Patrick Clarke
, March 15th, 2021 10:30
With his new modular project Microcorps, Alexander Tucker blurs the lines between human and humanoid as he investigates how language can shift our perception. He tells Patrick Clarke the story of new album XMIT
The algorithms that dictate so much of our consumption – the next song you listen to, the next film you watch, the next person you go on a date with – are now so complex that they are approaching the point where not even their creators can comprehend them. “One of the biggest sources of anxiety about AI is not that it will turn against us, but that we simply cannot understand how it works,” wrote the Harvard Business Review in 2019. Algorithms now make so many decisions without consulting the people they effect, wrote Towards Data Science in a lengthy essay on the need for increased ethics in the field, that “they have become the decision makers, and humans have been pushed into an artefact shaped by technology.”
How to build a DIY voice assistant with Pi and Arduino
It was good to catch this on twitter. One Gadget Master, Marcelo Jose Rovai, was tweeting about using an Arduino Nano with TinyML to recognise the word “Yes”. And looking into it, he flagged his project as Building an Intelligent Voice Assistant, using a Raspberry Pi and Arduino from scratch!
#Arduino#Nano recognizes the word YES (#TinyML), that is used to call the #Google Assistant in my #Raspberry Pi (in Cascade). The TinyML application is local (#EdgeAI) and the RaspberryPi is connected with Google Cloud, where a more complex model is used. Soon full tutorial! pic.twitter.com/Cvw2zatDFm
January 15th, 2021
Xinhua News Agency via Getty Images
COVID-19 has infected more than 23 million Americans and killed 386,000 of them to date, since the global pandemic began last March. Complicating the public health response is the fact that we still know so little about how the virus operates such as why some patients remain asymptomatic while it ravages others. Effectively allocating resources like ICU beds and ventilators becomes a Sisyphean task when doctors can only guess as to who might recover and who might be intubated within the next 96 hours. However a trio of new machine learning algorithms developed by Facebook’s AI division (FAIR) in cooperation with NYU Langone Health can help predict patient outcomes up to four days in advance using just a patient’s chest x-rays.
This year, I read fewer business books than I usually do. You probably did, too. The category’s sales are down 20% since March, according to NPD’s Bookscan.
It’s not hard to understand why. A lot happened this year to distract us from our usual routines: a pandemic, a recession, an election.
Faced with these upheavals, it might not have seemed like books, particularly business books, would have much advice on how to navigate a world that, on many fronts, was hard to recognize. Many of the books published this year were written before Covid-19.
And yet, this was also a year in which business played a tremendous role in how we responded to the pandemic, from the creation of vaccines to our shift to remote work and e-commerce to the growing dominance of big tech in our economy. We saw the acceleration of business trends and the upending of old business models. How could the business books of 2020 inform our understanding of these shifts?