I have tried HARD to generate a photo of a brain or a neuron that can be scanned. But unfortunately, either it cannot be recognized as a QR code or it is irrelevant to my prompts.馃槶 It is much easier to generate that of girls or natural scenery though. Perhaps it鈥檚 better to choose another stable diffusion checkpoint. (By the way, thanks to Stable Diffusion WebUI, it is quite easy to deploy famous diffusion models.) ...
In a docker container, you have full privileges to build the image of singularity or docker in it. But if only singularity is installed on the server and the root user sets up neither --fakeroot nor proot and you have exhausted your remote build minutes, what trick can you play to work around those restrictions? Software Selection To solve the problem, we need a virtual machine under control on the server for enough privileges to execute singularity build(or docker build) which requires sudo if you meet such a tough condition as mentioned before. Then an OS is run on the virtual machine. Finally, we could build the image. ...
Here are some immature ideas that I come up with when I am taking a walk or having a meal. Feel free to get some inspiration from this post and write some papers. I am glad to see study on these topics. This post will be updated from time to time. The research field underestimates the importance of optimization. You cannot expect one to have perfect memory. What we do every day is just adjusting our cognition. That鈥檚 what Mass Editing Memory in a Transformer does! This method remodels knowledge, namely the relation between object. But it does not involve behavioral remodeling, for example the procedure to solve a tedious math problem. Information of relations between texts and images is in cross-attention layers(e.g. prompt to prompt), while the knowledge-related relations are stored in MLP layers(e.g. https://rome.baulab.info/). Are procedural relations stored in cross-attention layers? ...
In this blog, we will prove the following theorem: Optimal Policy Existence Theorem: For any Markov Decision Process, There exists an optimal policy $\pi_\star $ that is better than or equal to all other policies, $ \pi_\star \geq \pi , \forall \pi$ All optimal policies achieve the optimal value function, $V_{\pi_\star}(s)=V_\star(s)$ All optimal policies achieve the optimal action-value function $Q_{\pi_\star}(s,a)=Q_\star(s,a)$ Definition To simplify the exposition, we first define some basic concepts. ...