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"While my company and the museum have distinct missions, both are important contributors to our society," said Whitney Museum of American Art vice chairman Warren B. Kanders. This statement, salvaged from a letter leaked by ARTnews in December, sets the tone as the opening visual for Forensic Architecture's installation at the Whitney Biennial--a 15-minute video delivering the collective's most recent foray into artificial intelligence, titled Triple Chaser. The London-based architecture and science research group chose to respond to the Kanders tear gas and munitions scandal not with a withdrawal from the biennial, but with the creation of a work of art-as-social justice tool, a submission that infiltrates the subject of derision's own institution. Their video, created in collaboration with director Laura Poitras and Praxis Films, is narrated by David Byrne cooly explaining how FA approached the training of a computer program to track and recognize images of "Triple Chaser" tear gas canisters and subsequently reduce the amount of human labor needed to do so. The program is trained to recognize the canisters, so named for the way they break into three distinct pieces after being fired, and not become used to identifying just the degraded landscapes they usually occur in.

David Harbour, best known for playing supernaturally beleaguered small-town cop Jim Hopper, is now on to even stranger things. In the mockumentary Frankenstein's Monster's Monster, Frankenstein, he plays a puffed-up version of himself, investigating the life of his father, David Harbour Junior, after he unearths footage of his dad's televised stage play while killing rats in his mother's attic. What Harbour discovers--the bizarre artifact that is the play Frankenstein's Monster's Monster, Frankenstein and lots more scandal besides--challenges everything he thinks he knows about his father in just about 30 minutes. Stranger Things' Noah Schnapp Has a Crush on Zendaya What Stranger Things' High Viewership Numbers Actually Mean What he finds is also bizarrely funny. In real life, Harbour's dad's name is Ken and he's in real estate.

Abstract: In the twilight of Moore's law, GPUs and other specialized hardware accelerators have dramatically sped up neural network training. However, earlier stages of the training pipeline, such as disk I/O and data preprocessing, do not run on accelerators. As accelerators continue to improve, these earlier stages will increasingly become the bottleneck. In this paper, we introduce "data echoing," which reduces the total computation used by earlier pipeline stages and speeds up training whenever computation upstream from accelerators dominates the training time. Data echoing reuses (or "echoes") intermediate outputs from earlier pipeline stages in order to reclaim idle capacity.

Abstract: We can define a neural network that can learn to recognize objects in less than 100 lines of code. However, after training, it is characterized by millions of weights that contain the knowledge about many object types across visual scenes. Such networks are thus dramatically easier to understand in terms of the code that makes them than the resulting properties, such as tuning or connections. In analogy, we conjecture that rules for development and learning in brains may be far easier to understand than their resulting properties. The analogy suggests that neuroscience would benefit from a focus on learning and development.

Significant advances are being made in artificial intelligence, but accessing and taking advantage of the machine learning systems making these developments possible can be challenging, especially for those with limited resources. These systems tend to be highly centralized, their predictions are often sold on a per-query basis, and the datasets required to train them are generally proprietary and expensive to create on their own. Additionally, published models run the risk of becoming outdated if new data isn't regularly provided to retrain them. We envision a slightly different paradigm, one in which people will be able to easily and cost-effectively run machine learning models with technology they already have, such as browsers and apps on their phones and other devices. Through this new framework, participants can collaboratively and continually train and maintain models, as well as build datasets, on public blockchains, where models are generally free to use for evaluating predictions.

Artificial intelligence, or AI, is one of the most intriguing topics in software development today. It is also one of the most widely misunderstood.

Computer pioneer and codebreaker Alan Turing will feature on the new design of the Bank of England's £50 note. He is celebrated for his code-cracking work that proved vital to the Allies in World War Two. The £50 note will be the last of the Bank of England collection to switch from paper to polymer when it enters circulation by the end of 2021. The note was once described as the "currency of corrupt elites" and is the least used in daily transactions. However, there are still 344 million £50 notes in circulation, with a combined value of £17.2bn, according to the Bank of England's banknote circulation figures.

AI Journalism and the 4IR will help companies, governments and people to have new tools for storing and analyzing information.