On Linear Algebra, it's rather rusty as it was a sudden leap into proof-heavy classes, so I didn't quite get what was going on most of the time. I have gone through an intro class on ML and Optimization as well (Rather superficial concepts without much exercises). I am going through a gap year - don't wanna be paying a hefty amount for zoom-classes next study year - so will be class-free for approximately 14 months. Personally aiming to devote 5 hours a day, 6 days a week.

When Camille François, a longstanding expert on disinformation, sent an email to her team late last year, many were perplexed. Her message began by raising some seemingly valid concerns: that online disinformation -- the deliberate spreading of false narratives typically designed to sow mayhem -- "could get out of control and become a huge threat to democratic norms". But the text from the chief innovation officer at social media intelligence group Graphika soon became rather more wacky. Disinformation, it read, is the "grey goo of the internet", a reference to a nightmarish, end-of-the world scenario in molecular nanotechnology. The solution the email proposed was to make a "holographic holographic hologram". The bizarre email was not actually written by François, but by computer code; she had created the message -- from her basement -- using text-generating artificial intelligence technology.

After decades of debate on the feasibility of open access (OA) to scientific publications, we may be nearing a tipping point. A number of recent developments, such as Plan S, suggest that OA upon publication could become the default in the sciences within the next several years. Despite uncertainty about the long-term sustainability of OA models, many publishers who had been reluctant to abandon the subscription business model are showing openness to OA (1). Although more OA can mean more immediate, global access to scholarship, there remains a need for practical, sustainable models, for careful analysis of the consequences of business model choices, and for "caution in responding to passionate calls for a'default to open'" (2). Of particular concern for the academic community, as subscription revenues decline in the transition to OA and some publishers prioritize other sources of revenue, is the growing ownership of data analytics, hosting, and portal services by large scholarly publishers.

A team from the Allen Institute for Artificial Intelligence and the University of Washington this week introduced TLDR generation, a new automatic summarization task for scientific papers. The researchers also provide an associated dataset and propose a multitask learning approach for generating TLDR using pretrained language models. Here is a quick read: AI2 & UW Researchers Propose'TL;DR' Paper Summarization Task The paper TLDR: Extreme Summarization of Scientific Documents is on arXiv.

It's very rare to see any travel video or brochure these days that doesn't have an image shot from overhead, on a drone. Life seems more dramatic up from above, right? The units themselves have gotten way easier to use, more affordable and the camera quality is pretty amazing. Imagine being able to throw a high-quality camera in the air that can get stunning overhead shots, smooth video even in wind and always somehow return home to sender. It's one of the major tech advancements of our time, but it can be a little confusing.

Those of you who work on GANs in PyTorch know that performance evaluation of this kind of models is highly dependent on TensorFlow, at least in the domain of 2D image generation. Efficiency: since these metrics share the same feature extractor (Inception V3), computing all of them together is not much longer than computing just one. Fidelity: discrepancies of the metrics are checked through a number of tests.

"A significant limitation of most soft robots is that they have to be attached to a bulky air compressor or plugged into a wall, which prevents them from moving," said Nathan Usevitch, a graduate student in mechanical engineering at Stanford. "So, we wondered: What if we kept the same amount of air within the robot all the time?" From that starting point, the researchers ended up with a human-scale soft robot that can change its shape, allowing it to grab and handle objects and roll in controllable directions. Their invention is described in a paper published March 18 in Science Robotics. "The casual description of this robot that I give to people is Baymax from the movie Big Hero 6 mixed with Transformers. In other words, a soft, human-safe robot mixed with robots that can dramatically change their shape," said Usevitch.

It won't be long before artificial intelligence is writing and creating films. As impossible as it seems, it won't be long before artificial intelligence is writing and creating films. For example, one AI computer was given hundreds of samples of 17th-century "Old Master" style paintings and was asked to create its own paintings. One of the paintings it came up with is titled "Portrait of Edmond De Belamy" and sold for a whopping $432,500 at a Christie's auction. Thus, AI can write entire stories, create visual images, and create music, and it will not be long before these abilities are combined with entire movies being created by AI, perhaps even emulating existing actors or creating new "stars" for a franchise.

In an endeavour to upskill the youth and promote e-learning during the COVID-19 lockdown, IIT Roorkee had launched an Advanced Certification Course on Deep Learning at Cloudxlab.com. It is an advanced course on deep learning and would cover cutting edge techniques applicable to audio processing, image processing, video processing, self-driving cars etc. This came in the wake of the current economic crisis which underscores the significance of technical skills to tackle the global slowdown. Further to the launch IIT Roorkee and CloudxLab will conduct a webinar on careers in AI and machine learning. The webinar will include faculty members from IIT Roorkee as well as members of the industry.

The basis for using technology to analyze human emotions according to facial cues was inspired by Paul Eckman's research into facial expressions and emotion in the 1960s and 70s. Intrigue and solutions based on the scientific link between emotion and facial expressions has continued ever since Eckman's early published work. Debate and scrutiny are the foundation of scientific inquiry, and scientific conclusions and inferences are built on observation and data. Such is the case with facial coding and Emotion AI technology. Recently, publications like Nature and the Verge have taken a close look at the merits and misconceptions of facial coding and emotion AI.