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9 Best YouTube Playlists and Videos -- Python for Machine Learning


YouTube is a great place to learn about Python for machine learning. Below are the best YouTube playlists for Python that I have accumulated over months of learning. To ensure retention in what you learn, I suggest you watch the videos and make notes, either on paper or Google Docs. This way, you can remember what you learn. Not only that, it is a good practice to write code along with the videos, and write it after chunks and not follow in real-time.

When immunity to coronavirus increases, will resistance to AI decrease? Forbes India Blog


In this desperate fight for saving ourselves and our species, the main weapon we have deployed is intelligence. What we are witnessing is a spectacular collaboration of individual and collective human and Artificial Intelligence (AI). As we deal with the fear of a biological apocalypse, will our fear of the other apocalypse, AI taking over humans, reduce to give way to more confidence and faith in tech based innovation? Artificial intelligence Canadian health monitoring company Blue Dot's AI algorithms had predicted coronavirus long before it went viral and was officially declared as a threat. Over the last few weeks, research teams worldwide have been using AI to study big data to power breakthroughs in finding the elusive cure for Covid-19.

How artificial intelligence data mining can help us fight COVID-19


While we focus on vaccines, anti-virals and respirators in the fight against COVID-19, there's another type of technology that gets less attention, but may be even more important in lessening the impact of the pandemic--information technology. Given that we've been hearing more and more about the importance of widespread testing, we're probably less surprised at this than we might have been a few weeks ago. It's becoming increasingly clear that knowledge is actually one of the most important tools we have. The good news is that we have people working all the angles on this, from artificial intelligence data mining to genetic sequencing. Why is this so important?

r/MachineLearning - [N] Launching a competition for more energy-efficient NLP models


The NLP community has been focusing a lot on chasing the SOTA on standard and recent leaderboards (GLUE, SentEval...) over the recent years. While this aspiration has led to improvements in model performances, it has also resulted in a worrisome increase in model complexity and computational resources required to train and use the current state-of-the-art models. There is currently a lack of incentive to keep models small and efficient and research the optimal trade-offs between performances and efficiency. SustaiNLP 2020 (co-located with EMNLP 2020) has officially launched a shared-task/competition to promote the development of effective, energy-efficient models for difficult NLU tasks. The competition will end on 08/28.

Biggest Spenders in AI - Talking AI with Matt Armstrong-Barnes, CTO at HPE PART 1


It is estimated that by 2021 the yearly spend on AI will be £52 billion dollars. From the retail sector, financial service, manufacturing and healthcare, AI is being invested in by all industries. Watch talk about this as well as how this is going to impact the consumer space!

Enlisting AI in our war on coronavirus: Potential and pitfalls


Given the outsized hold Artificial Intelligence (AI) technology has acquired on public imagination of late, it comes as no surprise that many are wondering what AI can do for the public health crisis wrought by the COVID-19 coronavirus. A casual search of AI and COVID-19 already returns a plethora of news stories, many of them speculative. While AI technology is not ready to help with the magical discovery of a new vaccine, there are important ways it can assist in this fight. Controlling epidemics is, in large part, based on laborious contact tracing and using that information to predict the spread. We live in a time in which we constantly leave digital footprints through our daily life and interactions.

'Fear' is the most widespread emotion on social media due to coronavirus

Daily Mail - Science & tech

Fear is spreading on social media as people share their thoughts on the deadly coronavirus and the impact of the efforts to combat it. Italian-based artificial intelligence company Expert System has been searching through tens of thousands of social media posts to track feelings towards COVID-19. They used a range of natural language systems to capture the emotional view of different English language social media posts related to the pandemic. The team plan to publish a daily update showing the changing attitudes and emotions surrounding the spread of the virus and efforts to slow it down. For the fourth day in a row fear has been the most dominant emotion expressed in posts, with all negative views increasing across the English-language world.

Automatic for the People: Pandemic-fueled rush to robo-moderation will be disastrous – there must be oversight


Analysis The Electronic Frontier Foundation on Thursday warned that the consequences of the novel coronavirus pandemic – staff cuts, budget cuts, and lack of access to on-site content review systems, among others – have led tech companies to focus even more resources on barely functional moderation systems. Technology platforms have tended to favor automated content moderation over human editorial oversight. The results of such algorithmic policing have been imperfect but, more importantly to those implementing these systems, inexpensive compared to salaried employees or underpaid contractors. Though most of the major tech companies involved in overseeing user-generated posts have been celebrating machine learning for years now, the EFF frets that AI-driven moderation has been talked up a bit too much lately. The advocacy group points to recent public statements by Facebook, Twitter, and YouTube that cite increased reliance on automated tools for content moderation.

Beyond analytics: Artificial intelligence!


Sign in to report inappropriate content. Anyvision has built the world's leading facial recognition platform based on 20 years of academic research and field experience. Their solution is now used across multiple industries, globally. At this webinar, you will hear from, industry expert, Adnan Kichlu from Anyvision.

Huawei open-sources TensorFlow competitor MindSpore


Huawei has announced that its framework for AI app development MindSpore is now open source and available on GiHub and Gitee. The lightweight suite is similar to Google's TensorFlow and Facebook's PyTorch as it lowers the barrier to entry for developers looking to add AI to their apps. We implement AI Algorithms As Code through on-demand collaboration for easier model development, and provide cutting-edge technologies, and co-optimization with Huawei Ascend AI processors to improve runtime efficiency and computing performance. We also support other processors such as GPU and CPU." MindSpore already has the backing of a number of partners including the University of Edinburgh, Peking University, Imperial College London and the robotics startup Milvus. The framework is able to run on processors, graphics cards and dedicated neural processing units such as the one in Huawei's own Ascend AI chips.