Notes

pWith confidential computing we want to guarantee confidentiality and integrity of a user’s computation running on a remote (cloud) system, including: The program Its inputs and outputs Intermediate state, control flow, etc. Even if do not trust the cloud provider! Usually it is easy to guarantee that kind of privacy if you are storing or communicating using encryption methods (see Asymmetric Cryptography, Block Ciphers), but it’s difficult to do so if the program is running. ...

Containers In this note, we introduce the famous docker containers. We also explore how #Linux Containers are implemented, and some parts of how #Docker works. What is a Container We have explored Virtual Machines in some past section. Containers do not virtualize everything, but just the environment where the application is run. This includes: Libraries Binaries We can see it as a lightweight VM, even if they do not offer the full level of isolation of traditional virtual machines. ...

CDNs are intermediary servers that replicate read intensive data to provide better performance when user requests them. A close relative of CDNs is edge computing (e.g. gaming stations) where lots of computation is done directly close to the user. Types of CDNs Mainly three types of CDNs: Highly distributed ones. -> Akamai Database based ones. Ad-hoc CDNs. Advantages and disadvantages The main reason we use CDNs is to lower the value of latency: we are in fact bringing the data closer to the user. We have much less data in length to be transmitted. Yet we have some disadvantages too: ...

This note is just a collection of past useful notes to know to apply machine learning methods for the analysis of topics interesting in the neural sciences. Estimators You need to know all Parametric Modeling. We want to estimate unknown random variables with some observations. Maximum Likelihood See Bayesian Linear Regression. Bias-Variance Decomposition Fisher Information See Parametric Modeling#Fisher information. Applications Echo-locating bats Egyptian fruit flies bats use echo location to locate the target, emitting clicks and capturing echo to navigate the environment. Bats use to click slightly left and right compared to their direction of motion. It is interesting to observe and study how these bats are clicking around to move. ...

The Potassium Exchange values We use the measurement by Cole and Curthis 40mS/cm squared was their measure of Potassium ions leaving the membrane $$ \Delta Q = Idt = GA \Delta E dt $$The potassium concentration is 0.155 moles per litre. Where $G$ is the conductance per unit area, $A$ the membrane surface, $E$ voltage deflection Remember that the conductance is the reciprocal of the resistance, and $V = IR \implies I = \frac{V}{R} = GV$ ...

The cloud is inefficient, and it looks like we can improve a lot on this side. Computer Science with their systems have reached industrial scales and can be compared to build airports, highways and metro systems in terms of public infrastructure, yet, due to their immaterial and intangible nature, the perception of these systems do not match their perceived reality by the majority of the people. While classical engineering designs physical objects, computer science designs virtual objects ~Gustavo Alonso CCA Lecture 14 May 2025 ETH Zürich ...

Vision is THE most important sense for humans. Most of the information we get is through vision 90% vision This is true for humans, but for mice for example it is different, they have probably a 64x64 pixel resolution equivalent. For humans, visual data is more important, it is faster compared to speech and other senses. We can also see this when we are talking about quantity of neurons: 30% of neurons in the cortex are for vision. 8% tactile, touch 3% hearing Rest is for other Precision of human vision Human vision is estimated to be about 576 Megapixels of data (3M snapshots patched together with saccades, that has that pixel image value), since it can distinguish 0.6arc-minutes (0.01 degrees). There is an estimate of about 60kk ± 12kk rods and 3kk ±0.5kk cones. This means that the image is constructed by high resolution saccades (patches). ...

We have a classical exploration-exploitation tradeoff, see Reinforcement Learning, a introduction. Why would animals explore, even if there is no immediate reward based on it? Animals are able to adapt and explore nonetheless. It would be thus nice to understand and implement these features in artificial systems. We will attack this from an evolutionary psychology perspective: Playfulness and intrinsic motivation. Curiosity Here we will talk about why animals are pushed to explore. ...

Here we attempt to answer what is memory, how is it stored and retrieved. Human Memory Definition of Memory Memory is a process by which information is: Encoded Stored Retrieved The brain has different types of memories, and certain brain regions are specialized for this task. Ebbinghaus Curves Other experiments destroy parts of the cortex and correlate this with recall. Types of memory We have the memory pipeline: ...

In general we want to understand how neurons encode the rate and temporal information to build specific features like place cells, grid cells, velocity, head direction, or how it can guide behaviour or coordination. Many neurons encode together some features, it is quite rare that you have the face neuron and similars. Imaging techniques help us to get more information about these parts. Basics of Microscopy Image of a classical microscope, from course slides ...