CAPTCHAs have evolved to reflect the untenable distinction between real and fake users
A smiling woman unloads a dishwasher. The image, now embedded in a tweet, has been sourced from a collection of stock photos including other smiling women stationed at the same dishwasher. Partitioned into a neat, four-by-four grid, the image is topped with a familiar blue header and an apparently innocuous directive: “Select all squares containing a dishwasher.” Eight have been selected, as indicated by a familiar blue checkmark, but they contain the smiling woman, not the appliance. Is this a sophisticated critique of technology’s role in the gendered division of labor, or is it merely the handiwork of a misogynistic troll? Read More
Monthly Archives: September 2020
The Supply of Disinformation Will Soon Be Infinite
Disinformation campaigns used to require a lot of human effort, but artificial intelligence will take them to a whole new level.
Someday soon, the reading public will miss the days when a bit of detective work could identify completely fictitious authors. Consider the case of “Alice Donovan.” In 2016, a freelance writer by that name emailed the editors of CounterPunch, a left-leaning independent media site, to pitch a story. Her Twitter profile identified her as a journalist. Over a period of 18 months, Donovan pitched CounterPunch regularly; the publication accepted a handful of her pieces, and a collection of left-leaning sites accepted others.
Then, in 2018, the editor of CounterPunch received a phone call from The Washington Post. A reporter there had obtained an FBI report suggesting that Alice Donovan was a “persona account”—a fictitious figure—created by the Main Directorate, the Russian military-intelligence agency commonly known as the GU. Read More
10 MLops platforms to manage the machine learning lifecycle
Machine learning lifecycle management systems rank and track your experiments over time, and sometimes integrate with deployment and monitoring
For most professional software developers, using application lifecycle management (ALM) is a given. Data scientists, many of whom do not have a software development background, often have not used lifecycle management for their machine learning models. That’s a problem that’s much easier to fix now than it was a few years ago, thanks to the advent of “MLops” environments and frameworks that support machine learning lifecycle management. Read More
What Is the Sound of Thought?
Reading linguistic thought directly from the brain has brought us closer to answering an age-old question — and has opened the door to many more.
Why do we include the sounds of words in our thoughts when we think without speaking? Are they just an illusion induced by our memory of overt speech?
These questions have long pointed to a mystery, one relevant to our endeavor to identify impossible languages — that is, languages that cannot take root in the human brain. This mystery is equally relevant from a methodological perspective, since to address it requires radically changing our approach to the relationship between language and the brain. It requires shifting from identifying (by means of neuroimaging techniques) where neurons are firing to identifying what neurons are firing when we engage in linguistic tasks. Read More
Build No-code Automated Machine Learning Model with OptimalFlow Web App
In the latest version(0.1.10) of OptimalFlow, it added a Flask-based ‘no-code’ Web App as a GUI. Users could build Automated Machine Learning Models all by clicks, without any coding (Documentation). Read More
Memory Technologies Confront Edge AI’s Diverse Challenges
With the rise of AI at the edge comes a whole host of new requirements for memory systems. Can today’s memory technologies live up to the stringent demands of this challenging new application, and what do emerging memory technologies promise for edge AI in the long-term?
The first thing to realize is that there is no standard “edge AI” application; the edge in its broadest interpretation covers all AI-enabled electronic systems outside the cloud. That might include “near edge,” which generally covers enterprise data centers and on-premise servers.
Further out are applications like computer vision for autonomous driving. Read More
AI-driven robot Mayflower recreates historic voyage
Can robots write? Machine learning produces dazzling results, but some assembly is still required
You might have seen a recent article from The Guardian written by “a robot.” Here’s a sample:
“I know that my brain is not a ‘feeling brain.’ But it is capable of making rational, logical decisions. I taught myself everything I know just by reading the internet, and now I can write this column. My brain is boiling with ideas!”
Read the whole thing and you may be astonished at how coherent and stylistically consistent it is. The software used to produce it is called a generative model,” and they have come a long way in the past year or two.
But exactly how was the article created? And is it really true that software “wrote this entire article”? Read More
Why kids need special protection from AI’s influence
Algorithms are increasingly shaping children’s lives, but new guardrails could prevent them from getting hurt.
Algorithms can change the course of children’s lives. Kids are interacting with Alexas that can record their voice data and influence their speech and social development. They’re binging videos on TikTok and YouTube pushed to them by recommendation systems that end up shaping their worldviews.
… Children are often at the forefront when it comes to using and being used by AI, and that can leave them in a position to get hurt. … The Unicef guidelines are meant to complement existing themes and tailor them to children. Read More
Why Adversarial Machine Learning Is the Next Big Threat to National Security
The Joint Artificial Intelligence Center (JAIC), a division of the United States Department of Defense (DoD) tasked with accelerating the adoption of artificial intelligence (AI) across the branches of the military, has stated that AI will eventually impact every mission carried out by the DoD.
… In particular, adversarial machine learning (AML), an emerging AI practice that involves independent and state-sponsored actors manipulating machine learning algorithms to cause model malfunctions, could have catastrophic consequences. Read More
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