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... 21:39
Ollama Deep Researcher: Amazing Web AI Research Assistant and AI Agents - Install and Run Locally

Aleksandar Haber PhD

1+ months ago 1K views

This tutorial explains how to install and run the Llama Deep Researcher model using the AMA framework on a local computer. The speaker emphasizes the ease of installation, the model's ability to perform comprehensive web searches, and summarize findings using iterative cycles. Key features include integrating large language models and enhancing AI agents to gather and process information effectively. Steps include downloading necessary components, setting up a Python environment, and configuring model parameters to facilitate advanced research capabilities. A practical demonstration follows, showcasing the model’s performance in gathering relevant AI literature.
01:57 - 02:10

Explains how Llama Deep Researcher can combine web searches with language models.

Ollama Machine Learning Research & Innovations
... 10:1
FREE Local AI Chat: No Subscriptions Needed (Open WebUI Setup Guide)

Leon van Zyl

1+ months ago 1K views

Ollama facilitates downloading and running large language models locally for offline, secure access. To enhance user experience beyond terminals, Open Web UI offers a visually appealing chat interface that integrates seamlessly with Olamo. Users can choose from downloaded models, engage in conversations akin to ChatGPT, upload files, and use code interpreters. The setup involves installing Olamo, downloading models, and utilizing Docker for Open Web UI. This allows users to interact with models like Llama 3.2, explore multimodal capabilities, customize system prompts, and leverage reasoning models for tasks like trip planning, thereby enhancing AI applications in practical scenarios.
02:52 - 03:06

Utilizing Docker for Open Web UI simplifies model deployment and access.

Ollama Chatbots Tech & Hardware
... 8:27
100% Local OpenAI Agents with Ollama in 8 mins!

Mervin Praison

1+ months ago 4K views

OpenAI Agents SDK enables the creation of AI agents entirely offline and privately, using the Llama 3.2 model and the OLLAMA framework. This video tutorial guides on building a research agent for internet searches, integrating a custom internet search tool, and running multiple agents seamlessly. Steps include setting up the environment, coding the agent functionality, and building a user interface for interaction. The final product is a news assistant capable of fetching and presenting news articles based on user queries in real-time, while maintaining local server functionality and privacy.
06:08 - 06:23

Execution of multi-agent workflow to provide formatted current news.

Ollama Natural Language Processing (NLP) Education
... 9:33
🦉 OWL Fully FREE Manus Alternative General AI Agent Tested locally FROM CAMEL-AI

Rithesh Sreenivasan

1+ months ago 4K views

A new AI agent named Owl from Camel AI offers an innovative framework for multi-agent collaboration and task automation. It features real-time information retrieval capabilities, leveraging online sources like Wikipedia and Google. Owl can process various data types including videos and images, automate browser tasks, and execute Python code with built-in toolkits. Users can install Owl locally via a Gradio app, allowing for interactive AI experiments. While promising, the system encounters some setup challenges needing resolutions before functioning correctly, showcasing a need for refinement in its environment setup and agent interactions.
02:07 - 02:16

Live demo showcases Owl's ability to research on Github effectively.

CAMEL-AI Machine Learning Research & Innovations
... 10:8
Open WebUI with DeepSeek on local by Ollama-Quick Introduction

Case Done by AI

1+ months ago 1K views

Integrating Deep Seek and O'Lama with Open Web UI allows users to run AI models locally. Users can download smaller models using a distillation technique from larger base models. The process involves setting up O'Lama, pulling models to local machines, and interfacing with Open Web UI for secure chatting with AI. The demonstration showcases running the 7 billion parameter model, highlighting how the model thinks and answers queries, exemplifying its application in conversational AI.
01:19 - 01:41

Discussing the distillation technique for creating smaller AI models.

Ollama Machine Learning Tech & Hardware
... 13:18
Ollama Deep Researcher: Local Web Research Assistant AI Tool

AI Anytime

1+ months ago 1K views

OLama Deep Researcher is introduced as an open-source tool created by the Langin team to assist with research activities. It draws from various data sources to generate search queries, gather results, and synthesize information using large language models (LLMs). The tool functions locally and requires an API key from either Tavaly or Perplexity for optimal operation. The setup process is straightforward, involving cloning a repository and configuring settings. Features include customizable options to enhance research productivity, leveraging multiple resources to support extensive inquiries.
02:01 - 02:28

Tool generates search queries then gathers information from the internet.

Ollama Natural Language Processing (NLP) Research & Innovations
... 9:35
The future of open source in AI | Lex Fridman Podcast

Lex Clips

1+ months ago 7K views

Tulu, a new model built from llama's open weight models, pushes the boundaries of post-training AI with a fully open-source approach. The development process has been inspired by various benchmarks, including Chatbot Arena, to evaluate models fairly. The model excels in performance against existing models like llama and DeepSeek V3, thanks to effective reinforcement learning techniques and a focus on safety evaluations. The aim is to improve accessibility for organizations while providing a clear path for further innovation in the open-source AI space, emphasizing the necessity for transparent data and models to foster advancement in AI technologies.
02:22 - 02:27

Reinforcement learning with domain rewards seeks to enhance model capabilities effectively.

Ethical AI frameworks AI Trends
... 9:13
ChatBot with DeepSeek R1 | Run DeepSeek AI Locally Without Internet! Full Offline ChatBot

The SkillPedia

1+ months ago 1K views

This video demonstrates how to build a chatbot using the Olama-hosted deep-seek model on a local machine. Key technologies include Streamlit and LangChain, which facilitate the installation of necessary packages and manage chatbot interactions. The speaker shows the command line execution to start the model and explains the importance of prompt templates in generating accurate AI responses. Finally, a hands-on example illustrates the chatbot’s capabilities when answering complex programming questions, emphasizing the potential applications and limitations of the AI model developed throughout the session.
01:51 - 03:41

Discusses prompt template configurations for generating accurate chatbot responses.

Chatbots Tech & Hardware
... 9:13
ChatBot with DeepSeek R1 | Run DeepSeek AI Locally Without Internet! Full Offline ChatBot

The SkillPedia

1+ months ago 1K views

This video demonstrates how to build a chatbot using the Olama-hosted deep-seek model on a local machine. Key technologies include Streamlit and LangChain, which facilitate the installation of necessary packages and manage chatbot interactions. The speaker shows the command line execution to start the model and explains the importance of prompt templates in generating accurate AI responses. Finally, a hands-on example illustrates the chatbot’s capabilities when answering complex programming questions, emphasizing the potential applications and limitations of the AI model developed throughout the session.
01:51 - 03:41

Discusses prompt template configurations for generating accurate chatbot responses.

Chatbots Tech & Hardware