Tesla and Spotify
Something seems to be up, with the car tickling an endpoint for connectivity perhaps? Its only 663 bytes up and 222 bytes down. This is still on v8.1 (36.2) Spotify traffic from Tesla
Something seems to be up, with the car tickling an endpoint for connectivity perhaps? Its only 663 bytes up and 222 bytes down. This is still on v8.1 (36.2) Spotify traffic from Tesla
In case you haven’t been following the news, Tesla is in the process of releasing the new firmware beta. I think many folks online are super interested in new autopilot upgrades. I reverse engineered the associated app and there are certainly a few new end points exposed, as outlined below. Need time to now figure out more details on this and what they entail. Also need time to see what changes in the existing code and json (data structure)....
Never trust an atom, they make up everything. 🤓 #GeekyJokes
Regularization is a fundamental concept in Machine Learning (#ML) and is generally used with activation functions . It is the key technique that help with overfitting. Overfitting is when an algorithm or model ‘fits’ the training data too well - it seems to good to be true. Essentially overfitting is when a model being trained, learns the noise in the data instead of ignoring it. If we allow overfitting, then the network only uses (or is more heavily influenced) by a subset of the input (the larger peaks), and doesn’t factor in all the input....
Wait. I have how many tabs open? I can’t count more than fingers I have, so not sure if this is accurate. Maybe time to reboot. 😄 PS – Yes, I can count using more than 10 (toes, remember?)
Some time ago, I talked about my Tesla Model 3 “keyfob” which essentially uses a Amazon IoT button to call some of Tesla API’s and “talk” to the car. This for me, is cool as it allows my daughter to unlock, and lock the car at home. And of course it is a bit geeky, and allowing one to play with more things. :) Since publishing this, I was surprised how many of you ping me asking on details on how they can did this for themselves....
Tonight, I was a large download by the car, and saw that it was a .ssq file. The file name is consistent with the firmware naming convention, but I am not sure on what it is. The file itself is 5.11 GB, and in my case its name starts with “NA”. I am guessing, this might be the maps its updating. Below are a couple of screenshots showing this. I am trying to make sense of the binary file, but not making much headway....
Neural Networks, today, help in a great set of tasks, that until very recently wasn’t possible at all - be it from computer vision, to medical diagnosis, to speech translation and forms a key cornerstone to a lot of ‘magic’ that Machine Learning and AI offers today. I did blog about Neural Network types (and MarI/O) sometime back ; I surely cannot take credit for creating these three cheat sheets but they are awesome and hope you get to use and enjoy them too....
My command prompt history is quite long, and a lot over time is not essentially garbage. I was looking at a way to clean it out. Most of the solutions online I found were not correct - I don’t know if things changed over time, but the latest version of Windows I am on (Windows 10 Pro 1803), it did not work. So, here are two ways that you can do this....
I don’t know how to get to debug / dev mode on a Tesla, but did come across this old post , on how someone was in a test drive, which did have this mode. Now this is quite old, so a lot has changed, but am impressed that a lot of the components and foundational architecture was setup. I am particularly impressed how each cell in the battery pack and report its state....
Beware of programmers that carry screwdrivers - Unknown
As I was trying to understand more on the capabilities of the car, and what options I can do. The voice recognition on the car is quite impressive, it does seem as good at understanding as Amazon’s Echo, at least in the early days of “Alexa” (but that is a different story for another time). I was trying to understand what things can I control, or the options one has via the voice....
Often once hears are Lines of Code (LoC) as a metric. And for you to get a sense of what it means, below is a info-graphic that outlines some popular products, and services and the LoC that takes. Always interesting to get perspective - either appreciate some home grown system you are managing, or worried about a stinking pile you are going to inherit or build. 😄
UPDATE: This cURL script doesn’t work anymore. This was originally published back in 2018 when it was the best way to do this. Over the last few years however Tesla has deprecated this endpoint (/oauth/token) and moved to a SSO service (auth.tesla.com) which is a completely different approach. I’ll have a look and if there is a simple way to do it, then will share it here. I did write a simple Windows (desktop) app called TeslaTokenGenerator, for those who wanted to create authentication tokens for their Tesla, and use with 3rd party apps/data loggers....
Inspired by a few folks on a few forums online , I took the liberty to extend their idea using a IoT Button, that acts as a simple “keyfob” for the Model 3. The main goal was being to allow my daughter to lock and unlock the car at home. She is too young to have a phone, and without a more traditional fob, this gets a little annoying. I extended the original idea, to understand the different presses (Single, Double, and Long press), and accordingly called the appropriate API to lock the car (single press - think of it as a single click), unlock on a double press, and open the charge port on a long press (when one presses and holds the button 2-3 secs)....
If you have a Tesla, and are using (or wanting to use) 3rd party tools or data loggers, the one think they of course need is to authenticate your details with Tesla. A simple, but insecure way is to use your Tesla credentials - and surprisingly many people just happily share and use this. I wasn’t comfortable doing this - after-all, they have access to your account where you can control a lot of things....
Thought of the week: Artificial Intelligence stands no chance against natural Stupidity. #ArtificalIntelligence
Seem like my training data for the car - perhaps a hint of #bias. 😂 #GeekyJokes #ML #AIJokes
Neural networks have a very interesting aspect – they can be viewed as a simple mathematical model that defines a function. For a given function $f(x)$ which can take any input value of $x$, there will be some kind a neural network satisfying that function. This hypothesis was proven almost 20 years ago (“ Approximation by Superpositions of a Sigmoidal Function ” and “ Multilayer feedforward networks are universal approximators ”) and forms the basis of much of #AI and #ML use cases possible ....
I was looking at something else and happen to stumble across something called Netron , which is a model visualizer for #ML and #DeepLearning models. It is certainly much nicer than for anything else I have seen. The main thing that stood out for me, was that it supports ONNX , and a whole bunch of other formats (Keras, CoreML), TensorFlow (including Lite and JS), Caffe, Caffe2, and MXNet. How awesome is that?...
Analog Islands
Someone recently asked me, what are some of the use cases / examples of machine learning. Whilst, this might seem as an obvious aspect to some of us, it isn’t the case for many businesses and enterprises – despite that they uses elements of #ML (and #AI) in their daily life – as a consumer. Whilst, the discussion gets more interesting based on the specific domain and the possibly use cases (of course understanding that some might not be sure f the use case – hence the question in the first place)....
Trained a model to create a synthetic sound that sounds like me. This is after training it with about 30 sentences - which isn’t a lot. To create a synthetic voice, you enter some text, using which is then “transcribed” using #AI and your synthetic voice is generated. In my case, at first, I had said AI, which was generated also as “aeey” (you can listen here ). So for the next one, changed the AI to Artificial Intelligence....
Over the last few weeks, I built a self-driving car - which essentially is a remote control Rx car that uses a raspberry pi running Python, TensorFlow implementing a end-to-end convolution neural network (CNN) Of course other than being a bit geeky, I do think this is very cool to help understand and get into some of the basic constructs and mechanics around a number of things - web page design, hardware (maker things), and Artificial Intelligence principles....
Despite all the cloud talk and where I live, it is like the cloud mecca, for enterprises it is still quite new and many are just starting to think about it. A hard lesson that many of us learn (and partly how we amass our scars) is to design for failures. For those, who run things in their enterprises data center, are quite spoilt I think. Failures are rare, and if machines or state goes down, moving to another one isn’t really a big deal (of course it is a little more complex, and not to say, there isn’t any down time, or business loss, etc....