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Trelis Research @UCruC3Lkt_-StdHlPiyWbPSg@youtube.com

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Trelis LTD is a research company based in Dublin, founded by


15:49
Create a Python Sandbox for Agents to Run Code
10:06
April 2025 Channel Update - Repos, Grants, Collabs, and ARC AGI Team
46:46
Build Custom LLM Benchmarks for your Application
18:08
Is it safe to use Cursor or Windsurf?
55:43
How to Build and Publish an MCP Server - A Detailed Guide
30:05
Qwen 2.5 Omni - The Most Multi-modal
55:39
How does MCP work? How to use MCP?
15:30
Price Comparison: OpenAI vs ElevenLabs vs DeepGram for TTS and STT
02:23:10
Fine-tune Text to Speech Models in 2025: CSM-1B and Orpheus TTS
27:54
PREVIEW A Prelude to Llama 4 Token Based Audio Models Orpheus, CSM 1B and Moshi
02:23:10
Diarization, Voice and Turn Detection
21:43
Gemma 3
01:02:57
Create and Fine-tune AI Avatar Videos
42:55
Document-Reading Agents with Read-Write Memory
30:20
Why use Keyword vs Vector Search?
48:46
Memory Management in LLMs and Agents
22:58
Train an LLM to Self-Correct with Verifiable Backtracking
55:15
SFT vs GRPO
32:44
How does GRPO work?
01:18:19
Reinforcement Learning for LLMs in 2025
11:27
The Best LLM? Google vs OpenAI, Anthropic and DeepSeek
01:11:20
Top Vision Models 2025: Qwen 2.5 VL, Moondream, & SmolVLM (Fine-Tuning & Benchmarks)
15:56
Run Distilled DeepSeek v3 Reasoning Models on Any Laptop with LMStudio
54:16
How to Boost RAG Accuracy with SmolAgents & BM25
14:08
OpenAI’s $500B ‘Stargate’ Project, GPU Export Bans, Musk’s Critique, and DeepSeek’s Reasoning Model
17:07
Channel Update - Playlists, Repos, Collabs, Grants, Memberships
49:45
Advanced Embedding Models and Techniques for RAG
33:21
Reasoning Models and Chinese Models
17:37
LiteLLM - One Unified API for for all LLMs
12:19
Nvidia RTX 5090 vs 4090, Project Digits & GB NVLink 72 at CES 2025
34:47
LLM Evals - Part 2: Improving Performance
01:01:57
How Deepseek v3 made Compute and Export Controls Less Relevant
34:23
LLM Evals - Part 1: Evaluating Performance
46:34
I Tested Every GPU
57:02
Serve Multiple LoRA Adapters on a Single GPU
01:17:56
Why Build Enterprise RAG with Postgres?
56:31
Multi modal Audio + Text Fine tuning and Inference with Qwen
01:00:38
How to Build an Inference Service
50:36
How to Fine-tune Florence 2: The Best Small Vision Model
24:23
Output Predictions - Faster Inference with OpenAI or vLLM
03:59
Coding Assistant for Jupyter Lab
25:09
Predicting Events with Large Language Models
34:44
Fine tune and Serve Faster Whisper Turbo
22:37
OpenAI Fine-tuning vs Distillation - Free Colab Notebook
01:17:59
Synthetic Data Generation and Fine tuning (OpenAI GPT4o or Llama 3)
01:00:00
Test Time Compute, Part 2: Verifiers
54:59
Test Time Compute, Part 1: Sampling and Chain of Thought
01:20:38
Distillation of Transformer Models
55:22
Fine tuning Pixtral - Multi-modal Vision and Text Model
39:40
Powering Gigawatt Data Centers
01:03:42
Full Fine tuning with Fewer GPUs - Galore, Optimizer Tricks, Adafactor
03:53
Make Cursor Understand Folder Structure - Coding with LLMs
45:52
Automated Prompt Engineering with DSPy
51:57
Fine Tune Flux Diffusion Models with Your Photos
40:40
How to use LLMs for Fact Checking
35:26
CONTEXT CACHING for Faster and Cheaper Inference
37:03
Run Speech-to-Speech Models on Mac or GPU
01:27:15
LLM Security 101: Jailbreaks, Prompt Injection Attacks, and Building Guards
02:56
Create an AI Assistant or Endpoint for your Documents
33:30
RAG - but with Verified Citations!