Software:AI Agent

From HandWiki
Short description: New type of software programs powered by AI


AI agent (or Autonomous AI agent or Autonomous LLM agent) is autonomous program powered by artificial intelligence, demonstrating the ability to independently generate, prioritize, and execute tasks in pursuit of a given objective, iterating until the objective is achieved.[1]. AI agents provide AI apps new capabilities through a combination of reasoning and planning, self-reflection, tool usage, and memory.[2]

Examples of popular AI agents are Auto-GPT, GPT-Engineer, Superagent, Aomni, or BabyAGI. These agents are designed to go beyond generating text and code; they function as versatile problem solvers. Autonomous agents can be applied across fields and serve variety of tasks, from managing a social media account, investing in the market, to coming up with the best children’s book.[3]

Characteristics

AI Agent Overview.png

In a LLM-powered autonomous agent system, the LLM serves as the agent's brain, supported by three key components:

Planning

Ai agents combine reasoning and acting, following the ReAct approach.[4]

Subgoal and decomposition: The agent breaks down large tasks into smaller, manageable subgoals, enabling efficient handling of complex tasks.[5]

Reflection[6] and refinement: The agent can do self-criticism and self-reflection on past actions, learn from mistakes and refine them for future steps, thereby improving the quality of final results.

Agents are guided to "think step by step,", following Chain of Thought[7], which helps breaking down challenging tasks into smaller, simpler steps.

Memory

Example of a generative agent architecture.png

Short-term Memory: Utilizes in-context learning for task-specific information.

Long-term Memory: Retains and recalls information over extended periods using external storage.

Tool Use

Agents can use "tools" by calling external APIs - for example, it can browse the web, use apps, read and write files, make payments, and even control a user's laptop[8]. Learns to utilize external APIs for additional information, enhancing capabilities beyond pre-training limitations.

History

On March 30, 2023, Auto-GPTwas released by Toran Bruce Richards, the lead game developer at video game company Significant Gravitas Ltd. Auto-GPT is an open-source autonomous AI agent based on OpenAI’s API for GPT-4, the large language model released on March 14, 2023. Auto-GPT is among the first examples of an application using GPT-4 to perform autonomous tasks.

Since then, AI agents have experienced a boom during Summer 2023.

OpenAI, that indicated before that it intended to allow users to define their own customizable AI agents[9], launched "GPTs" in November 2023[10], and the Assistants API, a developer-facing part of the GPTs. OpenAI avoided the term “AI agent” and used “GPTs”, even though they follow the characteristics of agents.[11]

Future

Anticipated within the next five years, the advent of AI agents promises a fundamental change[12]. Users will communicate with devices in everyday language, eliminating the need for multiple apps for distinct tasks. AI agents respond to natural language and execute various tasks based on a comprehensive understanding of the user, a concept that has evolved over nearly three decades and recently became practical due to AI advancements.

Common use cases

Today’s most common use cases are coding, personal daily tasks, or research. We may expect a further shift towards a vertical market, for example, one app with different underlying agents designed for code writing, code debugging, code migration, e-mail communication, calendar planning, and task management.[13]

Research

Research topics on AI agents include cognitive architecture for agents (e.g., CoALA framework[14]), multi-agent frameworks[15], reasoning and acting of agents[16], agents in various environments, benchmarking and evaluation.

To enhance the precision and reliability of answer quality assessment, a multi-agent evaluation framework[17] simulates the academic peer-review process within the AI agent context.

Impact on the software industry

Beyond transforming individual interactions, AI agents are predicted to revolutionize the software industry.[18] This shift is likened to the monumental change from typing commands to tapping on icons, signaling a significant computing paradigm shift. Andrej Karpathy envisions LLMs as kernels in a new operating system, indicating their growing importance[19]

Hundreds to thousands of people started to identify as AI Engineers[20]. There is a new ecosystem being formed around AI agents.[21]

References

  1. ↑ Schlicht, Matt. "The Complete Beginners Guide To Autonomous Agents" (in en). https://www.mattprd.com/p/the-complete-beginners-guide-to-autonomous-agents. 
  2. ↑ "AI Agents vs Developers" (in en-US). https://e2b-blog.framer.website/blog/ai-agents-vs-developers. 
  3. ↑ Schlicht, Matt. "The Complete Beginners Guide To Autonomous Agents" (in en). https://www.mattprd.com/p/the-complete-beginners-guide-to-autonomous-agents. 
  4. ↑ "ReAct: Synergizing Reasoning and Acting in Language Models". https://react-lm.github.io/. 
  5. ↑ "The State of Autonomous AI Agents" (in en). https://www.linkedin.com/pulse/state-autonomous-ai-agents-dean-meyer. 
  6. ↑ Shinn, Noah (2023-11-27), [NeurIPS 2023 Reflexion: Language Agents with Verbal Reinforcement Learning], https://github.com/noahshinn/reflexion, retrieved 2023-11-27 
  7. ↑ Wei, Jason; Wang, Xuezhi; Schuurmans, Dale; Bosma, Maarten; Chi, E.; Xia, F.; Le, Quoc; Zhou, Denny (2022-01-28). "Chain of Thought Prompting Elicits Reasoning in Large Language Models". ArXiv. https://www.semanticscholar.org/paper/Chain-of-Thought-Prompting-Elicits-Reasoning-in-Wei-Wang/1b6e810ce0afd0dd093f789d2b2742d047e316d5. 
  8. ↑ "The State of AI Agents" (in en-US). https://e2b-blog.framer.website/blog/the-state-of-ai-agents-reliability-sdks-benchmarking-and-market-trends. 
  9. ↑ Kinsella, Bret (2023-02-19). "OpenAI to Offer ChatGPT Customization and Shares Bias Guidelines". https://synthedia.substack.com/p/openai-to-offer-chatgpt-customization. 
  10. ↑ "New models and developer products announced at DevDay" (in en-US). https://openai.com/blog/new-models-and-developer-products-announced-at-devday. 
  11. ↑ Tizkova, Tereza (2023-11-07). "OpenAI DevDay" (in en). https://medium.com/e-two-b/openai-devday-d7286e484f0e. 
  12. ↑ Gates, Bill. "AI is about to completely change how you use computers". https://www.gatesnotes.com/AI-agents. 
  13. ↑ Tizkova, Tereza (2023-10-14). "The State of AI Agents" (in en). https://medium.com/e-two-b/the-state-of-ai-agents-c184b4f7dd0f. 
  14. ↑ Yao, Shunyu (2023-11-27), 🐨CoALA: Awesome Language Agents, https://github.com/ysymyth/awesome-language-agents, retrieved 2023-11-27 
  15. ↑ Wu, Qingyun; Bansal, Gagan; Zhang, Jieyu; Wu, Yiran; Zhang, Shaokun; Zhu, Erkang (Eric); Li, Beibin; Jiang, Li et al. (2023-08-16) (in en-US). AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation. https://www.microsoft.com/en-us/research/publication/autogen-enabling-next-gen-llm-applications-via-multi-agent-conversation-framework/. 
  16. ↑ "ReAct: Synergizing Reasoning and Acting in Language Models". https://react-lm.github.io/. 
  17. ↑ "On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering". https://paperreading.club/page?id=194511. 
  18. ↑ Gates, Bill. "AI is about to completely change how you use computers". https://www.gatesnotes.com/AI-agents. 
  19. ↑ Głogulska, Leokadia (2023-10-07). "The Future of Artificial Intelligence: LLMs as the Kernel Processes of a New Operating System" (in en-US). https://ts2.space/en/the-future-of-artificial-intelligence-llms-as-the-kernel-processes-of-a-new-operating-system/. 
  20. ↑ Vincent, James (2017-12-05). "Tencent says there are only 300,000 AI engineers worldwide, but millions are needed" (in en). https://www.theverge.com/2017/12/5/16737224/global-ai-talent-shortfall-tencent-report. 
  21. ↑ "AI Agents vs Developers" (in en-US). https://e2b-blog.framer.website/blog/ai-agents-vs-developers. 


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