raghavtoshniwal

Last week I came across another fascinating podcast by Penrose that you folks might also like: https://www.youtube.com/watch?v=orMtwOz6Db0

That's an interesting problem. Aside from HN, I frequent TechMeme alot for the more news-y side of tech. They have a leaderboard section [1], that has all of the biggest tech publications ranked. That could be a good starting filter?

[1]:https://www.techmeme.com/lb

It would be interesting to know how many standard deviations is 775% extra demand from the norm. More than six standard deviations is rarer than a 1 in 506797346 event.

Also worth noting that that Xeon processor takes somewhere around 350-400W and the V100 is also in the range of 300W. So not huge on energy savings. Although a really cool, potentially industry shaking breakthrough, regardless.

There are plenty of 'open' standards[0] for webhooking and reporting ads, however there isn't much client support. As far as listening metrics go, Apple has implemented non intrusive podcast analytics already[1].

Podcasts work really well as is. They don't need fixing. Barrier to entries are low, and like the early days of youtube, you can have a successful podcast with a relatively low production value. They are published openly, monetizing gets easier with some traction. There is so much cross promotion that discoverability isn't a challenge either. I just hope the 'open podcast ecosystem' can resist attempts to be destroyed by Spotify/Luminary etc. This happy medium doesn't need personalized targeted advertising.

[0]: https://rad.npr.org/dotorg/about-rad/ [1]: https://developer.apple.com/videos/play/wwdc2018/501/

Except with 1 major twist. The longest most and used stretches could be automated while the "last mile" could use a human. Best of both worlds.

This is pretty cool. I had to look Frontpage up! Logic dictates that there must have been a point in time where the prevailing opinion shifted from “Uses ancient UI” to “Has a cool retro feel”. Probably all technologies go through this? Like vinyl becoming cool a few years back. Has happened with Flash games recently. Is there a name for this?

Off topic but it is considered difficult for NLP models to do sarcasm detection (because it’s a really hard problem, no widely available datasets, some context awareness is required, etc.)

For better or worse, in the last few years we have been generating a dataset on social forums by using “/s” at the end of sarcastic statements.

I’ll try and mine the “/s” statements on HN at least and see if I get somewhere.

Hey, looks pretty good. I made https://www.podwhat.com , it allows you to make podcast lists of the shows you like. Are you using the iTunes API for search?

Whoops! Fixed it now.

Mostly due to strides made in color reproduction and screen panel quality, and more recently due to support for higher frame rates. The gains from increasing the resolution have been minimal.

This plays so well with the theory of AWS taking a slice of all web activity. They are commoditising more and more complex tasks and enabling huge number of engineers to bootstrap their idea with amazing tech from day 1. A huge jump from S3/EC2 to this. Commendable.

I’ve iterated over that one a few times. Added decryption and timers, it’s a much more complete service.

The author of the tweet has the original message, that can be shared and verified against the hash

That is a really good idea. It might be a little more complicated to teach graphics/simple physics but maybe it would be worth it.

Hey Craig,

I wrote a service, (nowhere close for public release), that segments audio based on speakers. You have to identify one speech segment, it is then capable of labelling others. It uses GMM and MFCC. Is something like this in the works? Cool idea! I consume a fair bit of podcasts, I can affirm that there is definitely a need for this

Hey, I tried doing something similar in my city. I found designing a useful curriculum a challenge. I would love to ask a few questions. Couldn't get hold of your email. My email is raghav.toshniwal at google's service.

Thanks!

Even for things that smart contracts are capable of doing, the cost of doing them on a decentralised blockchain is often prohibitively expensive. For instace the Oraclize service, that does get external data into the contract, costs around $0.02, per API call. Which isn't much on its own, but they add up when compared to the number of API calls an average 'centralized' application makes.

I've often found that for quite a few applications, the cost of executing the contract on a blockchain outweigh the benefits of decentralisation.

Although I agree with the whole YouTube deciding what they want on their platform narrative, the argument loses some steam when talking about edge cases. There are a lot of conflicts where the distinction between quelling extremist content and removing anti-establishment rhetoric is a thin one. Once YouTube starts content censorship of any kind, they might quickly find themselves having to pick sides in somewhat grey areas. Making such value judgements and making them consistently becomes a challenge.

This move (along with the smart speaker), might help put 'M' at an equal footing with Alexa, Cortana, Siri, Google Assistant and the likes in terms of media recognition. Somehow, M is not brought up as often when AI assistants are mentioned.

Clickbait at its worst.

Facebook leveraging its userbase to mimic snapchat stories and Google rolling out their feed on their mobile app to solve the Google Now vs Google Assistant dichotomy aren't really similar. Google trying to take on Social Giant behemoth by making an interactive non-social feed on their mobile app makes for a nice headline though.

Facebook did not invent pushing people towards their native apps by a long shot. Most websites with a native app urge their users to download apps for more engagement. Calling it a Facebook "feature" is laughable.