Phaverの‌価格SOCIAL

Economist and gold advocate Peter Schiff issued a dire forecast for the U.S. economy on April 3 in a series of posts on social media platform X, asserting that a global shift is underway that could leave the United States behind. He pointed to a sudden plunge in key commodities as a reflection of investor sentiment, but argued that only one part of the world is likely to suffer. Schiff stated: “Commodities like oil, silver, and copper are down sharply today as investors are pricing in a global recession.” He cautioned: But the recession will mainly be limited to the U.S. The rest of the world is about to boom, as they will be liberated from having to subsidize the U.S. economy. His comments suggest a growing divergence between the economic prospects of the U.S. and other regions. In addressing the implications of this divide, Schiff highlighted what he sees as the difficult choices ahead for American policymakers and businesses. He argued that the country must shift away from reliance on imports and invest in domestic production, even if the process is disruptive. “The U.S. has a difficult road ahead. We need to start producing all the stuff we’ve been importing. That requires significant investment and painful short-term sacrifice. On the other hand, all the rest of the world has to do is consume more of what they already produce. Not only is that easy to do, but it’s also fun.” Schiff’s analysis paints a picture of a U.S. economy in need of transformation, contrasted with global economies that may benefit from reduced dependency on American demand. Schiff also revisited his criticism of tariff policy under President Donald Trump, particularly its impact on the value of the U.S. dollar. He emphasized that his view had been an outlier when tariffs were first introduced. “All the financial experts agreed that Trump’s tariffs would strengthen the dollar. I was alone in my forecast for the reverse,” he said. Noting that the U.S. Dollar Index is experiencing steep losses, he warned that the economic pain for consumers may intensify. He opined: The U.S. dollar index has fallen to its lowest level since Oct. and looks like it’s headed much lower. The argument was that a stronger dollar was going to offset the sting of the tariffs on U.S. consumers. Instead, a weaker dollar will just make the sting that much more painful. 免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。

Jupiter Exchange has introduced Jupiter VERIFY , a token verification system that aims to help users identify trustworthy projects, straight from the source. This system is here as an answer to a basic need that is often overlooked, such as how to know if the token we see is really legit. Introducing Jupiter Verify – Token Verification, Now 4x Tastier! 🍽️ Token verification in defi is a permissionless nightmare and ever-evolving challenge but getting it right is crucial for the ecosystem to grow. That’s why Jupiter has grinded through multiple iterations of… — mei (@9yointern) April 2, 2025 Through the VERIFY system, Jupiter embeds a special badge next to the token name to indicate its level of trust. It’s like a blue tick on social media, but for tokens. There are several types of verification that tokens can get, and each has its own criteria. First, there is the Blue Chip category. Tokens that are included here are considered to have been tested by time and have wide recognition in the Solana ecosystem. The requirements are also quite strict, they must have a market capitalization of at least $ 100 million for a full month. The Jupiter team keeps track of this list manually as well. Tokens including USDC, JUP, SOL, and even WIF have earned this badge. Perhaps if this were in the actual world, they would be comparable to resilient “established brands.” On the other hand, for new tokens that have not reached that level but have a solid community, Jupiter provides the Community Assisted Verification category. This is where things like an active community, positive “vibes,” and even lore or stories about the token can be the deciding factor. Tokens like JELLYJELLY, for example, are not necessarily giants, but have social influence and trading momentum that make them noteworthy. Uniquely, projects no longer need to apply like in the old system. Now, the Jupiter team will filter 1-3 of the best tokens per day for verification, depending on market conditions. Tokens from celebrities, for example, are often the target of duplication by irresponsible parties. For this reason, Jupiter also introduces Social ID Verification, a kind of stamp that the token is officially recognized by a verified social account. This process can be done via an official tweet or a special form on the Jupiter website and will be released gradually. So that there are no more “similar” tokens that cause losses. No less interesting, there is also C.A.T. Report, stands for Certainty, Alignment, and Transparency. This is where Jupiter acts as a neutral party that verifies the token launch structure—from supply, distribution transparency, to how the project aligns with the interests of the community. This aims to prevent people from buying tokens with empty hopes. If you think about it, this approach is similar to checking hotel reviews before booking. It’s not enough to just look at the photos, but you also need to know the testimonials, reputation, and price structure. Well, Jupiter VERIFY is a kind of “TripAdvisor” of Solana tokens. Furthermore, VERIFY is only part of Jupiter’s big picture. In late February, CNF reported that the platform had also started its first buyback program for JUP tokens. All transactions were carried out transparently via on-chain, showing that they are serious about maintaining the values and trust of the community. Not long after that, Jupiter also acquired DRiP Haus, a digital collectibles platform. Interestingly, only half of the DRiP team immediately joined Jupiter. The rest will continue to run DRiP independently, but will help integrate NFTs into Jupiter. However, market conditions have not always been in line with these big moves. In the last 24 hours, JUP has corrected 2.09% and is trading at about $0.3845. This correction reflects how broader crypto market sentiment is still volatile, even as projects like Jupiter continue to make progress.

Mentorship is a timeless and universal concept that has the power to transform lives, careers, and communities. By pairing individuals with experienced guides, mentors can provide valuable insights, support, and guidance, helping mentees navigate challenges, achieve their goals, and realize their full potential. In this article, we'll explore the benefits, best practices, and impact of mentorship. # Benefits of Mentorship Mentorship offers numerous benefits for both mentees and mentors: 1. *Personal Growth and Development*: Mentorship fosters personal growth, self-awareness, and skill development. 2. *Career Advancement*: Mentorship can accelerate career advancement, providing valuable industry insights, networking opportunities, and job placement support. 3. *Increased Confidence and Resilience*: Mentorship can enhance confidence, resilience, and adaptability, helping mentees navigate challenges and setbacks. 4. *Diverse Perspectives and Networking*: Mentorship provides access to diverse perspectives, experiences, and networks, broadening mentees' understanding and opportunities. # Best Practices for Mentorship Effective mentorship requires commitment, empathy, and a structured approach: 1. *Clear Goals and Expectations*: Establish clear goals, expectations, and communication channels to ensure a productive and fulfilling mentorship experience. 2. *Active Listening and Empathy*: Foster a supportive and non-judgmental environment, actively listening to mentees' concerns and providing empathetic guidance. 3. *Regular Meetings and Feedback*: Schedule regular meetings and provide constructive feedback to ensure mentees stay on track and continue to grow. 4. *Respect and Trust*: Cultivate a relationship built on mutual respect, trust, and open communication. # Impact of Mentorship Mentorship has a profound impact on individuals, organizations, and communities: 1. *Improved Academic and Professional Outcomes*: Mentorship has been shown to improve academic achievement, job placement rates, and career advancement. 2. *Increased Diversity and Inclusion*: Mentorship can help address diversity and inclusion gaps, providing underrepresented groups with access to guidance, support, and opportunities. 3. *Stronger Communities and Social Bonds*: Mentorship fosters stronger communities and social bonds, promoting a sense of belonging, empathy, and social responsibility. 4. *Personal Fulfillment and Legacy*: Mentorship provides mentors with a sense of personal fulfillment, legacy, and impact, inspiring positive change and growth. # Conclusion Mentorship is a powerful tool for unlocking potential, fostering success, and creating positive change. By embracing the benefits, best practices, and impact of mentorship, individuals, organizations, and communities can cultivate a culture of support, growth, and empowerment. # Recommendations 1. *Establish Mentorship Programs*: Develop formal mentorship programs within organizations, schools, and communities to provide structured support and guidance. 2. *Train Mentors*: Provide training and resources for mentors to ensure they are equipped to provide effective guidance and support. 3. *Encourage Mentorship*: Promote mentorship as a valuable tool for personal and professional growth, encouraging individuals to seek out mentorship opportunities. 4. *Celebrate Mentorship Successes*: Recognize and celebrate mentorship successes, highlighting the positive impact of mentorship on individuals and communities. 5. *Continuously Evaluate and Improve*: Regularly evaluate and improve mentorship programs, incorporating feedback from mentees and mentors to ensure optimal effectiveness.

First Digital Trust, the issuer of the FDUSD stablecoin, has refuted recent allegations by Justin Sun. First Digital Trust labeled the allegations as false and unrelated to its operations. In a statement on X, FDT clarified that the controversy involves TrueUSD, not FDUSD ( FDUSD ). “This dispute is with TUSD and not with $FDUSD. First Digital is completely solvent,” FDT posted. The firm emphasized that FDUSD is fully backed by U.S. Treasury bills, with reserve details transparently outlined in its attestation reports. On April 2, Justin Sun claimed that First Digital Trust was insolvent after mismanaging nearly $456 million in TrueUSD reserves. Legal filings revealed that the funds were diverted into unauthorized investments, prompting Sun to provide emergency funding to Techteryx. “This is a typical Justin Sun smear campaign to attack a competitor,” FDT stated, accusing Sun of attempting to damage its business through a coordinated social media effort rather than allowing the TUSD dispute to be resolved in court. FDT reaffirmed its solvency and the security of FDUSD reserves, adding that all funds are accounted for with verifiable ISIN numbers. The company also announced plans to take legal action to defend its rights and reputation.

AI has reshaped a lot of industries since it appeared and it’s continuing to do so. The financial market is one of them, which particularly saw a big change with the introduction of AI-powered trading bots. These bots leverage machine learning, deep learning, and predictive analytics to identify trading opportunities and execute trades at blazing speed (one could say it’s even ludicrous speed). Unlike traditional algorithmic trading, AI-based systems continuously learn from new data and adapt to changing market conditions, making them powerful tools for traders. However, using AI for market prediction faces challenges and limitations. Predicting price movements with certainty remains difficult due to the inherent complexity of financial markets, external economic influences, and sudden, unpredictable events (which, considering human nature, is quite often). Let’s just say, the technology just isn’t quite there yet, or rather, people haven’t figured out all the kinks and nuances. As one might have gathered by now, predicting financial markets is far from straightforward, probably even more so today with the crypto industry in the mix. Multiple hurdles limit the effectiveness of AI-powered trading systems, starting with inherent complexity. Financial markets are complicated by nature and are influenced by a combination of several elements, that is, macroeconomic factors, geopolitical events, investor psychology, market sentiment, high-frequency trading, and institutional manipulation. A key issue is the lack of structured rules; markets lack fixed patterns and are often swayed by unforeseeable events. Artificial intelligence struggles to account for unexpected shifts, like regulatory crackdowns or economic crises, making accurate predictions challenging. The next set of challenges are data limitations and bias. AI models require vast amounts of high-quality data for precise predictions. Sounds simple enough, but the problem is that financial data often contains biases, missing information, or manipulated data that can mislead models. To give you an example, an AI model trained only on bull market data might perform poorly during a sudden market downturn because it has never encountered such conditions before. Similarly, historical data may not always reflect current market realities due to evolving economic policies and investor behaviors. Then, there are overfitting and model risks. At first glance, this doesn’t sound like an issue, but overfitting is a common problem in AI trading. It refers to a situation when an AI model performs exceptionally well on historical data but fails in live trading. Overfitting occurs when models memorize past trends rather than recognizing generalizable patterns. On top of that, large institutional traders actively adapt their strategies to counteract AI-driven retail trading, further diminishing the reliability of predictive models. Despite the challenges above, AI trading bots can still be useful as they use various techniques to generate market predictions. To name a few: Core AI components like supervised learning, reinforcement learning, and neural networks allow AI to learn from labeled past trading data for future predictions. Through a combination of these, AI learns from labeled past trading data and applies it to future predictions, all the while it continuously improves upon strategies via feedback from simulated trading. In addition, deep learning techniques recognize price patterns, helping AI detect trends. In summary, these models analyze historical price movements, trading volume, and volatility to forecast potential price actions. The name perhaps sounds complicated, but it basically involves AI bots scanning news articles, financial reports, and social media to assess market sentiment. Then, by analyzing text data, NLP models gauge investor outlook (bullish or bearish). For instance, an out-of-the-blue increase in positive sentiment about Bitcoin on social media might indicate an impending price surge. On the other hand, panic-driven discussions may signal a market downturn. NLP understands the context of these conversations, analyzing word relationships between words in a sentence across paragraphs to get the meaning. This is more technical in nature and is a bit more complicated as AI-powered trading bots rely on a bunch of technical indicators. These include moving averages (MA, EMA), relative strength index (RSI), moving average convergence divergence (MACD), Bollinger Bands, and liquidity analysis. If you’re not familiar with the terms, you’ve likely read a bunch of gibberish now. Put simply, these signals help AI determine potential entry and exit points for trades by: Last but not least, AI bots use and analyze alternative data sources to speculate. This could be blockchain data with on-chain transactions, whale movements, and DeFi activity for crypto markets. Also, it employs options market data where open interest and trading volumes help predict investor sentiment. Moreover, AI even uses Google, specifically Google Trends and web traffic data. It can look for spikes in searches for specific cryptocurrencies or stocks that may indicate upcoming market movements. It’s worth remembering that AI indeed is a powerful tool, but it’s not foolproof since it has its limitations. Impressive and at times unbelievable, it isn’t magical or a crystal ball where you can see your future. Who knows, that might be true in the next few years, but it certainly isn’t true today, as many people overestimate AI’s ability to predict price movements with absolute certainty (which is wrong on many levels). To help you avoid making these mistakes putting all your hopes in AI, it’s best to remember several things, such as: Keep in mind that AI can offer you an edge, but can’t guarantee you a profit. Though AI currently struggles with predictive certainty, there are likely several advancements coming in the future. Some are speculation, some more grounded, but sooner or later, at least a few improvements are bound to happen. We may get more advanced deep learning models, which would make AI models better at adapting to unexpected market conditions, thus improving predictive accuracy. Potentially, with the rise of decentralized finance (DeFi), AI trading bots could integrate directly into smart contracts, enabling autonomous trading without intermediaries. In addition, with the increasing regulatory issues regarding AI and ethical concerns over its impact on retail traders (or in general), we may also get new laws governing AI trading. Whatever happens in the years to come, it’s a fact that AI-powered trading bots have transformed financial markets by making trading faster, more efficient, and data-driven. The technology isn’t know-it-all, and it works best alongside human expertise, fundamental analysis, and strong risk management. As AI evolves, traders should stay informed, adhere to strategies, and above all, set realistic expectations about AI’s capabilities. The future of AI in trading is promising, but it remains a tool that requires careful application with oversight. Disclaimer: The information presented in this article is for informational and educational purposes only. The article does not constitute financial advice or advice of any kind. Coin Edition is not responsible for any losses incurred as a result of the utilization of content, products, or services mentioned. Readers are advised to exercise caution before taking any action related to the company.