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In the unfolding narrative of generative AI, an intriguing paradox emerges between expectations and reality. Contrary to the widespread anticipation, the path toward Artificial General Intelligence (AGI) is not resembling an elusive asymptote—a goal that seems forever out of reach (we cannot simply bury our heads in the sand, hoping this challenge will disappear). Instead, the effort to achieve parity with OpenAI, often perceived as a straightforward victory by industry giants, is turning out to be a journey closely akin to an asymptotic pursuit.
The Quest for Alternatives
The drive to disrupt monopolies in any domain, including the generative AI landscape dominated by technologies like GPT by OpenAI, is a critical endeavor. The natural aversion to monopolistic control underscores the importance and inevitability of introducing at least one substantial alternative, ideally with open weights. Historically, breaking monopolies has led to significant advancements and increased options for consumers and businesses alike. Examples include the emergence of Azure as a competitor to AWS's dominance in cloud computing, and Android's rise as an alternative to the iPhone's market control.
Disrupting monopolies undeniably yields significant advantages, paving the way for innovation and diversity. Yet, as we transition away from monopolies, the second order problem of forming duopolies emerges. Interestingly, nature seems more accommodating of duopolies than monopolies (quiz: how many poles does Earth and every other planet in the visible universe have?).
Challenges on the Path
As mentioned in the introduction, presenting an alternative to OpenAI appears to be a Herculean task for competitors. Each seems to be grappling with hysteresis—where past influences impede current progress. This phenomenon is evident among various contenders. For example, some established entities are so committed to upholding political correctness that it permeates their products, affecting usability and attracting widespread criticism (fortunately, they are now beginning to rectify their approach). Meanwhile, a significant player in social media is making bold strides in research but faces challenges in turning these initiatives into viable, production-level solutions (at least, not yet).
Wrapping Up
The journey of technological innovation is complex, demonstrating that not all innovations naturally progress to commercial success. This narrative is well illustrated by comparing IBM's collaboration-driven success with the Apache Software Foundation to Sun Microsystems' challenges in commercializing Java, highlighting the unpredictable path from innovation to market impact.
The sale of undersea dark fiber at significantly reduced costs post-Global Crossing's bankruptcy, which facilitated global internet expansion, serves as a poignant analogy to today's generative AI challenges. This historical parallel underscores the potential for major advancements to arise from unexpected sources, emphasizing the transformative power of democratization in technology.
Sam Altman's ambitious vision, proposing a $7 trillion investment to propel AI technology forward, suggests a future where the collaboration between nation-states and private entities could be essential. This collaboration might involve nations subsidizing the development of critical technologies, such as GPUs, to enhance accessibility and affordability. Such an approach not only underscores the strategic importance of AI on a global scale but also highlights the potential for a united effort to usher in a new era of innovation, where technological advancements are both a commercial and strategic priority.
