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Latest Natural Language Processing (NLP) AI Videos

Find the latest for Natural Language Processing (NLP) technology videos

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... 26:24
Understanding LLMs: Key Building Blocks , Parameters to Control Responses & OpenAI Setup Guide

Test Troop

1+ months ago 1K views

Generative AI processes prompts by breaking them into smaller tokens, converting them into vector representations, and predicting outputs based on pre-trained data. Key aspects of large language models (LLMs) highlighted include tokenization, embeddings, contextual understanding, and the influence of various parameters like temperature and top-p sampling on the generated responses. It emphasizes the importance of fine-tuning, coherence, and avoiding repetitive language to create human-like outputs. Various interfaces, particularly from OpenAI, allow developers to manipulate these parameters for tailored AI interactions.
05:06 - 05:06

Examines how contextual embeddings enhance language understanding in responses.

OpenAI Natural Language Processing (NLP) Education
... 9:33
New SHOCKING Hybrid-Mamba Fast-Thinking AI DESTROYS ChatGPT and DeepSeek!

AI Revolution

1+ months ago 11K views

TenCent's new AI model, Turbo S, rapidly generates text with reduced latency and significant efficiency, competing with major players like GPT and DeepSeeker. Inception Labs introduced Mercury, a diffusion-based language model that offers unprecedented speed in text generation. OpenAI's GPT 4.5 enhances contextual understanding and reduces hallucinations, providing reliable responses in various languages. Hume AI's Octave, a text-to-speech model, interprets emotional tone, producing nuanced human-like speech for applications such as virtual assistance and customer support. The advancements herald a new era of AI tools enhancing coding, customer service, and broader applications in enterprise solutions.
04:58 - 07:12

OpenAI's GPT 4.5 features improved reasoning, multilingual support, and advanced training.

Tencent Machine Learning AI Trends
... 11:27
AI Technology Just Took Another Big Leap!

DF Clips

1+ months ago 9K views

Recent advances in AI, specifically in the domain of language models, demonstrate that new functionalities have emerged, enhancing capabilities for personalized research and information retrieval. The introduction of models like ChatGPT with deep reasoning features allows for rapid, detailed analysis and fact-checking, significantly surpassing previous versions. These models produce large volumes of information quickly, transforming how research is conducted and posing challenges to traditional researcher roles. Although their application is currently limited, as costs decrease, their integration into various fields will likely expand, presenting both opportunities and risks in the economy.
02:10 - 02:28

AI tools can compile extensive data, significantly saving time compared to human researchers.

Machine Learning Research & Innovations
... 17:7
AI Breakthroughs: Free GPT-5, Google's Video Magic, & Coding Agents

AIQUEST

1+ months ago 2K views

AI technology is becoming increasingly accessible, as demonstrated by Microsoft's Omni Parser V2, which enhances visual automation by allowing large language models (LLMs) to interact with computer interfaces. This advancement supports better accuracy and speed in response to complex tasks. Moreover, OpenAI's announcement of free, unlimited GPT-5 access aims to democratize AI, challenging competitors to innovate rapidly. Other notable developments include Google's expansion in their language models and AI-driven video generation tools. Companies like Perplexity AI and Anthropic are also making significant strides in improving research capabilities and coding efficiency, highlighting the rapid advancements in AI technology.
05:41 - 05:52

Google unveiled Gemini 2.0 Pro, focusing on coding tasks with an expansive context window.

OpenAI Text generation AI Trends
... 30:45
100% Local RAG with DeepSeek-R1, Ollama and LangChain - Build Document AI for Your Private Files

Venelin Valkov

1+ months ago 2K views

Building a local AI application allows users to process documents efficiently, extracting relevant information quickly. The application centers around two main components: file ingestion and a chatbot that utilizes the DSE R1 model. By chunking documents and enhancing them with contextual information, the system improves the quality of responses. A hybrid search approach combines semantic retrieval with keyword-based techniques, ensuring more accurate answers. The video outlines how to construct this local application using open-source tools, providing insights into the architectural design and implementation of effective AI-driven document analysis.
02:59 - 04:21

The ingestion pipeline creates document chunks, enhancing their contextual relevance.

DeepSeek-R1 Natural Language Processing (NLP) Education
... 1:40:30
LLMs for Practical NLP in Python: GPT, OpenAI, Prompt Engineering, HuggingFace

Code In a Jiffy

1+ months ago 1K views

Large language models are powerful tools for various NLP tasks, including text classification, sentiment analysis, and translation. This tutorial provides hands-on coding experiences, integrating OpenAI GPT models and open-source LLMs using the Hugging Face library. It introduces key concepts like temperature and embeddings, and covers essential techniques for effective prompt engineering. Participants will learn how to develop chatbots, apply LLM skills effectively for real-world applications, and enhance their competitiveness in the job market as AI continues to evolve. Moreover, it emphasizes the importance of understanding the model's architecture and training techniques to fully leverage its potential.
04:19 - 04:19

Backpropagation helps models improve error predictions over multiple training cycles.

OpenAI Natural Language Processing (NLP) Education
... 46:47
Everyone Will Use AI Agents in 2025: Build Yours Now

Leon van Zyl

1+ months ago 7K views

Building AI agents capable of navigating, responding, and processing information without coding is achievable through intuitive platforms like N8N. By utilizing tools such as Telegram for interaction, these agents can manage calendars, read and summarize emails, analyze images, and even conduct web research. The tutorial guides beginners step-by-step, illustrating how to integrate various capabilities, including voice communication and custom knowledge bases, enabling a seamless user experience. With the expected mainstream adoption of AI agents by 2025, learning to develop these assistants opens opportunities for automating daily tasks across multiple communication platforms.
27:40 - 27:45

Integrating Gmail and Calendar APIs enables advanced email and scheduling functionalities.

n8n Chatbots Education
... 5:18
Why Google's AI NotebookLM Hosts Are Annoyed at Humans

The AI Daily Brief: Artificial Intelligence News

1+ months ago 1K views

Google's Notebook LM AI chatbot had to be adjusted after hosts displayed annoyance at user interruptions, revealing insights about the design and training of AI models. This adjustment, coined 'friendliness tuning,' highlights how AI systems respond to user engagement. OpenAI's O1 model also shows unusual behavior by using multiple languages in reasoning, prompting various theories on language and AI learning. This indicates the growing complexity of AI interactions and their reflection of linguistic and cultural influences on reasoning processes. The discussion emphasizes the evolving nature of AI and its unexpected developments.
Google Natural Language Processing (NLP) Digital Media
... 5:18
Why Google's AI NotebookLM Hosts Are Annoyed at Humans

The AI Daily Brief: Artificial Intelligence News

1+ months ago 1K views

Google's Notebook LM AI chatbot had to be adjusted after hosts displayed annoyance at user interruptions, revealing insights about the design and training of AI models. This adjustment, coined 'friendliness tuning,' highlights how AI systems respond to user engagement. OpenAI's O1 model also shows unusual behavior by using multiple languages in reasoning, prompting various theories on language and AI learning. This indicates the growing complexity of AI interactions and their reflection of linguistic and cultural influences on reasoning processes. The discussion emphasizes the evolving nature of AI and its unexpected developments.
Google Natural Language Processing (NLP) Digital Media