Will A.I. Steal All The Code And Take All The Jobs?

March 8, 2023 by Joseph Long 59 Comments

New technology often brings with it a bit of controversy. When considering stem cell therapies, self-driving cars, genetically modified organisms, or nuclear power plants, fears and concerns come to mind as much as, if not more than, excitement and hope for a brighter tomorrow. New technologies force us to evolve perspectives and establish new policies in hopes that we can maximize the benefits and minimize the risks. Artificial Intelligence (AI) is certainly no exception. The stakes, including our very position as Earth’s apex intellect, seem exceedingly weighty. Mathematician Irving Good’s oft-quoted wisdom that the “first ultraintelligent machine is the last invention that man need make” describes a sword that cuts both ways. It is not entirely unreasonable to fear that the last invention we need to make might just be the last invention that we get to make.

Artificial Intelligence and Learning

Artificial intelligence is currently the hottest topic in technology. AI systems are being tasked to write prose, make art, chat, and generate code. Setting aside the horrifying notion of an AI programming or reprogramming itself, what does it mean for an AI to generate code? It should be obvious that an AI is not just a normal program whose code was written to spit out any and all other programs. Such a program would need to have all programs inside itself. Instead, an AI learns from being trained. How it is trained is raising some interesting questions.

Humans learn by reading, studying, and practicing. We learn by training our minds with collected input from the world around us. Similarly, AI and machine learning (ML) models learn through training. They must be provided with examples from which to learn. The examples that we provide to an AI are referred to as the data corpus of the training process. The robot Johnny 5 from “Short Circuit”, like any curious-minded student, needs input, more input, and more input.

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AI Dreaming Of Time Travel

September 28, 2022 by Matthew Carlson 20 Comments

We love the intersection between art and technology, and a video made by an AI (Stable Diffusion) imagining a journey through time (Nitter) is a lovely example. The project is relatively straightforward, but as with most art projects, there were endless hours of [Xander Steenbrugge] tweaking and playing with different parts of the process until it was just how he liked it. He mentions trying thousands of different prompts and seeds — an example of one of the prompts is “a small tribal village with huts.” In the video, each prompt got 72 frames, slowly increasing in strength and then decreasing as the following prompt came along.

There are other AI videos on YouTube, often putting the lyrics of a song into AI-generated form. But if you’ve worked with AI systems, you’ll notice that the background stays remarkably stable in [Xander]’s video as it goes through dozens of feedback loops. This is difficult to do as you want to change the image’s content without changing the look. So he had to write a decent amount of code to try and maintain visual temporal cohesion over time. Hopefully, we’ll see an open-source version of some of his improvements, as he mentioned on Twitter.

In the meantime, we get to sit back and enjoy something beautiful. If you still aren’t convinced that Stable Diffusion isn’t a big deal, perhaps we can do a little more to persuade your viewpoint.

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AI Midjourney Imagines “Stairway To Heaven”

September 14, 2022 by Dave Rowntree 36 Comments

This modern era of GPU-accelerated AI applications have their benefits. Pulling useful information out of mountains of raw data, alerting users to driving hazards, or just keeping an eye on bee populations are all helpful. Lately there has been a rise in attempts at producing (or should that be curating?) works of art out of carefully sculpted inputs.

One such AI art project is midjourney, which can be played with via a Discord integration bot. That bot takes some textual input, then “dreams” with it, producing sometime uncanny, often downright disturbing images.

You can have a tinker with it for free, for a short while, but there is monthly cost if you want to use it ‘for real’ whatever that means. YouTuber [Daara] has been feeding the lyrics from Led Zeppelin’s “Stairway to Heaven” into it, producing a video tour of the resulting outputs for your perusal. Continue reading “AI Midjourney Imagines “Stairway To Heaven”” →

Chinese Anti-Porn Helmet Raises Eyebrows, Questions

July 14, 2022 by Kristina Panos 72 Comments

Did you know that pornography is completely illegal in China? Probably not surprising news, though, right? The country has already put measures in place to scour the Internet in search of explicit content, mostly using AI. But the government also employs human porn appraisers, called jian huang shi, whose job it is to judge images and videos to decide whether they contain explicit content. Also probably not surprising is that humans are better than AI at knowing porn when they see it — or at least, they are faster at identifying it. Weirdness and morality and everything else aside, these jian huang shi are regular people, and frankly, they get exhausted looking at this stuff all day.

So what is the answer to burnout in this particular field? Researchers at Beijing Jiaotong University have come up with a way to bring the technological and human aspects of their existing efforts together. They’ve created a helmet that can detect particular spikes in brainwaves that occur from exposure to explicit imagery. Basically, it flashes a combination of naughty and ho-hum images in rapid succession until a spike is detected, then it flags the offending image.

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A Baudot Code Speaking Chatterbot With A Freakish Twist

April 26, 2022 by Dave Rowntree 2 Comments

[Sam Battle] known on YouTube as [Look Mum No Computer] is mostly known as a musical artist, but seems lately to have taken a bit of shine to retro telecoms gear, and this latest foray is into the realm of the minicom tty device which was a lifeline for those not blessed with ability to hear well enough to communicate via telephone. Since in this modern era of chatting via the internet, it is becoming much harder to actually find another user with a minicom, [Sam] decided to take the human out of the loop entirely and have the minicom user talk instead to a Raspberry Pi running an instance of MegaHal, which is 1990s era chatterbot. The idea of this build (that became an exhibit in this museum is not obsolete) was to have an number of minicom terminals around the room connected via the internal telephone network (and the retro telephone exchange {Sam] maintains) to a line interface module, based upon the Mitel MH88422 chip. This handy device allows a Raspberry Pi to interface to the telephone line, and answer calls, with all the usual handshaking taken care of. The audio signal from the Mitel interface is fed to the Pi via a USB audio interface (since the Pi has no audio input) module.

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Neuromorphic Computing: What Is It And Where Are We At?

August 19, 2021 by Matthew Carlson 31 Comments

For the last hundred or so years, collectively as humanity, we’ve been dreaming, thinking, writing, singing, and producing movies about a machine that could think, reason, and be intelligent in a similar way to us. The stories beginning with “Erewhon” published in 1872 by Sam Butler, Edgar Allan Poe’s “Maelzel’s Chess Player,” and the 1927 film “Metropolis” showed the idea that a machine could think and reason like a person. Not in magic or fantastical way. They drew from the automata of ancient Greece and Egypt and combined notions of philosophers such as Aristotle, Ramon Llull, Hobbes, and thousands of others.

Their notions of the human mind led them to believe that all rational thought could be expressed as algebra or logic. Later the arrival of circuits, computers, and Moore’s law led to continual speculation that human-level intelligence was just around the corner. Some have heralded it as the savior of humanity, where others portray a calamity as a second intelligent entity rises to crush the first (humans).

The flame of computerized artificial intelligence has brightly burned a few times before, such as in the 1950s, 1980s, and 2010s. Unfortunately, both prior AI booms have been followed by an “AI winter” that falls out of fashion for failing to deliver on expectations. This winter is often blamed on a lack of computer power, inadequate understanding of the brain, or hype and over-speculation. In the midst of our current AI summer, most AI researchers focus on using the steadily increasing computer power available to increase the depth of their neural nets. Despite their name, neural nets are inspired by the neurons in the brain and share only surface-level similarities.

Some researchers believe that human-level general intelligence can be achieved by simply adding more and more layers to these simplified convolutional systems fed by an ever-increasing trove of data. This point is backed up by the incredible things these networks can produce, and it gets a little better every year. However, despite what wonders deep neural nets produce, they still specialize and excel at just one thing. A superhuman Atari playing AI cannot make music or think about weather patterns without a human adding those capabilities. Furthermore, the quality of the input data dramatically impacts the quality of the net, and the ability to make an inference is limited, producing disappointing results in some domains. Some think that recurrent neural nets will never gain the sort of general intelligence and flexibility that our brains offer.

However, some researchers are trying to creating something more brainlike by, you guessed it, more closely emulates a brain. Given that we are in a golden age of computer architecture, now seems the time to create new hardware. This type of hardware is known as Neuromorphic hardware.

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Imaging The Past With Time-Travel Rephotography

April 12, 2021 by Adam Zeloof 49 Comments

Have you ever noticed that people in old photographs looks a bit weird? Deep wrinkles, sunken cheeks, and exaggerated blemishes are commonplace in photos taken up to the early 20th century. Surely not everybody looked like this, right? Maybe it was an odd makeup trend — was it just a fashionable look back then?

Not quite — it turns out that the culprit here is the film itself. The earliest glass-plate emulsions used in photography were only sensitive to the highest-frequency light, that which fell in the blue to ultraviolet range. Perhaps unsurprisingly, when combined with the fact that humans have red blood, this posed a real problem. While some of the historical figures we see in old photos may have benefited from an improved skincare regimen, the primary source of their haunting visage was that the photographic techniques available at the time were simply incapable of capturing skin properly. This lead to the sharp creases and dark lips we’re so used to seeing.

Of course, primitive film isn’t the only thing separating antique photos from the 42 megapixel behemoths that your camera can take nowadays. Film processing steps had the potential to introduce dust and other blemishes to the image, and over time the prints can fade and age in a variety of ways that depend upon the chemicals they were processed in. When rolled together, all of these factors make it difficult to paint an accurate portrait of some of history’s famous faces. Before you start to worry that you’ll never know just what Abraham Lincoln looked like, you might consider taking a stab at Time-Travel Rephotography.

Amazingly, Time-Travel Rephotography is a technique that actually lives up to how cool its name is. It uses a neural network (specifically, the StyleGAN2 framework) to take an old photo and project it into the space of high-res modern photos the network was trained on. This allows it to perform colorization, skin correction, upscaling, and various noise reduction and filtering operations in a single step which outputs remarkable results. Make sure you check out the project’s website to see some of the outputs at full-resolution.

We’ve seen AI upscaling before, but this project takes it to the next level by completely restoring antique photographs. We’re left wondering what techniques will be available 100 years from now to restore JPEGs stored way back in 2021, bringing them up to “modern” viewing standards.

Thanks to [Gus] for the tip!

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