Emerging capabilities of INDIGO TALK / AutoGPT and GPT4 – EP06

/ Indigo's Digest

Original link: https://www.indigox.me/indigo-talk-ep06/

Emerging capabilities of INDIGO TALK / AutoGPT and GPT4 - EP06

In the sixth INDIGO TALK, Dai Yusen (Yusen), the managing partner of ZhenFund, is also the co-founder of Jumei Youpin. He is a successful entrepreneur and senior angel investor who has fully experienced the mobile Internet era. Under the background of the professional background, let’s talk about the new capabilities emerging from the recently popular AutoGPT and GPT4, as well as the new organizational form of intelligent agents and thoughts on AI entrepreneurship supported by large language models. As always, we will discuss AGI at the end impact on society.

To listen via Spotify or Apple Podcasts, click here !

Guest of this issue

Yusen (Dai Yusen – Managing Partner of ZhenFund)
Indigo (digital mirror blogger)

timeline

00:00:23 – Guest introductions at the opening of the program

00:03:03 – A paradigm shift between ChatGPT and AutoGPT

00:14:15 – Emergence of GPT 4 capabilities and connectionism

00:35:31 – Opportunities from ChatGPT Plugin features

00:45:34 – How to see AI entrepreneurship under the big language model

00:59:31 – New organizations run through intelligent agents

01:07:37 – The impact of the advent of AGI on society

01:19:52 – Summary of the conversation by INDIGO

01:25:56 – Summary from YUSEN

content outline

If there was only one thing to watch in the AI ​​world this April, it would have to be AutoGPT , which takes human use of large language models to a new level. Although the current technology is still limited and the task completion is relatively low, this conversion from language model to ” cyber embodiment ” is very important. For a detailed discussion on AutoGPT, please refer to orange.ai ‘s ” AutoGPT, from language model to Cyber ​​Embodiment “. In such an era where the growth rate of the model exceeds the speed of your startup and product development? How should we face this reality? What are the new opportunities for GPT-4’s more powerful reasoning capabilities? Also listen to this conversation!

The following content is generated by GPT-4 based on the dialogue content of each discussion summary (Prompt: summarize with ten meaningful points)

A Paradigm Shift with ChatGPT and AutoGPT

  • The artificial intelligence industry is developing rapidly, with new technologies and advancements appearing every day, such as the recent AutoGPT.
  • Large language models, such as ChatGPT, have rapidly broadened the application scenarios of AI in different fields.
  • The core change of AI technology lies in the combination of language and tools to improve the efficiency of all walks of life.
  • Although AutoGPT is still relatively rough, its development potential and advantages are obvious enough to change the entire technology ecology.
  • Language, knowledge, and logic are the three levels of the big language model, among which the logic level is the most challenging.
  • AI products such as ChatGPT not only enable ordinary users to directly use the new generation of AI technology, but also expand the market application of the entire AI technology.
  • The future development direction of AutoGPT is to focus on a certain field and improve execution efficiency.
  • AutoGPT realizes functions such as task automatic planning, tool invocation and result evaluation, which is similar to the way humans solve problems.
  • The componentization of AI technology enables various technologies to call and cooperate with each other to form a more powerful system.
  • Through laboratory practice, the integration and improvement of large language models in specific fields are realized.

Capability Emergence and Connectionism in GPT 4

  • Microsoft previously released a research paper on GPT-4, focusing on its emerging potential.
  • GPT-4 has powerful potential, such as reasoning, planning, problem-solving, and verification.
  • Software has entered the 2.0 era, and neural networks and algorithms are used together to form software for training.
  • Researchers have gradually realized that GPT-4 already has the characteristics of AGI in the embryonic stage.
  • The emerging ability of GPT-4 may become the main development direction of AI in the future, and the planning of complex tasks occupies a key position in its development process; it shows a strong generalization ability and solves many tasks that GPT-3.5 cannot solve.
  • GPT-4 has a richer worldview, and it is difficult for researchers to explain why, but it has many similarities with the way humans know and understand.
  • The order that artificial intelligence generates from chaos may become the norm for intelligence. The symbolism-connectionist debate may be triumphant in the field of AI.
  • Much of the research in quantum mechanics and beyond is about finding what works and then exploring how it works.
  • Philosopher Wittgenstein’s view of the continuity of the world inspires thinking about semiotics.
  • Currently training large language models such as GPT-4 creates a new form of intelligence for humans that is sometimes difficult to explain with human logic and rationality.
  • With the development of AI technology, we are entering an era in which humans and other intelligent agents jointly explain the world.
  • At present, the moral, social and legal status of AI has yet to be discussed, such as whether AI should enjoy similar human rights.
  • Future AI evolution may include new capabilities such as self-prompt, self-iteration, and self-drive, so as to be closer to human thinking patterns; AI’s logical ability and sense of purpose are expected to become stronger in future versions, which will help future Develop together.

In the future, AI may realize self-learning and real-time interaction in the common development with human beings, further simulating human thinking mode. How AI is perceived and used is influenced by subtle factors such as its origin, entity, and relationship to humans. As technology advances, we need to adjust our perceptions and attitudes towards AI accordingly.

Opportunities with ChatGPT Plugin Features

  • GPT-4 released the plugin function, which lowered the threshold for use and attracted many programmers to try.
  • The Plugin function makes up for the lack of information in ChatGPT by accessing external data sources.
  • Realize natural language-driven glue programming through plug-in functions, and simplify API docking.
  • Plug-ins enable ChatGPT to have stronger logic and code execution capabilities, forming a smarter assistant.
  • As a platform, ChatGPT can access third-party services to realize assistant-to-assistant scenarios.
  • Chat mode may become the main form of human-computer interaction in the future.
  • In the future, the App design logic may focus on language interaction to simplify interface operations.
  • AI will expand from generative capabilities to the ability to execute code, browse the web, and more.
  • Solve and optimize the efficiency of user query assistants by combining plug-in functions and external data sources.
  • The integration of languages ​​and existing tools into the industry environment will create transformative changes, opening up new opportunities for investment markets and end users.

How to look at AI entrepreneurship under the big language model

  • It is difficult to predict the future in the early stages of a technological revolution, so keep an open mind as much as possible.
  • The experience accumulated by early entrepreneurs in technological change has high barriers.
  • Profound technological change can come from innovations that at first appear to be toy-like.
  • Young people are more adaptable to the technological revolution, have a more open mind and have more time to try.
  • The competition between open source and closed source ecology, how to choose the appropriate technical framework.
  • The development space and future possibilities of the middle layer framework.
  • Attempts to reduce the cost and improve efficiency of AI models, such as Colossal.AI .
  • Pay attention to the active exploration of the younger generation in the field of AI, and discover entrepreneurs with potential and innovative spirit.
  • We should pay attention to the development process from the bottom big model to the middle layer framework to the specific application, and pay attention to the changes and opportunities at all levels.
  • Actively try new things, maintain a sense of AI, and personally experience and use new products and technologies.

A new organization run through intelligent agents

  • In the transformation of the intelligent age, the core goal is to seize the important trends and opportunities in the transformation period.
  • AI large models such as GPT-4 play a key role in the age of intelligence.
  • Utilize existing open source technologies and medium-scale models, combined with large models, to achieve mission planning and intelligent operations.
  • Organize AI models with different capabilities to perform more complex tasks or complete tasks faster.
  • Across the digital world and the real world, realize the all-round cognition and understanding of the intelligent body.
  • An organization based on intelligence will no longer be composed of people, but an organic system.
  • In the future, there may be a more efficient communication language between AIs instead of the current natural language.
  • Having sufficient computing power and data resources becomes the basis for training different occupations and division of labor.
  • In the ever-evolving field of AI, future finality remains uncertain.
  • Training AI with different capabilities to adapt to different tasks and scenarios can create more value.

In conclusion, the age of intelligence brings many new opportunities and challenges. We need to fully grasp the development of AI and utilize models of different capabilities to solve more complex problems. In the future, we may see more intelligent and automated organizations and applications.

The impact of the advent of AGI on society

  • With the advent of the AGI (General Artificial Intelligence) era, what is most lacking is energy, such as nuclear fusion and other new energy technologies.
  • The development of artificial intelligence and computing power requires the efficient development and utilization of energy, and the conversion of energy into computing power that serves human beings.
  • The future production method will become simpler and simpler, mainly relying on electricity for new intelligent manufacturing.
  • The world of bits will change much faster than the world of atoms; we always underestimate things in the world of bits, but overestimate things in the world of atoms.
  • The current AI development has a ladder attribute, and new technologies and paradigms may bring about sudden progress.
  • Not only should we pay attention to AI technology itself, but also its influence in sociology and psychology.
  • Human beings may not be ready to deal with all kinds of changes in the age of intelligence.
  • The era of AI poses great challenges to safety, ethics, etc., and corresponding rules and constraints need to be formulated.
  • Artificial intelligence is developing very fast, and it is easy for humans to look at problems with inertial thinking.
  • Humanity needs to be better prepared for the arrival of the AI ​​era, including addressing issues such as unemployment, ethics, and safety.
  • For the development of AI, we need to remain cautiously optimistic and pay attention to core issues such as alignment and safety.

related reference

Crossing the chasm – proposed by Jeffery Moore in 1991

AutoGPT – An experimental open-source attempt to make GPT-4 fully autonomous.
A more detailed introduction: refer to orange.ai ‘s ” AutoGPT, from language model to cyber embodiment “

Sparks of Artificial General Intelligence: Early experiments with GPT-4

Translation from ZhenFund:
The most detailed full-text translation (Part 1)｜Microsoft’s 155-page project reveals GPT-4 superpowers for the first time
The most detailed full-text translation (below)｜Microsoft’s 155-page project reveals GPT-4 superpowers for the first time

Sparks of AGI video version:
Sparks of AGI: early experiments with GPT-4 – Sebastien Bubeck

GPT-4 launch eve interview with Ilya Sutskever – kunchengblog translation video: GPT-4 Creator Ilya Sutskever

Yann LeCun on a vision to make AI systems learn and reason like animals and humans
Translation: The ability to learn ‘models of the world’ is key to building human-level AI
Turing Award Winner Yann LeCun

AI for the Next Era
Video: OpenAI’s Sam Altman on the New Frontiers of AI

ChatGPT Plugins – Plugins are tools designed specifically for language models with safety as a core principle and help ChatGPT access up-to-date information, run computations, or use third-party services.

LangChain – a framework for developing applications powered by language models

Colossal.AI – maximize the runtime performance of your large neural networks

In the era of big language models, who understands you better, AI or humans? – Picking Up Elephants x True Talk

Alignment

In the field of artificial intelligence, AI Alignment (alignment) research aims to guide the development of artificial intelligence systems towards the goals and interests expected by the designers. An aligned AI system advances the achievement of a desired goal; a misaligned AI system is capable of advancing a goal, but not the desired goal.

Emerging capabilities of INDIGO TALK / AutoGPT and GPT4 - EP06

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