@EpicGuyIsEpic@miniapeur Cool Worlds would have been nice to be recognized however i too question their criteria which put 3b1b & Veritasium where they fell.
@david_kipping@PBSSpaceTime Random fan thanking 2 of you (recent hero’s) speaking how best you bring the right material to right audience. My little will soon be inspired by new knowledge of lensed quasars…thx sabbaticals & MLD! Brilliant episode, well done.
Deep Dive into LLMs like ChatGPT https://t.co/jbQphaXFbK via @YouTube thank you andrej for channeling your 3bluebrown energy and sharing your teaching talent.
OpenAI o1 and o1 pro mode in ChatGPT — 12 Days of OpenAI: Day 1 https://t.co/7vtgX0UPwe via @YouTube
The power of Matrix Math & Transformers as showcased perfectly by @hwchung27 as he contemplates OpenAI 4o’s logic and phd’s math.
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LLMs : Adrian :: TI85 : Brandon
China or the US: Who is winning the new space race? | Mapped Out https://t.co/XqqkvLoOyI via @YouTube
23,000 known space objects in orbit.. if each one was a semi-truck driving full speed at same LEO height, how frequent are collisions?
But what is a neural network? | Chapter 1, Deep learning https://t.co/e2gaP4IkZt via @YouTube
7 lectures, Neural networks, attention, back propagation.
Ranked choice is 1951 Arrows thesis for what a voting system should have. Then proved that out to the Nth detail, you’ll find what you looking for.
Lots of stuff I like on this channel. @veritasium
Why Democracy Is Mathematically Impossible https://t.co/4ZN2OgXNsE
I learned the math behind ranked choice is pretty cool. Although ranked choice came about 1800’s, math cream, Arrow’s 5 condition thesis in 1951, and a Nobel prize in the 1970’s
How Google Translate Uses Math to Understand 134 Languages | WSJ Tech Be... https://t.co/B4oax4DmTP via @YouTube
Although at forefront today, suspect looks outdated in a few years
@GoogleAI Thank you for whoever creates these visuals as I am sure they are internalized much faster compared to the tools majority of us had going through.
Graph clustering merges similar items into groups to better understand relationships in data. Today, read about our recent works, including key techniques that enabled us to scale a high-quality algorithm that can cluster trillion-edge graphs. Read more → https://t.co/9pYF1xUEJ7