Lifeboat Foundation

“Don’t believe everything you see on the Internet” has been pretty standard advice for quite some time now. And according to a new report from European law enforcement group Europol, we have all the reason in the world to step up that vigilance.

“Experts estimate that as much as 90 percent of online content may be synthetically generated by 2026,” the report warned, adding that synthetic media “refers to media generated or manipulated using artificial intelligence.”

“In most cases, synthetic media is generated for gaming, to improve services or to improve the quality of life,” the report continued, “but the increase in synthetic media and improved technology has given rise to disinformation possibilities.”

Researchers have created a device that uses machine vision to spot cockroaches and zap them with a laser. They say the method could offer a cheaper and more environmentally friendly alternative to insecticides.

Ildar Rakhmatulin at Heriot-Watt University in Edinburgh, UK, and his colleagues equipped a laser with two cameras and a small computer running an AI model that can be trained to target certain types of insect.

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As AI spreads throughout the enterprise, organizations are having a difficult time balancing the benefits against the risks. AI is already baked into a range of tools, from IT infrastructure management to DevOps software to CRM suites, but most of those tools were adopted without an AI risk-mitigation strategy in place.

Of course, it’s important to remember that the list of potential AI benefits is every bit as long as the risks, which is why so many organizations skimp on risk assessments in the first place.

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📝 The paper “High Definition Video Generation with Diffusion Models” is available here:
https://imagen.research.google/video/

Continue reading “Google’s Video AI: Outrageously Good! 🤖” »

Scientists including an Oregon State University materials researcher have developed a better tool to measure light, contributing to a field known as optical spectrometry in a way that could improve everything from smartphone cameras to environmental monitoring.

The study, published today in Science, was led by Finland’s Aalto University and resulted in a powerful, ultra-tiny spectrometer that fits on a microchip and is operated using artificial intelligence.

The research involved a comparatively new class of super-thin materials known as two-dimensional semiconductors, and the upshot is a proof of concept for a spectrometer that could be readily incorporated into a variety of technologies—including quality inspection platforms, security sensors, biomedical analyzers and space telescopes.

If you’ve been closely following the progress of Open AI, the company run by Sam Altman whose neural nets can now write original text and create original pictures with astonishing ease and speed, you might just skip this piece.

If, on the other hand, you’ve only been vaguely paying attention to the company’s progress and the increasing traction that other so-called “generative” AI companies are suddenly gaining and want to better understand why, you might benefit from this interview with James Currier, a five-time founder and now venture investor who cofounded the firm NFX five years ago with several of his serial founder friends.

Currier falls into the camp of people following the progress closely — so closely that NFX has made numerous related investments in “generative tech” as he describes it, and it’s garnering more of the team’s attention every month. In fact, Currier doesn’t think the buzz about this new wrinkle on AI isn’t hype so much as a realization that the broader startup world is suddenly facing a very big opportunity for the first time in a long time. “Every 14 years,” says Currier, “we get one of these Cambrian explosions. We had one around the internet in ’94. We had one around mobile phones in 2008. Now we’re having another one in 2022.”

Managing data with AI-powered automation and data product managers.

ARTIFICIAL intelligence has predicted what “the last human on Earth” will look like.

The U.S. Sun asked DALL·E, an artificially intelligent software, to make the prediction and it came up with some rather creepy results.

DALL·E is a machine learning model that was created by OpenAI to conjure up unusual images from keyword prompts.

Next, you seem to assume that when I catch a ball, my mind solves equations unconsciously, brining together inertia, gravity, air resistance to calculate my response. You may be right, but I don’t think most neuroscientist agree with you. That’s another computationalist prejudice. Rather than solving equations, my nervous system uses experience and extrapolation through repeated trial and improvement to hone a skill in extrapolating paths; no equations involved. As I say, I could be wrong, it’s an empirical question. But as far as I know, the balance of evidence and theory supports my interpretation.

The meaning of semantics is not just that it means something, but that it can be used to make statements about the world, beyond the formal system used to express that meaning. That, too, is definitional.

Your main argument seems like a really desperate move to sustain the computationalist faith that you assert at the beginning in the face of huge, perhaps insuperable difficulties.