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Possible consequences of current developments

  1. WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia

    • Benefits:

      • Achieving 97.9% factual accuracy in conversations with human users helps to address one of the major concerns with large language model chatbots, which is their tendency to generate inaccurate or misleading information.
      • By grounding the chatbot’s responses in information sourced from Wikipedia, the accuracy and reliability of the conversations can be significantly improved.
      • This can enhance the usefulness of chatbots in providing accurate information to users, helping with tasks like answering questions, offering explanations, and providing recommendations.
      • It can also contribute to reducing the spread of misinformation and fake news, as the chatbot’s responses are fact-checked against reliable sources before being shared with users.

    • Ramifications:

      • While improving factual accuracy is crucial, there is a risk of over-reliance on information from Wikipedia, which may not always be completely accurate or up to date.
      • The chatbot’s responses may still be limited to the information available on Wikipedia, potentially leading to biased or incomplete answers.
      • It is important to ensure that the grounding process is done accurately, as any inaccuracies in the grounded information may be propagated by the chatbot, leading to the potential spread of misinformation.
      • Chatbots that heavily rely on pre-existing information sources like Wikipedia may struggle with providing personalized or context-specific responses, since they are primarily trained on general knowledge and may lack the ability to understand nuanced queries or situations.

  2. I built marimo - an open-source reactive Python notebook that’s stored as a .py file, executable as a script, and deployable as an app.

    • Benefits:

      • The marimo tool provides flexibility for Python notebook users, allowing them to store their notebooks in the more commonly used .py file format.
      • Executability as a script enables automation, allowing users to run the code without having to open a notebook interface.
      • The deployability as an app feature enables users to easily create and share interactive applications or dashboards, making it more accessible for others to interact with their code and analysis.
      • It can enhance collaboration and reproducibility of code, as Python scripts are typically more version-control-friendly than notebooks.

    • Ramifications:

      • While storing notebooks as .py files may provide advantages in terms of executability and version control, it may also limit the interactive and exploratory characteristics offered by notebook interfaces.
      • Some notebook-specific features, such as inline visualizations or interactive widgets, may not be easily converted to the .py file format.
      • There may be compatibility issues or limitations when deploying the app, depending on the chosen deployment platform or target system’s specifications.
      • The tool’s effectiveness and ease of use may depend on user familiarity with Python and its associated libraries, potentially excluding those who are less experienced in programming.
  • Meet TinyLlama: An Open-Source Small-Scale Language Model that Pretrain a 1.1B Llama Model on 3 Trillion Tokens
  • Tencent releases LLaMA-Pro-8B-Instruct Chat Demo on Hugging Face
  • A New MIT Research Announces a Vision Check-Up for Language Models
  • Computer Vision In Self-Driving Cars

GPT predicts future events

  • Artificial general intelligence (AGI): By 2030

    • AGI refers to highly autonomous systems that outperform humans at most economically valuable work. While the timeline for AGI development is uncertain, many AI researchers and experts predict that AGI could be achieved within the next decade or two. The rapid advancements in machine learning, natural language processing, and robotics contribute to the notion that AGI could become a reality by 2030.

  • Technological singularity: By 2045

    • Technological singularity refers to the hypothetical point in the future when AI surpasses human intelligence, leading to rapid self-improvement and an unpredictable impact on society. The timeline for the singularity is mostly speculative, but some academics like Ray Kurzweil predict it will occur by 2045 based on the accelerating pace of technological advancements. However, it remains a controversial topic with varying opinions among experts.