Google's Pichai on the Fate of Search in a World of AI
In a world of AI and personalized answers, will chatbots take over search? Here's what Google CEO Sundar Pichai had to say at the Bloomberg Tech Summit in San Francisco. (Source: Bloomberg)
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31 minutes ago
- Yahoo
If Elon Musk's Wealth Was Evenly Distributed Across America, How Much Money Would Every Person Get?
We've seen the headlines that reveal how rich the world's top billionaires are — but it's hard to comprehend just how rich they are. Consider this: Let's say you had $1 billion in your bank account and had to spend $100,000 every day, for an entire year. After 365 days, you would still have $963,500,000 (nine hundred sixty-three million five hundred thousand). Discover More: Find Out: Over the last two decades, billionaires have ballooned their wealth to unparalleled levels. In 2005, Microsoft co-founder Bill Gates ranked as the world's richest person, with a net worth of $46.5 billion, as reported by CNN. Today, that title belongs to Tesla CEO Elon Musk, whose net worth stands at $368 billion as of June 5, according to the Bloomberg Billionaires Index. Even when adjusted for inflation, Gates' former net worth would be equivalent to roughly $76 billion in today's dollars. It is worth noting that other billionaires have also increased their wealth during the same time. For instance, tech billionaires Mark Zuckerberg and Jeff Bezos are worth $229 billion and $227 billion, ranking second and third globally. For many Americans, this trend is not sitting well. The sky-high cost of living has catalyzed support for redistributive tax policies, especially among younger voters and the progressive base of the Democratic Party. While higher taxation may or may not happen in the years to come, here's hypothetically how much you'd get if the world's richest man gives a check to every American. The United States Census Bureau estimates the current population to be around 341 million people, ranking only behind India and China. If Musk's enormous $390 billion were equally divided in the U.S., each person would receive $1,144 (rounded to the nearest dollar). A couple would receive $2,288, while a family of four would get $4,576. Despite the enormous wealth of billionaires, much of their fortune is tied up in stocks, real estate, and other holdings. Only a small percentage of their assets is held in cash. Based on data from Forbes, Musk has a 12% ownership stake in Tesla and to date, he remains the largest shareholder in the $1.15 trillion electric vehicle company. This is in addition to a 42% slice in SpaceX and a 54% interest in xAI, among many other businesses. Interestingly, Bloomberg reported that Musk's financial holdings appreciated by 77% after joining the campaign trail with President Donald Trump late last year, as reported by Bloomberg. Investors became bullish on Tesla and Musk became the first person to ever reach a net worth exceeding $400 billion. Since then, Tesla's market value has fluctuated as a result of volatile market conditions, macroeconomic factors and the threat of a global trade war. More From GOBankingRates 4 Housing Markets That Have Plummeted in Value Over the Past 5 Years This article originally appeared on If Elon Musk's Wealth Was Evenly Distributed Across America, How Much Money Would Every Person Get? Sign in to access your portfolio
Forbes
35 minutes ago
- Forbes
What Could Future Banking Look Like If AI Takes Over?
Alex Kreger, UX Strategist & Founder of the financial UX design agency UXDA, designs leading banking and fintech products in 39 countries. getty The imminent integration of AI into daily routines promises to dramatically reshape our lives over the next five years, propelled by advancements akin to ChatGPT, Gemini, Grok, etc. This shift is driven by the recognition that human capacities, while remarkable, cannot match the vast research and creative and analytical potential of artificial intelligence (AI). As we project into the future, it becomes clear that AI will also redefine digital banking experiences and grant individuals with financial capabilities that were once unimaginable. As a design strategist developing financial services for leading banks and fintech providers in 39 countries, I'm curious to envision how AI will overhaul the typical banking experience for everyday consumers. Although the complete adoption of AI across the financial sector has yet to unfold, it is crucial to anticipate its eventual impact. The question is no longer 'What if?' but rather 'How?'—and how best to brace ourselves for the changes that lie ahead. Banks already maintain enormous stores of customer data, but unlocking its true power demands cutting-edge technology. AI may well be the solution that helps institutions tackle customer demands with speed and accuracy. By channeling this data effectively, banks can provide individualized products at precisely the right time—an endeavor impossible for standard processes alone. The current data stockpile is merely a starting point. As digital tools evolve, financial institutions will gather much more data from smartphones, social networks, public service APIs, open banking APIs and IoT devices through 5G. This explosion of information calls for a robust, near-superhuman capacity to sift through the noise and pinpoint what truly matters—something AI might deliver within the next decade. In the coming years, the most significant AI-driven breakthroughs are likely to include: • Personalized Offers: Data-rich approach makes customized proposals more precise and simultaneously mitigates risks by matching the ideal product to the ideal customer. • Investment: By eliminating human biases, AI could evaluate a multitude of market and business variables to foresee investment success. • Security: AI could expedite verification by reducing the constant need for identity confirmations. • Financial Advisory: With the aid of big data and personal profiling, AI could illuminate each client's needs, generating in-depth forecasts and healthier financial practices. • Support: AI-powered bots could offer prompt, tailored solutions, greatly enhancing customer service. • Alternative Processing: AI-powered voice, gestures, neurotechnology, VR and AR interfaces will enable banking transactions beyond conventional channels. With Statista expecting generative-AI spend in banking to rocket to $85 billion by 2030, it's time for leaders to start by putting AI into their strategic plan—not just the tech roadmap. Hire a senior executive (Chief AI) who owns value creation and AI risks and spin up a cross-functional 'AI initiatives' that groups stakeholders, data scientists and product designers that move to an API-first, event-streaming service architecture so models can surface predictions (e.g., 'potential cash shortfall Friday') in real time. Early adopters are showing where the value sits, and leaders should take note. J.P. Morgan's Quest IndexGPT can generate investable indices; Morgan Stanley's Debrief can summarize adviser meetings; NatWest's Cora+ can handle nuanced customer queries. At the same time, Wall Street majors—from Goldman to Citi—are scaling internal LLM-powered co-pilots for drafting IPO documents, surfacing research or searching policies. Customer-facing assistants are already setting the bar. Bank of America's Erica has served 20 million active users, Wells Fargo's Fargo went from 21 million interactions in 2023 to 245 million in 2024 by using a privacy-first pipeline that strips PII before any LLM call. On the insight side, RBC's NOMI Forecast crunches account data to predict the next seven days' cash flow; more than 900,000 clients have generated 10 million interactions since its late-2021 launch. Generative models excel at turning trillions of events into the next best micro-experience. Commonwealth Bank of Australia's Customer Engagement Engine, for example, ingests 3.1 trillion data points and runs 2,000 real-time models, lifting loyalty with recommendations so much that mobile users now log in 67 times a month on average. The key is to couple a real-time feature store with small language models that handle intent, then let a larger model draft the personalized nudge or insight. Start with one or two journeys where better prediction or conversation will be felt within weeks—fraud alerts or an SME cash-flow coach. Ship, measure, retrain and fold the learning into a reusable component library so subsequent squads stand on the shoulders of the first. The biggest headwind is regulation: Europe's AI Act is already in force and will classify credit-scoring, KYC, trading and robo-advice models as 'high risk' by August 2026. Finding talent and culture is also an ongoing challenge. Banks are hiring aggressively, yet even Deutsche Bank admits the scarcity of seasoned AI professionals and the difficulty of embedding them in legacy teams. Third, security and trust: four in five bank leaders say they fear AI-enabled cyberattacks, and front-office chatbots can still hallucinate or breach privacy if left unsupervised. Mitigate by adopting zero-trust data-access patterns, embedding red-teaming into MLOps, and running 'constitutional' or retrieval-augmented QA layers that force a model to cite source documents. Initially, AI's role is to automate foundational tasks. Over time, however, I expect that it will evolve to deliver comprehensive solutions across all industries, including finance. After two decades of digital self-service in finance, AI can restore the conversation—context-aware, always on, and scaled to every customer. AI's full potential is truly immeasurable, and its effects on banking customer experience—and countless other sectors—will be transformative. By merging technological advancements with thoughtful user experience design, forward-looking companies can build a future where AI not only empowers individuals but also redefines entire industries. The era of AI-driven finance is fast approaching, and now is the time to prepare for its far-reaching influence. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Forbes
35 minutes ago
- Forbes
Learning By Sharing: How GenAI Can Be The Giving Tree
Nitin Rakesh is the CEO and Managing Director of Mphasis and coauthor of the award-winning book 'Transformation in Times of Crisis.' Our world is witnessing a wave of advancements, from the emergence of automation to the implementation of artificial intelligence. For senior leaders, this acceleration presents opportunities and challenges. While striving to adopt cutting-edge technologies, they are also attempting to ensure these align with business objectives and ethical standards. One of the most transformative yet polarizing of these technologies is generative AI (GenAI). While it promises new avenues for creativity, problem-solving and efficiency, it also raises apprehensions about its impact on typical decision making processes. In this sense, GenAI remains a bit of a paradox for business leaders, as it is both a source of curiosity and a cause for concern. While executives see its immense potential as a transformative tool capable of boosting creativity, streamlining operations and generating efficiency gains across functions, there is an underlying wariness about how it can disrupt established workflows. In the face of GenAI's dual nature, executives are navigating a critical challenge of how to integrate this powerful technology without losing the distinctiveness of human intuition. Rather than framing GenAI as a disruptive force to be managed, a more productive perspective may be to see it as a collaborator—an enabler of shared growth and continuous learning. When viewed this way, I believe GenAI can become more of a partner in learning and development with whom leaders can foster a mutually beneficial relationship mirroring the spirit of mutual giving. However, embracing this potential demands a shift in mindset. It invites leaders to move beyond passive adoption and toward active stewardship of the human-AI dynamic. This reframing introduces important questions: Are leaders thoughtfully measuring GenAI's contributions, not just in efficiency but in depth and relevance? Are they engaging with it in ways that reflect their own values and expertise—training it, shaping it and learning from it in return? And perhaps most importantly, is their ongoing interaction with GenAI expanding their capacity for insight and growth? AI is not an autonomous force—it is a reflection of the data, intentions and perspectives we bring to it. Its development is inseparable from human input. The real opportunity lies not just in what AI can do for us, but in how the human-AI relationship can evolve into one of reciprocal enrichment. Consider an iconic children's literature classic: The Giving Tree by Shel Silverstein. In the story, the tree selflessly offers its apples, branches and eventually its entire trunk to the boy. This tale invites us to reflect on the nature of giving, taking and the balance of relationships. In much the same way, GenAI can be seen as a tireless provider—offering its computational power, adaptability and insights to organizations. Yet unlike the tree, GenAI does not give from a place of emotion or altruism. It responds to the quality of its inputs, the clarity of its training and the intentionality of its use. This analogy prompts a critical shift in how leaders approach AI. While it's tempting to focus solely on what GenAI can do for us—automating tasks, generating insights, fueling innovation—the more profound question is: What are we giving back? How are we shaping, stewarding and engaging with AI to ensure it grows in a direction aligned with human values and long-term impact? If organizations treat AI merely as an extractive tool, they risk building unsustainable dependencies. But if leaders approach the technology as a partner in co-evolution—offering guidance, expertise and ethical oversight—then GenAI becomes more than a resource. It becomes a trusted collaborator, capable of growing alongside the organization. Beyond GenAI's adoption, leaders must know its value, inspiring their teams to integrate AI into daily workflows. Evangelizing AI within the executive team is crucial to ensuring collective alignment, fostering a culture where AI is viewed as an augmentation of human expertise rather than a replacement. This requires a deep understanding of what GenAI can do, allowing leaders to define where it can have the most meaningful impact. For GenAI to truly benefit organizations, leaders must anchor its application in clear, measurable business objectives. Identifying the right problems for GenAI to solve and aligning its deployment with strategic goals ensures its use remains practical and value-driven. Governance is equally critical, ensuring that AI-driven decisions uphold ethical standards and comply with regulatory frameworks. Data quality, infrastructure readiness and an AI-savvy workforce further determine how effectively GenAI can be leveraged. The organizations that invest in these foundational aspects will be best positioned to turn AI into a long-term growth partner like the enduring relationship between the boy and the Giving Tree. When leaders take ownership and adopt an interactive approach, they create an environment of collaboration. Talented individuals are also drawn to such leaders—not just for their effectiveness but for their generosity and team-focused mindset. It is crucial that leaders actively coach GenAI so it evolves in tandem with organizational needs. By continuously refining and adapting its algorithms, leaders can make GenAI more iterative, refined, intelligent and thoughtful. Much like mentoring human employees, providing AI with feedback allows it to improve over time. For instance, organizations have enhanced customer service chatbots by training them on real user interactions, enabling them to respond with greater empathy and accuracy. These iterations ensure that AI evolves to handle more complex queries, improving both customer satisfaction and operational efficiency. With each successive interaction, AI becomes better suited to the evolving needs of an organization. This illustrates the timeless relevance of Moore's Law, which predicts that computing power will double every two years. Just as computing capacity expands exponentially, so too can GenAI's ability to solve complex problems as long as it is actively coached. As AI models become more advanced, the need for a growing network of skilled, human trainers becomes essential for their continued improvement. The constant feedback and refinement will fuel GenAI's exponential development—enhancing its capacity to transform businesses. The key to thriving in this new era of AI is learning how to strike the right balance with thoughtful strategy. As organizations continue to work closely with GenAI, partnerships will evolve, leading to exciting outcomes. What will be crucial to keep in mind is that this exchange between human and machine fosters sustainable progress built on collaboration and just practice. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
