AlphaGo versus Lee Sedol

4 min readMar 16, 2021

MACHINE LEARNING

Humans have brains which means they can answer that question also whose answer is not known to them but how a human is able to answer it’s just because he has a natural intelligence and past experience which helps them to predict the answer but the computer is hardware then how to give the brain to it ??

What do humans have?

Brain
Experience
Lots of data
Prediction power
The habit of not saying “no”

What computers do not have?

Brain
Prediction Power
the answer to that question whose data does not exist.

MACHINE LEARNING

It is an application of ARTIFICIAL INTELLIGENCE which provides machines to automatically learn and improve through experience.More data brings more experience to the robot without explicitly programmed.

It is of four types -

SUPERVISED LEARNING

Supervisor means an instructor who instructs to do something. In supervised learning, the labeled data is used to train the computer for future prediction.
Sentiment analysis is the best example of supervised learning.

UNSUPERVISED LEARNING

Unsupervised means there is no instructor. In Unsupervised Learning unlabeled data is present and the computer trains itself by that data.
Clustering is done by unsupervised learning.

SEMI — SUPERVISED LEARNING

Semi-Supervised learning comes in between supervised and unsupervised learning. In this small amount of labeled data and a large amount of unlabeled data is present.
Speech Analysis is an example of Semi-supervised Learning.

REINFORCEMENT LEARNING

It uses trial and error methods for learning. When we use a map for finding routes it uses reinforcement learning means which search for the smallest route.

Let’s take one company which built a program that beets human in boardgame called go

DeepMind

DeepMind is a company that will create programs for complex sensory

and one of the biggest achievement for them is AlphaGo

AlphaGo is a computer program that plays the board game Go. It was developed by DeepMind Technologies which was later acquired by Google. Subsequent versions of AlphaGo became increasingly powerful, including a version that competed under the name Master. After retiring from competitive play, AlphaGo Master was succeeded by an even more powerful version known as AlphaGo Zero, which was completely self-taught without learning from human games. AlphaGo Zero was then generalized into a program known as AlphaZero, which played additional games, including chess and shogi. AlphaZero has in turn been succeeded by a program known as MuZero which learns without being taught the rules.

Lee Se-dol, is a former South Korean professional Go player of 9 dan rank. As of February 2016, he ranked second in international titles (18), behind only Lee Chang-ho (21). He is the fifth-youngest (12 years 4 months) to become a professional Go player in South Korean history behind Cho Hun-hyun (9 years 7 months), Lee Chang-ho (11 years 1 month), Cho Hye-yeon (11 years 10 months), and Choi Cheol-han (12 years 2 months). His nickname is “The Strong Stone” (“Ssen-dol”). In March 2016 he played a notable series of matches against AlphaGo that ended in 1–4.

On 19 November 2019, Lee announced his retirement from professional play, stating that he could never be the top overall player of Go due to the increasing dominance of AI. Lee referred to them as being “an entity that cannot be defeated”.