Blog

Building a Vision Transformer Model From Scratch by Matt Nguyen The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A transformer model is what is used by OpenAI to...

Since the introduction of mass production in 1913 assembly lines are still mostly human — humanoids might change this Henry Ford is known as the father of mass production, streamlining the production of his “Model T” enabling cars to be widespread affordable. One of the key innovations at the time...

How to leverage large language models for robotic grasping and code generation Grasping and manipulation remain a hard, unsolved problem in robotics. Grasping is not just about identifying points where to put your fingers on an object to create sufficient constraints. Grasping is also about applying just enough force to...

Humanoids might finally solve the “brownfield” problem that plagues robotic adaptation, and recent breakthroughs in multi-modal transformers and diffusion models might actually make it happen. Not a week goes by without a flurry of humanoid companies releasing a new update. Optimus can walk? Digit has just moved an empty tote?...

Formal methods to tackle “Trial-and-Error” problems The ability to deal with unseen objects in a zero-shot manner makes machine learning models very attractive for applications in robotics, allowing robots to enter previously unseen environments and manipulating unknown objects therein . While their accuracy in doing so is incredible compared with...

Built-in function vs. numerical methods PCA is an important tool for dimensionality reduction in data science and to compute grasp poses for robotic manipulation from point cloud data. PCA can also directly used within a larger machine learning framework as it is differentiable. Using the two principal components of a...