A summary of recent happenings in the field of Artificial Intelligence (AI) for week 38 of 2020. For more regular updates and related discussions, join us in the Artificial Intelligence Community. As always, thanks for your support for sharing it with your friends and colleagues on social media.
Industry updates for week 38 of 2020
This section is for recent industry updates related to Artificial Intelligence.
- Car Insurance claims using AI: Insurance companies are shifting to virtual insurances as it fastens the entire process from months to a few hours. One such leader is Tractable, a UK based firm with CV experts that processes images from the crash site and suggests or authorizes the insurances. All you need to do is download the application to the respective insurer and get set go. To read more soon this, visit here.
- A self-taught ML Researcher: This is an interview session with Sanjeev Sharma, founder of Swaayatt Robots. To get motivated, read his entire talk here.
- IBM’s autonomous ship: AI guided ship developed by IBM is set to test launch before the actual launch date in 2021. The Mayflower Autonomous Ship (MAS) was pushed from coastal waters of England on Wednesday, September 16, 2020. To read the entire article, visit here Also, we can see the ships’ progress here.
- Tesla can control the wrong vehicles: The Chinese owners of Tesla have found a flaw in the Tesla app that was found to be connected to the wrong car and was hence being remotely controlled by them. To know more details, visit here.
- NVIDIA’s attempt to shift AI from the cloud: This big tech giant has cracked a $40 Billion deal with ARM with a long term strategic aim to strengthen their place in the AI race. With innumerable developments in AI and its corresponding applications, this move implies a bigger agenda that enables the semiconductor industry to help fulfill future AI possibilities.
Articles for week 38 of 2020
This section is for recent Blog Posts/Tutorials related to Artificial Intelligence.
- GAN Slimming: This is an image-to-image translation technique for compression. Here are the entire article and the code.
- Time series forecasting: Stock market prediction using LSTM is explained with supporting python script. A time saver for a newbie working in market prediction. Read the full article here.
- TensorFlow object detection: A step by step guide for training and then inferencing on the cloud using TensorFlow version 1.15 is explained here.
- Randomization to improve privacy: in the need to collect more and more data, the contributor’s identity also needs to be protected. The solution to maintain user identity is through Randomization. This article here explains the minute details of reasons for Randomization and ways to do it.
- Graph-based deep learning: A nice repository of all the publications related to Graph-based deep learning can be found here.
- Imitation Learning: Google’s PWML (Primal Wesserstein Imitation Learning) has a new IL algorithm based on the earth mover’s distance which does not involve adversarial training. Read more and watch its demonstration here.
- Improving Sparse training: The efficient sparse neural networks are preferred over the dense models and Google’s research team has introduced RigL (Rigging the Lottery) algorithm to train sparse networks while maintaining accuracy and fixed-parameter count. Read the full article here
- AI ethics group: The need to get all the AI researchers at a standard level without alarming the security concerns of AI is a hot topic across the western world. The need for proper medium to come to common ground is the key to AI ethics. To read the complete article, visit here.
- Latest Data science Newsletters: To stay updated with the latest developments in the data science field, here is the list of top 10 newsletters.
- Neural Networks struggle with the Game of Life: A grid-based automation algorithm remains a mystery to ANN (Artificial Neural Networks) as pointed by researchers at Swarthmore College and Los Alamos National Laboratory. The findings can be read here and the newsreel over here.
- Explainable Face Recognition (XFR): The article mentions the baseline for XFR and proposes Inpainting game along with a detailed evaluation f XFR. The article can be read here.
- The similarity between AI and Animal Intelligence: This article introduces astonishing dynamics that are shared between artificial and biological systems. To read the entire article, visit here.
This section is for recent Tools/Applications related to Artificial Intelligence.
- Dialog ranking Pre-trained Transformers: How likely a dialog response is given an upvote is predicted using Dialog RPT. The script is accessible here.
- Paint with ML: This script converts input segmentation into Landscape painting. The demo of the script is available here.
This section is for recent Lectures/Conferences/Webinars related to Artificial Intelligence.
- Call for papers in HIS 2020: The Hybrid Computational Intelligence is due to be held from 14 December 2020 to 16 December 2020. To submit a paper visit here.
- GAN Course: The course on the deep learning website for GAN is due to begin this September 30th, 2020. To enroll, visit here.
- Multimodal Emotion Recognition Competition: To join the competition, register here.
- Convert 2D to 3D: A video demonstration of deep fake neural networks to transform 2D into 3D images. Gender classification using Facial image: This video shows gender discrimination using a deep face library in just 5 lines of code.
This section is for recent research published related to Artificial Intelligence.
- Decoupling Representation learning from reinforcement learning: link
- Array Programming with Numpy: link
- Layered Neural Rendering for Retiming people in the video: link
- The Hardware Lottery: link
- Event Prop: Backpropagation for Exact Gradients in Spiking Neural Networks: link
This section is for updates for other various related topics to Artificial Intelligence.
That’s all for the week 38 of 2020. In case you think we have missed out something and that is significant to add, please free to reach out and submit to us via our Contact form or via Social media channels: Twitter and Facebook.