Sure, let's break it down to make it easier to understand:

1. **What is the article about?** The article talks about how computers (which we often call "AI" or Artificial Intelligence) are being used in trading stocks and other investments.

2. **Who wrote it?** A person named Vitaly Kudinov from a company called Devexperts.

3. **What has AI been good at for 7 years?** According to the article, AI has helped make computers that can talk to people and understand what they're saying better. It's also made games like chess and go much harder to play against because the computer players are so smart.

4. **What new things is AI learning now?** The article says AI is getting really good at looking at lots of data very quickly, like what happens in stock markets. This helps with making predictions about when it's a good time to buy or sell stocks.

5. **What might happen in the future?** According to Vitaly Kudinov, computers might be able to help people trade stocks much better by giving them really helpful advice based on lots of data and smart thinking.

6. **Who is this article for?** The article is written so that grown-ups who are interested in stock trading or AI can understand it. Read from source...

Based on the provided text, here are some aspects that could be improvement areas or points of criticism:

1. **Lack of Clear Thesis Statement**: While the piece discusses various uses and implications of AI in fintech, it doesn't start with a clear thesis statement outlining its main argument or perspective.

2. **Informal Tone**: The text switches between formal and informal language ("Vitaly Kudinov is a Senior Vice President at Devexperts" vs. "this article is from an unpaid external contributor"), which can make it less coherent and professional.

3. **Unsupported Claims**: Some statements are made without sufficient evidence or context, such as "AI assistants will feel less like tools and more like intuitive market advisors". It would be better to support such claims with examples, data, or expert opinions.

4. **Repetition**: The points about personalization and AI's ability to adapt to individual trading styles are repeated several times within a short span, which could make the text feel monotonous.

5. **Lack of Counterarguments or Critical View**: The piece presents potential benefits of AI in fintech but doesn't discuss any drawbacks, risks, or ethical concerns. Including these aspects would provide a more balanced view and demonstrate critical thinking.

6. **Target Audience**: It's not entirely clear who the target audience is for this piece. Is it meant to inform and persuade technologists, investors, regulators, or consumers? A clearer understanding of the audience could help tailor the language and arguments more effectively.

7. **Sources**: While the text mentions Vitaly Kudinov as a source, it doesn't provide any other sources or references for the information presented. Including links to relevant studies, reports, or expert opinions would enhance its credibility.

8. **Clarity**: Some sentences are complex and could be simplified or broken down into shorter, easier-to-understand components to improve readability.

Here's an example of how a paragraph could be revised for clarity and conciseness:

*Original*: "AI assistants will feel less like tools and more like intuitive market advisors, helping traders make more informed decisions to navigate markets confidently."
*Revised*: "With advancements in technology, AI assistants may evolve to provide deeply personalized insights, making them feel more like intelligent trading partners. This could enable traders to make more informed decisions, increasing their confidence as they navigate complex markets."

By addressing these points, the article's overall quality and impact could be improved.

Based on the provided article, here's a sentiment analysis:

- **Positive Points:**
- Highlights several benefits of AI in fintech, such as personalized trading experiences and adaptive insights.
- Mentions advancements that could make AI assistants feel more intuitive and helpful to traders.

- **Neutral Points:**
- The article mainly discusses potential future developments rather than current achievements or challenges.

- **No significant Bearish or Negative Points.**

Given these points, the overall sentiment of the article can be considered:
- **Positive**, as it focuses on opportunities and advancements in AI-driven fintech.
- **Neutral**, due to the lack of discussion about potential hurdles or existing challenges.

Based on the article, here are some key aspects of AI's potential in trading applications, along with associated opportunities and risks:

**Opportunities:**

1. **Personalized Trading Experiences:** By combining historical and real-time data, AI can adapt to individual trading styles, providing insights tailored to each user.
- *Upside:* Enhanced decision-making and confidence for traders.

2. **Intuitive Market Advisors:** As technology advances, AI assistants could become more sophisticated, acting as intuitive market advisors.
- *Upside:* Improved support for traders in navigating markets efficiently.

3. **Deep Learning Capabilities:** With AI's ability to learn from vast amounts of data and identify complex patterns, it can uncover trends undetectable by human traders alone.
- *Upside:* Unlocking new opportunities and generating alpha.

4. **Round-the-Clock Trading:** AI systems don't need to sleep or rest, allowing for continuous monitoring and trading across various markets worldwide.
- *Upside:* Seizing opportunities in diverse market conditions and time zones.

**Risks:**

1. **Overreliance on AI:** Becoming too dependent on AI's decisions could lead traders to overlook important context or misinterpret signals, potentially resulting in costly mistakes.
- *Downside:* Loss of the human touch and critical thinking in decision-making processes.

2. **Model Risks and Black Swans:** AI models rely on historical data patterns, which might not hold true in future market conditions (including 'black swan' events). If unexpected situations arise, AI systems could provide misleading or incorrect advice.
- *Downside:* Incorrect predictions leading to poor trading decisions.

3. **Data Privacy and Security Concerns:** Collecting, storing, and processing personal data related to trading behaviors can raise privacy and security concerns. Breaches or misuse of this data could have severe consequences for traders.
- *Downside:* Compromised user data, loss of trust, potential legal issues.

4. **Regulatory Uncertainty:** The evolving regulatory landscape surrounding AI in finance may introduce uncertainties that affect how AI-driven trading systems can operate legally.
- *Downside:* Potential restrictions or requirements that could limit the functionality of AI trading tools.

5. **Ethical Considerations and Bias:** AI models might inadvertently incorporate or exacerbate existing biases present in their training data, leading to unfair outcomes or market manipulation.
- *Downside:* Reputational damage for companies providing AI-driven trading services.

In conclusion, while AI offers substantial opportunities for enhancing trading capabilities, it also introduces risks that need to be carefully managed. Balancing the benefits and addressing potential drawbacks will be crucial for realizing the transformative power of AI in the trading landscape.