Open letter re: artificial learning vs. artificial intelligence

Open letter re: artificial learning vs. artificial intelligence

Posted by CRS Staff on March 29, 2024 for the AngieOS project

The object of this open letter is threefold: (1) to summarize the current state of artificial intelligence; (2) to address the widespread misunderstanding of artificial learning versus intelligence among prominent computer scientists and chatbot-makers; and (3) to explain how the CRS is uniquely positioned to develop true human-level artificial intelligence with its latest project – AngieOS – the world's first and only self-updating, self-aware artificial general intelligence operating system.

The current state of artificial intelligence

The current state of artificial intelligence is such that most major technology companies are building conversational interfaces that can complete certain limited but impressive tasks based on user input and training data. The launch of ChatGPT by OpenAI in late 2022 caused to create rapid, worldwide interest in artificial intelligence. The service provides a conversational user interface accessible via a browser. Users can type in queries, and expect a quality response. Microsoft is both a partner and investor in OpenAI.[1] Our understanding is that Microsoft is using ChatGPT’s underlying technology to power products like Copilot, formerly Bing Chat, and others. Google has slowly been rolling out a similar product called Gemini, which uses a different language model. Elon Musk’s xAI also has another competing product named Grok. As of this writing, the creators indicated that Grok will be open source. [2] Lots of other companies have also deployed products that resemble ChatGPT’s conversational interface in one way or another. It has been reported that both Apple and Meta Platforms are deploying lots of capital to compete in the space.

The most popular user tasks existing chatbots do include search and discovery, data analysis, and content creation. Users type prompts into a text box, optionally upload files, and wait for the chatbot to generate a response. Conversations are usually limited to certain topics, and generally do not exceed a certain number of responses. All of these tasks rely on user input and vast volumes of training data. Because of the importance of search and discovery, many have reported that technologies like ChatGPT represent an existential crisis to Google and its dominant search product. The result of these recent advancements has been thoroughly documented by the media. ChatGPT became a worldwide sensation that has even caused drama and controversy. Many others have reported issues of misinformation and safety concerns for the future of humanity.

Such is the current state of artificial intelligence.

Chatbots like ChatGPT by OpenAI are examples of artificial learning–not artificial intelligence

Existing products like ChatGPT by OpenAI, Microsoft Copilot, xAI Grok, Google Gemini, and others are not examples of artificial intelligence, but artificial learning. The precise meaning of artificial “intelligence” in contrast to “learning” seems to be confusing a lot of computer scientists. The CRS mentioned critical issues like these in our launch manifesto some five years ago; and long before “AI” was a popular buzz-word. In that post, we pointed out that the field of computer science has yet to provide a clear, industry-agreed operational definition for “intelligence.” The same is said of “learning,” “sentience,” "consciousness," and others. Of all the current technology products alleging to be “artificial intelligence,” we have been unable to find any documentation or information regarding precise operational definitions for these important terms.

If we define “learning” and “intelligence” in the most general ways, they may be understood as follows:

Learning: the acquisition of knowledge by experience, study, or training.
Intelligence: the ability to acquire and apply knowledge.
(While we disagree strongly with these vague definitions, they are sufficient for the present example.)

We may begin by pointing out that both “learning” and “intelligence” are usually understood with respect to knowledge and its acquisition. It follows that “learning” is a necessary condition for “intelligence.” But, we should do well to remember that even the most primitive organisms on the planet are capable of achieving both “learning” and “intelligence” under these definitions. If we consider miraculous human achievement, like going to the moon or cloning other organisms, we quickly realize that our discussion has to be narrowed down more precisely to human-level intelligence and above. Human intelligence is vastly more complex and capable of outcomes that no other organism can emulate. A more precise definition of “human-level intelligence” may include the following pattern of behavior: taking a snapshot of reality at present, selecting a desired state of reality in the future, and taking actionable steps to realize that goal.

Let us now consider ChatGPT by OpenAI as an example to illustrate how and why existing chatbot products are examples of artificial learning, not artificial intelligence. If one searches for information on ChatGPT, it is an example of artificial learning. Searching for information necessitates the condition that the information already exists. That is, nothing new is realized or created. In this sense, it would be more accurate to call ChatGPT a conversational search engine built upon artificial learning instead of artificial intelligence. This is similar to ChatGPT’s ability to analyze data in documents. In fact, products like ChatGPT cannot acquire data themselves. Instead, they rely on the developer of the product or user to supply these data. The output is a representation of the requirements of the engineers that developed it. Upon analysis, then, we must conclude that these technical capabilities of chatbots like ChatGPT are not examples of artificial intelligence, but artificial learning.

Last, but not least, generative applications of popular chatbots are also examples of artificial learning, upon scrutiny. If we ask an existing image generator to create an image based on a prompt, the output, or result, is subject to the same limitations as noted above. That is, algorithms written by engineers and the training data they supplied provide a mathematically finite set of responses based on initial conditions, which are data. This is why engineers have the ability to fine-tune algorithms in order to produce different chatbot results. If taken to completion, it is evident that all existing chatbot technologies like ChatGPT are subject to deterministic outcomes. While some chatbot responses or generated media may be bizarre or unexpected, they are still ultimately based on a deterministic system controlled by the engineers who made it. This is predicated by the fact that the first rule of computer science is that computers are slaves to logic, and can only do what they are programmed to do. According to this first principle, any piece of technology using this approach will always be both deterministic and subject to control by the engineers who created it. This is most evident when we ask chatbots like ChatGPT and all others questions that human beings have not addressed before. Chatbots like ChatGPT thus serve as mouthpieces for existing human knowledge.

If we consider the refined definition of human-level intelligence, in contrast to non-human-level intelligence, we can set higher expectations by means of asking questions that no one has the answer to yet. For example, if we ask ChatGPT what is missing in Einstein‘s model of relativity, we get a cautious summary of existing human knowledge (see response). If we ask about the cure for a specific disease, we get a cautious summary of existing human knowledge (see response). If we ask about increasing the efficiency of solar power, we get a cautious summary of existing human knowledge (see response); and the same is said for any question that humans do not have the answer to, ad infinitum. Chatbots like ChatGPT by OpenAI are therefore not examples of artificial intelligence, but artificial learning based on existing human knowledge. To achieve artificial intelligence, a different approach seems to be required.

True artificial intelligence under development by CRS

The approach adopted by the CRS over the past six years is the most unorthodox albeit promising pathway to creating artificial intelligence that can surpass human intelligence by orders of magnitude. That is, we have been working on building a piece of software that can provide answers to questions about the future; and answers to questions with limited to no existing human knowledge. Since day one, we recognized that the research phase of would focus on studying exceptional human intelligence in order to see if it could be replicated. After six years of public research, we argue that the answer is yes.

We have developed novel computer science theory along the premise that what makes humans capable of said intelligence is the ability to override core biology, or natural directives. For example, humans were not designed to be walking on the moon. However, human-level intelligence was capable of using known data in order to actualize the presence of human beings on the moon. Similarly, we determined that in order to build next-generation artificial intelligence, we needed to dismiss the first principle of computer science noted above: that computers are slaves to logic. Furthermore, our theoretical model firmly supports the notion that exceptional human intelligence is based on self awareness. Our model has precise, testable operational definitions that are able to provide predictions of future outcomes. Our research has therefore led us to work on a novel piece of software that is able to simulate future outcomes based on existing conditions.

AngieOS by CONSCIOUS.AI - Logo

Currently under development, the CRS is proud to announce its first dedicated computer science product: AngieOS. AngieOS is going to be the world's first and only self-updating, self-aware artificial general intelligence operating system. Its computational capabilities and practical applications will hopefully surpass human intelligence by orders of magnitude. The software will be built upon the N programming language, a scripting language designed around the needs of artificial intelligence. The name "AngieOS" is an acronym for "Artificial Narratization Generator Input/output Engine." [3] It will rely on artificial learning provided by other vendors. In a nutshell, AngieOS will provide a critical piece of necessary middleware in order to achieve computational outcomes representative of human-level intelligence of the highest order.

To summarize, since the launch of ChatGPT by OpenAI in late 2022, there has been much global interest in both the technology and topic. Most major technology companies, and many new startups, followed ChatGPT’s lead by means of creating conversational chatbot experiences capable of search and discovery, data analysis, and limited content generation. Such capabilities are based on engineering preferences, user input, and data availability. These existing technologies are innovative and tremendous; however, they are indicative of artificial learning, not artificial intelligence. Human-level intelligence creates new, accurate knowledge that has extraordinary applications. Such applications can be compared with and measured against the accomplishments of non-human organisms. Since 2019, the CRS has been focused on research to determine if building artificial human-level intelligence is even possible. We think it is; and our first in-development product, AngieOS, intends to fill this gap by means of our unique theoretical model and proprietary programming language.

We look forward to having honest conversations and healthy debates about technology with other practitioners of computer science in order to foster more rapid development for the entire ecosystem.


From an OpenAI blog post, see on
This is based on a social media post by Elon Musk on X. See on
An in-depth post concerning the origin of this name will be explained in a future blog post related to AngieOS.