@arvidkahl
Building podscan.fm in Public. Raising all the boats with kindness.
🎙️ tbf.fm · ✍️ tbf.link/blog · 🗞️ bootstrapped.news · 📚 arvidsbooks.com
Posts
57
13 decrease
This section shows tweet / post counts for the last 7 days compared to the previous 7 days. If you have less than 14 days of data, we will show the available data.
Impressions
264.2K
85.6% increase
This is the total number of impressions your posts have made in the last 7 days compared to the previous 7 days. If you have less than 14 days of data, we will show the available data.
Likes
1.4K
85.9% increase
This is the total number of likes you've received in the last 7 days compared to the previous 7 days. If you have less than 14 days of data, we will show the available data.
Followers
431
0.4% increase
This is the total number of followers you have acquired in the last 7 days compared to the previous 7 days. If you have less than 14 days of data, we will show the available data.
Impressions
Impressions
We collect new impression data each day if your graph isn't showing enough data yet, it's because we are waiting for more data to be available.
Followers
Followers
We collect new follower counts each day if your graph isn't showing enough data yet, it's because we are waiting for more data to be available.
Engagement
Engagement
We collect new engagement data each day if your graph isn't showing enough data yet, it's because we are waiting for more data to be available.
Top Posts
Top Posts
We show the top posts from the last 7 days.
| Post | Impressions | Retweets | Quotes | Likes | Replies | Engagement Rate | Actions |
|---|---|---|---|---|---|---|---|
| OpenAI just released a new transcription model called "whisper-large-v3-turbo" — which is 8 times as fast(!!!) as their most recent highest-quality model. 🤯 I am currently deploying this to my fleet of servers. This single change will likely 2x-4x the number of podcasts I can handle per day. Besides that, it will increase the baseline quality of ALL transcriptions on Podscan. It will EVEN allow me to go through my backlog much faster. That means faster alerts and more historical search data for https://t.co/tbiLRLmx9E customers. OpenAI is the gift that keeps on giving. | 116.5K | 21 | 4 | 636 | 45 |
1.01%
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| The startup world is never dull. So this AI code editor is a fork with all the project name occurrences changed in the code. Relicensed with a closed license made up by ChatGPT. And they got into YC with that. You couldn’t make it up. The grifting… https://t.co/pprZnptUT9 | 14.4K | 11 | 3 | 101 | 15 |
1.0%
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| In my never-ending efforts to optimize my own AI operations, I looked into Ollama today — a tool that allows me to run local LLMs from a pretty unified interface. The thing that impressed me most: the linux "installer" (pretty much a curl | sh) creates a full systemd config! | 13.1K | 4 | 1 | 72 | 13 |
0.85%
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| ★ Just published a new episode of The Bootstrapped Founder: 349: Navigating Constraints as a Bootstrapper. Listen: https://t.co/3etAT6ZZhj | 11.4K | 0 | 1 | 9 | 3 |
0.14%
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| Guess who started their Friday by adding an EU VAT ID to a customer's invoices today? 🤣 | 10.1K | 0 | 1 | 45 | 13 |
0.61%
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| They have found Podscan 🤣 https://t.co/9Abx2aMUgZ | 9.7K | 1 | 1 | 30 | 7 |
0.47%
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| This 809 M parameter model is now outperforming their "base" model with 74 M params. MASSIVE quality improvement that comes with even faster speed? What is going on 🤣 Open-source projects are scrambling to integrate this new model into their tools. https://t.co/pzCVVMdoj1 | 9.2K | 0 | 0 | 60 | 3 |
0.98%
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| Bootstrapping is all about dealing with constraints: no money, the day job, lack of experience, and having no distribution. This week, I share a few stories of how I tackle these issues, particularly while being barraged with thousands of new podcast episodes every hour. | 8.7K | 3 | 1 | 49 | 7 |
0.83%
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| Got this really cute review for my podcast 🥰 https://t.co/USkfnidOPa | 8.3K | 2 | 0 | 92 | 17 |
1.35%
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| The scraping wars are in full swing. https://t.co/HNwjV8aEPh | 8.2K | 0 | 1 | 24 | 5 |
0.5%
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Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (21 + 4 + 636 + 45 + 465) / 116503 * 100 =
For this tweet: (21 + 4 + 636 + 45 + 465) / 116503 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (11 + 3 + 101 + 15 + 14) / 14362 * 100 =
For this tweet: (11 + 3 + 101 + 15 + 14) / 14362 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (4 + 1 + 72 + 13 + 21) / 13095 * 100 =
For this tweet: (4 + 1 + 72 + 13 + 21) / 13095 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (0 + 1 + 9 + 3 + 3) / 11354 * 100 =
For this tweet: (0 + 1 + 9 + 3 + 3) / 11354 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (0 + 1 + 45 + 13 + 2) / 10057 * 100 =
For this tweet: (0 + 1 + 45 + 13 + 2) / 10057 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (1 + 1 + 30 + 7 + 7) / 9702 * 100 =
For this tweet: (1 + 1 + 30 + 7 + 7) / 9702 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (0 + 0 + 60 + 3 + 27) / 9215 * 100 =
For this tweet: (0 + 0 + 60 + 3 + 27) / 9215 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (3 + 1 + 49 + 7 + 12) / 8658 * 100 =
For this tweet: (3 + 1 + 49 + 7 + 12) / 8658 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (2 + 0 + 92 + 17 + 2) / 8344 * 100 =
For this tweet: (2 + 0 + 92 + 17 + 2) / 8344 * 100 =
Engagement rate is calculated as (interactions / impressions) * 100.
For this tweet: (0 + 1 + 24 + 5 + 11) / 8234 * 100 =
For this tweet: (0 + 1 + 24 + 5 + 11) / 8234 * 100 =