AI Anxiety Treatment - AI under classical product mindset (II)


The AI news keeps coming in waves after waves. One day, Claude takes the lead, only to be dethroned by Gemini the next, and then GPT-4 reclaims its dominance. Amidst this whirlwind of innovation, a plethora of new theories, open-source projects, and AI products are touted as the next big thing, each claiming to supersede its predecessors. Yet, the excitement seems to be theirs alone, leaving us, the average users, with nothing but anxious.

What is the source of this anxiety? With so much news, the topics discussed seem like divine battles, incomprehensible; with so many new products, which one should we use, is perplexing; with so many new technologies, which one truly represents the future, remains unclear.

In this article, I'll delve into the phenomenon of AI anxiety, exploring both business/product and technical perspectives. My aim is to provide some mental relaxation massage and serve up some soulful chicken soup for thought regarding AI.

Unraveling the Mystery

Let's peel back the layers of anxiety and get to the essence of the matter:

  1. Perhaps you feel AI is developing too rapidly, with a flood of new things emerging every day, leaving you surrounded by familiar faces reveling in unfamiliar new terms – that's just how AI evolves.
  2. Or maybe you think AI is progressing too slowly, failing to meet the intelligent features and user demands – yet again, that's how AI evolves.
  3. In the industry, AI has become a ubiquitous topic of discussion, with everyone chasing trends and seeking the next big thing. But there's a scarcity of tangible product launches or business outputs. People pursue an intangible fervor like they're chasing stars, leading to anxiety, fearing they'll miss out on this collective celebration and consequently miss an era. However, whether you're anxious or not – AI continues to evolve in this manner.

To gain a clearer perspective, let's examine the fundamental factors driving AI's development: overall computing power, scientific advancements, data accumulation, and external investment.

Learning from History

Let's take a historical detour to the late 1990s, the era of the .com bubble. Back then, the internet experienced an explosion of new websites and applications, each vying for attention and dominance. This era witnessed the rise of e-commerce ventures like and, social networking platforms like and ICQ, and internet-focused software like the Mosaic browser.

Just like today, the late 1990s were marked by a similar sense of anxiety surrounding the rapid advancements of the internet. People grappled with questions like:

  1. "The internet is evolving so rapidly. What are all these websites mentioned in the news, and what do they do?"
  2. "The internet is too slow. I can't even watch a video. What's the point?"
  3. "Everyone is browsing the internet, and it's free. How will website creators (like encyclopedia websites) make money? How can traditional software developers (like encyclopedia software companies) sell their products?"

Sound familiar? Today, we have answers to those questions:

  1. The internet was evolving too fast, with so many websites – most of them went bankrupt. Unless you're an internet historian, for most practitioners, they don't even need to know any about their existence.
  2. The internet speed was too slow, making it impossible to watch videos – but at some point, that ceased to be a problem, especially when you're surfing Tiktok.
  3. Profit models, how do I make money – it's still a major topic, but now there are too many options, like advertising, memberships, sponsorships, and more.

Revisiting back

Coming back to the realm of AI, anxiety can manifest in various forms. Let's explore some fresh perspectives to address these concerns.

Product Perspective:

  1. Embrace the Wisdom of Others: Seek inspiration from competitors and industry trends. Avoid the pitfalls of isolation. Remember those pizza-ordering computers and floppy disk digital cameras of the 2000s? These were all the crazy but unpractical ideas back then. In the AI domain, brilliant minds abound. Tap into their collective wisdom.
  2. Prioritize User Experience: Focus on enhancing user experience, not solely on model improvement. Model iterations often take months or even quarters. Strategic business decisions can compensate for model limitations, enabling faster product iteration and validation. Consider the enduring popularity of GIFs. In bandwidth-constrained scenarios, they effectively fulfill the need for (silent) short videos.

Technical Perspective:

  1. Embrace Patience and Focus: Avoid the frenzy of keeping up with the latest trends. If you can't catch up, neither can others. Slow and steady wins the race. Thoroughly grasp a concept, and you'll progress faster. Recall the early 2000s when you had to learn MFC, j2me, and eventually delve into underlying system architecture, data structures, and algorithms – knowledge that remains relevant today.
  2. Cultivate Independent Judgment: Trust your instincts. When Flash animation was the norm, Silverlight emerged. But it didn't seem likely to succeed – it didn't look promising, didn't feel promising, and lacked a sizable user base. So, we all know that Flash lived longer than silverlight. After all, in hindsight, HTML5 emerged as the next-generation technology.

Closing Thoughts

Of course, in terms of its developmental stage, today's AI corresponds more closely to the mid-1990s internet era, far from reaching a bubble scenario. Using the dot-com bubble as a reference point is simply to make comparisons more familiar. Therefore, considering this, there's even less reason to be anxious.

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