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Text to speech, automation and AI: How Google is backing Middle East news providers

ZDNet

Google has awarded just under $2m to 21 projects in the Middle East, Turkey and Africa, following the first Google News Initiative (GNI) Innovation Challenge in the region. The move is part of a wider series of regional innovation challenges, and a global commitment from Google News to give $300m "to help journalism thrive in the digital age". A key focus for funding is "to support projects that drive digital innovation and develop new business models". Specifically in the Middle East, proposals were asked to focus on projects that "increase reader engagement and/or explore new business models to build a stronger future for journalism". Engagement was defined as a key metric, given that "engaged users are … more likely to convert to paid subscribers", while the focus on business models sought to encourage "moves which go beyond the traditional means to generate revenues".


Artificial Intelligence (AI): What it is and isn't - GGconversations with Mr. Jean-François Gagné

#artificialintelligence

OTTAWA, Oct. 14, 2020 /CNW/ - Her Excellency the Right Honourable Julie Payette, Governor General of Canada, will be joined by Mr. Jean-François Gagné, Founder and CEO of Element AI. Their conversation will take place live on Thursday, October 15, 2020, at 1:30 p.m. EDT (French) and 2:30 p.m. EDT (English). Their conversation, entitled "Artificial Intelligence (AI): What it is and isn't" will focus on the roles that AI is expected to play in the near future in Canada and around the world. Mr. Gagné will also answer questions from Canadians from across the country. In addition to being the founder of Element AI, Mr. Gagné is an outspoken advocate of AI for Good and is actively involved in guiding AI's impact on business, people and society.


[P] tldrstory: Build AI-powered applications that understand headlines and story text

#artificialintelligence

A zero-shot classifier, backed by a large general language model with no labeled data, is used to label data. Additionally, a txtai index enables ad hoc similarity searches against the data. Example application that uses the tldrstory framework to explore objectivity and bias in recent news headlines related to the 2020 US Presidential Election shown in video above.


[D] Simple Questions Thread October 11, 2020

#artificialintelligence

The predict function in Python is Y X * Beta, where Y is a column vector, X is the design matrix, and Beta is the column vector of parameters. You could definitely programmatically create the equation in the form that you want though. I don't what function/module you are using for your regression. Are you processing the data into polynomial features, then feeding that to a linear regression model? You just have to feed it the original column names.


[D] Could AI use what it learns in one subject to assist learning in another?

#artificialintelligence

The problem with "AI" is that it almost never looks enough like our intelligence. So, depending on what we think is similar and what we think is not, the answer to your question will change, but we don't really know. I can answer your question with what I think can be similar: when you train an "AI" on cats and dogs, the AI will process the images with convolution filters. It'll process the image with a learned mathematical function. Well, this function can be applied to images of birds such that the information you extract from bird images is useful enough to learn faster what a bird is compared to a snake.


The Future of Fake News - KDnuggets

#artificialintelligence

Is Bitcoin the revolution against unequal economic systems, or a scam and money laundry mechanism? Will artificial intelligence (AI) improve and boost humankind, or terminate our species? These questions present incompatible scenarios, but you will find supporters for all of them. They cannot be all right, so who's wrong then? Ideas spread because they are attractive, whether they are good or bad, right or wrong.


Someone let a GPT-3 bot loose on Reddit -- it didn't end well

#artificialintelligence

A GPT-3-powered bot has been caught posing as a human on Reddit after more than a week of rampant posting on one of the site's most popular subreddits. Under the username of thegentlemetre, the bot had been churning out a post per minute on /r/AskReddit, a sub with more than 30 million users. That behavior raised the suspicions of writer Philip Winston. "I read through some of the posts and they reminded me of text I'd seen from OpenAI's language model GPT-3," Winston wrote on his blog. Winston shared his theory on the subreddit /r/GPT3. Another Redditor named Wiskkey noticed that the structure of its writing was similar to that used by the Philosopher AI, a controversial text generator powered by GPT-3.


The Future of Fake News

#artificialintelligence

Is Bitcoin the revolution against unequal economic systems, or a scam and money laundry mechanism? Will artificial intelligence (AI) improve and boost humankind, or terminate our species? These questions present incompatible scenarios, but you will find supporters for all of them. They cannot be all right, so who's wrong then? Ideas spread because they are attractive, whether they are good or bad, right or wrong.


A GPT-3 bot posted comments on Reddit for a week and no one noticed

MIT Technology Review

Busted: A bot powered by OpenAI's powerful GPT-3 language model has been unmasked after a week of posting comments on Reddit. Under the username /u/thegentlemetre, the bot was interacting with people on /r/AskReddit, a popular forum for general chat with 30 million users. It was posting in bursts of roughly once a minute. Fooled ya--again: It's not the first time GPT-3 has fooled people into thinking what it writes comes from a human. In August a college student published a blog post that hit the top spot on Hacker News and led a handful of people to subscribe.


[D] Simple Questions Thread September 27, 2020

#artificialintelligence

I have a large data set of images with associated spatial coordinates. This data set represents a large raster scan (in the spatial coordinate space.) I do have a simple cost function that takes these images and returns a single, positive real number. Let's call a spatial position x, and the real scalar F(x). If I were to consider **only** the spatial coordinates and these responses, I have a fairly straightforward optimization problem.