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From Credit Score to AI Score

From Credit Score to AI Score

Nov 24, 2024 | AI

TLDR

As the AI Score may become a key metric, professionalism in AI interactions will be crucial. Just as social media posts can impact one’s reputation, how individuals use AI—such as the tone, accuracy, and ethical considerations in their queries—may influence their AI Score. To succeed in an AI-driven future, we must approach these tools with responsibility, ensuring that every interaction reflects our expertise and integrity.

The Irreplaceable Role of Technology in Modern Life

Technology adoption has always followed a pattern of initial skepticism, widespread dependence, and eventual indispensability. Consider GPS: once a luxury, it has become a necessity for navigation, rendering traditional maps nearly obsolete. Similarly, smartphones started as communication devices but are now essential hubs for personal, professional, and social activities. AI is following the same trajectory, rapidly evolving from a niche tool to a cornerstone of work and life. In the future, much like we rely on GPS to drive or smartphones to connect, AI will become a fundamental requirement for professional productivity and decision-making.

The Evolution of Personal Scores

  1. Credit Score: Historically, personal assessment metrics began with financial health. Credit scores became critical for accessing loans, mortgages, and even certain jobs.
  2. Social Score: In some regions, like China, social credit systems expanded personal metrics to include behavior, trustworthiness, and social engagement, signaling how society values broader traits beyond financial reliability.

The Emergence of the AI Score

The future will belong to individuals who can effectively operate, collaborate with, and leverage AI. An AI Score could become the definitive metric for employability and career advancement. Here’s why:

  • AI Proficiency as a Core Skill: Just as computer literacy became a prerequisite in the digital age, AI literacy will be essential. The AI Score would measure one’s ability to use AI tools efficiently, creatively, and responsibly.
  • Dynamic Evaluation: Unlike static scores, an AI Score could evolve dynamically, reflecting continuous learning and adaptation as AI systems advance.
  • Implications for Employment: Employers could use AI Scores to assess candidates’ readiness for an AI-driven workplace. It would shift the focus from traditional qualifications to practical AI aptitude, making it a critical differentiator in a competitive job market.

Here’s an example

Strong AI Operators: The Workforce of the Future

As AI permeates every industry, the most valuable workers won’t just be those who understand their field but those who can integrate AI into their workflow to drive innovation and efficiency. These “strong AI operators” will:

  • Make better decisions with AI-generated insights.
  • Design and implement AI-driven processes.
  • Collaborate seamlessly with AI systems to solve complex problems.

Potential Challenges and Considerations

  • Bias and Accessibility: Ensuring the AI Score is fair and accessible to all will be vital to prevent inequality.
  • Over-Reliance on Metrics: While valuable, the AI Score must not oversimplify talent or reduce people to numbers.
  • Ethical Implications: Transparent criteria and ethical usage of the AI Score are crucial to prevent misuse.

Fluxbot review

Feb 7, 2024 | AI, Defi, Uncategorized

Some notes

  • Fluxbot is a new Telegram trading bot for the Solana ecosystem. It is a self custodial wallet.
  • The private key can be imported in another wallet. We successfully imported it to phantom wallet.
  • It uses Jupiter for DCA and other dex for swapping (Raydium, fluxbeam, etc…)
  • We can’t modfiy slippage for every transaction.
  • We can’t see a readable transaction history, we have to go to https://solscan.io/

FLUXB token usage:

The native token is not used for transaction fees, so there is no real demand for the token. However, holders of at least 1000 FLUXB token get “reflections”. In short, they get rewarded with a part of the fees generated by the platform. The more there are accounts above 1000, the less your balance becomes compared to the total number of FluxB pool so the less rewards you get. This will incentivize people to hold more tokens,

Reflections depend on the success of the platform, so marketing and adoption are a must. What distinguishes Fluxbot is the copy trader and sniper feature. However as more platforms start offering the same features for the Solana ecosystem, the fees will have to be lowered to stay competitive which will decrease the reflections as well.

What sets apart fluxb is the AI chatbot part. If the chatbot becomes more interactive and personal, users will become more attached to using it, so this is one path towards success.

We went on to test the AI assistant.

In the first example, we asked the assistant to convert 1$ worth of solana to fluxb token:

It replied insufficient balance although we have 1$ worth of solana in the balance. Probably it though we meant 1 SOLANA, so we rephrased it with the amount in solana:

This time it understood and prepared the right transaction. The next step is to test wether the AI bot remembers our discussion, so let’s ask him to buy FLYXB using PYTH, but let’s do it a bit vaguely to see the level of interaction:

We see that the bot assumed we wanted to buy pyth instead of fluxb, not buy pyth instead of fluxb. Our statement was vague and confusing and we expected the bot to ask which option it should choose. However we were a bit more specific:

We can see that the bot is following closely the conversion and was able to correct the transaction.

Overall, the assistant is satisfactory for a first version and some more improvements should be on the way.

We tried to take it a step further and ask the bot to modify the slippage on the fly:

But it still used the predefined slippage from the settings.