BitcoinWorld Mastering Foundation Models: Expert Strategies for Building Sustainable AI Businesses In the fast-paced world of artificial intelligence, new models seem to emerge constantly, while existing ones rapidly improve. For entrepreneurs and developers in the crypto and blockchain space, who are often at the forefront of technological shifts, this presents both immense opportunity and significant challenge. How can a startup build a robust, sustainable business when the underlying AI infrastructure is a moving target? This was a central question addressed by industry leaders from DeepMind, Twelve Labs, and Amazon at the Bitcoin World Sessions: AI event, where they shared practical strategies for navigating this dynamic landscape. Understanding the Shifting Sands of Foundation Models At the core of many recent AI breakthroughs are Foundation Models . These are massive models, pre-trained on vast amounts of data, capable of performing a wide range of tasks. Think of them as powerful generalists. Their existence has democratized AI development, allowing smaller teams to leverage capabilities that previously required immense resources to build from scratch. However, relying heavily on these models isn’t without its complexities. The models themselves are proprietary and controlled by large tech companies. They are updated frequently, their APIs can change, and their capabilities evolve. This creates a dependency that can feel unstable for a business trying to establish a long-term product or service. A model update could potentially break a core feature or change performance unexpectedly. Furthermore, if everyone is building on the exact same Foundation Models , how does a startup differentiate itself? The experts highlighted that understanding the nature of these models – their strengths, limitations, and inherent volatility – is the first step in devising a resilient strategy. What Does it Mean to Be Truly Building on AI? Simply calling an API isn’t enough to build a durable company. The discussion emphasized that successful ventures are those that build significant value around the AI model, not just on top of it. This involves several key areas: Data: Proprietary or unique data is a massive differentiator. How are you using data to fine-tune models, personalize experiences, or create unique features? Workflow Integration: AI is most powerful when integrated seamlessly into existing workflows or creating entirely new, efficient ones. Building intuitive interfaces and robust integrations adds significant value. Specialization: While foundation models are generalists, businesses need to be specialists. Focusing on a specific domain, use case, or vertical allows you to apply AI in a deeply knowledgeable way that general models cannot replicate out-of-the-box. User Experience: The best AI product isn’t just about the model’s output; it’s about how that output is presented, controlled, and used by the end-user. A superior user experience builds loyalty and defensibility. The takeaway here is clear: True Building on AI involves creating layers of value that are unique to your business, rather than just being a thin wrapper around a third-party model. Crafting Your AI Business Strategy for Sustainability A sustainable AI Business Strategy requires looking beyond the initial novelty of AI capabilities. It’s about identifying genuine problems that AI can solve and building a business model that captures value. The experts discussed various strategic considerations: Focusing on the Problem, Not Just the Tech: What specific pain point are you addressing for your customers? How does AI provide a significantly better solution than existing methods? The technology should serve the problem, not the other way around. Finding Your Niche: Trying to compete directly with the capabilities of large foundation models is often a losing game. Instead, find a specific niche where you can apply AI deeply and effectively. This could be a particular industry, a specific type of task, or a unique combination of data and AI. Building Defensibility: In a world where AI capabilities are becoming commoditized, what makes your business defensible? Is it your data, your user base, your brand, your integration into workflows, your domain expertise, or a combination of these? Your AI Business Strategy must articulate this defensibility. Monetization Models: How will you charge? API access, subscription fees based on usage or features, value-added services? The pricing model should align with the value you provide, which should be tied to the problem you solve, not just the cost of the underlying model calls. Building a robust AI Business Strategy involves constantly evaluating where you create unique value in the AI stack. Navigating the Nuances of Generative AI Development Much of the recent excitement revolves around Generative AI Development – models that create text, images, code, and more. Building reliable products using these models presents specific challenges. Controlling Outputs: Generative models can be unpredictable. Strategies discussed included sophisticated prompt engineering, using guardrails, implementing validation steps, and potentially fine-tuning models on specific datasets to steer their behavior. Dealing with Hallucinations and Bias: Generative models can produce incorrect or biased information. A key part of Generative AI Development is building systems to detect and mitigate these issues, ensuring the output your users receive is accurate and fair. Evaluation: How do you objectively measure the quality and relevance of generated content? Developing robust evaluation frameworks, both automated and human-in-the-loop, is crucial. Integration of Multiple Models: Sometimes the best solution involves chaining together different models or combining generative models with other AI techniques (like search or classification). Orchestrating these complex pipelines is a significant part of modern Generative AI Development . The experts underscored that successful Generative AI Development is less about magic and more about careful engineering and rigorous evaluation. The Critical Role of AI Infrastructure Choices The choices made regarding underlying AI Infrastructure have a profound impact on a startup’s scalability, cost, and flexibility. Should you rely on one provider (like OpenAI, Anthropic, or Google)? Should you use open-source models? Should you try to abstract away the model layer? Abstraction Layers: Some companies are choosing to build abstraction layers that allow them to swap out underlying models more easily. This reduces dependency on a single provider but adds engineering complexity. Cost Management: Inference costs for large models can be substantial. Strategies involve optimizing prompts, caching results, using smaller models where appropriate, and carefully monitoring usage. Performance and Latency: For many applications, the speed of response from the AI model is critical. Choosing providers and models based on performance characteristics is a key AI Infrastructure decision. Data Security and Privacy: Where is your data processed? What are the data retention policies of the model providers? These are vital considerations, especially for businesses handling sensitive information. Navigating AI Infrastructure means balancing flexibility, cost, performance, and reliability to support your specific business needs. Key Takeaways for Builders From the discussions with experts from DeepMind, Twelve Labs, and Amazon, several actionable insights emerged: Don’t just build on the model; build significant value around it using data, workflow, and UX. Focus on a specific problem and niche where you can apply AI deeply. Develop a clear defensibility strategy that isn’t solely reliant on the underlying AI model. For generative AI, invest heavily in prompt engineering, validation, and evaluation. Carefully consider your AI Infrastructure choices regarding cost, flexibility, and reliability. Stay adaptable; the AI landscape will continue to evolve rapidly. Conclusion Building a sustainable business on top of rapidly evolving Foundation Models is undeniably challenging, but the insights shared by leaders from DeepMind, Twelve Labs, and Amazon provide a clear roadmap. Success lies not just in leveraging powerful AI capabilities, but in strategically building unique value through data, specialized applications, robust user experiences, and careful infrastructure choices. By focusing on solving real problems and creating defensible layers around the core AI, startups can navigate the inherent volatility of the AI landscape and build businesses that thrive. To learn more about the latest AI trends, explore our article on key developments shaping AI features. This post Mastering Foundation Models: Expert Strategies for Building Sustainable AI Businesses first appeared on BitcoinWorld and is written by Editorial Team
The post Eric Trump Backs $TRUMP Token While Price Faces Bearish Pressure—Is a Rebound Coming? appeared first on Coinpedia Fintech News As political and crypto narratives continue to intersect, the Trump family’s crypto ambitions are once again making headlines. Following a heated dispute over an unauthorized Official TRUMP wallet, Eric Trump has stepped in to clarify the Trump family’s official stance. Besides, the price of this popular token continues to struggle under bearish technical pressure. Now the question emerges whether the TRUMP price rises above $13 and initiates a fresh upswing or drops back to $8, triggering millions of liquidations. Eric Trump Confirms Long-Term TRUMP Holdings In a move that surprised some market watchers, Eric Trump officially confirmed that World Liberty Financial, a financial firm linked to President Trump’s family, has acquired a substantial holding of TRUMP tokens as part of its long-term treasury strategy. The announcement came shortly after the public confusion over the digital wallet. Breaking News: I am proud to announce the $TRUMP Meme Coin has aligned with @WorldLibertyFi . Although their meme wallet isn’t moving forward, they remain focused on building the most exciting MEME on earth – $Trump . Moreover, we're proud to announce that World Liberty Financial… — Eric Trump (@EricTrump) June 6, 2025 According to Eric Trump, this accumulation is a part of a broader strategic positioning in the crypto space and aims to establish WLFI as a serious player in the emerging crypto niche. Despite this, the price of the OFFICIAL TRUMP token continues to trade within a bearish structure. What’s Next for the TRUMP Price Rally? As mentioned before, the price remains under pressure despite the Trump family’s support in the broader market. Following the WLFI news, the token saw a modest bounce of around 6.4%, but the move retraced quickly. The market is currently showing lower highs & weakening momentum, with no confirmed breakout above key resistance, while technicals remain neutral to bearish. As seen in the above chart, the TRUMP price is stuck within a descending parallel channel and is working hard to validate a bullish reversal. Moreover, the RSI also displays a similar movement, signaling the rally could be gaining strength henceforth. On the other hand, the supertrend has turned bearish, which could push the prices below the support of the channel. Therefore, the upcoming weekend may have a huge impact on the upcoming price action.
Altcoin season is heating up—and this time, it’s not the usual suspects leading the charge. Forget staking rewards you don’t understand, and gas fees that burn through your gains. A new wave is crashing in, and it's being mined from the palm of your hand. Bitcoin Solaris (BTC-S) has just emerged as the only serious contender making mobile mining not just possible—but profitable. While others are scrambling to scale, BTC-S is already delivering scalability, decentralization, and daily earning potential… from your smartphone. Why This Altseason Feels Different We’ve seen alt seasons before. But this one? It’s not just about flipping coins—it's about finding real infrastructure. Bitcoin Solaris didn’t ride the last wave. It’s leading this one. And unlike those trying to catch up to Ethereum or mimic Solana, BTC-S is forging a new lane altogether. Its unique dual-layer architecture gives it the speed of a high-frequency chain while maintaining the raw security of Proof-of-Work. The base layer uses SHA-256 and is fully compatible with traditional mining setups. The Solaris Layer? That’s where things fly—10,000 TPS, 2-second finality, and a validator rotation mechanism that ensures decentralization is always at the core. Mobile Mining Redefined: Welcome to Solaris Nova The most disruptive piece of this ecosystem is the upcoming Solaris Nova App. This isn’t just another wallet with a few gamified features. It’s a full-blown mining suite for mobile , browser, and desktop. Here’s what makes it groundbreaking: One-tap mining across devices, no expertise required Smart optimization to adapt to any hardware, whether smartphone or laptop Real-time analytics, tutorials, and an intuitive in-app wallet Remote wipe and biometric login for security-conscious users Energy-saving modes for efficiency on the go The app is set to redefine access. No rigs. No high entry points. Just pure earning. That’s why a growing number of influencers and crypto enthusiasts are taking notice, including a detailed review by Token Empire that breaks down what’s making BTC-S stand out during this cycle. The Presale Everyone’s Watching This isn’t a quiet rollout. Bitcoin Solaris’s presale has already raised over $3 million, with more than 11,000 participants locking in early positions. And there’s good reason—it’s one of the shortest, fastest-moving launches in the space right now. Current Price: $6 Next Phase: $7 Launch Price: $20 Bonus: 10% still available Launch Date: July 31, 2025 Projected ROI: Up to 1,900% With only about 8 weeks left, this window is shrinking fast. Unlike drawn-out sales that drag for months, this one is laser-focused, lean, and moving with serious momentum. More Than Hype: Deep Tech That Delivers At the technical level, BTC-S is built for serious performance: Dual-consensus system with PoW on the Base Layer and DPoS on the Solaris Layer Validator rotation every 24 hours ensures decentralization and fairness Dynamic block sizing on the Solaris Layer (up to 32MB) Optional Zero-Knowledge Proofs for privacy-enabled applications Rust-based smart contract support, optimized for speed and low gas This level of sophistication hasn’t gone unnoticed. One of the project’s standout strengths is its audit record—its smart contracts have been validated by Cyberscope , ensuring network robustness at launch. Security, Trust, and a Growing Community Bitcoin Solaris isn’t just building fast—it’s building right. The project’s team is KYC-compliant , making it one of the few rising projects that actually put transparency and credibility front and center. As the community grows, the conversation is spreading quickly across channels. The official Telegram is packed with early adopters, AMAs, and presale updates. For regular insights, their X page is equally active, offering sneak peeks into upcoming releases. Beyond Launch: The Roadmap Is Already in Motion BTC-S isn’t just selling a dream—it’s already building the infrastructure. According to its post-launch roadmap, the team is preparing for a full mainnet launch, global listing strategy, and the rollout of its Mining Power Marketplace—a decentralized platform where users can buy and sell computational power with smart contracts and performance-based payouts. Advanced scaling features, dApp development accelerators, and institutional partnerships are also on the horizon—all strategically designed to deliver long-term adoption, not short-term hype. Conclusion: Altseason Is Here—But One Coin Actually Lets You Earn It Altcoins will come and go. But Bitcoin Solaris is building something that sticks—a network where anyone, anywhere, can earn from their phone, with no barriers. Whether you're a first-timer or a pro, this isn’t just another altcoin—it’s the infrastructure layer for the next wave of wealth generation. The mobile mining revolution has a name now, and it’s Bitcoin Solaris. For more information on Bitcoin Solaris: Website: https://www.bitcoinsolaris.com/ Telegram: https://t.me/Bitcoinsolaris X: https://x.com/BitcoinSolaris Disclaimer: This is a sponsored article and is for informational purposes only. It does not reflect the views of Crypto Daily, nor is it intended to be used as legal, tax, investment, or financial advice.
Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial. When Satoshi wrote that “participants can be anonymous,” he also built in the assumption that the rules are enforced by software, not by people. Most of today’s decentralized exchanges keep that promise: once a trade hits the mempool, no custodian can halt or reverse it. Yet, the certainty that a smart contract will execute does not translate into certainty that the overall game is fair. The $ 110 million Mango Markets exploit in October 2022 was executed exactly as the contract allowed; nevertheless, a U.S. jury still found it to be fraudulent this April, underscoring the gap between legal code and moral code. You might also like: Rethinking money in the web3 era: From capital to code, narrative, and moral design | Opinion That gap is widening. In the first quarter of 2022, 97 percent of all stolen crypto came from DeFi protocols, a leap from 30 percent just two years earlier. Even after a 54 percent drop in headline losses last year, users still saw almost $2 billion disappear to hacks, scams, and exploits. We have eliminated trusted intermediaries, but not the need for trust itself. Anonymity’s hidden tax Because wallets are free, the reputation in DeFi is cheap. The Sybil problem is no longer academic; entire Telegram channels teach “airdrop farmers” how to spin up hundreds of addresses and recycle the lucky winners. A trader who wipes out today can be back tomorrow under a fresh ENS name, ready to court copy-trading deposits. Survivorship bias then does the rest. Traditional asset-management studies show that excluding dead funds inflates reported performance by double-digit percentages; in DeFi, the distortion compounds at machine speed because failure leaves no paperwork trail, just a silent wallet. When a leaderboard advertises “200 percent APY,” investors rarely see the denominator: the strategies that imploded on day two and were quietly abandoned. Attempts to patch this with social graphs or soul-bound tokens help, but without meaningful economic penalties, they simply create new points of friction. The open nature of blockchains means any identity scheme must assume an adversary with infinite wallets and infinite tries. In practice, that makes wallet-level reputation brittle and signals noisily. Code is law, but data is the loophole Even perfectly audited contracts can be gamed once economic context enters the picture. The first flash-loan attack on bZx in 2020 showed how a zero-collateral loan could distort an oracle for a single block and siphon six-figure profits. Four years on, oracle manipulation remains a favorite vector, with $403 million lost in forty-one such attacks during 2022 alone. More subtle forms of manipulation thrive on thin liquidity. Researchers still pick up spoofing and wash-trading patterns on modern perpetual-swap venues, despite automated surveillance. Because these tactics live around the contract rather than inside it, formal verification can’t catch them. The protocol behaves exactly as specified; the price feed, however, has been poisoned. Designing for credibility, not merely decentralization So, what would a trustworthy trading protocol look like? First, it would expose all the data, not just the success stories. Every strategy (profitable, flat, or wrecked) should leave an immutable on-chain scorecard. Second, reputation should cost money. Staking a percentage of notional volume or placing a refundable performance bond forces would-be gurus to internalize downside risk. Finally, identity can remain pseudonymous while still being provable. Zero-knowledge reputation proofs allow a trader to show “I have three years of verifiably positive PnL” without revealing a name, location, or passport number. These guardrails carry overhead, just as SOC-2 audits do in SaaS or capital ratios do in banking. But they convert “trust me” into “verify me.” Unlike marketing claims, cryptographic attestations cannot be photoshopped. My own team has baked these principles into the tooling we ship: immutable performance trails that include the blow-ups, mandatory skin-in-the-game deposits that price reputation, and public proofs of methodology. We regard that friction not as a drawback but as table stakes for capital that comes with fiduciary duty. The pensions and treasuries that will ultimately decide DeFi’s scale cannot defer diligence to a Discord handle with a frog avatar. Toward evidence-based transparency Critics argue that these layers re-introduce a form of centralization. Fair enough. But the real question is not decentralization versus control; it is opacity versus evidence. When a protocol advertises itself as “trustless,” the burden is on its architects to show that trust is nevertheless deserved. Failing that, we should expect more headline exploits and more juries asked to decide whether “code is law” absolves economic manipulation. I remain optimistic. Public ledgers make forensic auditing easier than in any legacy market; the tools are there, and the incentives to use them are growing. What we need is a cultural shift from “built on Ethereum, therefore safe” to “built for adversarial scrutiny, therefore credible.” Until then, the most innovative technology in the world will keep struggling to win the oldest asset in finance: belief. Read more: Redefining trust and ownership in the creator economy | Opinion Author: Nick Gates Nick Gates is the co-founder of Rank. Technical founder with a background in growth and product. Built an agency that shipped over 50 client websites and MVPs. Scaled over $10 million in Meta ad spend for clients.
The digital asset space is preparing for what many believe will be a landmark moment in global finance. July 14 is the date the Federal Reserve System is scheduled to transition from the current Fedwire Application Interface Manual (FAIM) to the ISO 20022 standard. Armando Pantoja, a well-respected figure in the cryptocurrency space, believes this move is good for XRP. He has pointed to what he thinks is a critical alignment between XRP and the incoming standards, suggesting the token is “built to thrive in this new era of finance.” Pantoja emphasized the ISO 20022 compliance of Ripple’s technology and noted that XRP is already being used in countries such as Japan , Brazil, the United States, and the UAE for cross-border settlements. Despite this, he notes that the asset remains undervalued, currently trading around $2. He predicts a significant price increase once ISO 20022 goes live, forecasting a potential range of $8 to $12 by the end of the year. $XRPs moment is near… July 14, thousands of banks transition to the ISO 20022. – XRP is already ISO 20022 compliant.⁰- Banks around the world are using XRP⁰- Institutions are filing $300M deals.⁰ But the price? Still quiet. #XRP is being 100% being suppressed…but that's… pic.twitter.com/rFUrOBOHAL — Armando Pantoja (@_TallGuyTycoon) June 6, 2025 Strategic Moves and Institutional Interest Further bolstering his position, Pantoja referenced a recent filing by Webus, a NASDAQ-listed FinTech company, which submitted an SEC Form C indicating its intention to purchase $300 million worth of XRP for a strategic reserve. He points to the market response, noting that Webus’ stock exploded more than 400%, while XRP’s price remained largely unaffected. This led him to argue that XRP is being artificially suppressed. We are on twitter, follow us to connect with us :- @TimesTabloid1 — TimesTabloid (@TimesTabloid1) July 15, 2023 This opinion about price suppression is not new in the XRP community, as market manipulation tactics often impact the asset’s price. However, Pantoja believes that this suppression cannot impact XRP’s value. Instead, such delays create a buildup of interest and energy around the token. He describes the process as a spring, gradually building up energy before an explosion. Regulatory History and Institutional Integration The video features commentary from other voices in the crypto space who highlight XRP’s history before regulatory scrutiny. One speaker noted that Ripple’s XRP was once the second-largest cryptocurrency before the SEC lawsuit. He also explained that Bank of America was conducting all internal transactions using Ripple’s system and that Ripple holds over 80 patents, linking to its institutional integration and intellectual property development. Timing and Expectations Ahead of the Transition With less than a month remaining before this major shift toward ISO 20022, analysts and retail investors alike are closely monitoring XRP’s behavior. XRP is trading at $2.18, up 3.54% in the last 24 hours. While the $8 to $12 range is unprecedented, a dominant role in global finance through ISO 20022 integration could help the asset reach this target. Disclaimer : This content is meant to inform and should not be considered financial advice. The views expressed in this article may include the author’s personal opinions and do not represent Times Tabloid’s opinion. Readers are advised to conduct thorough research before making any investment decisions. Any action taken by the reader is strictly at their own risk. Times Tabloid is not responsible for any financial losses. Follow us on X , Facebook , Telegram , and Google News The post XRP Moment Is Near: July 14 Could Change Everything for XRP appeared first on Times Tabloid .
According to recent data from Coinglass, a significant threshold looms for Bitcoin as it approaches the $106,000 mark. Should Bitcoin surpass this level, the short liquidation pressure across major centralized
Singapore’s ousting of unlicensed firms was not a sudden move and it’s among several regions tightening licensing duties.
Singapore’s looming licensing mandate forces offshore-only crypto providers into urgent compliance mode, threatening to cut off unregulated access to tokenized finance and digital asset markets. June 30 Sparks Compliance Race for Offshore-Only Crypto Providers in Singapore The Monetary Authority of Singapore (MAS) issued clarifications on June 6 regarding the scope and application of its regulatory
BitcoinWorld AI Safety: Vital Discussion on Ethics and Deepfakes As artificial intelligence tools become more powerful, cheaper, and easier to access, their influence on our digital world grows significantly. For those navigating the fast-paced cryptocurrency and blockchain space, understanding the broader technological landscape, including the crucial domain of AI Safety , is essential. The rapid evolution of AI brings incredible opportunities, but also presents complex challenges that demand careful consideration. A recent critical discussion brought together key voices to explore these very issues. The Urgent Need for AI Safety The conversation, featuring ElevenLabs’ Head of AI Safety Artemis Seaford and Databricks co-founder Ion Stoica, alongside Bitcoin World AI editor Kyle Wiggers, highlighted a pressing reality: the stakes for ensuring AI is safe and beneficial have never been higher. The accessibility of sophisticated AI models means more people can deploy powerful tools, sometimes without a full understanding of the potential consequences. This democratization of AI technology necessitates a proactive approach to identifying and mitigating risks before they cause significant harm. The discussion centered on why prioritizing AI Safety is not just a technical challenge but a societal imperative. As AI systems are integrated into critical infrastructure, financial systems, and information channels, ensuring their reliability, robustness, and safety becomes paramount. Failures or malicious uses of AI could have widespread and damaging effects. Experts stressed that safety considerations must be woven into the fabric of AI development from the earliest stages, rather than being treated as an afterthought. Key areas of concern regarding AI Safety include: Unintended Consequences: AI systems behaving in ways not predicted by their creators. Security Vulnerabilities: AI models being susceptible to attacks that compromise their function or data. Systemic Risks: The potential for widespread disruption if interconnected AI systems fail or are compromised. Addressing these points requires collaboration across industry, academia, and policy-making bodies. The insights from leaders at companies like Databricks, which provides the infrastructure for scaling AI, and ElevenLabs, which works with advanced generative models, offer valuable perspectives on the practical challenges and potential solutions in achieving robust AI Safety standards. Navigating the Landscape of AI Ethics Beyond safety, the discussion delved deep into the complex terrain of AI Ethics . As AI systems make decisions that affect individuals and society, questions of fairness, transparency, and accountability come to the forefront. The ethical challenges are multifaceted, touching upon issues ranging from algorithmic bias to the impact of automation on employment and the nature of human interaction. Artemis Seaford and Ion Stoica shared their perspectives on the ethical considerations that companies developing and deploying AI must grapple with daily. They emphasized that building ethical AI is not a matter of simply following rules, but requires a fundamental commitment to considering the broader impact of the technology on people and communities. This involves anticipating potential harms and actively working to prevent them. Core ethical challenges discussed included: Ethical Challenge Description Example Context Algorithmic Bias AI systems reflecting or amplifying societal biases present in training data. Loan applications, hiring decisions, criminal justice. Lack of Transparency Difficulty understanding how an AI system arrived at a particular decision (‘black box’ problem). Credit scoring, medical diagnoses. Accountability Determining who is responsible when an AI system causes harm. Autonomous vehicle accidents, incorrect medical advice from AI. Privacy Concerns AI systems requiring vast amounts of data, raising issues about surveillance and data protection. Facial recognition, behavioral tracking for advertising. Addressing these AI Ethics issues requires a combination of technical solutions, such as developing methods for detecting and mitigating bias, and policy frameworks that establish guidelines and regulations. The conversation highlighted the need for ongoing dialogue between technologists, ethicists, policymakers, and the public to shape the future of AI in a way that aligns with human values. Confronting the Threat of Deepfakes One of the most tangible and immediate ethical challenges discussed was the proliferation of Deepfakes . These AI-generated synthetic media, particularly realistic audio and video, have the potential for significant misuse, from creating fraudulent content for scams and misinformation campaigns to damaging reputations and interfering with democratic processes. ElevenLabs, working at the cutting edge of generative voice AI, is acutely aware of the risks associated with this technology. Artemis Seaford provided insights into the measures being taken to combat the malicious use of Deepfakes created with their technology. This includes implementing safeguards to prevent the cloning of voices without consent, developing watermarking techniques to identify AI-generated content, and building detection tools to help identify synthetic media. The rise of Deepfakes is particularly concerning in the context of information integrity. The ability to create highly convincing fake audio and video makes it harder for individuals to discern truth from falsehood, potentially eroding trust in media and institutions. In the financial world, Deepfakes could be used in sophisticated phishing attacks or market manipulation schemes. The experts emphasized that combating Deepfakes requires a multi-pronged approach: Technical Solutions: Developing better detection and attribution tools. Platform Responsibility: Social media and content platforms implementing policies and tools to flag or remove malicious Deepfakes . Media Literacy: Educating the public on how to identify synthetic media and be critical of online content. Legal Frameworks: Establishing laws and regulations to address the creation and distribution of harmful Deepfakes . The discussion underscored that while the technology behind Deepfakes continues to advance, so too must the efforts to counter their harmful potential. Collaboration between AI developers, cybersecurity experts, and policymakers is vital in this ongoing battle. Implementing Responsible AI Deployment Given the challenges of safety and ethics, a key focus of the conversation was on how to ensure Responsible AI deployment. This involves more than just building ethical AI systems; it encompasses the entire lifecycle of AI, from conception and development to deployment, monitoring, and eventual decommissioning. Companies and organizations deploying AI have a responsibility to consider the potential impacts of their systems and take steps to mitigate risks. Ion Stoica offered perspectives from Databricks’ position as a platform provider, emphasizing the importance of providing tools and frameworks that enable customers to deploy AI responsibly. This includes features for data governance, model monitoring, and ensuring transparency in AI workflows. Enabling Responsible AI deployment means empowering users to understand their models, track their performance, and identify potential issues like bias or drift over time. Key elements of Responsible AI deployment include: Impact Assessments: Evaluating the potential societal and ethical impacts before deploying an AI system. Stakeholder Engagement: Consulting with affected communities and individuals. Monitoring and Evaluation: Continuously monitoring AI system performance for bias, drift, and unintended consequences. Explainability: Making AI decisions understandable to humans where necessary. Human Oversight: Maintaining appropriate levels of human control and intervention, especially in high-stakes applications. Robust Security: Protecting AI systems from adversarial attacks. The experts agreed that fostering a culture of Responsible AI within organizations is crucial. This involves training developers and product managers on ethical considerations, establishing internal review boards, and creating clear processes for addressing ethical concerns throughout the development pipeline. Responsible AI is not a one-time task but an ongoing commitment. Shaping the Future of AI Development Ultimately, the discussion circled back to how safety and ethics considerations are fundamentally reshaping the landscape of AI Development . The days of simply pursuing performance metrics without regard for broader impacts are fading. There is a growing recognition that sustainable and beneficial AI Development must prioritize safety, fairness, and transparency. The conversation highlighted the need for greater collaboration and knowledge sharing across the AI community. Companies, researchers, and policymakers must work together to establish best practices, develop common standards, and address the complex challenges that no single entity can solve alone. Open dialogue, like the one facilitated by Bitcoin World AI, is essential for fostering a shared understanding of the risks and opportunities. Trends shaping the future of AI Development with a focus on safety and ethics include: Regulation and Governance: Governments worldwide are developing frameworks to regulate AI, influencing how systems are built and deployed. Ethical AI Tools and Frameworks: Development of software and methodologies specifically designed to help identify and mitigate bias, improve transparency, and ensure robustness. Interdisciplinary Research: Increased collaboration between computer scientists, social scientists, ethicists, and legal scholars. Focus on Explainable AI (XAI): Research into making complex AI models more understandable to humans. Safety-Focused Benchmarks: Development of evaluation metrics that go beyond performance to include safety and fairness criteria. The path forward for AI Development involves balancing innovation with caution. It requires investing in research not only to make AI more capable but also to make it safer and more aligned with human values. The insights from leaders at companies building the future of AI infrastructure and applications provide a glimpse into how these crucial considerations are being integrated into the core of technology development. Actionable Insights and the Path Ahead The discussion provided several actionable insights for anyone involved with or impacted by AI: For Developers and Companies: Integrate safety and ethics from the design phase. Invest in tools and expertise for bias detection, transparency, and security. Establish clear processes for responsible deployment and monitoring. For Policymakers: Develop agile and informed regulations that encourage responsible innovation while mitigating risks. Foster international cooperation on AI governance. For Users and the Public: Develop critical media literacy skills, especially regarding synthetic content like deepfakes. Demand transparency and accountability from AI providers. Participate in discussions about how AI should be shaped. The challenges are significant, but the commitment from leaders in the field to address them is a positive sign. The conversation between Databricks, ElevenLabs, and Bitcoin World AI underscores the importance of ongoing dialogue and collaborative action to navigate the complex future of artificial intelligence safely and ethically. Conclusion The deep dive into AI Safety and AI Ethics with experts from Databricks and ElevenLabs illuminated the critical challenges facing the rapid advancement of artificial intelligence. From the pervasive threat of Deepfakes to the fundamental need for Responsible AI deployment, the discussion made it clear that the technical progress in AI Development must be matched by a corresponding commitment to societal well-being. Ensuring AI is safe, fair, and transparent is not just a technical problem to be solved, but a continuous effort requiring the collective intelligence and collaboration of developers, companies, policymakers, and the public. As AI continues to integrate into every facet of life, including areas relevant to the cryptocurrency space, understanding and actively engaging with these ethical and safety considerations will be paramount for building a future where AI benefits everyone. To learn more about the latest AI news trends, explore our article on key developments shaping AI features. This post AI Safety: Vital Discussion on Ethics and Deepfakes first appeared on BitcoinWorld and is written by Editorial Team
In the constantly evolving crypto market, it is important to stay ahead of the market by identifying unique market opportunities. One of the best projects right now is Mutuum Finance (MUTM) , which is on the cusp of changing Defi forever. Let us take a deep dive into this transformative project. Technological innovation Powers Mutuum Finance (MUTM) Mutuum Finance (MUTM) aims to transform the Defi industry with technical innovation. It does not simply aim to be another project in the Defi space; it aims to be the go-to project for all Defi investors seeking out long-term growth. This innovation can be seen in the design of its lending protocol. Lenders on the protocol can deposit their funds in a pool governed by an audited smart contract. Once in the pool, funds begin to accumulate interest at a rate defined by the pool’s utilization rate. The utilization rate is a measure of the amount of borrowed assets against the total assets in the pool. When most of the pool’s assets are in use, the interest rate rises. This encourages borrowers to repay their loans, while also incentivizing lenders to deposit more funds into the pools to earn higher yields. In the reverse, when the pool’s utilization rate drops, borrowers are incentivized to take more loans at the low rates, while the number of lenders goes down. That causes the rate to rise again, creating a self-sustaining cycle. The result is that the pool achieves optimal capital efficiency without external interference. Protocol Safeguards On Mutuum Finance The Mutuum Finance project is based on a philosophy of finding a balance between encouraging mass adoption and protecting the protocol’s solvency in the long term. To achieve this, it carefully examines assets that can be used on the protocol. Overcollateralization One of the most basic safeguards used on Mutuum Finance is overcollateralization. It simply means that when borrowers take a loan, they must provide collateral that is of a higher value than the loan. This ensures that there is sufficient headroom in case of market volatility. If a position sinks below an established threshold, then it becomes eligible for liquidation. The liquidators are offered a chance to buy the debt at a discount, which ensures there is a buffer between assets and liabilities on the platform. Deposit And Borrow Caps These caps are used to establish an upper limit on how much of an asset can be borrowed or deposited. It helps to limit the exposure of the protocol to some assets, which may have low liquidity or high volatility. Additionally, it mitigates against exploits related to unlimited asset minting. To determine caps, factors like on-chain volume, price stability, and historical price data are used. The borrow caps are used to reduce the chances of insolvency due to manipulated price fluctuations. Restricted Collateralization Mutuum Finance may categorize certain tokens under the Restricted Collateralization Mode. This mode sees a single collateral asset used only for borrowing the same asset, with strict limitations. For instance, if the oracle data is unreliable, restricting usage ensures there is no system-wide impact due to rapid price changes. Enhanced Collateral Efficiency For assets that are known to have correlated price movements, such as popular stablecoins, Mutuum Finance can use the Enhanced Collateral Efficiency (ECE) mode. In this mode, users have elevated borrowing limits when the collateral and loan assets are in the same group. The main benefits are improved capital efficiency while ensuring there is no system-wide impact. Only tokens that demonstrate consistent pegs and near-identical behavior qualify for ECE. Loan-to-Value (LTV) Ratio The LTV ratio limits how much a user may borrow in relation to the value of their assets. For instance, an 80% LTV means that a user who pledges 1 ADA worth of collateral can only borrow up to 0.80 ADA worth of another asset. The LTV of an open position is dynamically set by the changing value of an asset over time. Liquidation Threshold A liquidation threshold is triggered when the debt becomes undercollateralized. For instance, if the threshold is set at 80% of the value of the collateral, and it drops below it, a liquidation is triggered. When that happens, liquidators can acquire the collateral at a discount, which protects the long-term stability of the ecosystem. Liquidation Penalty When a position is liquidated, a liquidation penalty applies, which is equivalent to the liquidation bonus the liquidator receives. A portion of this amount may go to the protocol treasury, where it is used as part of the risk module. An allocation factor is used to determine how much of the penalty goes to the liquidator and the treasury. It helps to balance incentives for liquidations with the long-term solvency of the ecosystem. The Reserve Factor A reserve factor collects some of the interest from the borrower. An aggregate is used to collect assets and is used to offset any potential default during extreme market movements. Tokens with higher stability feature a small reserve factor and vice versa. Success Of The Mutuum Finance (MUTM) Presale The unique technical innovations mentioned above have resonated with crypto investors and led to a surge in interest in the presale. So far, the presale has received over $10.1 million from investors. Over 11,700 investors have taken part in the presale, which is currently in phase. The pace of the phase 5 presale has been quite fast, with over 1% of the tokens set aside already sold. In the upcoming phase 6, the token price will go up by 16.67%, reducing the guaranteed ROI to 71.43% from the current 100%. As such, this phase presents your best opportunity to be part of a revolutionary crypto project that will transform Defi forever. For more information about Mutuum Finance (MUTM), visit the links below: Website: https://www.mutuum.com/ Linktree: https://linktr.ee/mutuumfinance