This is extracted from C-10-S-0-response 1, part of experiment 10.
In this editorial, we will explore several articles that cover different aspects of artificial intelligence (AI) and its implications. We will delve into the use of AI in content creation, the hype around Artificial General Intelligence (AGI), the release of a new AI model by Mistral AI, the potential consequences of the AI bubble, and the dangers of automated chatbots. Through these articles, we will gain insights into the current state of AI and its impact on various industries and society as a whole.
The first article, "I Trained ChatG PT on My Notes To Create Content. Here’s What Happened", presents an experiment in which the author trained ChatGPT, an AI model, on their extensive notes to aid in content creation. The author explores three different approaches to utilizing AI in their notes but ultimately finds limited value in these methods. This highlights the current limitations of AI in generating meaningful and reliable content.
The second article, "Artificial General Bullshit. AI, AGI, and its other hallucinations…", takes a critical stance on the hype surrounding Artificial General Intelligence (AGI) and large language models. The author argues that these models are merely parlor tricks and emphasizes the need for responsible and ethical use of AI. They also discuss concerns such as economic hardships, enabling malicious actions, and loss of purpose or identity. Additionally, the article raises questions about liability and the open-sourcing of language models.
In "A Quiet Revolution? Mistral AI Releases Sensational New AI Model", we learn that startup Mistral AI has released a new language model called "Mixture Of Experts." This model, comparable to GPT4, combines highly specialized language models and employs a training method that utilizes sub-models and a gating network. The release of this model showcases the ongoing advancements in AI technology and brings new possibilities for language processing tasks.
The fourth article, "What kind of bubble is AI?", explores the potential consequences of the AI bubble. Drawing parallels with previous economic bubbles, such as the dotcom and crypto bubbles, the article discusses the risks associated with a potential burst in the AI bubble. Economic concerns, including the impact on the AI industry and the displacement of human workers, are highlighted. The article suggests that smaller AI models may survive a bubble burst, but raises concerns about the sudden disappearance of most AI technologies.
Finally, the article "Oops! We Automated Bullshit" sheds light on the potential dangers associated with automated chatbots, specifically focusing on ChatGPT. It points out the lack of logic and factual basis in text generated by these chatbots, as well as concerns expressed by experts about the generation of super-persuasive yet unintelligent text. The article also touches on the concept of "bullshit jobs" and how training people to generate meaningless content contributes to the proliferation of such jobs. Furthermore, it highlights the absence of algorithms to verify the truthfulness of AI-generated output, drawing parallels with how politicians can spread misinformation through Twitter.
Overall, these articles shed light on different facets of AI and its effects on content creation, responsible use, advancements in language models, economic bubbles, and the dangers of automated chatbots. They collectively emphasize the need for responsible and ethical AI practices, ongoing discussions, and guidelines to navigate the evolving landscape of AI. As AI continues to advance, it is essential to address the concerns and challenges it presents while harnessing its potential for the betterment of society.
I Trained ChatGPT on My Notes To Create Content. Here’s What Happened
The author trained ChatGPT, an AI model, on their extensive notes to assist with content creation. They explored three ways to use AI in their notes, including using AI features within each note, finding relevant notes or linking them together, and using AI to interact with their notes. However, they found limited value in these approaches and were ultimately disappointed with the results.
Artificial General Bullshit. AI, AGI, and its other hallucinations…
The author criticizes the hype around Artificial General Intelligence (AGI) and believes that large language models are just parlor tricks. The conference focused on responsible use of AI. The benefits of AI include raising efficiency and performing previously unattainable tasks, but there are also concerns about economic hardship, enabling evil at scale, and loss of purpose or identity. The author discusses the need for ongoing discussion and guidelines for responsible AI. They draw parallels with the print industry and raise questions about liability and open-sourcing language models.
A Quiet Revolution? Mistral AI Releases Sensational New AI Model
Startup Mistral AI has released a new language model that is comparable to GPT4. The model, called "Mixture Of Experts," combines several highly specialized language models and has a context size of 32k tokens. It uses a training method in which sub-models are used instead of a single model, with a gating network assigning tasks to the experts and combining their insights. The model can be tested on Poe.com and app.fireworks.ai/models.
What kind of bubble is AI?
The article discusses the potential consequences and risks associated with the AI bubble. It compares the AI bubble to previous economic bubbles, such as the dotcom bubble and the crypto bubble, and highlights the potential negative impact on the AI industry if investor subsidies dry up. It also examines the value and risk tolerance of AI applications and raises concerns about the potential displacement of human workers in certain industries. The article concludes by suggesting that smaller AI models may survive the bubble burst, but raises the question of what will happen if the AI bubble pops and most AI technologies disappear overnight.
Oops! We Automated Bullshit
The article discusses the potential dangers of automated chatbots, specifically ChatGPT, which has been found to generate text that sounds good but lacks logic or factual basis. MIT Professor Rodney Brooks and AI expert Geoff Hinton express concerns about chatbots generating super-persuasive yet unintelligent text. The article also highlights the concept of "bullshit jobs" and how training people to generate bullshit contributes to the prevalence of such jobs. Additionally, it mentions that ChatGPT lacks an algorithm to verify the truthfulness of its output, which parallels how politicians use Twitter to spread bullshit that can then be used to train automatic bullshit generators.