"We seem to be safe for the moment, however - the MIT team said it has no interest in taking artificially intelligent horror machines to the next level or exploring their darker possibilities. "We wanted to playfully commemorate humanity's fear of AI, which is a growing theme in popular culture, but we currently have no plans to use the immense power of AI to scare people further," Yanardag said. "The world is already pretty scary!""
"As part of her undergraduate research, Alice Xue studied whether a machine could pass a Visual Turing Test by producing images that people cannot tell were made by a machine. Xue trained an algorithm using 2,192 traditional Chinese landscape paintings collected from art museums. The resulting AI-generated paintings were mistaken for being made by humans 55 per cent of the time."
"Contemporary AI systems are now becoming human-competitive at general tasks,[3] and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us? Should we risk loss of control of our civilization? Such decisions must not be delegated to unelected tech leaders. Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. This confidence must be well justified and increase with the magnitude of a system's potential effects. OpenAI's recent statement regarding artificial general intelligence, states that "At some point, it may be important to get independent review before starting to train future systems, and for the most advanced efforts to agree to limit the rate of growth of compute used for creating new models." We agree. That point is now."
"PhotoGuard works by altering select pixels in an image such that they will disrupt an AI's ability to understand what the image is. Those "perturbations," as the research team refers to them, are invisible to the human eye but easily readable by machines. The "encoder" attack method of introducing these artifacts targets the algorithmic model's latent representation of the target image - the complex mathematics that describes the position and color of every pixel in an image - essentially preventing the AI from understanding what it is looking at."
"Until recently, I was deeply sceptical of the idea of AI art. I saw it as hype and casuistry, and with some cause: widely publicised efforts such as Ai-Da the robot artist obviously exaggerate the independence of the machine and play on our fascination with sentient artificial beings. But now the dream is coming true, at least in art. And art is surely one of the most inimitable expressions of the human mind."
"Researchers put AI normally used to search for helpful drugs into a kind of "bad actor" mode to show how easily it could be abused at a biological arms control conference.
All the researchers had to do was tweak their methodology to seek out, rather than weed out toxicity. The AI came up with tens of thousands of new substances, some of which are similar to VX, the most potent nerve agent ever developed. Shaken, they published their findings this month in the journal Nature Machine Intelligence."
"This is the dystopian nightmare that Russell fears if his discipline continues on its current path and succeeds in creating super-intelligent machines. It's the scenario implicit in the philosopher Nick Bostrom's "paperclip apocalypse" thought-experiment and entertainingly simulated in the Universal Paperclips computer game. It is also, of course, heartily derided as implausible and alarmist by both the tech industry and AI researchers. One expert in the field famously joked that he worried about super-intelligent machines in the same way that he fretted about overpopulation on Mars."
"Google is using romance novels to teach its artificial intelligence (AI) system to better understand how people communicate.
Researchers at Google Brain, the company's AI-focused deep learning project, presented a paper earlier this month that detailed techniques they used to teach its AI to write fiction - and the results were unexpectedly haunting."
"Recent advances in AI are likely to spell the end of the traditional school classroom, one of the world's leading experts on AI has predicted.
Prof Stuart Russell, a British computer scientist based at the University of California, Berkeley, said that personalised ChatGPT-style tutors have the potential to hugely enrich education and widen global access by delivering personalised tuition to every household with a smartphone. The technology could feasibly deliver "most material through to the end of high school", he said."
"Yes of course. We are basically the last generation, or maybe there will be one more after us, who grew up without strong AI writing assistants. But these AI assistants are here now, especially in English. In German the systems are following suit, even though they're still much stronger in English. You get to a stage where someone who cannot write very well, can be pulled to a decent level of writing through machine assistance. And this raises important questions: Are we no longer learning the basics? In order to step up and really improve your writing, you will probably always need to be deeply proficient in the cultural practice of writing. But we need to ask, what proportion of low and medium level writers will be raised with the help from machines to a very decent level? And what repercussions does this have on teaching and learning, and the proficient use of language and writing? We shouldn't neglect our writing skills, because we believe machines will get us there. Anyone who has children can clearly see the dangers autocorrect and autocomplete will have for the future of writing."
"Over the Bridge hopes the project emphasizes exactly how much work goes into creating AI music. "There's an inordinate amount of human hands at the beginning, middle and end to create something like this," explained Michael Scriven, a rep for Lemmon Entertainment whose CEO is on Over the Bridge's board of directors.
Scriven added, "A lot of people may think [AI] is going to replace musicians at some point, but at this point, the number of humans that are required just to get to a point where a song is listenable is actually quite significant.""
"The camera never lies. Except, of course, it does - and seemingly more often with each passing day.
In the age of the smartphone, digital edits on the fly to improve photos have become commonplace, from boosting colours to tweaking light levels.
Now, a new breed of smartphone tools powered by artificial intelligence (AI) are adding to the debate about what it means to photograph reality.
Google's latest smartphones released last week, the Pixel 8 and Pixel 8 Pro, go a step further than devices from other companies. They are using AI to help alter people's expressions in photographs.
It's an experience we've all had: one person in a group shot looks away from the camera or fails to smile. Google's phones can now look through your photos to mix and match from past expressions, using machine learning to put a smile from a different photo of them into the picture. Google calls it Best Take. "
"If you've been job hunting recently, chances are you've interacted with a resume robot, a nickname for an Applicant Tracking System, or ATS. In its most basic form, an ATS acts like an online assistant, helping hiring managers write job descriptions, scan resumes and schedule interviews. As artificial intelligence advances, employers are increasingly relying on a combination of predictive analytics, machine learning and complex algorithms to sort through candidates, evaluate their skills and estimate their performance. Today, it's not uncommon for applicants to be rejected by a robot before they're connected with an actual human in human resources.
The job market is ripe for the explosion of AI recruitment tools. Hiring managers are coping with deflated HR budgets while confronting growing pools of applicants, a result of both the economic downturn and the post-pandemic expansion of remote work. As automated software makes pivotal decisions about our employment, usually without any oversight, it's posing fundamental questions about privacy, accountability and transparency."
"Green Light uses machine learning systems to comb through Maps data to calculate the amount of traffic congestion present at a given light, as well as the average wait times of vehicles stopped there. That information is then used to train AI models that can autonomously optimize the traffic timing at that intersection, reducing idle times as well as the amount of braking and accelerating vehicles have to do there. It's all part of Google's goal to help its partners collectively reduce their carbon emissions by a gigaton by 2030."
"A UK-based startup has used an AI algorithm to identify a previously unknown kind of rare-earth free magnet, in a potential breakthrough for how we discover and create new materials.
Materials Nexus, headquartered in London, used its machine learning algorithm to identify and analyse over 100 million combinations of materials that could produce a viable rare-earth free magnet."
"Researchers have shown that given access to only an API, a way to remotely use software without having it on your computer, it's possible to reverse-engineer machine learning algorithms with up to 99% accuracy. In the real world, this would mean being able to steal AI products from companies like Microsoft and IBM, and use them for free. Small companies built around a single machine learning API could lose any competitive advantage."
"At the heart of the problem that troubles Ming is the training that computer engineers receive and their uncritical faith in AI. Too often, she says, their approach to a problem is to train a neural network on a mass of data and expect the result to work fine. She berates companies for failing to engage with the problem first - applying what is already known about good employees and successful students, for example - before applying the AI."
" The observations made at Facebook are the latest in a long line of similar cases. In each instance, an AI being monitored by humans has diverged from its training in English to develop its own language. The resulting phrases appear to be nonsensical gibberish to humans but contain semantic meaning when interpreted by AI "agents." "
"This type of approach can speed up learning times and improve the efficiency of algorithms, says Max Jaderberg at Google's AI company DeepMind. The company used a similar technique last year to teach an AI to explore a virtual maze. Its algorithm learned much more quickly than conventional reinforcement learning approaches. "Our agent is far quicker and requires a lot less experience from the world to train, making it much more data efficient," he says."
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