the fact that his excuse for the Rabbit R1 not having any defining feature is that there are technical restraints is ridiculous, it's like if SpaceX had a problem with their engines so decided to just build rockets without them
sebastian retweeted
last year my friends and I fed 15,000 people
this year our goal is to feed 30,000 people around the world
here’s how you can help
1. every retweet = 1 person fed
2. every 10 likes = 1 person fed
3. every $2 donated = 1 person fed – at San Francisco, CA
sebastian retweeted
i'm putting a small team together to build my next venture in my holdCo (@halationco)
✦ double digit revenue share
✦ get to work w/ exited operators
✦ ideal experience in growth & sales
either we get acquired in 7 months, or it becomes a high cashflow company
who's down?
Isn't this the case for all Apple products vs competitors
So, Mark Zuckerberg finally tried the Apple Vision Pro and compared it to the Meta Quest 3
He says:
- Quest is 7x less expensive yet way more comfortable
- Quest is better for gaming, Xbox, YouTube
- "I'm surprised how much better Quest is better for majority of things"
My biggest takeaway:
The future of ads feels like his IG post.
This is real. No marketing talk, just saying it as it is.
Zuck's Apple Vision Pro feels like I'm listening to a tech reviewer not a guy worth $165B.
I feel like I'm having a convo in a living room with my friend Mark. You feel his enthusiasm.
Reminds me of the Kayne Superbowl ad. The guy spent $7M and took a 30s selfie video. Highly effective. He sold $19M of product within 24h of that video.
So my point is, if you're creating an "ad"
More living room, less high budget.
Be real.
sebastian retweeted
I'M BUYING!
I'm acquiring SaaS products in the 1-50k MRR range.
DM are open -- if you're interested in exiting 📬
I've heard a few people say this but I will say it again, what is wrong with the comment sections on viral tweets?
90% of the comments have nothing to do with the original tweet, they're just some random videos or memes
Day 3 of 100 days of ML paper implementations:
decided to use Tiny Imagenet as full ImageNet is a bit large and will take too long to train on
haven't had much time to work on this, but progressed with my AlexNet implementation, the paper is a lot nicer to read than Lenet
Day 5 of 100 days of ML paper implementations (yesterday was 4, typo):
Still working on Alexnet, trying to get local response normalization to work (I got a bit confused by the notation)
Day 3 of 100 days of ML paper implementations:
wasn't able to post yesterday due to weather complications, started today on Alexnet, getting Imagenet downloaded on a cloud GPU provider
Day 2 of 100 days of ML paper implementations:
Finished Lenet-5, was too lazy to implement the RBF layer so just used softmax