After a crisis in which the Venezuelan economy collapsed, hundreds of thousands of workers from Venezuela have signed up to work at companies such as Mighty AI that cater to the autonomous vehicle industry.
These crowdwork competitions “are the result of the growing competition to develop self-driving cars” and have brought some attention to the debate over AI being powered by underpaid workers annotating data. For the Venezuelans in such dire straits, however, this gig work represents an improvement for them and allows them to bring a steady income to their homes.
This is another reminder that progress in AI is driven in part by a lot of often overlooked human labor, as also highlighted in a recent NY Times article on the subject:
“A.I., most people in the tech industry would tell you, is the future of their industry, and it is improving fast thanks to something called machine learning. But tech executives rarely discuss the labor-intensive process that goes into its creation. A.I. is learning from humans. Lots and lots of humans.
Before an A.I. system can learn, someone has to label the data supplied to it. Humans, for example, must pinpoint the polyps. The work is vital to the creation of artificial intelligence like self-driving cars, surveillance systems and automated health care.”
Despite a silly seeming title, this is a good overview of the very real efforts of tech companies to win military contracts for their AI services:
“Dutch NGO Pax ranked 50 companies by three criteria: whether they were developing technology that could be relevant to deadly AI, whether they were working on related military projects, and if they had committed to abstaining from contributing in the future. … Twenty-two companies were of “medium concern,” while 21 fell into a “high concern” category, notably Amazon and Microsoft who are both bidding for a $10 billion Pentagon contract to provide the cloud infrastructure for the U.S. military.”
The results are detailed in a post by Pax titled Major Tech Companies may be putting world at risk from Killer Robots, which also includes examples of good practices for tech companies to follow. Leveraging AI advances for lethal military technology is a very real concern already, and organizations such as The Campaign to Stop Killer Robots are advocating to stop this from happening.
How YACHT fed their old music to the machine and got a killer new album - On how the band YACHT had been spending the last three years writing a new album called Chain Tripping using “a machine-learning generated composition process.”
Hello, This Is Artificial Intelligence. How Can I Help You? Eye on A.I. - On using AI to help people who call companies to ask questions about their cable bills or complain about their Internet service being out are increasingly talking to artificial intelligence.
AI thinks this flood photo is a toilet. Fixing that could improve disaster response. - A new data set aims to teach computer vision systems to recognize images from disasters.
Synapse Technology Wins Additional Air Force Contract to Develop and Deploy Automated Threat Detection at X-Ray Security Checkpoints - The Air Force awarded the Artificial Intelligence (AI) security and defense company Synapse Technology today a second contract to develop and deploy artificial intelligence technology for detecting weapons, sharps, and Improvised Explosive Devices at X-ray security checkpoints at Air Force bases.
AI And Societal Impact - Addressing Large, Complex Unresolved Problems With AI - The idea that AI will conjure up an apocalyptic, robot-ruled future, where mechanical overlords govern humans is an extremely low probability event, even in the very distant future.
Fraudsters Used AI to Mimic CEO’s Voice in Unusual Cybercrime Case - “Criminals used artificial intelligence-based software to impersonate a chief executive’s voice and demand a fraudulent transfer of €220,000 ($243,000) in March in what cybercrime experts described as an unusual case of artificial intelligence being used in hacking.”
Scientist to Hollywood: Artificial Intelligence Doesn’t Work the Way You Think it Does - As movie audiences anticipate the return of Arnold Schwarzenegger to his signature role as the original Terminator in November — yes, he WILL be back — scientist and rising star in the Artificial Intelligence world Matt Allen has a few thoughts for filmmakers about how AI is depicted in popular media.
Jordan Peterson: The deepfake artists must be stopped before we no longer know what’s real - Something very strange and disturbing happened to me recently. If it was just relevant to me, it wouldn’t be that important (except perhaps to me), and I wouldn—t be writing this column. But it—s something that is likely more important and more ominous than we can even imagine.
Are Engineers Afraid of AI Taking Their Jobs? What Can They Do about It? - An engineer checking and controlling welding robotics automatic arms machines in an intelligent industrial automotive factory using a monitoring system software used to belong to the science fiction realm. However, this is the reality of digital manufacturing operations in today’s Industry 4.
Data Annotation: The Billion Dollar Business Behind AI Breakthroughs - When Lei Wang became a data annotator two years ago her job was fairly simple: Identifying people’s gender in images.
Douglas Adams was right — knowledge without understanding is meaningless - Fans of Douglas Adams’s Hitchhiker’s Guide to the Galaxy treasure the bit where a group of hyper-dimensional beings demand that a supercomputer tells them the secret to life, the universe and everything. The machine, which has been constructed specifically for this purpose, takes 7.
Interpretability of Deep Learning Models with Tensorflow 2.0 - This article dives into the tf-explain library. It provides explanations on interpretability methods, such as Grad CAM, with Tensorflow 2.0.
How to get up to speed on Machine Learning and AI - A list of resources on AI for both technical and non-technical friends eager to learn more about this hot topic.
Text Generation - An overview post about text generation. How are these models trained? How are they used? Are they really that good? And dangerous?
Prejudice in A.I. - An explanatory post on why AI agents in the real world often go haywire.
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