Hi everyone! I found this Twitter discussion extremely interesting and would like to know your thoughts. It could be a great way to inspire writers/creators to produce more interesting articles about ML/DL (as highlighted here: https://www.reddit.com/r/MachineLearning/comments/co37ut/regarding_beginners_guides/)

Here’s the post for those of you who are too lazy to follow a link, lol

What’s a ML problem you are interested in but for which you haven’t found a good tutorial/introduction? Preferably a *task* rather than a *technique* (what you are trying to do vs. how you are trying to do it). Too many people jump to tools that may be far from optimal when simpler, better solutions exist. Also, if you are working with a specific dataset, please describe it – François Chollet

I need to convert facebook’s RoBERTa which is in pytorch into tensorflow, I can see a lot of info about conversion from pytorch to tensorflow but not the opposite. Can anyone guide me about the same?

I’ve been working in ecommerce exclusively for the past four years, and a lot of that time has been spent shaping customer experience using tools like Saleforce’s Einstein (within the context of Salesforce Commerce Cloud). That work tends to focus on products and their attributes first and foremost, but we’re also beginning to gather more browsing data to build better models for customer intent (to drive more conversions, show more effective presentations of products, etc.).

That all drove me pretty deeply down the rabbit hole, and I started writing about it to try to get some of my ideas solidified. I wrote this piece about activity nodes, successful endpoints, behavioral cohorts, and ways to tie that all together to rank, predict, and drive desired outcomes.

https://medium.com/datadriveninvestor/where-did-you-come-from-where-did-you-go-where-are-you-headed-ai-will-know-9d623d1cf52f

Anyway, I’d love to discuss it if anyone is interested, because this is an area where I don’t get the chance to delve deeply with my own team or colleagues (it’s really not in their wheelhouse, and we have too much focused work to do for thought experiments on the clock).

Workshop paper at AIIDE 2019 Experimental AI in Games

http://www.exag.org/papers/EXAG_2019_paper_21.pdf

Abstract:

We introduce gym-city, a Reinforcement Learning environment that uses SimCity 1’s game engine to simulate an urban environment, wherein agents might seek to optimize one or a combination of any number of city-wide metrics, on gameboards of various sizes. We focus on population, and analyze our agents’ ability to generalize to larger map-sizes than those seen during training. The environment is interactive, allowing a human player to build alongside agents during training and inference, potentially influencing the course of their learning, or manually probing and evaluating their performance. To test our agents’ ability to capture distance-agnostic relationships between elements of the gameboard, we design a minigame within the environment which is, by design, unsolvable at large enough scales given strictly local strategies. Given the game engine’s extensive use of Cellular Automata, we also train our agents to “play” Conway’s Game of Life – again optimizing for population – and examine their behaviour at multiple scales. To make our models compatible with variable-scale gameplay, we use Neural Networks with recursive weights and structure – fractals to be truncated at different depths, dependent upon the size of the gameboard.

Associated project:

https://github.com/smearle/gym-city

As a professional data sciencetis and algorithm developer I ofent encounter serious errors in the use and design of machine learning software. One of the most ignoring is incorporation of numerical identifiers in data sets used for machine learning. Many data sets come with identifiers in the feature set, however they should never be used when validating or estimating models!

Take for example Forensic Science Glass Identification data, it comes with a id column. Use the data as is, I can get an error rates of less than 1%, too good to be true, and it is. Removing the id column and the error rate is approximately 35%! Details can be found in my code-snippet here: http://roasted.space/?page=codeZglass and short in my blog post: http://roasted.space/?page=blogZglass

Help us train an AI that recognizes hands. We will be able to further develop our app for Visually Impaired People (VIP) using tactile images in swell/embossed/raised paper. This way they won’t need another person to explain what they are touching, the app will see their hand position and explain what they are touching. What if mom can’t help with Chemistry, Mathematics, Geography homework? Use our app! A big leap towards e-learning and self-developing tool for VIPs.

I made a video (English captions available) to better explain the situation: what we have and what we need. Useful for distributing on social media?

Video with what the app learned by now: It only works with limited parameters and is not very precise – that’s why we are asking for support to improve it. Please take pictures in different lighting, from different angles, with different textures. Various hand sizes and skin tones welcome!

WHAT TO DO (for IOS): If you have an iPhone, download the IOS app from here: (First, install TestFlight from Apple, then install Keypoints app. No accounts needed.)

Short tutorial: – take pictures by touching the left upper corner camera button – after taking the pictures a folder will appear in the app. Open it and set the points as seen in the tutorial – after you finish setting the markers, use the right upper corner send button to send them to developer@teistudios.ro by email or transfer (Google Drive, Dropbox, etc)

Keypoints (as seen in the pictograms down the screen) are: 1. Index finger tip 2. Index finger base 3. Thumb tip 4. Little finger base

Only place keypoints on the visible hand elements. If 1, 2, 3 or 4 are not visible do not activate that keypoint(s). You can always reset the points by using the curve arrow on top right. You can finish setting keypoints some other time. You can also continue taking pictures anytime. Just remember to send us the pictures after setting keypoints. After sending the pictures you can delete the folder by sliding left on it.

WHAT TO DO (for nonIOS): If you don’t have an IOS device, just take 50 pictures and send them to developer@teistudios.ro through online transfer.

Hello everyone!

I’m currently doing a CS Project which identifies one object in a game running on window mode and take actions by itself (by autoclicking or pressing a key). Basically, I will set a canvas on the up right side of my desktop, match it with the game window size and then start trying to identify one specific object. For exemple, i use an image of a monster in the identification algorithm, if it appears on screen and matches, it takes an action.

I’m just a beginner in ML… Do I need a neural net for doing that object identification? If so, how do i create a dataset if it’s only trying to identify one specific object?

I accept literally every possible tip you guys can get me. Libraries I can use, image processing tips for that… anything.

Thanks!

Seems like Salesforce burnt some of their TPU credits to train a really large language model: https://einstein.ai/presentations/ctrl.pdf

I am really curious what the community thinks about the advances Apple seems to be claiming on device with their neural engine and GPUs with each new phone. What applications do you foresee for AI applications on device? Training as well or just inference? Where do you think they are taking this? Super curious to hear some opinions on this.