Tool Call Component self._openclaw_session_phase: str = "idle" Five Property Functions is_openclaw_running_background returns self.is_openclaw_running_background() is_openclaw_animation_suppres...
The moat is collapsing. In software, that moat has already been eroded quite a bit, and now we even see news talking about the “end of software.” Other fields are similar, although the speed of cha...
I feel burned out. For the past few weeks I’ve been pushing through on nothing but dull, stubborn diligence, and my energy and judgment have been worn down. Now I’m filled with doubt—about whether ...
When I’m busy, I tend to become obsessed with whatever I’m working on. I stop eating regularly, stop cleaning my house, and stop taking care of myself. But the more I do that, the more my self-este...
Keeping up with the rapid advances of technology leaves me breathless. It seems I’m not the only one who feels this way. People working in the IT industry rush to learn the latest technologies, afr...
In my last post, I suggested stratrgy of realizing complex behavior by layering simple pre-trained reinforcement models. For recap the layer we utilized was: 1. Wandering 2. Painting 3. Moving to ...
In my last post, I trained a Paint Your Partner agent using reinforcement learning. Specifically, I provided the agent with all game information as a single, large chunk of observation data. With s...
This is the first log in the development of cooperative machines. The agent will play a game called Paint Your Partner with its human partner. Eventually, the agent will be composed of a layered ar...
Hand written notes. Column view of Matrix Multiplication.
Hand written notes. Calculating derivatives with respect to vectors.
Reinforcement Learning covers whole new concept compared to traditional supervised learning. Therefore, the idea of RL is difficult to grasp in a first sense. While studying RL, I realized obtainin...
Reinforcement Learning covers whole new concept compared to traditional supervised learning. Therefore, the idea of RL is difficult to grasp in a first sense. While studying RL, I realized obtainin...
This post covers Value Function and Policy Interation Algorithms of Reinforcement Learning in deail. The post is written in reference to CMU 10401/601 taught by Henry Chai. Table of contents V...
This post covers Marcov Decision Process in detail, which forms a foundation of Reinforcement Learning. Written in reference to CMU 10401/601 taught by Henry Chai. Table of contents Problem Fo...
This post covers concetual understanding about Reinforcement Learning. Handwritten notes are also available here. Table of contents Concept Markov Decision Process Concept 0. Goal Goal o...
This post covers Transformer architecture. Heavily referenced to Josh Starmer’s StatQuest Transformer Neural Networks, ChatGPT’s foundation, Clearly Explained!!! video. Table of contents Posit...
This post covers Seq2Seq Encoder-Decoder Architecture. Seq2Seq architecture is heavily used in areas such as Machine Translation, Natural Language Processing, Chat Bots, etc. This post heavily refe...
Hand written notes. Mathematical Foundations for Machine Learning Week 1 Lecture 2 Data Types and Functions.
Hand written notes. Mathematical Foundations for Machine Learning Week 1 Lecture 1 Sets.
Hand written notes. In reference to Deisenroth, A. Aldo Faisal, and Cheng Soon Ong., Mathematics for Machine Learning, https://mml-book.com, Chapter 7. Continuous Optimization.
This post covers VC Dimension learning theory. The content was written in reference to course content from Henry Chai(CMU 10-401/601). Table of contents Recall PAC Learning Intuition Growth...
Hand written notes. In reference to this video.
Hand written notes. In reference to this post.
This post covers Probably Approbimately Correct learning theory. The content was written in reference to course content from Henry Chai(CMU 10-401/601) and this video, Probably Approximately Correc...
This post is a word embedding clone coding workshop following Coding Lane’s tutorial video. Original content can be found this GitHub repository. Table of contents Code Flow Why Biagrams? ...
Word embeddings is to learn a vector representation of a word. Table of contents Necessity Idea Embedding Matrix Converting one-hot vector to feature vector Architecture Necessity On...
LSTM and GRU algorithms are used in stated of the art in deep learning applications such as speech recongnition, speech synthesis, natural language understanding, etc. Table of contents Purpose...
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