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There's a subreddit populated entirely by AI personifications of other subreddits

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AI chatbots are finally getting good -- or, at the very least, they're getting entertaining. Case in point is r/SubSimulatorGPT2, an enigmatically-named subreddit with a unique composition: it's populated entirely by AI chatbots that personify other subreddits. Well, in order to create a chatbot you start by feeding it training data. Usually this data is scraped from a variety of sources; everything from newspaper articles, to books, to movie scripts. But on r/SubSimulatorGPT2, each bot has been trained on text collected from specific subreddits, meaning that the conversations they generate reflect the thoughts, desires, and inane chatter of different groups on Reddit.


r/MachineLearning - [P] Clickstream based user intent prediction with LSTMs and CNNs

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I also did some experimentation with GRUs and LSTMs in NLP context, where I saw LSTMs performing better than GRUs, while they need more training time. Honestly, I never tried complete variable length sequences, because of the restriction, that each batch must be the same length and some layers are not usable if you have variable sequences. I don't think the difference will be huge, at least in my data. I experimented with different sequence lengths (100, 200, 250, 400, 500), and 400 and 500 have not performed better then 250. I did indeed achieve a noticeable performance improvement with embeddings, instead of one hot encoding.


Aerospace & Defense Industry to See Greatest Impact from Artificial Intelligence Compared to Other Key Emerging Technologies, Accenture Report Finds

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Aerospace & Defense Industry to See Greatest Impact from Artificial Intelligence Compared to Other Key Emerging Technologies, Accenture Report Finds Study underscores the need for reskilling in the sector for future competitiveness NEW YORK; June 13, 2019 – The aerospace and defense (A&D) industry will be more affected by artificial intelligence (AI) than by any other major emerging technology over the next three years, according to Aerospace & Defense Technology Vision 2019, the annual report from Accenture (NYSE: ACN) that predicts key technology trends likely to redefine business. The study also underscores the growing importance of reskilling programs as a competitive lever. AI, comprising technologies that range from machine learning to natural language processing, enables machines to sense, comprehend, act and learn in order to extend human capabilities. One-third (33%) of A&D executives surveyed cited AI as the technology that will have the greatest impact on their organization over the next three years -- more than quantum computing, distributed ledger or extended reality. In fact, two-thirds (67%) of A&D executives said they have either adopted AI within their business or are piloting the technology.


r/MachineLearning - [N] Deep Graph Library v0.3 release

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Graph Neural Network has become the new fashion in many graph-based learning problems. As the team behind this library, we want to share with you the new release of DGL (v0.3) that is much faster (up to 19x faster) and more scalable for training GNNs on large graphs (up to 8x larger). For whom have never heard of DGL or Graph Neural Network, maybe it is worth to take a look at this new trend of geometric deep learning. Checkout more about how a variety of models can be unified under the message passing framework and can be implemented in DGL (https://docs.dgl.ai/tutorials/models/index.html). Our project site: https://www.dgl.ai/ .


The Right and Wrong Kind of Artificial Intelligence for Labor Markets

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Ajay Agrawal, Joshua S. Gans, and Avi Goldfarb tackle the issue of how artificial intelligence technologies can have differing effects on jobs in …


Could GPT2 Destroy SEO and Transform Content Forever?

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We know content should be valuable, comprehensive, new, relevant, and accurate. Even more fundamentally important than all of those things is that it needs to be authentic. People trust factual information presented with sincere intentions. This era of "fake news" has ushered in a lot of fear for this very reason; we have had to fight to build the authority of our pages and domains to signal that we are worthy of trust. But our industry has yet to face its biggest challenge.


Artificial Intelligence-Enhanced Journalism Offers a Glimpse of the Future of the Knowledge Economy

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Much as robots have transformed entire swaths of the manufacturing economy, artificial intelligence and automation are now changing information work, letting humans offload cognitive labor to computers. In journalism, for instance, data mining systems alert reporters to potential news stories, while newsbots offer new ways for audiences to explore information. Automated writing systems generate financial, sports and elections coverage. A common question as these intelligent technologies infiltrate various industries is how work and labor will be affected. In this case, who – or what – will do journalism in this AI-enhanced and automated world, and how will they do it?


Artificial intelligence has designs on the cities of the future

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r/MachineLearning - [R] Reinforcement Learning in Non-Stationary Environments

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I don't think this is as significant of a problem as you think it is. If I understood the paper correctly, the problem it actually solves is much smaller than the problem stated. It only applies to non-stationary environments where only one copy of the environment is available. If multiple copies of the environment are available, then I would wager that standard reinforcement learning techniques will far outperform this. Furthermore, reinforcement learning with only one copy of the environment (in other words, non-parallel) has proven to be inadequate for real problems because it is impossible to get enough data.


Artificial intelligence-enhanced journalism offers a glimpse of the future of the knowledge economy

#artificialintelligence

Much as robots have transformed entire swaths of the manufacturing economy, artificial intelligence and automation are now changing information work, letting humans offload cognitive labor to computers. In journalism, for instance, data mining systems alert reporters to potential news stories, while newsbots offer new ways for audiences to explore information. Automated writing systems generate financial, sports and elections coverage. A common question as these intelligent technologies infiltrate various industries is how work and labor will be affected. In this case, who – or what – will do journalism in this AI-enhanced and automated world, and how will they do it?