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CNN 003

· 약 3분

Image Gradient​

  • It is a directional change in the intensity or color in an image.
  • can be used to extract valuable information from images.
  • commonly used in edge detection.
  • ➡️ Change is X-directions, ⬇️ Change is Y-directions.
  • Combining both X and Y diretion to estimate if changes are in both directions.

HoG, Histogram of Oriented Gradient​

To find edge and shape of the object in the image

  • Computing Image Gradient
    • Use the horizontal and vertical filters to compute gradient values
  • Compute the strength/magnitude and direction of gradient
    • Strength/Magnitude(g): gx2+gy2\sqrt{g_x^2 + g_y^2}
    • Direction(θ\theta): tan⁡−1(gy/gx)\tan^{-1}(g_y / g_x)
  • Create orientation histogram
    • Divide the image into small connected regions called Cells which is a 8x8 patch
    • Create cell histogram based on gradient direction and magnitude
    • 64 (8x8) gradient vectors are put into a 9-bin histogram.
    • The bins are the gradient directions (θ\theta) quantized into 9-bins
  • Block Normalization
    • 16x16 pixels blocks or 22 cells are used for normalization, which has 4 histograms.
    • Normalization will make it scale/multiplication invariant
    • Each block will represent 36x1 element vector
  • Intensity: brightness of the pixel
  • Saturation: HSV color space, the amount of gray in the color
  • Calculate the HoG feature vector
    • Each of the 36x1 vectors in each blocks are concatenated into one big vector
    • Size of the vector will be 36xN, where N is the number of blocks in the image
  • Hog feature extractor

LBP, Local Binary Pattern​

To describe the image textures

LBPP,R(xc,yc)=∑p=0P−1s(gp−gc)⋅2pLBP_{P,R}(x_c, y_c) = \sum_{p=0}^{P-1} s(g_p - g_c) \cdot 2^p

  • An eifficient texture operator which labels each pixels of an image by thresholding their neighbours.
  • A powerful feature for texture classification
  • LBP operator is to describe the image textures using two measures namely, local spatial patterns and the gray scale constract of its strength.
  • S(x)S(x) is a thresholding function
  • (xc,yc)(x_c, y_c) is the center pixel in the 8 pixel neighbourhood
  • gcg_c is gray level of the center pixel
  • gpg_p is gray value of a smpling point in an equally spaced circular neighbourhood of P sampling points and radius R around the point (xc,yc)(x_c, y_c)
  1. Sample pixel neighbourhood
  2. Difference result
  3. Thresholding result

LBP

ANN​

L(a,y)=−(ylog⁡a+(1−y)log⁡(1−a))L(a, y) = -(y \log a + (1-y) \log (1-a)) GD(w,b)=x=1m∑i=1mL(a(i),y(i))GD(w, b) = x = \frac{1}{m} \sum_{i=1}^{m} L(a^{(i)}, y^{(i)})

TIM 003

· 약 3분

Push & Pull Factors​

  • Techonology - Push (Supply-side Pushing Innovation)
  • Demand - Pull (Demand-side Pulling Innovation)
Technology PushDemand Pull
Starts with Scientific BreakthroughStarts with Customer need
iPadZoom (COVID-19)
VR HeadsetSelfie Stick
Post-it NotesTesla Model 3

Disruptive Innovation​

  • Creative Destruction
    • a process by which new innovations and technological advancements ("creative")
    • desmantle long-standing economic structures, practices, and organizations ("destruction")
    • while creating new markets and opportunities
  • Disruptive Innovation
    • a process where a smaller company successfully challenges estabilished businesses bgy offering simpler, more affordable, or more accessible products or services.
    • low-cast, low-performance, alternative, improve over time and displace established playwers
  • Innovator's Dilemma
    • successful, well-managed companies often fail when disuptive technologies emerge
    • even when they do everything "right" according to traditional management principles.
Sustaining InnovationDisruptive Innovation
Improves existing productsCreates new markets or value
Higher marginsInitially lower margins
High-end customersLow-end market segments
  • Sustaining Innovation: Tesla improving battery range
  • Disruptive Innovation: Netflix replacing Blockbuster

Attention Economy​

  • Human attention a scarce resource
  • The attention economy is made up of anything trying to capture our limited attention.

Responsible Innovation​

  • Innovation can create benefits (growth, efficiency, solutions) but also risks (inequality, pollution, privacy loss).

  • Responsible Innovation is about developing new techonologies, products, or services in a way that is ethically acceptatble, socially desirable, and environmentally sustainable, while actively considering their potential impacts on society.

  • Anticipation: Exploring possible risks, unintended consequences, and long-term effects.

  • Reflexivity: Innovators reflecting on their own values, assumptions, and biases.

  • Inclusion: Engaging stakeholders (citizens, users, regulators, communities), not just engineers or investors shaping outcomes.

  • Responsiveness: Ability to change direction if concerns arise.

Product questionsProcess questionsPurpose questions
How will the risks and benefits be distributed?How should standards be drawn up and applied?Why are researchers doing it?
What other impacts can we anticipate?How should risks and benefits be defined and measured?Are these motivations transparent and in the public interest?
How might these change in the future?Who is in control?Who will benefit?
What don't we know about?Who is taking part?What are they going to gain?
What might we never know about?Who will take responsibility if things go wrong?What are the alternatives?
-How do we know we are right?-

Sustainability​

  • No poverty
  • Zero hunger
  • Good health and Well-being
  • Quality education
  • Gender equality
  • Clean water and Sanitation
  • Affordable and Clean energy
  • Decent work and Econnomic growth
  • Industry, Innovation and Infrastructure
  • Reduced Inequalities
  • Sustainable Cities and Communities
  • Responsible consumption and Production
  • Climate action
  • Life below water
  • Life on land
  • Peace, Justice, and Strong Institutions
  • Partnerships for the goals

Sustainability Dilemma​

Externailities​

Impacts on third parties

Sustainability Tree

  • Ecology / Environmental
    • Bio-diversity
    • Habitat loss
    • Pollution
    • Carbon footprint
  • Social - human side
    • Human trafficking
    • Working conditions
    • Child labour
    • Social cohesion
    • Addiction and psychological damages

Internal Perspectives​

  • Economic - Business sustainability
    • Solvency
    • Regulations
    • Management
    • Succession planning
    • Disaster management
    • Short-term thinking / goals
    • Fiduciary obligations to Shareholders

CNN 002

· 약 3분

Type of ML Systems​

  • Supervised Learning
  • Unsupervised Learning
  • Semi-supervised Learning
  • Reinforcement Learning
  • Batch and Online Learning
    • Whether system can learn on the fly
  • Instance-based and Model-based Learning
    • Comparing data points or detect patterns in training data to build a predictive model

Evaluation Metrics​

Interesction over Union (IoU)​

IoU

  • a metric used for the evaluation of object detection detectors
  • how good is the predicted bounding box for an object detected closely matches.

IoU=Area of OverlapArea of UnionIoU = \frac{Area\ of\ Overlap}{Area\ of\ Union}

Digital Image​

  • made of picture elements (pixels)
  • an array or a matrix of Pixels arranges in columns and rows
  • Each Pixel has its own intesity value, or brightness
  • Intensity values in digital images are defined by bits.
    • 8 bits image = 256 (2^8) intensity values (0-255)
  • Black & White images have a single 8-bits intensity range.

Image Processing Basics​

  • Image dimension = 5×5×35 \times 5 \times 3
  • Number of Channels = 3 (Red, Green, Blue)
  • So, 24-bit color dpeth (8 bits per channel)
    • Each pixel has 3 intensity values (R, G, B) each in the range of 0-255
    • Total number of possible colors = 2563256^3 (16,777,216)

Image Processing Types​

  • Image Enhancement
  • Image Restoration
  • Image Segmentation
  • Image Recognition & Classification
  • Image Compression
  • Image Transformation
  • Image Filtering
  • Morphological Processing
  • Color Image processing
  • 3D Image Processing

Image Thresholding (Segmentation)​

  • Easist method for image segmentation
  • Converts gray-scale image into a binary image
    • f(x,y)<Threshold⇒0f(x,y) < \text{Threshold} \Rightarrow 0 (black)
    • f(x,y)≥Threshold⇒255f(x,y) \geq \text{Threshold} \Rightarrow 255 (white)

Image Thresholding methods​

  • Histogram shape: Peaks, valleys, and curvature of the histogram are analyzed to determine the optimal threshold value.
  • Clustering based: The Otsu method, good for bimodal distribution
  • Adaptive thresholding: Instade of a single threshold, have thresholds for different regions in the image.

Image Transformation​

  • Rotation
  • Translation
  • Uniform Scaling
  • Non-Uniform Scaling
  • Reflection
  • Shearing

Edge Detection (Image Filtering)​

  • Edge?
    • The points/pixels in an image where brightness/intensities changes sharply.
    • A simple and fundamental tools in image processing and computer vision, useful in feature detection/extraciton
  • Canny Edge detection
  • Sobel Edge detection
  • How to detect edges?

Prewitt Filters​

  • Vertical Edge detector: [10−110−110−1]\begin{bmatrix} 1 & 0 & -1 \\ 1 & 0 & -1 \\ 1 & 0 & -1 \end{bmatrix}
  • Horizontal Edge detetor: [111000−1−1−1]\begin{bmatrix} 1 & 1 & 1 \\ 0 & 0 & 0 \\ -1 & -1 & -1 \end{bmatrix}

Sobel Filters​

  • Vertical Edge detector: [10−120−210−1]\begin{bmatrix} 1 & 0 & -1 \\ 2 & 0 & -2 \\ 1 & 0 & -1 \end{bmatrix}
  • Horizontal Edge detetor: [121000−1−2−1]\begin{bmatrix} 1 & 2 & 1 \\ 0 & 0 & 0 \\ -1 & -2 & -1 \end{bmatrix}

Morphological Processing​

  • Dilation: Shrinks the image pixels from the boundaries of objects in an image, making them thicker.
  • Erosion: Adds pixels to the boundaries of objects in an image, making them thinner.

Free up storage space on mac

· 약 1분

Issue​

  • Mac storage setting didn't show the actual storage usage, and it was always showing "Other" taking up a lot of space.
  • It also didn't check cache files, which took up at least 10GiB of space.

CLI​

GUI​

  • OmniDiskSweeper
  • Click "Macintosh HD" and "Sweep Macintosh HD Drive..."
  • You can manually select the files to delete including cache files.

IQC 002

· 약 7분

Ket​

∣ψ⟩=(ψ0ψ1)|\psi\rangle = \begin{pmatrix} \psi_0 \\ \psi_1 \end{pmatrix}

∣0⟩=(10)|0\rangle = \begin{pmatrix} 1 \\ 0 \end{pmatrix}

∣1⟩=(01)|1\rangle = \begin{pmatrix} 0 \\ 1 \end{pmatrix}

∣ψ⟩=ψ0∣0⟩+ψ1∣1⟩=ψ0(10)+ψ1(01)|\psi\rangle = \psi_0 |0\rangle + \psi_1 |1\rangle \\ \quad = \psi_0 \begin{pmatrix} 1 \\ 0 \end{pmatrix} + \psi_1 \begin{pmatrix} 0 \\ 1 \end{pmatrix}

Matrices​

  • Matrices represent linear transformations (quantum gates). A general 2x2 matrix is: A=(α00α01α10α11)A = \begin{pmatrix} \alpha_{00} & \alpha_{01} \\ \alpha_{10} & \alpha_{11} \end{pmatrix}
  • Identity matrix: I=(1001)I = \begin{pmatrix} 1 & 0 \\ 0 & 1 \end{pmatrix}
  • Linearity: A(∣ψ⟩+∣ϕ⟩)=A∣ψ⟩+A∣ϕ⟩A(|\psi\rangle + |\phi\rangle) = A|\psi\rangle + A|\phi\rangle

Bra and Daggers​

Dagger​

  • Conjugate Transpose: swap rows/columns and complex-conjugates every entry.
  • Ket becomes Bra: ∣ψ⟩†=(ψ0ψ1)†=(ψ0‾ψ1‾)=⟨ψ∣|\psi\rangle^\dagger = \begin{pmatrix} \psi_0 \\ \psi_1 \end{pmatrix}^\dagger = \begin{pmatrix} \overline{\psi_0} & \overline{\psi_1} \end{pmatrix} = \langle\psi|
  • For a matrix: A†=(α00‾α10‾α01‾α11‾)A^\dagger = \begin{pmatrix} \overline{\alpha_{00}} & \overline{\alpha_{10}} \\ \overline{\alpha_{01}} & \overline{\alpha_{11}} \end{pmatrix}
  • Key Identities:
    • (αA)†=α‾A†(\alpha A)^\dagger = \overline{\alpha} A^\dagger
    • (A†)†=A(A^\dagger)^\dagger = A
    • (AB)†=B†A†(AB)^\dagger = B^\dagger A^\dagger

Hermitian and Unitary Matrices​

  • Hermitian: H†=HH^\dagger = H
    • Self-adjoint matrices, their eigenvalues are always real.
    • Observables in quantum mechanics are Hermitian.
  • Unitary: U†U=UU†=IU^\dagger U = UU^\dagger = I
    • The inverse of a unitary matrix is its conjugate transpose.
    • Unitary matrices preserve norms

Inner Product​

  • The angle between two vectors ∣ψ⟩|\psi\rangle and ∣ϕ⟩|\phi\rangle is defined as bra-ket: ⟨ψ∣ϕ⟩=(ψ0‾ψ1‾)(ϕ0ϕ1)=ψ0‾ϕ0+ψ1‾ϕ1\langle\psi|\phi\rangle = (\overline{\psi_0} \overline{\psi_1}) \begin{pmatrix} \phi_0 \\ \phi_1 \end{pmatrix} = \overline{\psi_0}\phi_0 + \overline{\psi_1}\phi_1
  • Important properties:
    • Order Matters: ⟨ψ∣ϕ⟩≠⟨ϕ∣ψ⟩\langle\psi|\phi\rangle \neq \langle\phi|\psi\rangle
    • But ⟨ψ∣ϕ⟩=⟨ϕ∣ψ⟩‾\langle\psi|\phi\rangle = \overline{\langle\phi|\psi\rangle} (Complex Conjugate)
    • The modulus is symmetric: ∣⟨ψ∣ϕ⟩∣=∣⟨ϕ∣ψ⟩∣|\langle\psi|\phi\rangle| = |\langle\phi|\psi\rangle|
  • The Magnitude of a vector is given by: ∥∣ψ⟩∥2=⟨ψ∣ψ⟩=∣ψ0∣2+∣ψ1∣2\| |\psi\rangle \|^2 = \langle\psi|\psi\rangle = |\psi_0|^2 + |\psi_1|^2

Orthonormal of the Computational Basis​

  • The basis states ∣0⟩|0\rangle and ∣1⟩|1\rangle are orthonormal: ⟨0∣0⟩=1,⟨1∣1⟩=1,⟨0∣1⟩=0,⟨1∣0⟩=0\langle 0|0\rangle = 1, \quad \langle 1|1\rangle = 1, \quad \langle 0|1\rangle = 0, \quad \langle 1|0\rangle = 0
  • This simplifies inner products enormously when working with the computational basis: ⟨ψ∣ϕ⟩=(ψ0‾⟨0∣+ψ1‾⟨1∣)(ϕ0∣0⟩+ϕ1∣1⟩) \langle\psi|\phi\rangle = (\overline{\psi_0}\langle0| + \overline{\psi_1}\langle1|) (\phi_0|0\rangle + \phi_1|1\rangle)
  • All corss terms vanish due to orthogonality, leaving: =ψ0‾ϕ0⟨0∣0⟩+ψ0‾ϕ1⟨0∣1⟩+ψ1‾ϕ0⟨1∣0⟩+ψ1‾ϕ1⟨1∣1⟩ = \overline{\psi_0}\phi_0 \langle0|0\rangle + \overline{\psi_0}\phi_1 \langle0|1\rangle + \overline{\psi_1}\phi_0 \langle1|0\rangle + \overline{\psi_1}\phi_1 \langle1|1\rangle =ψ0‾ϕ0+ψ1‾ϕ1= \overline{\psi_0}\phi_0 + \overline{\psi_1}\phi_1

Outer Products​

  • The outer product of two vectors produces a matrix: ∣ψ⟩⟨ϕ∣=(ψ0ψ1)(ϕ0‾ϕ1‾)=(ψ0ϕ0‾ψ0ϕ1‾ψ1ϕ0‾ψ1ϕ1‾)|\psi\rangle\langle\phi| = \begin{pmatrix} \psi_0 \\ \psi_1 \end{pmatrix} \begin{pmatrix} \overline{\phi_0} & \overline{\phi_1} \end{pmatrix} = \begin{pmatrix} \psi_0\overline{\phi_0} & \psi_0\overline{\phi_1} \\ \psi_1\overline{\phi_0} & \psi_1\overline{\phi_1} \end{pmatrix}
  • Basis outer products: ∣0⟩⟨1∣=(0100),∣1⟩⟨0∣=(0010)|0\rangle\langle1| = \begin{pmatrix} 0 & 1 \\ 0 & 0 \end{pmatrix}, \quad |1\rangle\langle0| = \begin{pmatrix} 0 & 0 \\ 1 & 0 \end{pmatrix}
  • Any matrix can be expanded in terms of outer products of the computational basis: A=α00∣0⟩⟨0∣+α01∣0⟩⟨1∣+α10∣1⟩⟨0∣+α11∣1⟩⟨1∣A = \alpha_{00} |0\rangle\langle0| + \alpha_{01} |0\rangle\langle1| + \alpha_{10} |1\rangle\langle0| + \alpha_{11} |1\rangle\langle1|

The Qubit​

A qubit is the fundamental unit of quantum information

∣ψ⟩=α∣0⟩+β∣1⟩|\psi\rangle = \alpha |0\rangle + \beta |1\rangle

  • where α,β∈C\alpha, \beta \in \mathbb{C} are complex numbers such that ∣α∣2+∣β∣2=1|\alpha|^2 + |\beta|^2 = 1 (normalization condition).
  • Any normalized single-qubit state can be parameterized using two angles θ\theta and ϕ\phi (real numbers): ∣ψ⟩=cos⁡θ∣0⟩+eiϕsin⁡θ∣1⟩|\psi\rangle = \cos\theta|0\rangle + e^{i\phi}\sin\theta|1\rangle
  • Key difference from a bit: a bit is either 0 or 1, while a qubit can be in a superposition of both states simultaneously until measured.

Measurement​

  • When you measure a qubit ∣ψ⟩=α∣0⟩+β∣1⟩|\psi\rangle = \alpha |0\rangle + \beta |1\rangle in the computational basis, you get:
    • ∣0⟩|0\rangle with probability ∣α∣2|\alpha|^2
    • ∣1⟩|1\rangle with probability ∣β∣2|\beta|^2
OutcomeProbabilityPost-measurement State
0$\alpha
1$\beta
  • The result of measuring a qubit is a single classical bit.
  • For ∣ψ⟩=cos⁡θ∣0⟩+eiϕsin⁡θ∣1⟩|\psi\rangle = \cos\theta|0\rangle + e^{i\phi}\sin\theta|1\rangle:
    • Probability of measuring ∣0⟩|0\rangle: cos⁡2θ\cos^2\theta
    • Probability of measuring ∣1⟩|1\rangle: sin⁡2θ\sin^2\theta
    • The phase ϕ\phi does not affect measurement outcomes.

One-Qubit Gates​

Pauli Matrices​

Unitary matrics

I=(1001),X=(0110),Y=(0−ii0),Z=(100−1)\mathbb{I} = \begin{pmatrix} 1 & 0 \\ 0 & 1 \end{pmatrix}, \quad X = \begin{pmatrix} 0 & 1 \\ 1 & 0 \end{pmatrix}, \quad Y = \begin{pmatrix} 0 & -i \\ i & 0 \end{pmatrix}, \quad Z = \begin{pmatrix} 1 & 0 \\ 0 & -1 \end{pmatrix}

  • XX is the quantum NOT gate:
    • X∣0⟩=∣1⟩X|0\rangle = |1\rangle
    • X∣1⟩=∣0⟩X|1\rangle = |0\rangle
  • ZZ filps the phase of ∣1⟩|1\rangle:
    • Z∣0⟩=∣0⟩Z|0\rangle = |0\rangle
    • Z∣1⟩=−∣1⟩Z|1\rangle = -|1\rangle
  • All three (X,Y,Z)(X, Y, Z) are both Hermitian and unitary.

Hadamard Gate​

H=12(111−1)H = \frac{1}{\sqrt{2}} \begin{pmatrix} 1 & 1 \\ 1 & -1 \end{pmatrix}

  • HH creates superpositions:
    • H∣0⟩=∣0⟩+∣1⟩2H|0\rangle = \frac{|0\rangle + |1\rangle}{\sqrt{2}}
    • H∣1⟩=∣0⟩−∣1⟩2H|1\rangle = \frac{|0\rangle - |1\rangle}{\sqrt{2}}
  • HH also "un-does" superpositions:
    • H(∣0⟩+∣1⟩2)=∣0⟩H\left(\frac{|0\rangle + |1\rangle}{\sqrt{2}}\right) = |0\rangle
    • H(∣0⟩−∣1⟩2)=∣1⟩H\left(\frac{|0\rangle - |1\rangle}{\sqrt{2}}\right) = |1\rangle

Rotation Gate​

R(θ)=(cos⁡θsin⁡θ−sin⁡θcos⁡θ)R(\theta) = \begin{pmatrix} \cos\theta & \sin\theta \\ -\sin\theta & \cos\theta \end{pmatrix}

  • R(θ)R(\theta) rotates the state vector by an angle θ\theta in the ∣0⟩|0\rangle-∣1⟩|1\rangle plane.

The Bloch Sphere​

Every single-qubit state ∣ψ⟩=cos⁡θ∣0⟩+eiϕsin⁡θ∣1⟩|\psi\rangle = \cos\theta|0\rangle + e^{i\phi}\sin\theta|1\rangle maps to a point on the surface of a unit sphere

  • θ\theta is polar angle from north pole
  • ϕ\phi is azimuthal angle around equator
  • ∣0⟩|0\rangle is at the north pole
  • ∣1⟩|1\rangle is at the south pole
  • ∣0⟩+∣1⟩2\frac{|0\rangle + |1\rangle}{\sqrt{2}} is on the equator at ϕ=0\phi=0

Exercises​

  1. For any two-dimensional state vector ∣ψ⟩=α∣0⟩+β∣1⟩|\psi\rangle = \alpha |0\rangle + \beta |1\rangle, it holds that ∣α∣2+∣β∣2=1|\alpha|^2 + |\beta|^2 = 1.
  2. Measuring a qubit in the {∣0⟩,∣1⟩}\{|0\rangle, |1\rangle\} basis yields a probabilistic outcome when both α\alpha and β\beta are non-zero.
  3. A global phase factor eiγe^{i\gamma} applied to a qubit state does not change the probabilities of measurement outcomes in the computational basis.
  4. The Bloch sphere represents all pure single-qubit states as points on the surface of the sphere.
  5. A real 2×22 \times 2 matrix is a valid quantum gate only if it is unitary, not merely invertible.
  6. The Pauli-X gate flips ∣0⟩|0\rangle to ∣1⟩|1\rangle and ∣1⟩|1\rangle to ∣0⟩|0\rangle.
  7. When a qubit is measured in a given basis, the state collapses to the basis state corresponding to the measurement outcome.
  8. Unitary matrices preserve the norm of any vector they act on.
  9. If ∣ψ⟩=cos⁡(θ)∣0⟩+eiϕsin⁡(θ)∣1⟩|\psi\rangle = \cos(\theta)|0\rangle + e^{i\phi}\sin(\theta)|1\rangle, then the probability of measuring ∣0⟩|0\rangle is cos⁡2(θ)\cos^2(\theta).
  10. The state 12∣0⟩+32∣1⟩\frac{1}{2}|0\rangle + \frac{\sqrt{3}}{2}|1\rangle is properly normalized.
  11. If ∣ψ⟩=13∣0⟩+23eiπ/4∣1⟩|\psi\rangle = \frac{1}{\sqrt{3}}|0\rangle + \sqrt{\frac{2}{3}} e^{i\pi/4}|1\rangle, then the probability of measuring ∣0⟩|0\rangle is 13\frac{1}{3}.
  12. The states 12(∣0⟩+∣1⟩)\frac{1}{\sqrt{2}}(|0\rangle + |1\rangle) and 12(∣0⟩−∣1⟩)\frac{1}{\sqrt{2}}(|0\rangle - |1\rangle) are orthogonal.
  13. The Pauli-X matrix X=(0110)X = \begin{pmatrix}0 & 1 \\ 1 & 0\end{pmatrix} satisfies X2=IX^2 = I, where II is the 2×22 \times 2 identity matrix.
  14. Applying the Pauli-Z gate Z=(100−1)Z = \begin{pmatrix}1 & 0 \\ 0 & -1\end{pmatrix} to 12(∣0⟩+i∣1⟩)\frac{1}{\sqrt{2}}(|0\rangle + i|1\rangle) produces 12(∣0⟩−i∣1⟩)\frac{1}{\sqrt{2}}(|0\rangle - i|1\rangle).

TIM 002

· 약 3분

Market Structure​

Perfect CompetitionMonopolistic CompetitionOligopolyMonopoly
Number of firmsAlmost InfiniteManyFewOne
Barriers to EntryNo barriersNo barriers / Low barriersSome barriersHigh barriers
Influence over PricePrice TakerLimitedSomePrice Maker
Nature of ProductHomogeneousDifferentiatedSimilar, DifferentiatedNo close substitutes
ExamplesCommon agricultural productsFast-food restaurantsAuto IndustryUtilities

Porter's 5 Competitive Forces​

  1. Threat of New Entrants: Profitable industries that yield high returns will attract new firms. New entrants eventually will decrease profitability for other firms in the industry.
  2. Threat of Substitutes: A substitute product uses a different technology to try to solve the same economic need.
  3. Bargaining Power of Customers: The market outputs. The ability of customers to put the firm under pressure, which also affects the customer's sensitivity to price changes.
  4. Bargaining Power of Suppliers: The market inputs. Suppliers of raw materials, components, labor, and services (such as expertise) to the firm can be a source of power over the firm when there are few substitutes.
  5. Competitive rivalry: For most industries the intensity of competitive rivalry is the major determinant of the competitiveness of the industry.

Threat of New Entrants​

Barriers to entry ⬆️, Profits ⬆️

  • How difficult it is for new business to enter an industry and compete with already established ones.
  • Many competitors lead to lower average profits
  • Threat of New Entrants:
    • Barriers to entry
    • Economies of scale
    • Brand loyalty
    • Capital requirements
    • Cumultative experience
    • Government policies
    • Access to distribution channels
    • Switching costs

Threat of Substitute Products​

  • A substitute product or service is an alternative that serves the same purpose for the customers, from a different industry.
  • For example,
    • Taxi vs. Uber
    • Train vs. Plane
    • Tea vs. Coffee vs. Soft Drinks
  • Threat of Substitutes Products:
    • Number of substitute products available
    • Buyer propensity ot substitute
    • Relative price performance of substitute
    • Perceived level of product differentiation
    • Switching costs

Bargaining Power of Customers and Suppliers​

  • Bargaining power of customers:
    • Number of customers
    • Size of each customer order
    • Differences between competitors
    • Price sensitivity
    • Buyer's ability to substitute
    • Buyer's information availability
    • Switching costs
  • Bargaining power of suppliers:
    • Number of suppliers
    • Size of suppliers
    • Uniqueness of each supplier's product
    • Focal company's ability to substitute

Rivalry among Existing Competitors​

  • The extent of competition within an industry
  • Price wars
  • Rivalry among existing competitors:
    • Number of competitors
    • Diversity of competitors
    • Industry concentration
    • Industry growth
    • Quality differences
    • Brand loyalty
    • Barriers to exit
    • Switching costs
  • For example,
    • Woolworths vs. Coles
    • Apple vs. Samsung

KANO Model​

  • Expected (Basic or Must-be) Attribute: whose presence doesn't directly increase satisfaction, but their absence causes extreme dissatisfaction.
    • car: a functioning brake is a must be quality
    • hotel: providing a clean room is a basic necessity
  • One-Dimensional (Performance) Attribute: can both satisfy and dissatisfy customers depending on their execution.
    • car: acceleration
    • hotel: waiting service at a hotel
  • Attractive (Delight) Attribute: differentiate products and services, creating a "wow factor" and delighting customers when present, but causing no dissatisfaction when absent.
    • car: advanced parking sensor
    • hotel: providing free food
  • Indifferent Attribute
    • car: the color of the car
    • hotel: highly polite speacking and very prompt responses not be necessary to satisfy customers
  • Reverse Attribute
    • web: auto-playing videos/audio
    • venue: unnecessary security checks at the entrance of a venue

Possible movement of Attributes' place​

  • As customer expectations change with the level or performance from competing products, attributes can move from delighter to performance need and then to basic need.

Innovation Tactics

· 약 9분

Profit Model​

  • Ad-Supported: Provide content or services for free to one party while selling listneners, viewers, or "eyeballs" another party.
  • Auction: Allow a merket-and its users-to set the price for goods and services.
  • Bundled Pricing: Sell in a single transaction two or more items that could be sold as standalong offerings.
  • Cost Leadership: Keep variable costs low and sell high volumes at low prices.
  • Disaggregated Pricing: Allow customers to buy exactly-and only-what they want.
  • Financing: Capture revenue not from the direct sale of a product but from structured payment plans and after-sale interest.
  • Flexible Pricing: Vary prices for an offering based on demand.
  • Float: Receive payment prior to building the offering; earn interest on that money prior to delivering the goods.
  • Forced Scarcity: Limit the supply of offerings available, by quantity, time frame, or access, to drive up demand and/or prices.
  • Freemium: Offer basic services for free while charging a premium for advanced or special features.
  • Installed Base: Offer a "core" product for slime margins (or even a loss) to drive demand and loyalty; then realize profit on additional products and services.
  • Licensing: Grant permission to a group or individual to use your offering in a defined way for a specified payment.
  • Membership: Charge a time-based payment to allow access to locations, offerings, or services that non-members don't have.
  • Metered Use: Allow customeres to pay only for what they use.
  • Microtransactions: Sell many items for as little as a dollar-or even only one cent- to drive impulse purchases.
  • Premium: Price at a higher margin than competitors, usually for a superior product, offering, experience, service, or brand.
  • Risk Sharing: Waive standrad fees or costs if certain metrics aren't achieved, but receive outsize gains when they are.
  • Scaled Transactions: Maximize margins by pursuing high-volume, large-scale transactions when unit costs are relatively fixed.
  • Subscriptiuon: Create predictable cash flows by charging customers upfront (a one time or recurring fee) to have access to the product or service orver time.
  • Switchboard: Connect multiple sellers with multiple buyers. The more buyers and sellers who join, the more valuable the switchboard becomes.
  • User-Defined: Invite customers to set the prcie they wish to pay.

Network​

  • Alliances: Share risks and revenues to jointly improve individual competitive advantage.
  • Collaboration: Partner with others for mutual benefit.
  • Complementary partnering: Leverage assets by sharing them with companies that serve similar markets but offer different products and services.
  • Consolidation: Acquire multiple companies in the same market or complementary markets.
  • Coopetition: Join forces with someone who would normally be your competitior to achieve a common goal.
  • Franchising: License business principles, processes, and brand to paying partners.
  • Merger/Acquisition: Combine two or more entities to gain accesss to capabilities and assets.
  • Open Innovation: Obtain access to processes or patents from other companies to leverage, extend, and build on expertise, and/or do the same with internal IP and processes.
  • Secondary Markets: Connect waste streams, by-products, or other alternative offerings with those who want them.
  • Supply Chain Integration: Coordinate and integrate information and/or processes across a company or different parts of the value chain.

Structure​

  • Asset Standardization: Reduce operating costs and increase connectivity and modularity by standardizing your assets.
  • Competency Center: Cluster resources, practices, and expertise into centers that support functions across the organization to increase efficiency and effectiveness.
  • Corporate University: Provide job-specific or company-specific training for managers.
  • Decentralized Management: Devolve decision-making governance closer to the people or business interfaces.
  • Incentive Systems: Offer rewards (financial or non-financial) to provide motivatino for a particular course of action.
  • IT Integration: Integrate technology resources and applications.
  • Knowledge Management: Share releavant information internally to reduce redundancy and improve job performance.
  • Organizational Design: Make from follow function and align infrastructure with core qualities and business processes.
  • Outsourcing: Assign to a vendor responsibility for developing or maintaining a ssystem.

Process​

  • Crowdsourcing: Outsource repetitive or challenging work to a large group of semi-organized individuals.
  • Flexible Manufacturing: Use a production system that can rapidly react to changes and still operate efficiently.
  • Flexible Manufacturing: Use a production system that can rapidly react to changes and still operate efficiently.
  • Intellectual Property: Use a proprietary process to commercialize ideas in ways that others cannot copy.
  • Lean Production: Reduce waste and cost in your manufacturing process and other operations.
  • Localization: Adapt an offering, process, or experience to target a specific culture or region.
  • Logistics Systems: Manage the flow of goods, information, and other resources between the point of origin and the point of use.
  • On-Demand Production: Produce items after an order has been received to avoid carrying costs of inventory.
  • Predictive Analytics: Model past performance data and predict future outcomes to design and price offerings accordingly.
  • Process Automation: Apply tools and infrastructure to manage routine activities in order to free up employees for other tasks.
  • Process Efficiency: Create or produce more while using less in terms of materials, energy consumption, or time.
  • Process Standardization: Use common products, procedures, and policies to reduce complexity, costs, and errors.
  • Strategic Design: Employ a purposeful approach that manifests itself consistently across offerings, brands, and experiences.
  • User-Generated: Put your users to work in creating and curating the content that powers your offerings.

Product Performance​

  • Added Functionality: Add new capabilities to an existing offering.
  • Conservation: Design your product so that end users can reduce their use of energy or materials.
  • Customization: Enable altering to suit individual requirements or specifications.
  • Ease of Use: Make your product simple, intuitive, and comfortable to use.
  • Engaging Functionality: Provide an unexpected or newsworthy feature that elevates the customer interaction from the ordinary.
  • Environmental Sensitivity: Create offerings that do no harm—or relatively less harm—to the environment.
  • Feature Aggregation: Combine a number of existing features from disparate sources into a single offering.
  • Focus: Design a product or service for a particular audience.
  • Performance Simplification: Omit superfluous details, features, and interactions to reduce complexity.
  • Safety: Increase the customer’s level of confidence and security.
  • Styling: Impart a noteworthy style, fashion, or image to create a product that customers covet.
  • Superior Product: Develop an offering of exceptional design, quality, and/or experience.

Product System​

  • Complements: Sell additional related or peripheral products or services to a customer.
  • Extensions/Plug-ins: Allow additions from internal or third-party resources that add functionality.
  • Integrated Offering: Combine otherwise discrete components into a complete experience.
  • Modular Systems: Provide a set of individual components that can be used independently, but gain utility when combined.
  • Product Bundling: Put together several products for sale as one combined offering.
  • Product/Service Platforms: Develop systems that connect with other partner products and services to create a holistic offering.

Service​

  • Added Value: Include an additional service or function as part of the base price.
  • Concierge: Provide premium service by taking on tasks for which customers don’t have time.
  • Guarantee: Remove customer risk of lost money or time from product failure or purchase error.
  • Lease or Loan: Let customers pay over time to lower their upfront costs.
  • Loyalty Programs: Provide benefits and/or discounts to frequent and high-value customers.
  • Personalized Service: Use the customer’s own information to provide perfectly calibrated service.
  • Self-Service: Provide users with control over activities that would otherwise require an intermediary to complete.
  • Superior Service: Provide service(s) of higher quality, efficacy, or which offer(s) a better experience than any competitor.
  • Supplementary Service: Offer ancillary services that fit with your offering.
  • Total Experience Management: Provide thoughtful, holistic management of the consumer experience across an offering’s lifecycle.
  • Try Before You Buy: Let customers test and experience an offering before investing in it.
  • User Communities/Support Systems: Provide a communal resource for product and service support, use, and extension.

Channel​

  • Context-Specific: Offer timely access to offerings that are appropriate for a specific location, occasion, or situation.
  • Cross-Selling: Offer appealing additional products, services, or information that will enhance an experience in situations where customers are likely to want to buy them.
  • Diversification: Add and expand into new or different channels.
  • Experience Center: Create space that encourages your customers to interact with your offerings—but purchase them through a different (and often lower cost) channel.
  • Flagship Store: Create a retail outlet to showcase quintessential brand and product attributes.
  • Go Direct: Skip traditional retail channels and connect directly with customers.
  • Indirect Distribution: Use others as resellers who take responsibility for delivering an offering to the final user.
  • Multi-Level Marketing: Sell bulk or packaged goods to an affiliated but independent sales force that turns around and sells it for you.
  • Non-Traditional Channels: Employ novel and relevant avenues to reach and service customers.
  • On-Demand: Deliver goods in real-time whenever or wherever they are desired.
  • Pop-Up Presence: Create a noteworthy but temporary environment to showcase and/or sell offerings.

Brand​

  • Brand Extension: Offer a new product or service under the umbrella of an existing brand.
  • Brand Leverage: Allow others to use your brand name to lend them your credibility and extend your company’s reach.
  • Certification: Develop a brand or mark that signifies and ensures certain desirable characteristics in third-party offerings.
  • Co-Branding: Combine brands to mutually reinforce key attributes or enhance the credibility of an offering.
  • Component Branding: Brand a discrete piece of the offering to make the whole appear more valuable.
  • Private Label: Provide goods made by others packaged under your company’s brand.
  • Transparency: Let customers see into your operations and participate with your brand and offerings.
  • Values Alignment: Make your brand stand for a big idea or a set of values and express them consistently in all aspects of your company.

Customer Engagement​

  • Autonomy and Authority: Grant users the power to shape their own experience.
  • Community and Belonging: Facilitate visceral connections to make people feel they are part of a group or movement.
  • Curation: Create a distinct point of view to build a strong identity for yourself and give your followers exactly what they want.
  • Experience Automation: Remove the burden of repetitive tasks from users to simplify their lives and make new experiences seem magical.
  • Experience Enabling: Extend the realm of what’s possible to offer a previously improbable experience.
  • Experience Simplification: Reduce complexity and focus on delivering specific experiences exceptionally well.
  • Mastery: Help customers to obtain great skill or deep knowledge of some activity or subject.
  • Personalization: Alter a standard offering to allow the projection of the customer’s identity.
  • Status and Recognition: Offer cues that confer meaning, allowing users—and those who interact with them—to develop and nurture aspects of their identity.
  • Whimsy and Personality: Humanize your offering with small flourishes of on-brand, on-message ways of seeming alive.

Reference​

  • Keeley, L., Walters, H., Pikkel, R., & Quinn, B. (2013). Ten Types of Innovation: The Discipline of Building Breakthroughs. John Wiley & Sons, Incorporated.

Agentic SDLC

· 약 1분

Agentic SDLC​

  • Agentic Software Development Life Cycle (SDLC) is an approach that integrates autonomous agents into the software development process.
  • This method decreases human intervention by allowing AI agents to handle various stages of development, from requirements gathering to deployment and maintainance.
  • It reduces the cycle time for SW development. Traditional SDLC takes weeks-to-months, while Agentic SDLC can potentially reduce this to days or even hours.

Cycles​

Key differences​

AspectTraditional SDLCAgentic SDLC
Cycle TimeWeeks to MonthsDays to Hours
FlowLinear, SequentialFluid, Iterative
Human InvolvementHuman codes everythingHuman guides, agent executes
DocumentationDocs as afterthoughtAuto-generated inline docs
TestingManual testingAutomated agent testing
Incident ResponseManual Incident handlingAgent-assisted remediation

Ref​

로컬 도커 환경 툴 비교

· 약 2분

비교​

옵션지원 OS기업 내 사용(유/무료)라이선스/유형런타임/구조K8S
Docker DesktopmacOS/Windows/Linux조건부, 그 외 유료상용Desktop 앱 + 백엔드/가상화(Windows는 WSL2 등)O
Podman DesktopmacOS/Windows/Linux무료(상업적 사용 포함)OSS (Apache-2.0)Podman + (mac/win) VM(podman machine)O
ColimamacOS/Linux무료(상업적 사용 포함)OSS (MIT)Lima 기반 VM + docker/containerd 선택O
OrbStackmacOS 전용개인만 무료, 기업/상업은 유료상용경량 VM 기반(통합/성능 강조)O
  • Docker Desktop
    • 기업 내 유/무료 판단 기준(공식)
      • 무료: 개인용, 교육용, 비상업 오픈소스, 소규모 사업자(직원 250명 미만 AND 연매출 1,000만 달러 미만).
      • 유료 구독 필요: 위 조건을 넘는 조직의 업무/상업적 사용, 정부기관 사용은 유료 필요.
    • 강점
      • 크로스플랫폼 표준화
    • 리스크
      • 조직 규모/매출에 따라 라이선스 비용 리스크가 명확.
  • Podman Desktop
    • 기업 내 유/무료
      • Apache-2.0 오픈소스라 상업적 사용 포함 무료.
    • 특징
      • Podman(daemonless/rootless 지향) 기반.
    • 트레이드오프
      • macOS/Windows에서는 보통 podman machine(VM)을 사용하게 되어 네트워킹/볼륨/호환성 체감이 환경별로 달라질 수 있음.
  • Colima
    • 기업 내 유/무료
      • MIT 라이선스(오픈소스)로 상업적 사용 포함 무료.
    • 특징
      • macOS/Linux에서 가볍게 컨테이너 런타임을 돌리는 CLI 중심(기본은 Lima VM).
    • K8s
      • 옵션으로 활성화 가능(프로젝트 기능으로 제공).
  • OrbStack
    • 기업 내 유/무료(공식)
      • Free = 개인/비상업만.
      • Pro(유료) = 비즈니스/상업적 사용(가격 페이지에 $8/user/month, 연간 청구로 표기).
      • 설치 시 30일 Pro 트라이얼(상업적 사용 가능) 후 Free로 내려감.
    • 강점
      • macOS에서 성능/통합 강점, 간단한 UI
    • 리스크
      • macOS 전용 + 상용/폐쇄형 + 업무용은 유료.

결론​

  • 맥유저 개인이면 OrbStack이 성능/통합 측면에서 매력적. (메모리 적게 먹음, UI 지원)
  • 기업/조직에선 Podman Desktop
  • CLI 선호, 가벼운 도커 환경 원하면 Colima