2/8 The system can complete tasks, generate new tasks based on results, and prioritize tasks in real-time. It demonstrates the potential of AI-powered language models to autonomously perform tasks within various constraints and contexts.
LLMS
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Autonomous Agent Architecture with GPT-4 Pinecone LangChain
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3/8 The autonomous agent uses GPT-4 for task completion, Pinecone for efficient search and storage of task-related data, and the LangChain framework to enhance decision-making processes. #GPT4 #Pinecone #LangChain
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Autonomous Task Management in AI-Powered Language Models
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4/8 The system maintains a task list for managing and prioritizing tasks. It autonomously creates new tasks based on completed results and reprioritizes the task list accordingly, showcasing the adaptability of AI-powered language models.
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Task-Driven Autonomous Agent with GPT-4 and LangChain
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1/8
Introducing " Task-driven Autonomous Agent" An agent that leverages @openai
's GPT-4, @pinecone vector search, and @langchain framework to autonomously create and perform tasks based on an objective. "Paper": https://
yoheinakajima.com/task-driven-au
tonomous-agent-utilizing-gpt-4-pinecone-and-langchain-for-diverse-applications/
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Comparing Neural Parameters to LLM Parameters: Apples and Oranges
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Yeah, I agree, I would not use number of neurons/synapses/dendrides/etc as the number of parameters that can be compared to LLM parameters. These are very different systems. It's like comparing apples and oranges 🙂
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Physics-Grounded AI Agents: Learning, Reasoning, Robotics Integration
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1) learning from experience (although you already mentioned it in the dynamic memory part) 2) physics grounding: llm-agent that can observe and act in an environment, reason spatially, plan, etc 3) integration with robotics
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GPT-4 Regulation Agreement: Definition and Implementation Questions
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I wonder how this will work out… So many questions. – How many people who are actually working on systems that exceed GPT-4 will sign this? – What is a system that exceeds GPT-4 ? How about React / Self-reflective agent build on LLAMA? – Why 6 months? What is it going to
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Google CoLT5 Processes Long Inputs via Conditional Computation
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Google’s CoLT5 Processes Extremely Long Inputs via Conditional Computation https://
syncedreview.com/2023/03/28/goo
gles-colt5-processes-extremely-long-inputs-via-conditional-computation/
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ChatGPT and GPT-4: Parameter Efficiency in Knowledge Distillation
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We don't appreciate enough that ChatGPT & GPT-4, using just a few hundred GB of parameters, can distill immense human knowledge, and display exceptional reasoning & generalization skills. And you? How many GB of parameters are in your brain?
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LLMs Integrated into Medical Care Plan UI
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🩺 Now that LLMs can pass Medical Licensing Exams, they have been built into a great UI for generating medical care plans.
— AI Breakfast (@AiBreakfast) 28 mars 2023
Try Glass Health AI 2.0: https://t.co/RbcaE26WNZpic.twitter.com/T2yEUZSnMsNow that LLMs can pass Medical Licensing Exams, they have been built into a great UI for generating medical care plans. Try Glass Health AI 2.0: http://
glass.health/ai