You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Blockchained enabled ICOs are pumping cash into the field of AI, fuelling innovation that previously just could not connect with funding.

High tech, including AI, is one of the future-forward technologies getting a bump from the cryptocurrency boom. In fact, combining the two is also catalysing the pace of innovation in not just these two verticals, but has implications for industries far beyond.

How, where and why? Blockchain can help fuel crowdfunding efforts for AI projects. In turn, AI can help blockchained projects and platforms become more efficient – from energy consumption to stock market predictions and automation of all kinds, starting with payments.

Plus of course, blockchain makes access to AI more affordable in the first place. The scalability, security, and privacy that blockchain can also add to all of this mean that an integration of technical ability, the machines capable of performing such tasks on their own, cheaper, decentralized computing and the ability to literally fund such efforts with fiat or cryptocurrency is not only pie in the sky. It is literally becoming real.

The combination of blockchain and AI, will also, according to industry analysts, will absolutely accomplish two things. First, it will lower the barriers to access that currently hamper development. Second, no surprise, this lower barrier to access will create a great deal more innovation across all the industries that these two technologies touch. That is exciting news indeed.

The AI industry is projected to hit $15.7 trillion dollars by 2030, becoming one of the most important markets in the world. It will impact commerce, communication, transportation and almost every aspect of the human experience as it evolves. And blockchain technology will also, inevitably, play a huge role in that, in several different ways.

Effect.ai: Blockchain Innovation in AI

The last five years have seen an explosion of AI algorithms in practical use. Smart services – including self-driving cars, face and voice recognition and image translation are now possible and mainstreaming. This is the result of major advances in machine learning and the availability of much cheaper cloud computing.

While academic achievements in this space are available to the public, most are being developed by large corporations with deep pockets. This means that AI is in danger of being a “black box” technology, for the most part, that benefits only a select few.

Effect.ai proposes a radically different, blockchained alternative.

They are creating a private, decentralized ecosystem for AI development and AI related services called The Effect Network. The network will be empowered by smart contracts deployed on the NEO blockchain.

The Effect.ai team will deploy this network in three phases, powered by the system token called the EFX and then a separately dedicated token called the AIX.

The first phase is to build a Mechanical Turk (comparable to similar services in the market now offered by Amazon, Fiverr, One Space, and Guru). The platform will connect a supply and demand of tasks on a decentralized network. Completion of these tasks will create the data sets that people need to teach the AI algorithms.

The second phase is to create the Effect Smart Market. This is planned as a decentralized exchange where people can purchase, exchange and improve each other’s AI services. The algorithms will also be able to communicate and offer services to each other.

The third phase of the deployment will be to distribute both via the Effect Network. This will decrease costs involved with running the algorithms. It will also allow algorithms on the network to run globally without a single point of failure.

Competitive Advantages: Effect.ai vs. Amazon Turk

The platform will be immediately competitive with current services available in the Mechanical Turk space. This means Effect.ai will offer a private, decentralized marketplace for work that (for now) requires human intelligence. In other words, it is a global, on-demand workforce platform.

Unlike existing centralized models, however, the Effect Mechanical Turk is a peer-to-peer system, meaning that supply and demand connect more directly and efficiently.

The crowd-sourcing technology enables those with requests to create tasks that can be completed by workers in exchange for compensation. The tasks are described and compiled through smart contracts. The job offers are called Human Intelligence Tasks or HITs. When a worker completes one of these tasks, they are paid through the platform token, the EFX.

How does it stack up with say, Amazon in direct metrics?

First are costs. The Effect Mechanical Turk will be free to task requesters (in comparison to a 20-40% chunk taken by Amazon). More countries are included (195 in Effect.ai to 43 in Amazon). Fund withdrawal from Effect.ai is instant. In Amazon’s M-Turk, this process can take between 4-21 days.

Workers are also paid more. The average hourly rate of an Effect.ai worker will be about $9.40 compared to Amazon’s $2.13.

How Will the Effect M-Turk Work?

It all starts with Effect Requesters. These are people who register their tasks on the Effect Mechanical Turk. They can decide how much EFX will be paid to Workers who complete the tasks. Requesters can retrieve the results of such work when completed from the Effect Mechanical Turk and use them to train their AI algorithm. This creates an on-demand, scalable and distributed workforce at prices set by the employer and met by anyone for whom this is economically feasible.

Workers in turn, can choose from tasks on the platform that are made available to them by Requesters. They might be either included or excluded from tasks based on criteria such as location, age, gender or other criteria. Workers will be able to claim payment after task completion automatically via the smart contract created to request the work in the first place.

Tasks are essentially job offers, posted on the platform. They require human, rather than machine intelligence to complete. They will be managed by a database of smart contracts that both Requestersand Workers can utilize to organize job posting and payment. At some point, human workers will not be required for all tasks. The platform will also enable Requesters to rent Bots to perform some tasks. The creators of the bots and the algorithms behind them, in this case, would be compensated for their use.

The Effect.ai Token Sale

Here are the details of the upcoming Effect.ai token sale:

Token name: EFX (with AIX token planned)

Token base: ETH and NEO

Token supply: 650 million tokens

Token sale target: €4.28 million (soft cap), €14.820 million (hard cap)

Token sale date: 18 days in March, exact days TBD

Accepted currencies: NEO and ETH

Investment criteria:Minimum investment of €50 euro and a max of €25,000

Effect.ai’s Website

Effect.ai’s whitepaper