This week DARPA kicks off a competition called the Subterranean Challenge, where hordes of robots are unleashed into caves and tunnels to test how well they can autonomously navigate these environments. One team, headed up by NASA’s Jet Propulsion Lab (JPL), is entering a crew of bots that could inform future designs of spacefaring robots that explore caves and lava tubes on other planets and moons.
Scientists have developed an automated tool for mapping the movement of particles inside cells that may accelerate research in many fields, a new study in eLife reports.
The movements of tiny molecules, proteins and cellular components throughout the body play an important role in health and disease. For example, they contribute to brain development and the progression of some diseases. The new tool, built with cutting-edge machine learning technology, will make tracking these movements faster, easier and less prone to bias.
Currently, scientists may use images called kymographs, which represent the movement of particles in time and space, for their analyses of particle movements. These kymographs are extracted from time-lapse videos of particle movements recorded using microscopes. The analysis needs to be done manually, which is both slow and vulnerable to unconscious biases of the researcher.
Putin’s robo-nauts prepare for lift-off: Fedor as he gets ready to board the International Space Station crew next week…
Icknamed Fedor, the anthropomorphous machine — which is remarkably agile — was seen undergoing a battery of stress-tests at the Baikonur Cosmodrome in Kazakhstan, last month.
Two trends that are dominating the technology industry are the Internet of Things (IoT) and Artificial Intelligence (AI). But for industrial automation, these two technologies are much more than the buzzwords or trending topics. The convergence of AI and IoT will redefine the future of industrial automation. It is set to lead the Industry 4.0 revolution.
IoT and AI are two independent technologies that have a significant impact on multiple industry verticals. While IoT is the digital nervous system, AI becomes the brain that makes decisions which control the overall system. The lethal combination of AI and IoT brings us AIoT — Artificial Intelligence of Things — that delivers intelligent and connected systems that are capable of self-correcting and self-healing themselves.
To appreciate the promise of AIoT, we need to look at the evolution of connected systems.
Blockchain startup BitFury launched an artificial intelligence (AI) unit, Reuters reports on Aug. 13.
“Data is the new oil”
Bitfury chief executive officer and co-founder Valery Vavilov reportedly said that the company’s dive into AI is motivated by the need to analyze and extract information from great quantities of data. He reportedly noted that data is becoming the new oil and stated:
Algorithms meant to spot hate speech online are far more likely to label tweets “offensive” if they were posted by people who identify as African-American.
AI systems meant to spot abusive online content are far more likely to label tweets “offensive” if they were posted by people who identify as African-American.
The news: Researchers built two AI systems and tested them on a pair of data sets of more than 100,000 tweets that had been annotated by humans with labels like “offensive,” “none,” or “hate speech.” One of the algorithms incorrectly flagged 46% of inoffensive tweets by African-American authors as offensive. Tests on bigger data sets, including one composed of 5.4 million tweets, found that posts by African-American authors were 1.5 times more likely to be labeled as offensive. When the researchers then tested Google’s Perspective, an AI tool that the company lets anyone use to moderate online discussions, they found similar racial biases.
A hard balance to strike: Mass shootings perpetrated by white supremacists in the US and New Zealand have led to growing calls from politicians for social-media platforms to do more to weed out hate speech. These studies underline just how complicated a task that is. Whether language is offensive can depend on who’s saying it, and who’s hearing it. For example, a black person using the “N word” is very different from a white person using it. But AI systems do not, and currently cannot, understand that nuance.
The art of matchmaking has traditionally been the province of grandmas and best friends, parents, and even—sometimes—complete strangers. Recently they’ve been replaced by swipes and algorithms in an effort to automate the search for love. But Kevin Teman wants to take things one step further.
The Denver-based founder of a startup called AIMM has built an app that matches prospective partners using just what they say to a British-accented AI. Users talk to the female-sounding software to complete a profile: pick out your dream home, declare whether you consider yourself a “cat person,” and describe how you would surprise a potential partner.
At first glance, that doesn’t seem too different from the usual swiping-texting-dating formula of modern online romance. But AIMM, whose name is an acronym for “artificially intelligent matchmaker,” comes with a twist: the AI coaches users through a first phone call, gives advice for the first date, and even provides feedback afterwards. Call it Cyrano de Bergerac for the smartphone era.
Posted in ethics, robotics/AI
An AI system introduced in 2015 with much fanfare in the U.S. failed to recognise faces of African Americans with the same accuracy as those of Caucasian Americans. | Photo Credit: AP
Posted in law, robotics/AI
If you want a vision of the future, imagine a thousand bots screaming from a human face – forever (apologies to George Orwell). As U.S. policymakers remain indecisive over how to prevent a repeat of the 2016 election interference, the threat is looming ever more ominous on the horizon. The public has unfortunately settled on the term “bots” to describe the social media manipulation activities of foreign actors, invoking an image of neat rows of metal automatons hunched over keyboards, when in reality live humans are methodically at work. While the 2016 election mythologized the power of these influence-actors, such work is slow, costly, and labor-intensive. Humans must manually create and manage accounts, hand-write posts and comments, and spend countless hours reading content online to signal-boost particular narratives. However, recent advances in artificial intelligence (AI) may soon enable the automation of much of this work, massively amplifying the disruptive potential of online influence operations.
This emerging threat draws its power from vulnerabilities in our society: an unaware public, an underprepared legal system, and social media companies not sufficiently concerned with their exploitability by malign actors. Addressing these vulnerabilities requires immediate attention from lawmakers to inform the public, address legal blind spots, and hold social media companies to account.
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