# 10 Math Games That'll Boost Your Brain Power By 80%

TLDRDive into a brain-boosting adventure with '10 Math Games to Increase Your Brainpower by 80%'. This intense brain boot camp challenges you with a variety of puzzles, starting with counting squares and progressing through increasingly complex shapes like pentagons and crosses, to decoding the hidden mysteries in geometric felines and 3D blocks. Each puzzle is timed, pushing you to find squares, triangles, and circles within set intervals. From easy teasers to tricky questions that stump 95% of people, these puzzles are designed to sharpen your cognitive skills and offer a fun, engaging way to give your brain a serious workout. Join the challenge and see if you can solve these riddles that even include a surprising twist on the classic chessboard. Share your results, compare with friends, and remember, life is brighter on the brainy side!

###### Takeaways

- π The video features 10 math puzzles and brain teasers to challenge viewers
- π Several puzzles involve counting shapes like squares, triangles and circles
- π§ Viewers are given time limits to solve the puzzles and test their skills
- π€ Some puzzles have visual tricks that make the answers less obvious
- π’ The puzzles increase in difficulty and complexity over the course of the video
- β±οΈ Hints, explanations and solutions are provided after the time limit expires on each puzzle
- π± One puzzle involves finding triangles in the image of a cat
- π The final puzzle is an iconic chess board that most people assume has 64 squares
- π₯ Viewers are encouraged to share their answers in the comments
- π The host signs off by asking viewers to like, share and subscribe to the channel

###### Q & A

### What is the purpose of the video?

-The purpose is to challenge viewers with math brain games and number puzzles to boost brainpower.

### How many squares are there in the first puzzle?

-There are 40 squares in the first puzzle, including both large and small squares.

### What percentage of people typically can't find the last square in the second puzzle?

-95% of people typically can't find the last square in the second puzzle.

### How many triangles are in the Pentagon puzzle?

-There are 35 triangles in the Pentagon puzzle.

### What are perfect squares and how many are hidden in the cross puzzle?

-Perfect squares consist of four dots with one dot on each corner. There are 21 perfect squares hidden in the cross puzzle.

### How many triangles are there in the colorful triangle puzzle?

-There are 44 triangles in the colorful triangle puzzle, including all possible sizes and color combinations.

### What formula is provided to help count figures in similar riddles?

-The formula involves counting the number of triangles by side length, starting from the largest size and working down to the smallest.

### How many circles are actually in the cat picture puzzle?

-There are 20 triangles in the cat picture puzzle, including the letters O in the text.

### What makes determining the number of blocks in the 3D picture tricky?

-Some of the blocks are hidden from view below other blocks, making it harder to get an accurate count.

### What do viewers need to do to solve the final chessboard puzzle?

-Viewers need to work together in the comments section to determine if there really are 64 squares on the chessboard.

###### Outlines

##### π Warming up with square counting puzzles

The first paragraph introduces the video as a math brain workout involving 10 games focused on counting shapes like squares and triangles. It starts with a simple warm up of counting the number of squares in an image, which has 40 squares total.

##### π€ More complex shape counting puzzles

The second paragraph continues with more challenging shape counting puzzles, involving identifying squares in a complex image (11 total) and triangles in a pentagon (35 total). Solutions are provided to explain the methodology.

##### π§ Final chessboard brain teaser puzzle

The third paragraph ends with a question about the number of squares on a chessboard, challenging viewers to double check the commonly known answer of 64 squares. The narrator encourages discussion in the comments.

###### Mindmap

###### Keywords

##### π‘Brainpower

##### π‘Squares

##### π‘Triangles

##### π‘Pentagon

##### π‘Perfect squares

##### π‘Formulas

##### π‘3D picture

##### π‘Chessboard

##### π‘Mental agility

##### π‘Problem-solving

###### Highlights

The speaker introduces the concept of adversarial examples, which are inputs modified to cause machine learning systems to make mistakes.

Adversarial attacks can reveal blind spots, biases, and vulnerabilities in AI systems that impact safety and security.

Defenses against adversarial attacks include adversarial training, more robust models, and input pre-processing.

Future research is needed to make AI systems more robust and secure against evolving adversarial threats.

The speaker proposes a new detection method to identify adversarial examples based on analyzing the internal representations of the model.

They introduce a technique called input randomization that adds noise to inputs as a defense against adversarial examples.

Their method outperforms previous defenses on benchmark datasets while maintaining high accuracy on clean inputs.

They discuss limitations of current adversarial defenses and the need for an adaptive, multi-faceted approach.

Future work could explore ensembles, multi-task learning, and increasing model capacity as ways to improve robustness.

The speaker emphasizes the importance of adversarial robustness for deploying AI systems safely in the real world.

They introduce the concept of adversarial examples in speech recognition systems.

Small perturbations to audio can cause misclassifications while being virtually imperceptible to humans.

Defenses against audio adversarial attacks are challenging due to the complexity of speech signals.

Their method applies random frequency masking as a defense, improving robustness against targeted audio attacks.

Adversarial robustness remains an open research problem critical to deploying reliable AI systems.

###### Transcripts

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