Igniting the Fury of an AI Enthusiast: A Critique of Modern AI Practices

#AIethics#AIfuture#AIcritique#AIdevelopment#techinnovation

TL;DR

This article critiques the current state of artificial intelligence, focusing on the perceived superficiality and lack of fundamental understanding in many AI applications. The author argues that the current focus on quick profits and superficial techniques, rather than in-depth study, is detrimental to the field's long-term progress. The piece draws parallels between the AI field and other technical disciplines, highlighting the importance of fundamental principles and rigorous research.

The author expresses a deep frustration with the perceived shortcuts and lack of genuine understanding in modern AI, particularly in areas like image and natural language processing. They lambast the reliance on techniques like "bag-of-words" models and the general disregard for the inherent properties of data, arguing that these methods are merely superficial attempts at generating quick results without a true grasp of the underlying principles. The author accuses the field of being a "scam," driven by a pursuit of funding rather than genuine scientific inquiry. This strongly-worded criticism presents a stark contrast to the prevailing optimism surrounding AI.

A Profound Discontent with Current AI Practices

The passionate critique presented in the original Chinese text lays bare a profound discontent with the current state of artificial intelligence. The author paints a picture of a field obsessed with quick profits and superficial techniques, rather than a deep dive into fundamental principles. This sentiment mirrors similar criticisms often voiced by researchers concerned about the lack of rigorous study and the prevalence of "black box" approaches in many current AI applications.

The author's condemnation of "deep learning" as "dog shit" is a forceful expression of a belief that the current focus on complex algorithms without a strong theoretical foundation is fundamentally flawed. They argue that a critical understanding of the data's inherent properties—the nature of images, the meaning of words, the limitations of statistical models—is paramount. The assertion that current AI merely "copies" existing processes without understanding their core principles is a potent critique.

The analogy to "alchemy" or "elixirs" suggests a concern that current AI practice lacks a genuine understanding of the underlying principles of the problems being addressed. The author implies that the practice of "tuning parameters" without understanding the theoretical underpinnings is akin to a futile search for a magical solution.

Beyond the Critique: A Call for Deeper Understanding

While the author's critique is stark and potentially overly critical, it does raise crucial questions about the direction of AI research. The criticism highlights the importance of rigorous study and a commitment to understanding the fundamental principles of the data being analyzed. The author's frustration speaks to the need for a more theoretically grounded approach, one that prioritizes a deep understanding of the subject matter over the pursuit of quick results.

The article's raw emotion underscores the passionate dedication of researchers who feel that the field is deviating from its core principles. While potentially polarizing, this critique serves as a vital reminder that the true advancement of AI requires a commitment to fundamental understanding and a critical eye towards the methods used. Without addressing the concerns raised, the field risks becoming more of a "money-making" enterprise rather than a genuine scientific pursuit.

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