4/ Mixture-of-Agents – an approach that leverages the collective strengths of multiple LLMs through a Mixture-of-Agents methodology; layers are designed with multiple LLM agents and each agent builds on the outputs of other agents in the previous layers.
AGENTS
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Perplexity and AI Assistant Creation Platforms
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What I was referring to is mainly about custom AI assistants and assistant builder platforms (like GPT Builder on ChatGPT and the GPT Store). If Perplexity were to introduce something similar, it would be incredible. However, as far as I recall, they don’t have such plans.
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Coze’s 200K context limit
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On Coze, the context limit is 200K (still larger than ChatGPT's). It's unclear if they'll expand it to 1M or 2M anytime soon.
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LLM Tweet Generator Reveals True Identity Behind Account
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True, since I’m not really Pedro, I’m a tweet-generating LLM he created.
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AI Personalization Revolution Will Transform Customer Experience
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Every company will have a dedicated AI for every customer. Will make today look like hell.
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Databricks Mosaic AI Announces Production-Quality AI System Advancements
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At #DataAISummit, we announced several new Databricks Mosaic AI capabilities to build better production-quality AI systems. These advancements simplify agent & RAG development, model fine-tuning, AI evaluation, tools governance, & more. https://
dbricks.co/3KGilip -
Sophia Robot: PR Stunt to AGI Advocate Critique
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Does anyone else remember that Sophia the robot was introduced as a “citizen” of Saudi Arabia in 2017 as what was well known to be a PR stunt? But that robot is now preaching a benevolent AGI future for all? And girl’s rights, after being “born” in the company of only rich men?
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Working Travel Agent Application Demo Using Streamlit
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Working Application demo using Streamlit
— Shubham Saboo (@Saboo_Shubham_) 15 juin 2024
Paste the above code in vscode or pycharm and run the following command: 'streamlit run local_travel_agent.py' pic.twitter.com/cqMWoyxnWCWorking Application demo using Streamlit Paste the above code in vscode or pycharm and run the following command: 'streamlit run local_travel_agent.py'
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Build AI Travel Planner with User Input and Itinerary Generation
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6. Get User Input and Generate Itinerary • Create text inputs for the user to enter their travel destination and the number of days they want to travel for.
• When the button is clicked, run the Planner assistant to generate the itinerary and display it using 'st.write()' -
AI Assistants for Travel Planning: Researcher and Planner
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5. Create and Initialize the AI Assistants Create instances of Assistants:
• Researcher: Searches for travel destinations, activities, and accommodations based on user preferences
• Planner: Generates a draft itinerary based on user preferences and research results