Tyler Pearson
@tylerdpearson.bsky.social
Reposted by Tyler Pearson
There’s a terrifying trend (particularly in academia) of signaling authenticity by dismissing popularity.
One might commit to “pure” intellectual pursuit rather than pandering to wider audiences.
Simplification is treated as intellectual dilution.
One might commit to “pure” intellectual pursuit rather than pandering to wider audiences.
Simplification is treated as intellectual dilution.
March 11, 2025 at 9:40 PM
There’s a terrifying trend (particularly in academia) of signaling authenticity by dismissing popularity.
One might commit to “pure” intellectual pursuit rather than pandering to wider audiences.
Simplification is treated as intellectual dilution.
One might commit to “pure” intellectual pursuit rather than pandering to wider audiences.
Simplification is treated as intellectual dilution.
Modern Computing is only possible because Honeywell filed a lawsuit a few minutes early.
The invalidation of ENIAC’s patent in Honeywell vs Sperry Rand placed the invention of the digital computer into the public domain.
Without it, the U.S could have easily lost tech dominance.
The invalidation of ENIAC’s patent in Honeywell vs Sperry Rand placed the invention of the digital computer into the public domain.
Without it, the U.S could have easily lost tech dominance.
March 4, 2025 at 10:36 PM
Reposted by Tyler Pearson
Most hashing algorithms are designed to avoid collisions.
What if they weren’t?
Locality-sensitive-hashing (LSH) is a way to group similar inputs into the same “buckets” with high probability.
Collisions are maximized, not minimized.
What if they weren’t?
Locality-sensitive-hashing (LSH) is a way to group similar inputs into the same “buckets” with high probability.
Collisions are maximized, not minimized.
January 28, 2025 at 7:48 AM
Most hashing algorithms are designed to avoid collisions.
What if they weren’t?
Locality-sensitive-hashing (LSH) is a way to group similar inputs into the same “buckets” with high probability.
Collisions are maximized, not minimized.
What if they weren’t?
Locality-sensitive-hashing (LSH) is a way to group similar inputs into the same “buckets” with high probability.
Collisions are maximized, not minimized.
Reposted by Tyler Pearson
The fact that Deepseek R1 was released three days /before/ Stargate means these guys stood in front of Trump and said they needed half a trillion dollars while they knew R1 was open source and trained for $5M.
Beautiful.
Beautiful.
January 28, 2025 at 3:02 AM
The fact that Deepseek R1 was released three days /before/ Stargate means these guys stood in front of Trump and said they needed half a trillion dollars while they knew R1 was open source and trained for $5M.
Beautiful.
Beautiful.