Large Language Models (LLMs) are often hailed as the next frontier for AI, ushering in a new era of technological advancement. In the realm of artificial intelligence, we hark back to the days of old when the Turing Test served as the benchmark for determining machine intelligence. This test, named after the esteemed Alan Turing, often referred to as the Father of Artificial Intelligence, revolved around the evaluation of natural language conversations between a human and a machine designed to emulate human-like responses. Picture a scenario where a human judge engages in text-based exchanges, unaware of which conversational partner is the machine. If the judge cannot reliably distinguish the machine from the human, the machine would be deemed successful in passing the test.
Enter ChatGPT, a remarkable computer program created by OpenAI. This ingenious creation has already proven its mettle by passing the Turing Test. Thousands upon thousands of web pages, media articles, and news pieces have been penned by ChatGPT, without anyone realizing it. Recognizing the potential of this breakthrough, Microsoft made a bold move, investing a staggering 10 billion USD in OpenAI with the intention of integrating this functionality into its products, thereby reaping the benefits. Microsoft’s CEO, Satya Nadella, renowned for his strategic prowess in acquiring LinkedIn, Skype, and Github, displayed shrewd foresight. However, as is often the case with ambitious endeavors, Satya’s gamble did not yield the desired outcome. Nevertheless, I am confident that Microsoft will persevere and overcome any challenges encountered on this innovative path.
Stepping back for a moment, we realize that the true opportunity lies not solely in monetary gains. Just last month, the distinguished scientist Steven Wolfram eloquently expounded upon the significance of ChatGPT in a lengthy treatise. It became increasingly apparent that ChatGPT constitutes a genuine scientific discovery. After careful examination and reflection, I find myself inclined to concur with Wolfram. The mere fact that this program functions so effortlessly hints at something extraordinary—language itself is inherently computable.
This revelation bears profound implications for our understanding of the human brain and intelligence. It demonstrates that the knowledge embedded within language can be compressed and modeled. ChatGPT and Stable Diffusion possess the uncanny ability to generate text and images that resonate with our human cognition. However, it is disconcerting that Wolfram barely touched upon a sobering aspect of this revelation.
The reason ChatGPT succeeded lies in the realization that crafting text that appeals to human sensibilities is not as formidable a challenge as previously believed. Such a realization humbles us and evokes a sense of trepidation, for it potentially provides an explanation for the Fermi paradox. Perhaps there is no insurmountable barrier impeding interaction with other civilizations; instead, we may simply lack the level of intelligence required for meaningful engagement. As Neil deGrasse Tyson succinctly phrased it, “Maybe aliens glanced at Earth and concluded, ‘We don’t see any signs of intelligence here.'”
Let us ponder this: OpenAI engineers invested countless hours, while their company dedicated a staggering 60 million dollars to train a 175 billion parameter model/algorithm, thereby birthing ChatGPT, a masterful generator of human-like text. Yet, in a surprising turn of events, Andrew Karpahy, a former Tesla AI engineer, managed to create a similar program within a mere two hours. Perhaps our self-perception of human intellect warrants reevaluation—we may not be as astute as we perceive ourselves to be.
Zooming in on the realm of technology companies, LLMs have stirred up a sense of panic within Google’s ranks. As I mentioned earlier, Google has encountered considerable challenges in commercializing AI technology. The struggle seems to emanate from the fact that these technological behemoths are no longer helmed by their visionary founders but rather by MBA-trained technologists, who prioritize product enhancement and financial gains.
Furthermore, political division and a lack of unity have spurred employee activism within companies like Google and Apple, with their focus shifting toward social causes rather than breakthroughs in AI technology. In essence, Google has become overly sensitive and excessively MBA-oriented, impeding its ability to create something as groundbreaking as ChatGPT.
As for Apple, one must inquire, “Are you alright?” Apple continues to produce exceptional products, with the spirit of Steve Jobs seemingly roaming their headquarters, relentlessly urging employees to preserve the fusion of art and innovation that defines the company. Unfortunately, Siri remains underwhelming, and Apple lacks cutting-edge AI technology that can rival the offerings of Google, Facebook, Microsoft, or OpenAI. Regrettably, Apple’s focus lies primarily on artistry and remarkable products, neglecting the realm of AI. Apple, with its noble ethos, possesses the potential to harness AI technology for the betterment of humanity. Yet, instead, they offer us another season of Ted Lasso.
While I can delve into the enthralling intricacies of ChatGPT’s inner workings for the benefit of my readers, I recognize that the general public may not harbor an avid interest in such technicalities. Such matters typically captivate the minds of devoted enthusiasts. However, if you happen to be curious and seek to explore these details, feel free to leave a comment or reach out via email. I am more than willing to engage in an enlightening conversation.
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