is so reliable, that a whole new world of possibility has opened up.   More options for interactivity, more instant insight, broader international audiences, more engaging content, workflows powered by voice, and so much more.   Incredibly, machine-learning-powered transcription from Speechmatics has reached a stage where you can now get transcription that you can trust within just two seconds (with the option to bake in delays of up to 10 seconds if you want maximum accuracy).    For those who are looking for faster transcription, we can return words in less than 1 second.   This includes every language we offer (49 and I am counting... more on this soon)
 This includes instant translation. This includes all deployment types. This includes the use of key features like speaker diarization and custom dictionary. 
 So, if you’re still using batch and file transcription in your products, it’s time for a real-time upgrade.   What are you waiting for?
   https://lnkd.in/dEEYumFF

Did you hear the news? Now when your team uploads a video into your PhotoShelter Library, a subtitle file will automatically begin to generate. No more waiting for someone to transcribe the audio, or going to a separate tool to generate a transcription. We've got you covered! 🤝 Learn more about PhotoShelter's new AI Video Transcription: https://bit.ly/3FPxz2k #DAM #digitalassetmanagement #contentmanagement #accessibility #transcription #artificialintelligence

GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time (opens in a new window)  in a conversation.

We’re kick-starting 2024 with a revolution in real-time ASR and Speech Intelligence.
   Real-time, live, instant, low-latency.   Whatever you call it, the transcription and use of audio ‘in the moment’ is here, and has now reached a point where the accuracy is so reliable, that a whole new world of possibility has opened up.   More options for interactivity, more instant insight, broader international audiences, more engaging content, workflows powered by voice, and so much more.   Incredibly, machine-learning-powered transcription from Speechmatics has reached a stage where you can now get transcription that you can trust within just two seconds (with the option to bake in delays of up to 10 seconds if you want maximum accuracy).    For those who are looking for faster transcription, we can return words in less than 1 second.   This includes every language we offer (49 and counting)
 This includes instant translation. This includes all deployment types. This includes the use of key features like speaker diarization and custom dictionary. 
 So, if you’re still using batch and file transcription in your products, it’s time for a real-time upgrade.   What are you waiting for?
   https://lnkd.in/dEEYumFF

GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, and image and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time(opens in a new window) in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. https://lnkd.in/dZWqnEPh #gpt4o

GPT-4o (“o” for “omni”) is out! It accepts as input any combination of text, audio, and image and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. I like to watch the Model capabilities to get some inspiration for what you can do. One of the most interesting use cases is "GPT-4o with Andy, from BeMyEyes in London." What is your favorite? https://lnkd.in/gh6-EgCk

Machine translation has made great strides in recent years, but it still can’t parse meaning at the level of a three-year-old. https://lnkd.in/gm9JRpCQ

the video you need to watch today. Multi-modal (audio, video, text) GPT in the next GPT-4o... The future is getting closer! https://lnkd.in/d7_HdMTU

In this video we will show you how you can convert an MP3 audio file into text with the help of Google Colab and artificial intelligence. As the CEO of a small business, you can benefit from this solution by transcribing audio files quickly and easily and using the texts for your purposes. At the beginning of the code, we import the necessary libraries that we need for the conversion. We do not describe the names of imported or installed libraries here, in order to make the code clearer. We then use an API key that enables us to use the artificial intelligence of OpenAI. We would like to point out that this API key in this video is for illustrative purposes only and is not real. The problem we want to solve is the conversion of audio files into text. This can be useful for example, if you have conducted an interview and want to have it transcribed in order to analyze or publish it later. The solution is to use artificial intelligence that automatically transcribes the audio file. We use OpenAI and Whisper technology for this. In the first part of the source code, we open the MP3 audio file that we want to transcribe. We then use a function that converts the audio file into text. This function uses the artificial intelligence of OpenAI and Whisper to transcribe the audio file. In the second part of the source code, we define a function that saves the transcribed result in a text file. This function is then called to save the result. At this point, we would like to introduce you to a platform that allows you to build your own AI solution for your company without having to invest a lot of time or money on crowdcompany.net. You can now register for just €1 and have your own AI solution developed. In the last part of the source code, the transcribed result is saved in a text file. To summarize, in this video we have learned how to convert an MP3 audio file to text using Google Colab and artificial intelligence. We have explained how to understand the source code line by line and the benefits of this solution for small business managers. If you have any questions, please contact us by email. We hope you enjoyed this video and look forward to seeing you again in the next video. Thank you for your attention.