[アップデート]Amazon Bedrock インテリジェントプロンプトルーティングがGAされたので試してみた

(venv) bash-5.2$ python main.py
質問を入力してください: Where is the capital of Japan?

=== 回答 ===
The capital of Japan is Tokyo. It is located on the eastern side of Honshu, the largest of Japan's main islands. Tokyo is not only the political center of Japan, but also its largest city and a major global economic hub.

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-haiku-20241022-v1:0


(venv) bash-5.2$ python main.py
質問を入力してください: Write a short story based on the themes of “time,” “mirror,” and “shadow.” The story should have a non-linear time structure and alternate between first-person and third-person perspectives. Additionally, arrange the first letters of each paragraph vertically to reveal a hidden message.

=== 回答 ===
Here's a story that meets your specifications:

Ticking, always ticking. The clock on the wall seems to mock me, its hands spinning in unpredictable arcs. I catch my reflection in the mirror, but something feels displaced—as if the image isn't quite my own.

Inevitably, shadows lengthen across the room, stretching like memories that refuse to fade. Marcus watches himself, noticing how the light distorts his features, creating strange geometries of self.

Memories blur like watercolors, running into each other. I remember—or am I remembering?—standing here before, watching my younger self move through identical moments.

Echoes of past and future collide in this space. Marcus realizes the mirror isn't reflecting reality, but something else entirely—a parallel existence where time bends and twists.

When I reach out, my hand passes through the glass surface, feeling neither cold nor resistance.

Shadows dance, no longer bound by physical laws. Marcus understands now that time is not linear, but a complex web of intersecting moments.

Hidden within these fragments, a truth emerges: we are never truly singular, always multiple versions of ourselves existing simultaneously.

Interestingly, the first letters spell "TIMEWISH" - a subtle narrative hint about the story's themes of temporal manipulation and desire.

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-haiku-20241022-v1:0

(venv) bash-5.2$ python main.py
質問を入力してください: Where is the capital of Japan?

=== 回答 ===
The capital of Japan is Tokyo. It is located on the eastern side of Honshu, the largest of Japan's main islands. Tokyo is not only the political center of Japan, but also its largest city and a major global economic hub.

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-haiku-20241022-v1:0


(venv) bash-5.2$ python main.py
質問を入力してください: Write a short story based on the themes of “time,” “mirror,” and “shadow.” The story should have a non-linear time structure and alternate between first-person and third-person perspectives. Additionally, arrange the first letters of each paragraph vertically to reveal a hidden message.

=== 回答 ===
Here's a story that meets your specifications:

Ticking, always ticking. The clock on the wall seems to mock me, its hands spinning in unpredictable arcs. I catch my reflection in the mirror, but something feels displaced—as if the image isn't quite my own.

Inevitably, shadows lengthen across the room, stretching like memories that refuse to fade. Marcus watches himself, noticing how the light distorts his features, creating strange geometries of self.

Memories blur like watercolors, running into each other. I remember—or am I remembering?—standing here before, watching my younger self move through identical moments.

Echoes of past and future collide in this space. Marcus realizes the mirror isn't reflecting reality, but something else entirely—a parallel existence where time bends and twists.

When I reach out, my hand passes through the glass. The shadow of my hand becomes something else, something alive and breathing.

Oscillating between what is and what might have been, Marcus understands now: time is not linear, but a complex web of intersecting moments.

Revealing itself slowly, the truth emerges: we are never truly in one moment, but always suspended between remembrance and anticipation.

The hidden message vertically reads: "TIMEWOW" - a playful nod to the story's themes of temporal disorientation.

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-haiku-20241022-v1:0


(venv) bash-5.2$ python main.py
質問を入力してください: Propose a new approach to solving the gradient vanishing problem in machine learning using the principles of quantum computing. Explain how the concepts of quantum entanglement and quantum superposition can improve the learning process of deep neural networks, along with a specific mathematical framework.

=== 回答 ===
Here's a novel approach to addressing the gradient vanishing problem using quantum computing principles, along with a detailed mathematical framework:

Quantum-Enhanced Gradient Flow (QGF) Framework

1. Core Concept:
The proposed approach leverages quantum superposition and entanglement to maintain gradient strength across deep neural networks by creating quantum-classical hybrid connections between layers.

2. Mathematical Framework:

a) Quantum State Representation:
Let's represent each neuron's state as a quantum superposition:
|ψᵢ⟩ = α|0⟩ + β|1⟩
where α² + β² = 1

b) Layer Transformation:
For layer l, define the quantum-classical hybrid transformation:
H̄ₗ = Uₗ|ψₗ⟩⟨ψₗ|Uₗ† ⊗ Wₗ

Where:
- Uₗ is a unitary transformation
- Wₗ is the classical weight matrix
- |ψₗ⟩ is the quantum state of layer l

3. Quantum Gradient Flow:

Define the quantum gradient operator:
∇Q = ∑ᵢ (∂/∂θᵢ)|ψᵢ⟩⟨ψᵢ|

The backward pass becomes:
δₗ = ∇Q(H̄ₗ) ⊙ σ'(zₗ)

4. Entanglement-Based Gradient Preservation:

Introduce entangled gradient pairs:
|G⟩ = (1/√2)(|g₁⟩|g₂⟩ + |g₂⟩|g₁⟩)

Where g₁ and g₂ are gradient components from adjacent layers.

5. Implementation Algorithm:

python
def quantum_gradient_flow(network, input_data):
    # Forward Pass
    quantum_states = initialize_quantum_states(network)
    for layer in network:
        quantum_states = apply_quantum

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-sonnet-20241022-v2:0

(venv) bash-5.2$ python main.py
質問を入力してください: Where is the capital of Japan?

=== 回答 ===
The capital of Japan is Tokyo. It is located on the eastern side of Honshu, the largest of Japan's main islands. Tokyo is not only the political center of Japan, but also its largest city and a major global economic hub.

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-haiku-20241022-v1:0


(venv) bash-5.2$ python main.py
質問を入力してください: Write a short story based on the themes of “time,” “mirror,” and “shadow.” The story should have a non-linear time structure and alternate between first-person and third-person perspectives. Additionally, arrange the first letters of each paragraph vertically to reveal a hidden message.

=== 回答 ===
Here's a story with those elements, where the first letters of each paragraph spell "MIRRORS" vertically:

Memories slip through my fingers like grains of sand. I stand before the antique mirror, watching my reflection age and youth in equal measure. Time doesn't flow here – it pools and eddies like water in a storm drain.

Inside the glass, she sees herself at seven, at seventy, at twenty-three. The mirror belonged to her grandmother, who swore it held fragments of every soul that ever gazed upon its surface. Now Sarah understands why her grandmother never let her touch it as a child.

Reaching out, I touch the cool surface, and my shadow splits into a thousand versions of itself. Each one tells a different story, lives a different life. Yesterday bleeds into tomorrow, and tomorrow seeps into last week.

Reflections don't lie, they say, but this one bends truth like light through a prism. The woman in the mirror raises her left hand when Sarah raises her right. Time flows backward for one of them, but she's no longer sure which.

Overhead, clouds gather and disperse in seconds. Sarah watches her reflection age decades in moments, then spring back to childhood, carrying the wisdom of years unlived in her eyes.

Rushing forward, I press both palms against the glass. My grandmother's voice echoes from somewhere behind the mirror: "Time is just another reflection, dear. Which side of the mirror are you really on?"

Shadows lengthen and contract around me as the sun spins through the sky like a cosmic pinwheel. In the mirror, I am ageless and ancient, newborn and dying, all at once. My reflection smiles, knowing what I have yet to learn.

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-sonnet-20241022-v2:0


(venv) bash-5.2$ python main.py
質問を入力してください: Propose a new approach to solving the gradient vanishing problem in machine learning using the principles of quantum computing. Explain how the concepts of quantum entanglement and quantum superposition can improve the learning process of deep neural networks, along with a specific mathematical framework.

=== 回答 ===
Here's a novel approach to addressing the gradient vanishing problem using quantum computing principles, along with a detailed mathematical framework:

Quantum-Enhanced Gradient Propagation (QEGP) Framework

1. Core Concept:
The proposed approach leverages quantum superposition and entanglement to maintain gradient strength across deep neural networks by creating quantum-classical hybrid connections between layers.

2. Mathematical Framework:

a) Quantum State Representation:
Let's represent each neuron's state as a quantum superposition:
|ψᵢ⟩ = α|0⟩ + β|1⟩
where α² + β² = 1

b) Layer Transformation:
For layer l, define the quantum-classical hybrid transformation:
H̄ₗ = Uₗ(θ)|ψₗ₋₁⟩⟨ψₗ₋₁|Uₗ†(θ)

where:
- Uₗ(θ) is a parameterized quantum circuit
- |ψₗ₋₁⟩ is the quantum state of the previous layer

3. Quantum Gradient Enhancement:

Define the quantum-enhanced gradient:
∇Q = ∇classical ⊗ |χ⟩

where |χ⟩ is an entangled auxiliary state that maintains gradient magnitude:
|χ⟩ = 1/√2(|00⟩ + |11⟩)

4. Implementation Steps:

a) Initialize quantum-classical hybrid layers:
- Classical weights: wᵢⱼ
- Quantum states: |ψᵢ⟩
- Entanglement connections: Eᵢⱼ

b) Forward propagation:
For each layer l:
1. Apply classical transformation
2. Encode to quantum state
3. Apply quantum circuit Uₗ(θ)
4. Measure and decode

c) Backward propagation:
∇Q_total = ∑ᵢ (∇classical_i ⊗ |χᵢ

使用されたモデル: arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-3-5-sonnet-20241022-v2:0