Lighthearted bite-sized ML videos for your AI Coffee Break! πŸ“Ί Mostly videos about the latest technical advancements in AI, such as large language models (LLMs), text-to-image models and everything cool in natural language processing, computer vision, etc.!

We try to post twice a month! 🀞 But you know, Letitia has a full-time job, and Ms. Coffee Bean tends to enjoy time off to go out and have fun. πŸ˜„

Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.


Impressum: https://aicoffeebreak.com/impressum.html

AlphaEvolve: Using LLMs to solve Scientific and Engineering Challenges | AlphaEvolve explained
8:57
AlphaEvolve: Using LLMs to solve Scientific and Engineering Challenges | AlphaEvolve explained
Token-Efficient Long Video Understanding for Multimodal LLMs | Paper explained
9:20
Token-Efficient Long Video Understanding for Multimodal LLMs | Paper explained
4-Bit Training for Billion-Parameter LLMs? Yes, Really.
15:40
4-Bit Training for Billion-Parameter LLMs? Yes, Really.
s1: Simple test-time scaling: Just β€œwait…” + 1,000 training examples? | PAPER EXPLAINED
6:09
s1: Simple test-time scaling: Just β€œwait…” + 1,000 training examples? | PAPER EXPLAINED
Training large language models to reason in a continuous latent space – COCONUT Paper explained
9:52
Training large language models to reason in a continuous latent space – COCONUT Paper explained
LLM Lecture: A Deep Dive into Transformers, Prompts, and Human Feedback
1:31:09
LLM Lecture: A Deep Dive into Transformers, Prompts, and Human Feedback
REPA Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You ...
6:37
REPA Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You ...
Math Anxiety? and what it has to do with AI – πŸ”΄at #HLF24 with Prof. Yael Tauman Kalai
7:52
Math Anxiety? and what it has to do with AI – πŸ”΄at #HLF24 with Prof. Yael Tauman Kalai
Graph Language Models EXPLAINED in 5 Minutes! [Author explanation πŸ”΄ at ACL 2024]
6:38
Graph Language Models EXPLAINED in 5 Minutes! [Author explanation πŸ”΄ at ACL 2024]
How OpenAI made o1 think – Here is what we think and already know about o1 reinforcement learning
9:24
How OpenAI made o1 think – Here is what we think and already know about o1 reinforcement learning
I am a Strange Dataset: Metalinguistic Tests for Language Models – Paper Explained [πŸ”΄ at ACL 2024]
4:08
I am a Strange Dataset: Metalinguistic Tests for Language Models – Paper Explained [πŸ”΄ at ACL 2024]
Transformer LLMs are Turing Complete after all !?
28:47
Transformer LLMs are Turing Complete after all !?
Mission: Impossible language models – Paper Explained [ACL 2024 recording]
11:05
Mission: Impossible language models – Paper Explained [ACL 2024 recording]
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution – Paper Explained
11:22
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution – Paper Explained
My PhD Journey in AI / ML (while doing YouTube on the side)
37:18
My PhD Journey in AI / ML (while doing YouTube on the side)
[Own work] On Measuring Faithfulness or Self-consistency of Natural Language Explanations
8:48
[Own work] On Measuring Faithfulness or Self-consistency of Natural Language Explanations
Supercharging RAG with Generative Feedback Loops from Weaviate
11:08
Supercharging RAG with Generative Feedback Loops from Weaviate
GaLore EXPLAINED: Memory-Efficient LLM Training by Gradient Low-Rank Projection
11:38
GaLore EXPLAINED: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Shapley Values Explained | Interpretability for AI models, even LLMs!
9:59
Shapley Values Explained | Interpretability for AI models, even LLMs!
Stealing Part of a Production LLM | API protects LLMs no more
18:49
Stealing Part of a Production LLM | API protects LLMs no more
Genie explained 🧞 Generative Interactive Environments paper explained
9:22
Genie explained 🧞 Generative Interactive Environments paper explained
MAMBA and State Space Models explained | SSM explained
22:27
MAMBA and State Space Models explained | SSM explained
Sparse LLMs at inference: 6x faster transformers! | DEJAVU paper explained
13:17
Sparse LLMs at inference: 6x faster transformers! | DEJAVU paper explained
Transformers explained | The architecture behind LLMs
19:48
Transformers explained | The architecture behind LLMs
Direct Preference Optimization: Your Language Model is Secretly a Reward Model | DPO paper explained
8:55
Direct Preference Optimization: Your Language Model is Secretly a Reward Model | DPO paper explained
FunSearch from DeepMind explained | LLM hallucinations discover new math solutions!?
11:36
FunSearch from DeepMind explained | LLM hallucinations discover new math solutions!?
DALL-E 3 is better at following Text Prompts! Here is why. β€” DALL-E 3 explained
8:03
DALL-E 3 is better at following Text Prompts! Here is why. β€” DALL-E 3 explained
Adversarial Attacks and Defenses. The Dimpled Manifold Hypothesis. David Stutz from DeepMind #HLF23
13:06
Adversarial Attacks and Defenses. The Dimpled Manifold Hypothesis. David Stutz from DeepMind #HLF23
What is LoRA? Low-Rank Adaptation for finetuning LLMs EXPLAINED
8:22
What is LoRA? Low-Rank Adaptation for finetuning LLMs EXPLAINED
Are ChatBots their own death? | Training on Generated Data Makes Models Forget – Paper explained
11:53
Are ChatBots their own death? | Training on Generated Data Makes Models Forget – Paper explained