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🚨 WHY PEOPLE DON’T MAKE AS MUCH PROFITS AS THEY SHOULD FROM CRYPTO If you’ve been in #crypto for months or even years and still haven’t made tangible profits, here’s why: --- 1. Wrong Timing You buy at the wrong time. You book profits at the wrong time. You sell at the wrong time. 📉 If you’ve repeatedly bought high and sold low, step back and recalibrate. Timing is the root of your problem. --- 2. Wrong State of Mind Panic trading destroys your chances of success. Trading requires calmness, patience, and confidence in your strategy. 😟 Anxiety-driven decisions = More losses. --- 3. Wrong Capital Stop investing: College fees Loans Rent money Survival funds 💡 Invest only what you can afford to lose. Detached capital helps you stay calm and make better decisions without fear of losing it all. --- 4. Misunderstanding Market Phases You wait for dips during accumulation phases. Then you buy during selling phases. 📈 Understand when to accumulate and when to sell, or you’ll lose more than you gain. --- 5. Waiting for Unrealistic Profits Don’t lose your profits by waiting for 100x gains every time. Small moves of 10-50% daily are still progress. 🔒 If you’ve already hit 2-3x returns, book profits, secure your capital, and let the rest ride. --- Final Thought The market will reward patience and knowledge, but it can be cruel to those who act recklessly. 🚀 The Bullrun is coming, but are you prepared? 💬 Need help diversifying your portfolio? Comment below, and let’s discuss!

Solana explains outage as SOL continues to pump The recent disruption was the first in a year since the 20-hour network jam recorded in February 2023. The recent outage that halted transactions on the Solana [SOL] mainnet for five hours was due to a known bug identified by developers last week, Solana Labs admitted in an elaborate root cause report. The bug was the cause of a Devnet outage seen previously. While developers issued a fix for one of the triggers of the bug, the fix for the other trigger was supposed to go into the version 1.18 cycle. The fix for the latter was eventually released as part of version 1.17.20. Solana stated in the report that a “more complete fix” would be released in the future and align with the regular release cycle. Solana, which prides itself on its lightning fast transaction speeds, theoretically up to 50,000–65,000 transactions per second (TPS), has often received.

Revolutionizing Scientific Discovery with Artificial Superintelligence ($ASI ) Artificial Superintelligence ($ASI ) is poised to redefine the landscape of scientific discovery, accelerating breakthroughs and uncovering new knowledge across disciplines. By combining computational power, advanced learning algorithms, and multidimensional data analysis, ASI could transcend human limitations in scientific exploration. --- 1. Automating Hypothesis Generation and Testing ASI can autonomously propose hypotheses, design experiments, and analyze results at speeds far surpassing human researchers. Example: Simulating millions of chemical reactions to identify novel compounds for drug development in hours rather than years. --- 2. Exploring Complex Systems ASI can model and analyze intricate systems, such as ecosystems, the human brain, or the cosmos, uncovering patterns and relationships that humans might miss. Example: Mapping the entire connectome of the human brain to advance neuroscience and treatments for mental health disorders. --- 3. Accelerating Materials Science ASI can predict the properties of new materials by analyzing atomic structures, enabling breakthroughs in energy storage, superconductors, and nanotechnology. Example: Discovering new materials for quantum computing or ultra-efficient solar panels. --- 4. Transforming Biomedical Research ASI could analyze genetic, proteomic, and clinical data to uncover the root causes of diseases and design personalized treatments. Example: Developing therapies for rare genetic disorders by identifying key genetic mutations and their biological pathways. --- 5. Expanding Space Exploration ASI could optimize spacecraft designs, analyze data from space missions, and predict celestial phenomena. Example: Identifying habitable exoplanets by analyzing vast datasets from telescopes and satellite observations. --- 6. Unifying Interdisciplinary Research ASI can bridge knowledge gaps between fields like physics, biology, and computer science, fostering integrated discoveries. Example: Linking quantum mechanics with biological processes to explore quantum biology and its implications for life sciences. --- 7. Simulating the Unobservable ASI can model phenomena that are difficult or impossible to observe directly, such as black hole formation or the behavior of subatomic particles. Example: Simulating the early moments of the universe to refine theories of cosmology. --- 8. Real-Time Data Analysis and Discovery ASI can process real-time data from sensors, satellites, and experiments to make instantaneous discoveries and adjustments. Example: Monitoring environmental changes globally to predict and mitigate the impact of natural disasters. --- 9. Ethical Implications in Scientific Research The speed and autonomy of ASI in scientific discovery raise ethical questions: Ownership of Discoveries: Who owns the intellectual property of ASI-generated breakthroughs? Research Prioritization: Should ASI focus on urgent human challenges or purely theoretical exploration? --- 10. Democratizing Access to Knowledge ASI could make scientific knowledge more accessible by summarizing complex research and translating it into actionable insights for policymakers and the public. Example: Providing developing nations with cutting-edge insights for addressing local challenges like water scarcity or food security. --- Challenges and Risks Data Dependency: ASI’s effectiveness relies on the availability of high-quality, unbiased data. Unintended Consequences: Discoveries made by ASI could have unforeseen negative implications (e.g., dangerous applications of new technologies). Resource Inequity: Advanced ASI tools might only be accessible to wealthy nations or corporations, exacerbating global inequalities. --- Conclusion ASI’s ability to revolutionize scientific discovery could lead to profound advancements across disciplines, tackling humanity’s biggest challenges and unlocking new frontiers of knowledge. However, careful governance, ethical safeguards, and equitable access will be critical to ensure its transformative power benefits all. $ASI (@Cryptosmith2✍️)

Every time I think of @taraxa_project, I’m reminded of its unique edge in the DAG space. $TARA isn’t just any DAG; it’s the world’s only PoS, blockDAG, and EVM-compatible L1. Like $KAS, which leads as a prominent blockDAG token, Taraxa’s blockDAG tech also allows multiple blocks to be added simultaneously. However, Taraxa stands out with its focus on efficiency, ensuring no data is wasted, while GHOST rule ordering prevents double-spending and tackles the blockchain trilemma. $TARA's Ficus Root Bridge is secured by ETH and Taraxa’s L1, offering seamless, spam-resistant cross-chain transfers without relying on oversized bridge networks. IMO, @taraxa_project is criminally undervalued and should be known more than this🤝 Probably nothing actually 👀 NFA DYOR

Expert opinions on risk management tools and resources emphasize the importance of having a comprehensive approach to identifying, assessing, and mitigating potential risks. Here are some key risk management tools and techniques: - *Risk Assessment Templates and Checklists*: Simple yet effective tools for identifying and recording potential risks in a structured format ¹. - *Risk Analysis Software*: Advanced software applications that use statistical models and simulations to analyze risk scenarios and their potential impacts ¹. - *Project Management Software*: Integrated risk management tools that offer risk management features within a broader framework, allowing seamless risk tracking alongside project milestones ¹. - *Financial Risk Management Tools*: Tools that focus on identifying and mitigating risks related to financial operations, such as market risk, credit risk, and liquidity risk ¹. - *Enterprise Risk Management (ERM) Software*: Comprehensive platforms that facilitate identifying, assessing, and managing risks across an organization by integrating risk management into corporate strategy [1). Some expert-recommended risk management techniques include: - *Probability and Impact Matrix*: Evaluates and prioritizes risks based on their likelihood of occurrence and potential impact on project objectives ¹. - *SWOT Analysis*: Identifies internal strengths and weaknesses, as well as external opportunities and threats ¹. - *Risk Register*: A document that contains all information about identified risks, including their status and mitigation plans ¹. - *Root Cause Analysis*: A problem-solving method that aims to identify the main cause of risk or issues rather than merely addressing their symptoms ¹. For small businesses, experts suggest using cost-effective, easy-to-implement, and scalable risk management tools, such as simple risk registers, SWOT analysis, cloud-based project management tools, financial management software, and cybersecurity assessment tools ¹.