Musk's XAI Grok 3 Shatters AI Limits with 200,000 GPU-Strong 'Colossus'

Introduction

The pace of technological advancement in artificial intelligence (AI) continues to accelerate, as evidenced by groundbreaking achievements like Elon Musk's XAI with its latest milestone, Grok 3. This AI model has set a new benchmark in the AI domain, harnessed by a formidable infrastructure housed within the Colossus data center. The facility's use of 200,000 NVIDIA H100 GPUs exemplifies the trend of leveraging extensive computational resources for AI development. Such a strategy has propelled Grok 3 to surpass its competitors on platforms like Chatbot Arena, establishing it as a formidable contender in the AI space. Learn more about this significant breakthrough [here](https://substack.com/home/post/p-157370460).

The establishment of the Colossus data center underscores a strategic shift towards owning dedicated AI infrastructure, avoiding reliance on external cloud services. This colossal project, completed in just 18 months, showcases an innovative approach by repurposing existing industrial architectures, thereby bypassing traditional, lengthy data center construction phases. The capital investment, estimated at $8-9 billion, not only reflects the financial commitment required but also highlights the trend towards intensifying capital flows into AI infrastructure. Explore more about XAI's infrastructure strategy [here](https://substack.com/home/post/p-157370460).

A critical aspect of XAI's approach is its emphasis on energy-efficient practices. By integrating Tesla batteries and innovative cooling solutions, the Colossus data center sets a benchmark in sustainable computing practices within the AI industry. Such measures are crucial, given the ever-expanding energy footprints of AI models; they represent an important step towards minimizing the environmental impact of high-performance computational facilities. Additionally, future plans to expand this setup underscore the scaling possibilities when sustainability and technological prowess intersect. For further insights, access the details [here](https://substack.com/home/post/p-157370460).

Elon Musk's XAI and the Grok 3 Breakthrough

Elon Musk's XAI has recently made headlines with its groundbreaking achievement in the AI arena. At the heart of this development is Grok 3, a result of herculean efforts toward creating a cutting-edge AI model that outranks competitors including OpenAI and Anthropic. Central to Grok 3's success is the 'Colossus' data center, a mammoth computing facility brimming with 200,000 NVIDIA H100 GPUs, built in just 18 months—an impressive feat that highlights XAI's commitment to innovation and speed [1](https://substack.com/home/post/p-157370460).

The strategic investment in infrastructure, reportedly amounting to $8-9 billion, underscores XAI's dedication to maintaining an edge in the highly competitive AI field. The facility's unique power and cooling systems leverage Tesla batteries, reflecting a merging of Elon Musk's innovative pursuits across different technological sectors. This strategic integration not only optimizes performance but also sets a precedent for efficient resource utilization in AI computation [1](https://substack.com/home/post/p-157370460).

Beyond the sheer scale of Grok 3's computing power, XAI's approach signals a shift in the landscape of AI development. By opting for a 'brute-force' infrastructure strategy, XAI ensures total control over its AI resources and development processes, circumventing reliance on third-party cloud solutions. This autonomy allows XAI to push the boundaries of AI capabilities swiftly and securely, fostering an environment ripe for innovation [1](https://substack.com/home/post/p-157370460).

However, these advancements are not without their challenges. The robust infrastructure requirements inevitably raise questions regarding sustainability. The heat generated by such massive computing operations necessitates efficient cooling solutions and highlights the environmental impact of large-scale AI systems. As AI continues to evolve, balancing technological progress with environmental considerations and energy efficiency will be critical [1](https://substack.com/home/post/p-157370460).

Public reaction to Grok 3 has been a mix of awe and skepticism. Tech enthusiasts celebrate its capabilities, particularly in fields such as complex reasoning and computational estimation. Notably, Andrej Karpathy, the former director of AI at Tesla, has lauded its performance. However, skeptics call for independent verification of its benchmarking results, reinforcing the need for transparency in AI development [7](https://www.cnbctv18.com/technology/grok-3-launch-live-updates-elon-musk-xai-ai-startup-chatbot-smartest-ai-on-earth-chatgpt-rival-liveblog-19560404).

Looking ahead, Grok 3's success has significant implications for the future of AI. The development of even larger superclusters, as planned by XAI, indicates an ongoing trend towards consolidation within the industry where only the most well-funded entities can participate meaningfully. This capital-intensive trajectory could stifle smaller competitors and limit diverse innovation unless balanced with robust regulatory oversight and sustainable frameworks [1](https://substack.com/home/post/p-157370460).

Infrastructure Investment and Development

Infrastructure investment and development are at the forefront of technological advancement, particularly in the realm of artificial intelligence. Elon Musk's company, XAI, exemplifies this trend with their recent unveiling of Grok 3, a breakthrough enabled by a significant $8-9 billion infrastructure investment. Utilizing a custom-built data center named 'Colossus,' this supercomputer is equipped with 200,000 NVIDIA H100 GPUs, marking a pivotal point in AI technology. By considerably outpacing competitors such as OpenAI and Anthropic, Grok 3 has set new standards for AI performance and capability. For more details, the full story on this technological milestone can be found [here](https://substack.com/home/post/p-157370460).

XAI's approach to infrastructure investment and development is notable for its speed and innovation. Despite the typical prolonged timelines associated with constructing data centers, XAI swiftly converted an existing factory and utilized generators alongside Tesla batteries to meet power needs. This efficiency not only facilitated the rapid deployment of their AI technology but also highlights the integral role of innovative power solutions in modern infrastructure projects. This approach has allowed XAI to gain a significant competitive advantage by maintaining greater control over their computational resources, thus demonstrating the potential of agile infrastructure development in tech industries [source](https://substack.com/home/post/p-157370460).

The implications of large-scale infrastructure investments extend beyond immediate technological achievements. As seen with XAI, these investments are increasingly crucial for maintaining competitiveness in the AI space. The trend indicates that future AI advancements will largely hinge on substantial capital input, potentially sidelining smaller companies and creating higher barriers to entry. This underscores a shift towards a market dominated by well-funded entities capable of undertaking such massive projects. Additionally, these developments foreshadow a growing emphasis on infrastructure that supports sustainable and efficient energy consumption, which is becoming a crucial consideration as the need for large-scale data centers grows. The broader implications of these advancements are discussed in this [article](https://substack.com/home/post/p-157370460).

In comparison, other major tech players are recognizing similar needs in their infrastructure strategies. For instance, Meta has announced a $15 billion AI research facility in Texas, emphasizing renewable energy and innovative cooling systems to mitigate environmental impact [as detailed here](https://www.datacenterknowledge.com/meta/meta-announces-15b-texas-ai-research-facility). Similarly, Google Cloud, in partnership with Nvidia, is constructing an 'AI Hypercluster' in Singapore—a $2.3 billion initiative that incorporates cutting-edge liquid cooling technologies [information can be found here](https://www.datacenterdynamics.com/news/google-nvidia-launch-singapore-ai-hypercluster). These examples illustrate a broader industry trend towards integrating sustainable practices with advanced technological infrastructure.

Unique Strategies and Innovation at XAI

Elon Musk's XAI is exemplifying a paradigm shift in AI by implementing groundbreaking strategies that are redefining innovation. The development of the Grok 3 AI, spearheaded through their proprietary "Colossus" data center, shows an unprecedented commitment to in-house infrastructure investments, estimated between $8-9 billion. This facility isn't just a technical marvel due to its mission-critical scale and speed—constructed within 18 months—but also for its innovative application of Tesla batteries for cooling and power management. Such visionary moves enable XAI to avoid traditional dependencies on external cloud computing resources, positioning it ahead of competitors like OpenAI and Anthropic in benchmarks, including Chatbot Arena's top ranks. More on this can be explored here.

XAI's strategic construction of its supercomputing infrastructure in such a short timeframe was made possible by a unique approach that deviates from conventional methods. By converting an existing factory into the Colossus data center and employing innovative power solutions like generators and Tesla batteries, XAI surpassed traditional data center construction timelines. This "brute-force" approach to developing compute capabilities internally gives XAI a competitive edge by retaining control over proprietary resources and data, thus bypassing cloud service dependencies. Such advancements suggest that major capital investments are becoming crucial for future AI developments, restricting significant contributions to well-funded organizations more details.

Sustainability concerns surrounding XAI's rapid development of massive computing infrastructure highlight the potential environmental impacts of increased compute demands. The creation of energy-intensive facilities like the Colossus data center brings into question the long-term feasibility of such operations amidst growing environmental and physical limitations. The future might see AI progress being dictated not just by available compute resources but also by the efficiency of algorithms and power footprints, a balance not yet fully realized by many leading tech firms. This underscores the need for groundbreaking, sustainable innovations in both hardware and algorithm efficiency, a topic further explored here.

Broader Implications of XAI's Approach

The approach taken by Elon Musk's XAI with Grok 3 extends beyond just the technological breakthrough of having a superior AI model; it represents a paradigm shift in how artificial intelligence is developed and deployed. The creation of the "Colossus" data center, equipped with 200,000 NVIDIA H100 GPUs, underscores a massive capital investment, believed to be in the range of $8-9 billion, which has enabled XAI to leapfrog competitors like OpenAI and Anthropic. By focusing on owning substantial compute resources, XAI has not only positioned itself as a leader in AI model performance but has also underscored a broader trend where AI advancement is increasingly reliant on significant financial commitment [1](https://substack.com/home/post/p-157370460).

XAI's unique "brute-force" strategy, leveraging its colossal infrastructure, allows it to maintain complete autonomy over its resources, thus avoiding the pitfalls of dependency on third-party cloud providers. This approach ensures that XAI can push the boundaries of AI development independently, potentially setting a new standard in AI research where possession of vast computing power is directly linked to competitive advantage. However, this also raises questions about the future landscape of AI development, potentially creating entry barriers that only well-funded organizations can overcome [1](https://substack.com/home/post/p-157370460).

The implications of XAI's strategy are manifold, impacting both the technological and socio-economic spheres. As AI systems like Grok 3 continue to become more advanced, the need for ever-more-substantial infrastructure grows. This demand may necessitate innovation not just in AI models themselves, but also in the supporting technology, such as innovative cooling and power solutions that XAI has started exploring with Tesla batteries. This has led to plans for a supercluster expansion that would be five times larger than the current facility, highlighting the shift towards mega-scale AI infrastructure [1](https://substack.com/home/post/p-157370460).

Furthermore, XAI's developments imply significant environmental considerations. The large-scale data centers, while powering incredible advancements in AI, also bring up sustainability issues—the same issues prompting movements like the "Green AI Act," passed by the European Union, which demands AI companies to meet strict energy efficiency standards. This act symbolizes a growing recognition of the need to balance AI development with environmental responsibility [3](https://www.euractiv.com/section/artificial-intelligence/news/eu-passes-landmark-green-ai-legislation).

In essence, XAI's approach with Grok 3 suggests a new frontier in AI development, one that is distinctly marked by its exclusive focus on harnessing mighty compute power and infrastructure. The implications of this strategy go beyond immediate technological advancements, as they echo across regulatory, environmental, and economic spheres, shaping the future discourse on the sustainable integration of AI into society.

Sustainability Challenges and Solutions

Sustainability is one of the most pressing challenges in the rapid development of AI technology. As AI models become increasingly powerful, the infrastructure required to support them grows exponentially. This expansion is not just in terms of scale and financial investment, but also in its environmental footprint. For instance, Elon Musk's XAI, through its fast-tracked development of the "Colossus" data center, highlights both the potential and the sustainability challenges at the forefront of AI advancement. The facility, which houses 200,000 NVIDIA H100 GPUs, depends heavily on substantial power sources and innovative cooling solutions to maintain operations efficiently [1](https://substack.com/home/post/p-157370460).

An effective solution for sustainability in AI involves integrating renewable energy sources. A significant development in this arena is Meta's $15 billion investment in Texas, which combines advanced cooling systems and renewable energy to mitigate environmental impacts [1](https://www.datacenterknowledge.com/meta/meta-announces-15b-texas-ai-research-facility). These initiatives show a growing recognition within the tech industry of the need to align technological advancements with environmental sustainability. However, achieving this balance is fraught with challenges, primarily due to the enormous capital required to support such infrastructures. This trend may inadvertently marginalize less-funded entities that cannot afford similar investments.

On the regulatory forefront, governmental bodies worldwide are beginning to respond to these infrastructural shifts. The European Union's "Green AI Act" serves as a landmark regulation requiring AI companies to disclose their carbon footprints and adhere to strict energy efficiency standards by 2026 [3](https://www.euractiv.com/section/artificial-intelligence/news/eu-passes-landmark-green-ai-legislation). Acts like these are crucial in setting benchmarks for sustainable practices and ensuring that the growth of AI does not come at the expense of the planet's well-being, though compliance might further widen the gap between large companies and smaller players struggling to meet these standards.

Another promising solution lies in developing more efficient algorithms that can perform complex tasks without the need for proportionately massive infrastructure. Innovative methodologies, such as DeepMind's "EcoScale," and China's allocation of 50GW of renewable energy specifically for AI data centers, present viable pathways to reduce energy consumption while still achieving desired performance outcomes [5](https://www.scmp.com/tech/policy/article/china-state-grid-ai-renewable-energy). Such initiatives demonstrate the potential to reconcile the growing demands of AI with environmental stewardship.

Importance of Efficient Algorithms

With the AI landscape rapidly advancing, efficient algorithms remain at the heart of computational innovation. They enable developers to create powerful applications capable of operating effectively within the limitations of current hardware. As companies like XAI demonstrate the immense benefits of well-integrated hardware and software solutions, efficient algorithms will continue to drive the competitive edge in AI development [1](https://substack.com/home/post/p-157370460). This is especially pertinent as global competition intensifies, with nations investing heavily in AI infrastructure to establish leadership in this frontier technology. The significance of algorithms becomes increasingly evident as they pave the way for smarter, more resourceful AI systems, ultimately shaping the future of technological progress.

Related AI Infrastructure Developments

The rapid development in AI infrastructure has seen remarkable strides with the unveiling of facilities like XAI's "Colossus" data center. This monumental effort, accomplished in just 18 months, houses 200,000 NVIDIA H100 GPUs, positioning XAI as a leader in AI capability with their Grok 3 model outperforming competitors. This is indicative of a broader trend of massive investment in physical infrastructure to support advanced AI applications, as highlighted in an [article on Substack](https://substack.com/home/post/p-157370460?utm_campaign=post&utm_medium=web). Such developments underscore the ongoing arms race in AI technology, where custom data centers, like the recently announced $15 billion Meta research facility in Texas, become crucial competitive assets.

Reflecting on these infrastructure developments, key industry players are investing heavily to overcome existing limitations. Meta's facility in Texas, featuring advanced cooling systems and renewable energy integration, and Google's AI Hypercluster in Singapore with $2.3 billion worth of infrastructure for 32,000 H100 GPUs, demonstrate the sky-high stakes and fiscal commitments involved. These initiatives aim not just at enhancing AI capabilities but also at addressing the environmental impact of such massive operations, aligning with new regulations like the European Union's "Green AI Act" which mandates transparency in the carbon footprint of AI operations.

XAI's strategy of "owning" their computing resources allows them unparalleled control over their infrastructure, enabling rapid advancements such as their recent achievements with Grok 3. This approach circumvents traditional dependencies on cloud providers and reflects a broader industry shift towards self-reliance. The implications of this strategy are profound, as it suggests that future AI capabilities might heavily depend on those who can afford and manage significant capital investments in bespoke AI infrastructure. This aspect is further emphasized by China's allocation of 50GW of renewable energy for AI data centers, marking significant government-backed strides in infrastructure investment.

As AI models continue to grow in complexity, their computational demands will also increase, raising concerns about sustainability and feasibility. Innovations like DeepMind's "EcoScale" signify critical steps towards reducing energy consumption in AI processes, ensuring that AI advancements do not come at the cost of environmental health. The ongoing discourse about AI's environmental footprint highlights the urgent need for sustainable practices in the industry, as argued in a [Nature article](https://www.nature.com/articles/s41586-025-5789-2). This necessitates collaboration across sectors to pioneer breakthroughs in green computing technologies.

The broader implications of developments in AI infrastructure extend to global competition and technological leadership. As seen with China's power allocation and the EU's regulatory measures, AI infrastructure is becoming a focal point of national strategic importance. This competitive landscape compels countries to cultivate their AI capacities zealously, as the ability to lead in AI could influence global economic and technological hierarchies significantly in the coming decade. The necessity for sustainable and equitable AI infrastructure investment is likely to drive future policies, prompting a balanced approach towards technological and environmental challenges.

Expert Opinions on Grok 3

Andrej Karpathy, former Director of AI at Tesla, has shared his perspective on Grok 3's impressive capabilities, particularly highlighting the AI's proficiency in "Thinking" mode. This mode excels in handling complex tasks and computational estimations, which marks a significant leap forward in AI technology. According to Karpathy, Grok 3's performance rivals that of OpenAI's latest models and often outperforms them in tasks that require deep reasoning and research capabilities [].

Despite the accolades, Karpathy notes some limitations in Grok 3's abilities, particularly in generating creative content and humor. It also displays an overly cautious approach to ethical reasoning, which can sometimes hinder its performance in certain tasks. However, the progress achieved by Grok 3 in just over a year is described as unprecedented [].

The AI's benchmark performances suggest that XAI has developed a formidable contender in the AI race, potentially setting new standards in AI research and application. Although Grok 3 shows some areas for improvement, particularly in creative endeavors, it stands as a testament to the rapid progress and potential of Elon Musk's AI initiatives [].

Public Reactions to Grok 3 and Colossus

Elon Musk's XAI has made headlines with the release of Grok 3, hailed as a technologically advanced chatbot that's setting new standards in the AI field. The public reaction to Grok 3 and its powerful backend, Colossus, reflects a mix of admiration and scrutiny. Tech enthusiasts have celebrated Grok 3's capabilities, particularly its dominance in benchmarks and unique features, such as the `Deep Search` that outshines competitors like ChatGPT. This has sparked vibrant discussions across social media about the vast potential of Grok 3 in transforming various technical domains [5](https://frontend-snippets.com/blog/elon-musks-xai-grok-3-outperforms-chatgpt-deepseek-in-early-testing).

However, not everyone is convinced. Skeptics have pointed to the need for independent verification of the claimed benchmark superiority over established models like GPT-4 and Gemini 2 Pro. This demand for transparency is a recurring theme in online forums and discussions. Interestingly, Grok 3 itself provides a critical view on Elon Musk, humorously suggesting the dichotomy between developer and creation. A relevant Reddit discourse also gained traction, discussing the irony of a Musk-associated AI questioning its own founder's credibility [2](https://www.reddit.com/r/mathmemes/comments/1gtes1u/grok3/).

The rapid establishment of Colossus, the brainchild of futuristic "brute-force" algorithms, has itself garnered polarized opinions. While some praise the efficiency and scale of the accomplishment—converting a factory into a powerful data center in record time—others express concern over the environmental footprint. With 200,000 NVIDIA H100 GPUs under one roof, the concerns revolve particularly around sustainability and energy usage, echoing broader industry debates about environmentally responsible tech innovations [1](https://www.newsweek.com/elon-musk-grok-chatgpt-deepseek-2032500).

Aside from environmental anxieties, the financial barrier posed by such massive infrastructure raises additional ethical questions. The concentration of computational power within financially robust entities threatens to stifle competition from smaller entrants in the AI market. This could lead to a "computing dictatorship" where only giants like XAI possess the resources and infrastructure to lead in AI development. Such issues underscore the growing call for a balanced approach to AI growth—where efficiency and innovation are not sacrificed at the altar of expansive computational efforts [1](https://www.newsweek.com/elon-musk-grok-chatgpt-deepseek-2032500).

Future Implications of AI Advancement

The formidable advancement of AI technology is poised to reshape the world in unprecedented ways. At the forefront of this transformation is XAI's latest development, the Grok 3, powered by Colossus, a data center replete with 200,000 NVIDIA H100 GPUs. Valued at an estimated $8-9 billion, and enhanced by innovative cooling solutions involving Tesla batteries, this infrastructure not only catapults XAI beyond its competitors, but also sets a benchmark in AI technology [news article](https://substack.com/home/post/p-157370460). As the ace in XAI's deck, Grok 3 has outstripped its opponents in model benchmarks, heralding a new era where raw computational power is a key determinant of competitive edge.

The implications of such advancements are manifold, not least because the success of AI models like Grok 3 underscores a new trend: AI development is becoming an arena dominated by firms with the capacity for massive capital investment. This shift threatens to establish steep entry barriers, potentially stymieing innovation from smaller players who lack resources to match the infrastructural might demonstrated by XAI [news article](https://substack.com/home/post/p-157370460). Consequently, we may witness a landscape where vigorous industry consolidation becomes the norm, with well-funded entities monopolizing AI innovation.

This trajectory is not without significant challenges, particularly concerning sustainability. As these colossal data centers proliferate, so does the environmental footprint of AI. The energy-intensive nature of these facilities necessitates an urgent reevaluation of current energy strategies. As an answer to environmental callings, innovations like DeepMind's "EcoScale" emphasize the importance of energy-efficient algorithms [news article](https://www.nature.com/articles/s41586-025-5789-2). The future of AI increasingly hinges not just on computing power, but on sustainable practices that mitigate the ecological impacts of technological progress.

Moreover, as AI's presence deepens across industries, expect profound transformations within the workforce. AI's capacity to automate and optimize processes foreshadows significant disruptions to traditional job roles, especially in sectors like customer service and data analytics. This shift necessitates a corresponding evolution in workforce skills, emphasizing retraining and upskilling to stay relevant in an AI-enhanced job market [news article](https://substack.com/home/post/p-157370460).

The rapid leaps in AI's capability and infrastructure also invite regulatory scrutiny. As concerns mount over the energy consumption and environmental impact of large-scale AI systems, regulatory frameworks must evolve to address sustainability issues. Legislation like the EU's "Green AI Act," enforcing disclosure of AI models' carbon footprints, exemplifies initial steps towards more stringent regulations [news article](https://www.euractiv.com/section/artificial-intelligence/news/eu-passes-landmark-green-ai-legislation). Such measures will likely become more prevalent, shaping the future landscape of AI development.

Conclusion

As we look to the future, the advancements in AI led by XAI's Grok 3 and the Colossus data center underscore a pivotal moment in technological development. The remarkable rapidity of their construction—completed within 18 months—points to a new era of accelerated innovation where the physical constraints of traditional infrastructure are overcome by sheer computational power. However, such advancements also raise pivotal questions about sustainability and economic accessibility. Massive investments are becoming the cornerstone of AI progression, potentially reshaping the industry landscape and creating higher entry barriers for smaller and less-funded organizations. This evolution could lead to market consolidation, where only the most well-resourced players can continue to innovate and thrive [1](https://substack.com/home/post/p-157370460).

Furthermore, the development of this behemoth computing infrastructure reflects a broader trend in which AI is becoming an ever-more central component of strategic national interests. Just as XAI has boldly forged ahead, other tech giants and nations might intensify their focus on similar projects, aiming to carve out a competitive edge on the global technological stage. This could result in a geo-political race to establish AI dominance, akin to the early days of the space race but with data centers as the battlegrounds [3](https://www.scmp.com/tech/policy/article/china-state-grid-ai-renewable-energy). Such a shift posits AI infrastructure not merely as a technological asset but as a critical element of national power and influence.

Despite the barriers and competitive nature of this new landscape, the XAI initiative also charts a path for innovation in auxiliary areas such as power efficiency and renewable energy integration. The use of Tesla batteries and innovative cooling solutions could set new industry standards, potentially sparking a wave of eco-conscious technology that other firms might adopt to lessen their environmental footprint. This development is vital, echoing societal calls for more environmentally friendly practices in all sectors, including AI [1](https://www.datacenterknowledge.com/meta/meta-announces-15b-texas-ai-research-facility).

Moreover, the implications of Grok 3 extend far beyond industrial boundaries and touch on societal transformations. The advent of a supercomputer with capabilities surpassing current models could transform sectors like healthcare, education, and workforce dynamics. Enhanced AI systems promise to revolutionize job markets, necessitating a retraining and upskilling revolution as more automated solutions replace traditional roles [4](https://opentools.ai/news/elon-musks-xai-unveils-grok-3-claiming-the-title-of-smartest-ai-on-earth). Education too stands at the brink of transformation, with AI enabling tailored learning experiences that could revolutionize educational practices, although this also risks widening the gap between well-funded and under-resourced schools.

In conclusion, while Grok 3 signifies a leap forward in AI capabilities, its development is emblematic of a rapidly changing industry entwined with environmental, economic, and social challenges. The future will inevitably call for a balance between these elements, as the demand for more powerful and efficient AI systems continues to grow. As we stand on the cusp of this potential revolution, the path forward must be tread with caution, ensuring that innovation does not sideline sustainability and equity for technological progress [2](https://euractiv.com/section/artificial-intelligence/news/eu-passes-landmark-green-ai-legislation). By learning from and building upon the past, we can craft a future where technology serves the broader good of society.