markov chains are simple but powerful.
they model systems where the next state depends on the current state.
not the whole past.
โข states โ possible conditions
โข transitions โ ways the system moves
โข probabilities โ uncertainty with structure
โข memorylessness โ only now matters
โข steady state โ long term behavior emerges
weather.
markets.
language.
biology.
robot navigation.
queues.
markov chains teach you a brutal systems lesson:
complex behavior can emerge from simple transition rules.
At first glance, Gradient, Divergence, and Curl may look like just more symbols from vector calculus. In reality, they describe three fundamentally different ways a field can behave. Understanding the intuition behind them makes many concepts in physics and engineering much easier to visualize.
The Gradient points in the direction of the steepest increase of a scalar quantity and tells us how rapidly that quantity changes. Divergence measures the net flow leaving or entering a point, helping identify sources and sinks within a vector field. Curl, on the other hand, measures the tendency of a field to rotate or circulate around a point.
These three operators form the mathematical language behind phenomena such as heat flow, fluid motion, gravity, and electromagnetism. Mastering their physical meaning is often more important than memorizing their formulas, because they provide a powerful way to understand how fields behave in the real world.
The laptop hasn't changed in 30 years. NVIDIA just changed it
RTX Spark is their first PC chip ever.
- RTX 5070 level GPU
- 128GB unified memory
- 1 petaflop of local AI
- thin, light, barely throttles unplugged
Your AI agent lives on the machine. 24/7. No cloud.
This is step one of the agentic AI PC, and everyone else is about to copy it.
@myshawti kalo fisik kelewat jomplang cukup sering lihat: cowok burik deketin cewek cakep.
tapi kalo ekonomi yg kelewat jomplang, apalagi gajinya sampe imut2 jika dibandingkan foundation cewenya, itu dimana ada yg kaya begitu njir
@whatever never mind annual incomeโeven with a net worth of $20M - $100M, you've got way more attractive and sustainable options when it comes to a partner
@AFpost mungkin dia sangat ahli di biologi, tapi sangat buruk di matematika, statistika, dan ilmu komputer. tidak heran mengapa ia memilih biologi, bukan fisika