The Psychology of Innovation How NVIDIA’s Partnership with Faraday Future Reveals Modern Entrepreneurial Risk-Taking – Startup Capital Mindset The Role of Psychology in NVIDIA’s 2023 Deal Structure

NVIDIA’s 2023 stock surge, a phenomenal 385% increase, showcases its commanding position in the AI arena. Fueling this success is a bold strategy of investing heavily in startups. This shift, from a mere $300 million in investments to over $15 billion, demonstrates how a carefully fostered entrepreneurial psychology can significantly boost innovation. NVIDIA’s approach, characterized by high-stakes partnerships, symbolizes a new era of calculated risk in business. This necessitates a careful balance of both emotional and rational thinking in the decision-making process. Through its venture arm, Nventures, NVIDIA is actively accelerating the growth of fledgling companies, while also highlighting the importance of a growth mindset. This mindset embraces adaptability and ongoing refinement over the pursuit of perfection. By blending psychological elements with strategic allocation of resources, NVIDIA is fundamentally changing the landscape of entrepreneurship. Its model emphasizes that innovation can flourish when carefully nurtured, a lesson that resonates across a range of industries.

Looking at NVIDIA’s aggressive venture capital strategy in 2023, it’s fascinating how psychological factors likely played a crucial role in their deal-making approach. Entrepreneurs, including those driving NVIDIA’s initiatives, often see risks as opportunities. This perspective is key in situations like negotiating with a startup like Faraday Future, where potential downsides can easily be reframed as potential gains.

We also see the impact of loss aversion. Companies like NVIDIA, while willing to take chances on growth, are likely motivated to avoid losses just as much as anyone else. This tendency likely shaped their deal terms, prioritizing safeguards against unfavorable outcomes, even while pushing the boundaries of growth.

The process of partnering with a startup like Faraday Future could have stirred up internal debate and cognitive dissonance within NVIDIA. Different departments and individuals likely had contrasting views on risk and reward, potentially influencing how the deal was structured and negotiated.

It’s also likely that the initial proposals from both sides served as anchors, influencing how the final agreement was reached. Similar to how initial prices set the stage for future negotiation, those early figures would have influenced expectations and the subsequent back-and-forth.

Moreover, NVIDIA’s actions may have been driven by a desire to mimic other tech giants’ success – a case of social proof. Seeing successful partnerships in the AI world could have reinforced their own willingness to take risks. We can’t rule out the role of overconfidence either. Entrepreneurs often possess a degree of self-assurance, and perhaps NVIDIA’s team believed their expertise and resources were sufficient to navigate the uncertainties of such a partnership.

Framing of information is another key element. The way NVIDIA presented the partnership to potential investors likely shaped their perceptions. Highlighting the potential upsides and subtly minimizing the downsides could have increased investor confidence and secured favorable terms.

It’s also worth considering the role of networking and relationships. NVIDIA’s established connections and professional networks might have enabled them to assess and mitigate risks in the partnership. Such networks offer an inherent buffer and comfort in uncertain environments.

The whole effort is likely supported by a growth mindset, prioritizing adaptability over perfection. This type of flexible thinking is common in entrepreneurial environments and helps navigate complex partnerships with firms like Faraday Future.

However, we need to remember the psychological bias towards immediate gains over long-term ones—the temporal discounting effect. NVIDIA likely needed to craft deal terms that accounted for this tendency, ensuring short-term incentives aligned with the longer-term strategic goals of the partnership. Ultimately, understanding these psychological nuances is crucial to understanding the forces driving NVIDIA’s aggressive and successful venture capital approach.

The Psychology of Innovation How NVIDIA’s Partnership with Faraday Future Reveals Modern Entrepreneurial Risk-Taking – Behavioral Economics Behind Modern Tech Partnerships From Intel to NVIDIA

The partnerships forged between tech giants like Intel and NVIDIA, and the innovative ventures they support, reveal a fascinating blend of economics and human psychology. Behavioral economics provides a framework for understanding how decisions are made within these partnerships, moving beyond simplistic economic models. The concept of bounded rationality highlights the limits of human cognition when evaluating complex technological ventures and the inherent biases that can influence risk assessment. For example, NVIDIA’s association with Faraday Future underscores how the pursuit of innovation often intertwines financial calculations with the psychological drive to turn perceived risks into opportunities.

These partnerships showcase a shift in entrepreneurial psychology where calculated risk-taking is paramount. Factors like loss aversion, a natural human tendency to avoid losses, and social proof, the tendency to follow the actions of others, often shape the decision-making process. It is not merely a matter of rational evaluation, but also a dynamic interplay of emotional and social influences. This recognition of the human element in economic decision-making provides a more nuanced perspective on how companies like NVIDIA navigate strategic alliances. Understanding these behavioral patterns becomes crucial in the evolving landscape of innovation, as it sheds light on the underlying motivations and potential pitfalls inherent in technology partnerships.

The study of how people make choices, often called behavioral economics, has become increasingly important in understanding how modern technology partnerships work, much like the partnerships of the past. For instance, the Bell Labs model, with its blending of physics, engineering, and economics, serves as a reminder of how diverse skills and perspectives can produce breakthrough innovations. The way information is presented, what economists call the framing effect, seems to play a big role in shaping how tech partnerships develop. Presenting potential gains in a favorable light can make other companies more likely to agree to the deal’s terms.

We see this play out in Silicon Valley, where a phenomenon called “herding behavior” has taken root. Entrepreneurs tend to copy successful strategies, as seen in the surge of investments into AI and related startups after NVIDIA’s incredible growth. It’s a case of “if it’s working for them, it’ll work for me,” and this herd mentality may contribute to over-excitement or lack of critical thinking in a given industry. Another interesting aspect is optimism bias, a type of mental shortcut that makes us underestimate risk. This could explain why companies like NVIDIA are willing to jump into collaborations with startups like Faraday Future, even though those ventures might not always prove to be successful or well-planned.

Looking back at history, we can see that a company’s appetite for risk depends a lot on the economic conditions at that time. For example, during periods of strong economic growth, the tech sector sees more investment. But we must be careful, as the tendency to over-invest can sometimes lead to situations resembling historical financial bubbles. We’ve also seen that a company’s self-image within the tech industry plays a role in determining how it builds partnerships. A firm that positions itself as a pioneer or innovator may be more inclined to work with startups that share that self-image, and those alliances may be driven more by values or a common goal than by strict cost/benefit analysis.

Power dynamics, or the difference in influence or status between companies, affect how negotiations play out. Larger companies like NVIDIA often use their influence to secure better terms with smaller firms who are seeking recognition or resources. Then there is loss aversion, a tendency to fear losing what one has more than the possibility of a greater gain. It makes sense that tech companies would be careful about partnering with new ventures, and their goal is often to ensure that existing assets and profits are protected. From a philosophical perspective, the precautionary principle teaches us that anyone suggesting an action that might harm someone else bears the responsibility to prove that it will not. This principle guides tech firms to be thorough and careful when they are considering forming partnerships, especially if they’re operating in a very unstable environment.

Finally, from an anthropological perspective, we can see that business relationships are very similar to social structures, and firms with deeply held beliefs and a strong shared culture are more likely to create partnerships that reflect their shared worldview. These partnerships can have a larger influence on collaborative success and innovative achievements. Ultimately, understanding how behavioral economics and related areas impact tech partnerships helps us gain a broader view of how these alliances emerge and what factors drive innovation and risk-taking.

The Psychology of Innovation How NVIDIA’s Partnership with Faraday Future Reveals Modern Entrepreneurial Risk-Taking – Risk Management Through Neural Networks How Silicon Valley Changed Deal Making

The way Silicon Valley handles risk is changing, with neural networks becoming a crucial part of the process. This shift is fundamentally altering how financial institutions and businesses manage uncertainty. By using AI, particularly a type of AI called convolutional neural networks, firms can analyze data in much more sophisticated ways than before. This not only improves their ability to predict future problems but also sheds light on the behavioral patterns that drive things like credit risk. We’re starting to see how psychology and behavior influence things like loan defaults and investment choices.

The recent failures of certain companies have highlighted a need for real-time risk assessment. This means that decision makers need systems that are constantly monitoring for potential problems. The new approach blends human understanding with data analysis in a way that wasn’t possible before. This new blend of psychology and technology fits into a larger entrepreneurial trend, one that sees calculated risk-taking and the ability to adapt as core parts of modern deals and business structures. The era of just relying on gut feelings and simple models is fading, replaced by an environment that prioritizes understanding how individuals and the market behave.

Neural networks, a cornerstone of contemporary risk management, draw inspiration from the intricate architecture of the human brain. This connection highlights how millennia of evolutionary refinement in human cognitive processes continue to inform cutting-edge technology. The way Silicon Valley approaches deal-making increasingly mirrors the collective decision-making strategies observed in primate societies, where social standing and the actions of others strongly influence individual choices. This anthropological perspective reveals the deep-seated human tendency to follow the crowd, a powerful force shaping investment trends in the tech sector.

Loss aversion, a fundamental concept in behavioral economics, underscores our psychological predisposition to view losses as significantly more impactful than comparable gains. This ingrained trait shapes Silicon Valley’s deal structures, pushing companies to prioritize risk mitigation over potential profit maximization in contract negotiations. The idea of bounded rationality suggests that decision-makers in high-pressure environments like Silicon Valley often face cognitive overload as they navigate complex information streams. This inherent limitation in our cognitive abilities has historically influenced the success or failure of business partnerships throughout economic history.

Historically, financial bubbles frequently expose the dangers of “herding” in investment patterns, illustrating how groupthink can lead to irrational exuberance. The tech sector faces this same issue as firms replicate seemingly successful ventures without fully considering the inherent risks. Entrepreneurial optimism bias often leads investors to underestimate the possibility of setbacks, propelling companies like NVIDIA into partnerships with inherently risky startups. This tendency can lead to inadequate due diligence, a pattern we’ve witnessed in previous economic cycles across world history.

The way information is framed significantly influences the terms of a deal, as strategic communication can drastically alter how risk is perceived. This pattern of persuasive communication mirrors historical negotiation tactics, suggesting it’s a deeply ingrained human behavioral pattern. Silicon Valley’s fast-paced and rapidly evolving innovation landscape bears resemblance to the philosophical concepts explored in chaos theory, where seemingly small decisions can have vast and unpredictable consequences. This inherent uncertainty makes risk assessment exceptionally challenging, even for the most sophisticated neural network models.

Research in cultural anthropology indicates that organizations with strong shared values and deeply ingrained corporate cultures are more likely to build successful partnerships. This finding parallels the historical observation that alliances rooted in mutual understanding and shared goals tend to thrive. This emphasizes that organizational culture can be as important as strategic planning when making investment decisions. The precautionary principle, originating in ethical philosophy, serves as a guiding framework for technology partnerships, promoting cautious innovation. Historically tied to public health and environmental policy, this principle now holds relevance in the realm of business, helping to manage the inherent uncertainty surrounding technological advancements.

The Psychology of Innovation How NVIDIA’s Partnership with Faraday Future Reveals Modern Entrepreneurial Risk-Taking – Innovation Cycles in Transportation Tech From Ford Model T to Faraday Future

The history of transportation technology reveals a series of innovative bursts that have fundamentally altered how we move. Starting with the Ford Model T and its groundbreaking assembly line, which made car ownership accessible to a wider population in the early 1900s, to the present day vision of companies like Faraday Future, we see a steady shift towards technology as the driving force. Today, we’re in the midst of another significant change in the auto industry, with innovations like advanced safety features and AI taking center stage. This is a fascinating blend of traditional engineering and software expertise, revealing both the adaptability of the auto sector and the powerful influence of factors like risk tolerance and strategic alliances, such as NVIDIA’s partnership with Faraday Future. Ultimately, this dynamic interplay shows how innovation isn’t just about better vehicles; it’s a catalyst for broader social and consumer shifts in the world of transportation.

The Ford Model T, introduced in 1908, wasn’t just a car; it was a catalyst for change, revolutionizing not only the automotive industry but also manufacturing itself through the widespread adoption of the assembly line. This innovative approach dramatically sped up production, shrinking the time it took to build a car from over 12 hours to a mere 90 minutes.

Interestingly, alongside innovation, the Model T also gave rise to a new concept: “affordable luxury.” While designed for the masses, the Model T’s accessibility sparked a desire for personalized, high-end vehicles, influencing consumer trends and laying the groundwork for the luxury car market we see today. This highlights how the initial goal of affordability can sometimes evolve into more complex consumer desires.

Public perception of transportation technologies is heavily shaped by the prevailing cultural narratives of the time. For example, the rise of car ownership in post-war America was fueled by the ideals of freedom and individualism. These concepts, deeply ingrained in American identity, are still a core part of how automakers market their vehicles, even in our current era of ride-sharing and shared mobility. It’s a reminder that marketing and consumer behavior are deeply intertwined with social and cultural values.

The 1970s oil crises served as a stark reminder that economic pressures can significantly impact innovation cycles. Consumers began shifting towards compact, fuel-efficient cars, demonstrating how economic factors can drive changes in transportation preferences. This trend spurred the development of more energy-efficient technologies in subsequent decades, showcasing how innovation can be triggered by societal needs.

Faraday Future, founded in 2014, is a modern example of a venture leveraging lessons from the past. Unlike the Model T’s focus on mass production of a single model, Faraday emphasizes the creation of bespoke electric vehicles, reflecting a shift in consumer preferences towards customization and individuality. This signifies that while basic transportation needs remain constant, what consumers value in a vehicle can evolve significantly over time.

Early automobile successes, in retrospect, led to a kind of collective optimism—a belief in the inherent safety and reliability of this new technology. This overshadowed some of the challenges that came with it, much like the current wave of tech startups often face with regulatory hurdles. This pattern suggests that sometimes early successes can lead to a degree of hubris, overlooking potential obstacles.

The history of transportation technology reveals a recurring pattern: innovations like internal combustion engines or electric vehicles are often met with public skepticism initially. This suggests that promoting new technologies requires effective marketing and education to change consumer behavior and foster acceptance. It also highlights the difficulty in overcoming ingrained habits and fears.

The development of the automobile was also intricately linked to the philosophy of the American Dream in the 20th century. Owning a car wasn’t just about convenience; it represented a path towards upward mobility and a tangible symbol of success. This influenced not only consumer desire but also fundamentally shaped individual ambitions and the pursuit of economic opportunity.

Furthermore, we see that transportation innovation is often strongly connected to broader social and political shifts. For instance, the rise of carpooling and ride-sharing reflects a change in social values towards community and sustainability, driven by a mix of economic incentives and evolving cultural beliefs. This pattern suggests that the way we choose to get around is intertwined with the societal and environmental values that are most important to us at a given time.

The partnerships we see today, like that between NVIDIA and Faraday Future, represent a significant shift in entrepreneurial risk-taking. These collaborations are not only about technological innovation; they are also driven by social networks, shared ideologies, and the importance of cultural alignment. This mirrors historical patterns observed in past technological revolutions, demonstrating that successful innovation rarely happens in isolation and often involves complex human interactions and shared goals.

The Psychology of Innovation How NVIDIA’s Partnership with Faraday Future Reveals Modern Entrepreneurial Risk-Taking – Philosophical Frameworks That Drive Modern Corporate Innovation Strategy

Modern corporate innovation strategies are guided by a complex set of philosophical ideas, blending risk assessment, cultural understanding, and ethical considerations. Companies like NVIDIA, when partnering with ambitious ventures like Faraday Future, demonstrate a cautious yet optimistic approach to innovation. This approach is influenced by behavioral economics, recognizing that people aren’t always perfectly rational in their decisions. It also stems from a sense of historical awareness, reminding us that past innovation cycles often had unintended consequences.

Innovation within large corporations increasingly relies on fostering a strong sense of shared values and a supportive organizational culture. Insights from anthropology help us understand how these shared beliefs and culture can affect the success of partnerships and innovation efforts. Additionally, the precautionary principle provides a crucial ethical framework, prompting companies to consider potential harm alongside potential benefits when pursuing novel technologies and strategies. Essentially, this principle encourages a careful and thoughtful approach to innovation.

By understanding these underlying philosophical ideas, we can gain a clearer picture of how major companies balance the competitive drive for innovation with the need to act in a responsible and forward-looking way. It’s a tightrope walk, where careful consideration of potential consequences is just as important as the drive for growth.

Big companies, especially those steeped in tradition, often struggle to innovate. It’s a problem that’s been around for a while, at least two decades. They tend to move slowly and are often hesitant to take risks, understandably so. However, this can be a big obstacle when it comes to keeping up with a rapidly changing world.

Leaders are increasingly looking for ways to manage this challenge. Tools that combine a strategic overview with more flexible, adaptable innovation approaches are being developed and tested. One example is what some researchers call the “innovation basket” – a way to organize and refine innovative projects.

The study of how people think in groups and make decisions has changed quite a bit over the last 30 years. It’s greatly informed how we think about managing companies and how they make decisions. Researchers now try to study innovation in a more nuanced way, taking into account the circumstances and situations that influence innovation. This approach reflects an effort to address previous shortcomings in how innovation was studied and analyzed.

There’s a growing interest in understanding the role of leaders, especially the top folks like CEOs and management teams, and their impact on a company’s success. The research is suggesting that the way these leaders encourage idea development, risk-taking, and decision-making can have a huge effect on whether a company is innovative.

Technological innovation, whether it’s a big jump forward or small improvements, impacts how products and services are designed and delivered. Innovation cuts across a huge range of areas.

Experts have been stressing for some time that companies need to find innovative solutions to stay afloat in today’s world. It’s a challenge that will only grow more important over the coming years.

The willingness of a business to take on risks and pursue opportunities is a big factor in how successful they will be, and whether or not they embrace innovation. This isn’t always a straightforward decision.

The cooperation between NVIDIA and Faraday Future represents a modern example of how technology and car companies are navigating high-stakes risks. These are not the first such examples, however, and they surely won’t be the last. The auto sector, in particular, has a long history of partnership and innovation.

It’s also interesting how philosophers and others who study human behavior are influencing our understanding of how these partnerships work. For example, pragmatism, a philosophy that emphasizes the value of actions and results, is playing a greater role in shaping decision-making. This focus on practicality helps steer companies toward the innovations that can make a concrete impact in the real world, not just in the abstract. We see this with NVIDIA’s involvement in areas like artificial intelligence, where they are actively supporting start-ups.

Another idea, the Socratic method, which uses questions to stimulate thinking and problem-solving, is being used in company meetings and other settings. This approach promotes critical thinking and allows companies to examine assumptions and find solutions that might have been overlooked otherwise. However, it’s worth pointing out that this type of probing can sometimes result in increased anxiety and scrutiny of individuals, especially in a fast-paced industry.

The ideas of philosophers like Foucault, who highlighted how surveillance can change how people act, are influencing how companies view productivity. In other words, the focus on observing and evaluating how well employees are working is impacting creativity. We could see this as positive – it’s an incentive for some employees to work harder. However, the pressure to perform and stick to certain rules can also limit how people think outside the box.

Risk is another big topic that is examined through the lens of philosophy. Determinism and free will are longstanding ideas and, as the world changes and becomes more complex, it’s important for decision-makers to find the right balance between planning and responding to the unexpected. This is especially true when it comes to a field like the auto industry, which has historically experienced a multitude of risks, challenges, and setbacks. It’s important to remain flexible and not assume control of future events in such circumstances.

The Enlightenment had a big impact on how we view personal liberty. It’s not surprising that the idea of giving individuals more independence is being adopted in modern businesses that seek to encourage innovation. That’s because innovation can flourish when people are allowed to experiment and develop their own creative ideas, and are encouraged to take risks and learn from their failures.

Companies are also exploring ways to navigate competition using game theory. This branch of mathematics helps companies consider the consequences of actions and to anticipate how competitors or partners will respond. It’s very relevant in the context of partnerships, which can be high-stakes affairs. For example, how NVIDIA collaborates with other firms can be partly influenced by how it sees other firms acting, and anticipating these actions ahead of time is often helpful.

It’s interesting to note how social norms impact innovation. Ideas about how society views progress and innovation influence how businesses are run and what kinds of solutions are adopted. As we’ve seen in many industries, it’s important for companies to understand what people in society value and to design solutions that appeal to their interests and beliefs.

The importance of ethical decision-making is growing, with many companies increasingly interested in what some researchers call virtue ethics, based on the ideas of Aristotle. There’s a desire to cultivate leaders who have a clear sense of ethical principles and to make sure those principles influence how innovation is pursued.

Anthropology provides insights into how collaboration works in groups. Researchers are looking at how different cultures affect how teams are organized and work together. It’s all about finding the best ways for groups to combine skills and find solutions that create the biggest impact.

And finally, studying innovation through the course of history can also reveal important insights. For example, by looking at successful and failed innovations in the past, organizations might gain a better understanding of why and how some innovations thrive, while others falter. Looking at past innovations can also help firms navigate complex socio-economic environments with more confidence and foresight.

While there’s still much to understand, it’s clear that modern corporate innovation is heavily impacted by a multitude of factors, from practical considerations to philosophical ones. These influences are playing a key role in the decisions big companies are making about the future

The Psychology of Innovation How NVIDIA’s Partnership with Faraday Future Reveals Modern Entrepreneurial Risk-Taking – Ancient Trade Routes to Modern Supply Chains Historical Patterns in Tech Innovation

The journey from the ancient world’s trade routes to today’s complex supply chains illustrates a remarkable transformation in how we move goods and resources. Early civilizations, through innovations like the Roman road network or the Silk Road, established the fundamental concepts of interconnectedness and efficient distribution. These early systems, while rudimentary compared to today’s technology, profoundly influenced how we manage commerce on a global scale. Now, in a world saturated with AI and automation, we see a constant drive towards optimizing supply chains, often resulting in a greater degree of speed and efficiency. But this historical perspective also serves as a reminder that each significant change in productivity throughout history has been interwoven with its own set of social, political, and environmental consequences. By exploring the evolution of supply chains through the lens of history, we gain a deeper appreciation for the multifaceted relationship between innovation and risk in the modern entrepreneurial environment. This historical perspective is vital for anyone trying to understand the challenges and opportunities present in our ever-changing economic landscape.

The intricate dance between ancient trade routes and modern supply chains offers a fascinating lens through which we can examine humanity’s ongoing quest for efficiency and innovation. Take, for instance, the Silk Road, which began around 130 BCE. It wasn’t just a conduit for silk and spices; it spurred a remarkable exchange of ideas and technologies, including things like papermaking, gunpowder, and the compass. These were foundational innovations that foreshadowed modern supply chain practices.

Similarly, the Roman Empire’s impressive network of roads and sea routes wasn’t solely for military purposes. It fueled a vibrant trade economy across Europe and North Africa. Their approach to managing resources, particularly allocating them across long distances, bears a striking resemblance to today’s “just-in-time” inventory methods.

Even further back in time, the Abbasid Caliphate during its Golden Age (750-1258 CE) built a sprawling global trade system that put a premium on the sharing of knowledge. This transcontinental exchange of ideas echoes in the collaborative partnerships that fuel today’s tech innovations. Startups routinely leverage global expertise, a practice inspired by these historical precedents.

Medieval Italy’s merchant cities introduced revolutionary financial instruments like letters of credit and bills of exchange, significantly simplifying international trade. These early methods of financial transactions share remarkable parallels with the modern-day financial systems that underpin tech innovation.

The very notion of “logistics” itself has roots in the past. The Roman military meticulously developed logistical models to manage their vast supply networks. This early use of structure in supply chain management paves the way for the sophisticated data analytics and optimization strategies used today.

Interestingly, the spread of religions like Islam and Buddhism along trade routes promoted not only religious doctrine, but a globalized way of thinking, fostering cosmopolitanism. This emphasis on inclusivity and global perspectives continues to influence contemporary business practices, where diverse perspectives are vital to success.

Anthropological studies of trade relationships reveal that they’ve always hinged on mutual cultural understanding and social networks. These observations underscore the critical role of interpersonal connections in modern entrepreneurial ecosystems, a reality readily apparent in the vibrant startup scene of Silicon Valley.

But the past also offers reminders of pitfalls to avoid. Historically, trading empires frequently misjudged the stability of their trade routes—a form of overconfidence. This echoes in modern tech firms that may blindly follow trends without fully analyzing market risks.

Furthermore, examining historical trade patterns reveals how deeply ingrained societal values influence markets. The marketing strategies surrounding luxury goods in ancient Rome, for instance, find their modern counterparts in how tech companies position and launch new products to appeal to certain consumer desires.

Technological advancements have always been a game changer. The printing press, for example, transformed information sharing in the 15th century. Today, blockchain technologies are poised to revolutionize supply chains through increased transparency and security, elements that companies like NVIDIA incorporate into their collaborations.

Ultimately, understanding the history of trade reveals a fundamental continuity in the challenges and triumphs that define innovation. The lessons embedded in these ancient networks offer a rich tapestry of wisdom that informs how we build and manage supply chains today, allowing us to adapt and innovate for a future yet unwritten.