pinter69

Num. 2 especially relatable. A good mark of high quality professional is if he presents his plan before execution to hear feedback and comments - even if they are totally against his original idea, and he can then take this feedback and incorporate effectively in a re-design.

You're right. But, nowadays these terms get more context meaning. For example - a user is someone who platforms sell their data to customers. Or a user is someone gullible you trick into making decisions that are good for the business. The literal term of someone who is using your system/product has evolved.

For me the term users sometimes sounds similar to traffic. I prefer customers - that you serve with your product.

Interesting, thanks

Interesting, thanks for the reference. I wonder what other products do this

1000 true fans and Seth Godin's approach to marketing - that you should focus on the smallest group of people in your market and amaze them

These concepts helped me a lot with marketing to consumers and SMBs

Also, follow @mtlynch's content - even though he says he's not an expert, I feel that atleast regarding marketing to devs and builders - he is one of the best out there

Thanks for your work Michael!

Correct. I fixed the typo

You mean Vulkan? In the blog post there is reference to all vulkan supported platforms

If you mean ffmpeg build with whisper - from memory I didn't see ffmpeg-builds for mac, so you will probably need to compile yourself

I tend to agree. The thing I like most about version 8 is actually pad_cuda - nice performance boost for resizing video with an Nvidia GPU

This is a 3 part series, the first one discusses the new native whisper integration. And correct, for the first post - the point is to show that you can only use ffmpeg to transcribe and embed subtitles in a video

Author here, available for questions

People in the community can be hardcore there sometimes, r/ffmpeg especially. But, there are communities online and information resources that help.

This is a nice resource: https://amiaopensource.github.io/ffmprovisr/

And also I've written this cheatsheet, which is designed to be used alongside an LLM: https://github.com/rendi-api/ffmpeg-cheatsheet

Let me know if you're interested in more resources

Thanks Dan, as usual, deep and insightful

Your question is very interesting.

Going over the comments the only plausible explanation I could see is KV cache being extremely useful - don't know if this is really just the case.

Would love to know the true answer to the question.

Author here. Happy to take any questions or feedback.

It doesn't look to be self hosted

Amazing story.

Had something similar happen to us with our dev-tools saas. Non devs started coming to the product because gpt told them about it. Had to change parts of the onboarding and integration to accommodate it for non-devs who were having a harder time reading the documentation and understanding what to do.

My friends and people who work with us are on different platform groups (discord, telegram, facebook, slack, I myself have a sub-reddit I moderate), and we all see that the whatsapp groups are the stickiest for us, the most personal and the ones we engage with the most

For anyone who gets here, the best solution I found was creating your own signed certificate with a long expiry time, installing it in gcp load balancer and having cloudflare work in strict mode (not full) so it will check for encrypted traffic but not validate the certificate with an registering authority

Interesting - how did you know in retrospect that it was effective breaking down the series?

Had to stop all my campaigns because of it

Thanks for the input

I'm a user of this lib - it's nice for building audio processing pipelines in python

Something I found that helps me is asking the question - if in retrospect the outcome of my plan will not be as positive as I have planned - will I regret not researching more right now.

But, this came with a lot of experience. In the beginning it's hard to imagine how and in what ways the outcome can be not positive and how it connects to the research today. And, I feel my experience is still lacking around this.

The way to measure transcription accuracy is word error and not character error. I have not really checked or trusted) speechmatics' accuracy benchmarks But, from my experience and personal impression - it looks good, haven't done a quantitative benchmark

Right you are. I've used speechmatics, they do a decent jon with transcription

I consult a company in the space (not resemble) and I can definitely say it can narrate a book

I did a quick google search before positing and only found a reference in a comment. But, I searched for the link to the GitHub.

Yes. And just makes chatgpt responses unbearable to read..

I do like perplexity's style though, the organization of search results in comparison tables is nice