seems every company that has spare engineering resource all builds such thing internally
1,860 karma · joined August 31, 2014
Email: wenbin@listennotes.com
seems every company that has spare engineering resource all builds such thing internally
Alphabet’s investment holdings (eg, spacex, anthropic..) are worth in the same order of magnitude of BRK’s (~$300B)
The track record of google’s M&A is pretty good.
Except for search and cloud, many of Google’s important products were from M&A - Maps, Docs, android, doubleclick, youtube , deep mind, etc.
This could also make abusing use / DDoS attack very costly
why do people create fake podcasts? they want to get backlinks from all podcast directories
podcasts are distributed via rss feed. and spammers/"growth hackers" put tons of links in the rss feed.
and podcast hosting services (especially those allow free trials, e.g., rss.com, ) could help them one-click to distribute to a bunch of podcast apps / websites. this is like one-click large scale spamming automation
any examples? here you go -
* https://podcasts.apple.com/us/search?term=UU88%20
* https://podcasts.apple.com/us/search?term=%E6%B6%A8%E7%B2%89
* https://open.spotify.com/search/%E6%B6%A8%E7%B2%89/podcasts
most podcast websites / apps don't delete fake podcasts like we do at listennotes.com . so i guess the backlink hack w/ fake podcasts works. real human podcast listeners might suffer with spammy fake shows even on Apple Podcasts and Spotify.
The compensation can be high, but the psychological cost is real. Over time, that tradeoff isn’t always worth it: someone might earn more in the short term, yet pay for it with chronic stress, declining mental health, and even a shorter lifespan compared to a lower-paid role that’s more meaningful and less draining.
And Listen Notes is removing 4000 to 8000 ai slop podcasts per month - https://www.listennotes.com/podcast-stats/#growth
I always have growing lists of short texts, facts, and links that I wanted to host on a standalone site rather than burying them in a notes app. The workflow is simple: a browser extension to clip links with remarks, which then feeds into a public-facing list.
I’ve also added a "Substack-lite" feature. Instead of long-form writing, it lets you send simple roundup email digests (e.g., "Top 5 links this week") to opt-in subscribers.
My personal blog (wenbin.org) is currently powered by the tool.
CurateKit.com is in private beta while I'm fine-tuning a few things now, but I’m opening up invites to the waitlist over the next few days if anyone wants to give it a try.
Every big cloud provider has its share of UX/stability/customer support issues.
At this point, it feels less like AWS is the 'least bad' option because alternatives are even worse.
The catch was that old boxed software eventually breaks on new OS versions or devices.
However, SaaS has the potential to "freeze" features while remaining functional 20+ years down the road. Behind the scenes, developers can update server dependencies and push minor fixes to ensure compatibility with new browsers and screen sizes.
From the end-user's perspective, the product remains unchanged and reliable. To me, that’s very good!
It takes real courage for a builder to say, "It’s good enough. It’s complete. It serves the core use cases well." If people want more features? Great, make it a separate product under a new brand.
Evernote and Dropbox were perfect in 2012. Adding more features just to chase new user growth often comes at the expense of confusing the existing user base. Not good
Imagine how deceptive llm slop contents are to the general population.
Here's a dataset of 26,000+ ai-generated "podcasts"
https://www.kaggle.com/datasets/listennotes/ai-generated-fak...
[0] AI-generated fake podcasts (mostly via NotebookLM) https://www.kaggle.com/datasets/listennotes/ai-generated-fak...
Once synthetic data becomes pervasive, it’s inevitable that some of it will end up in the training process. Then it’ll be interesting to see how the information world evolves: AI-generated content built on synthetic data produced by other AIs. Over time, people may trust AI-generated content less and less.
AI generators don't have a strong incentive to add watermarks to synthetic content. They also don't provide reliable AI-detection tools (or any tools at all) to help others detect content generated by them.
The problem is becoming urgent: more and more so-called “podcasts” are entirely fake, generated by NotebookLM and pushed to every major platform purely to farm backlinks and run blackhat SEO campaigns.
Beyond SynthID or similar watermarking standards, we also need models trained specifically [0] to detect AI-generated audio. Otherwise, the damage compounds - people might waste 30 minutes listening to a meaningless AI-generated podcast, or worse, absorb and believe misleading or outright harmful information.
[0] 15,000+ ai generated fake podcasts https://www.kaggle.com/datasets/listennotes/ai-generated-fak...
[0] https://www.listennotes.com/blog/use-betterstack-to-replace-...