AI: A New Paradigm for a Post-Big Tech Internet

The past five years in technology have largely been characterized by incremental advancements rather than transformative shifts, leading to a palpable sense of stagnation for many. While innovations such as advancements in space exploration, the burgeoning electric vehicle market, and Apple’s powerful new chips have captured attention, they have not fundamentally altered daily life in the way prior technological waves did. This period of relative calm, however, now appears poised for disruption with the meteoric rise of artificial intelligence.

Opinions on neural networks vary widely, from those who dismiss them as sophisticated mimicry to enthusiasts who are already integrating multiple AI tools into their workflows. Regardless, their increasing popularity is undeniable, permeating everyday conversations and attracting colossal investments from companies annually. Indeed, a significant proportion of new startups today proudly declare themselves “AI-powered.” Marc Andreessen, a prominent venture capitalist, likens this moment to the invention of the microprocessor, arguing that AI represents a new kind of computer capable of rebuilding virtually everything that computers currently do. He posits that this fundamental technological paradigm shift presents an unparalleled opportunity for a new generation of companies to surpass the current giants, driving venture capital from a “search mode” for the next big thing to an aggressive “hill-climbing mode” of development. The release of OpenAI’s o1 model, in particular, solidified the potential for AI’s reasoning capabilities, convincing many that the technology’s theoretical promise was becoming tangible.

This perspective resonates with a growing public frustration over the state of the internet, which many feel is increasingly “broken.” The dominance of a few “Big Tech” giants—Google, Meta, Apple, Microsoft, and Amazon—has grown to an unprecedented scale, with these companies collectively accounting for a quarter of the entire S&P 500 index. Yet, critics argue they deliver insufficient value to justify their immense market capitalization, often at the expense of user experience and fair competition.

Google’s search quality, for instance, has visibly declined for years. Its ad-driven business model frequently clashes with user experience, leading to search results dominated by advertisements and SEO-optimized content riddled with affiliate links. This conflict of interest has prompted users to increasingly append “Reddit” to their search queries, seeking authentic, unoptimized discussions over curated articles. Internal concerns about this decline, reportedly stemming from pressure to meet ad revenue targets, even led to leadership changes within Google’s search division. While spam filters remain active, they are struggling to keep pace with the proliferation of review farms, bots, and automated content, forcing users to sift through irrelevant information to find reliable answers.

Meta, meanwhile, has shifted its mission from fostering human connection to maximizing user attention for advertising revenue. This is evident in the aggressive algorithmic feeds and recommended content on platforms like Instagram, where chronological feeds are deliberately buried. Engagement rates on social media platforms have reportedly dropped, with many personal posts receiving minimal interaction, suggesting that these networks are less about genuine connection and more about extracting attention.

Apple, though not reliant on advertising, faces criticism for its tight ecosystem control and perceived resistance to innovation. Its App Store policies, including a 30% revenue cut on in-app purchases, have drawn fire for stifling developers, even forcing some to navigate complex exceptions to avoid significant financial penalties. Beyond these economic issues, Apple’s slow progress in core AI areas like Siri, its cancelled car project, and the premature release of products like Vision Pro suggest a company struggling to adapt to the rapid pace of AI development, exemplified by a research paper from its own researchers that was later refuted for flawed assumptions about AI reasoning.

Microsoft, despite its early leadership in AI with GitHub Copilot, has struggled to maintain its innovative edge against more agile startups. While Copilot was initially a “killer app” for language models, its evolution has been hampered by Microsoft’s corporate machinery. Startups like Cursor have rapidly developed superior coding tools by leveraging newer models like GPT-4, which offered a massive leap in capabilities. Microsoft’s rushed attempt to challenge Google’s search dominance with its GPT-4-based Bing chatbot, Sydney, famously failed due to its unreliability and “pathological liar” tendencies. Subsequent internal reorganizations and a chaotic “Copilot” branding strategy further diffused focus. This mirrors Microsoft’s historical anti-competitive tactics, such as bundling Teams to squeeze out rivals like Slack, highlighting a pattern of leveraging ecosystem dominance rather than pure innovation.

Amazon, too, has faced significant scrutiny for systematically suppressing competition. Lawsuits allege the company penalizes sellers who offer lower prices elsewhere by burying their listings, effectively forcing them to use Amazon’s expensive shipping services to attain Prime status, thereby locking them into the platform. Aggressive advertising prominently displayed in search results further burdens sellers with a “visibility tax,” ultimately driving up prices for consumers across all platforms. Beyond its market practices, Amazon has been criticized for its harsh working conditions in warehouses, where employees are subjected to constant surveillance and tight monitoring, treated as cogs in an optimized production line, all while facing decreasing wages.

In light of these widespread frustrations and the perceived shortcomings of Big Tech, the prospect of an AI-driven technological wave offers a glimmer of hope. Many believe that traditional regulatory bodies or corporate self-correction are unlikely to address these systemic issues. Instead, a fundamental reshaping of the economic landscape through new technological conditions, as envisioned by proponents of AI disruption, may be the only path toward a healthier, more equitable internet.