Sam Witteveen
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#1about 3 minutes
Navigating the current AI hype and research secrecy
The term "AI" is often used for marketing, while the competitive landscape has made research labs more secretive about their work.
#2about 3 minutes
Understanding Google's open weights Gemma models
Gemma models are "open weights," not fully open source, meaning developers can use the model weights for commercial projects but don't have the training data or code.
#3about 2 minutes
The training process of large language models
LLMs are trained in stages, starting with pre-training to predict the next token, followed by post-training and reinforcement learning to align with human instructions.
#4about 2 minutes
Comparing proprietary Gemini and open Gemma models
Gemini models are Google's proprietary, cloud-based offerings, while Gemma models are open-weight versions that can be run on-premise or on-device.
#5about 3 minutes
How AI models are becoming smaller and more efficient
Models are made smaller and more powerful through training on vast amounts of data and using techniques like distillation to transfer knowledge from larger models.
#6about 7 minutes
The rise of multilingual and multimodal AI
Modern models like Gemma 3 are trained on over 140 languages, and multimodal models like Gemini can process text, audio, video, and images simultaneously.
#7about 4 minutes
Improving text in AI-generated images and videos
Recent models are finally getting better at rendering accurate text in images, while video generation models can create complex, realistic scenes from prompts.
#8about 3 minutes
AI tools for advanced content creation and editing
AI-powered tools can now edit video by manipulating the transcript and even insert new words in a cloned voice, simplifying the post-production process.
#9about 4 minutes
Using large language models as a learning tool
LLMs serve as powerful educational tools by explaining complex concepts at different levels, acting as a personal tutor for learning new technical skills.
#10about 6 minutes
How deep reasoning models 'think' before answering
Reasoning models improve accuracy by generating an internal monologue to break down a problem and explore possibilities before providing a final answer.
#11about 10 minutes
The evolution of AI-powered coding assistants
AI coding tools are evolving into agents that can write code, run tests, and fix errors, shifting the developer's role toward architectural and conversational guidance.
#12about 2 minutes
How to get started with Google's Gemma models
Developers can start experimenting with Gemma models through Google's AI Studio, Hugging Face, or by running them locally with tools like Ollama and LM Studio.
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