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RT @MartinNebelong: Used to work with @janusch_patas  at @hedra_labs and I knew all along that he would do great stuff with Gaussian Splats…

RT @MartinNebelong: Used to work with @janusch_patas at @hedra_labs and I knew all along that he would do great stuff with Gaussian Splats…

Founder and CEO of https://t.co/5MjtfpwEU3 | Your guide to radiance fields | Host of the podcast @ViewDependent | FTP: 279 | discord: https://t.co/lrl64WGvlD

avatar for MrNeRF
MrNeRF
Mon Nov 10 16:18:24
Immediately after posting this I saw a tweet saying how "if you invested the savings in monthly payment you'll make way more than the interest you pay."

Lies and scams hidden behind an idealized truth delivered to masses that revolve credit.

Immediately after posting this I saw a tweet saying how "if you invested the savings in monthly payment you'll make way more than the interest you pay." Lies and scams hidden behind an idealized truth delivered to masses that revolve credit.

I'm a small business owner riding a rock through space. Domain names matter․ Champion of self determination. Cincy born and raised․

avatar for Drew Wash
Drew Wash
Mon Nov 10 16:16:49
I’ll take the other side, here are a few approaches that advantage app layer startups:

1 Categories that benefit from being *multi-model* -  labs and big tech will only ever be able to offer their 1P models and in coding / creative tools etc you get better results by multiplexing across many providers

2 Cornered resource (data) - you note this but there are many categories where startups have locked up a proprietary dataset and are 10x better than labs (open evidence, vlex)

3 Networks / compounding loops 

4 Ecosystems that imply a ton of feature surface area (sure you can replicate Granola’s recorder but is OpenAI really going to build the entire ecosystem of productivity apps implied by it)

The labs are ambitious and formidable but this is the same as saying Google will win everything on the web in 2004…

I’ll take the other side, here are a few approaches that advantage app layer startups: 1 Categories that benefit from being *multi-model* - labs and big tech will only ever be able to offer their 1P models and in coding / creative tools etc you get better results by multiplexing across many providers 2 Cornered resource (data) - you note this but there are many categories where startups have locked up a proprietary dataset and are 10x better than labs (open evidence, vlex) 3 Networks / compounding loops 4 Ecosystems that imply a ton of feature surface area (sure you can replicate Granola’s recorder but is OpenAI really going to build the entire ecosystem of productivity apps implied by it) The labs are ambitious and formidable but this is the same as saying Google will win everything on the web in 2004…

AI Apps investing @ A16Z; A1111; Boards of Krea, Deel, Clutch, Titan, Arc Boats, Untitled, Happy Robot + more; If you’re not at the table, you’re on the menu

avatar for Anish Acharya
Anish Acharya
Mon Nov 10 16:14:49
I’ll take the other side, here are a few approaches that advantage app layer startups:

1 Categories that benefit from being *multi-model* -  labs and big tech will only ever be able to offer their 1P models and in coding / creative tools etc you get better results by multiplexing across many providers

2 Cornered resource (data) - you note this but there are many categories where startups have locked up a proprietary dataset and are 10x better than labs (open evidence, vlex)

3 Networks / compounding loops 

4 Ecosystems that imply a ton of feature surface area (sure you can replicate Granola’s recorder but is OpenAI really going to build the entire ecosystem of productivity apps implied by it)

The labs are ambitious and formidable but this is the same as saying Google will win everything on the web in 2004…

I’ll take the other side, here are a few approaches that advantage app layer startups: 1 Categories that benefit from being *multi-model* - labs and big tech will only ever be able to offer their 1P models and in coding / creative tools etc you get better results by multiplexing across many providers 2 Cornered resource (data) - you note this but there are many categories where startups have locked up a proprietary dataset and are 10x better than labs (open evidence, vlex) 3 Networks / compounding loops 4 Ecosystems that imply a ton of feature surface area (sure you can replicate Granola’s recorder but is OpenAI really going to build the entire ecosystem of productivity apps implied by it) The labs are ambitious and formidable but this is the same as saying Google will win everything on the web in 2004…

AI Apps investing @ A16Z; A1111; Boards of Krea, Deel, Clutch, Titan, Arc Boats, Untitled, Happy Robot + more; If you’re not at the table, you’re on the menu

avatar for Anish Acharya
Anish Acharya
Mon Nov 10 16:14:49
I don’t understand how some people raise millions in funding yet not have any money for themselves. 🤔

I don’t understand how some people raise millions in funding yet not have any money for themselves. 🤔

I build stuff. On my way to making $1M 💰 My projects 👇

avatar for Florin Pop 👨🏻‍💻
Florin Pop 👨🏻‍💻
Mon Nov 10 16:13:10
shoutout to the many awesome people in the replies helping me collect some more gems into my keep going folder :)

really awesome to look into each thread of replies and find 1000s of amazing keep going propaganda

shoutout to the many awesome people in the replies helping me collect some more gems into my keep going folder :) really awesome to look into each thread of replies and find 1000s of amazing keep going propaganda

curious guy creating things @ https://t.co/HXWladhJaA - up and coming wife guy

avatar for jack friks
jack friks
Mon Nov 10 16:05:11
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