Stability AI releases Stable Doodle, a sketch-to-image tool

Stability AI, the startup behind the image-generating model Stable Diffusion, is launching a new service that turns sketches into images.

The sketch-to-image service, Stable Doodle, leverages the latest Stable Diffusion model to analyze the outline of a sketch and generate a “visually pleasing” artistic rendition of it. It’s available starting today through ClipDrop, a platform Stability acquired in March through its purchase of Init ML, an AI startup founded by ex-Googlers,

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Under the hood, powering Stable Doodle is a Stable Diffusion model — Stable Diffusion XL — paired with a “conditional control solution” developed by one of Tencent’s R&D divisions, the Applied Research Center (ARC). Called T2I-Adapter, the control solution both allows Stable Diffusion XL to accept sketches as input and guides the model to enable better fine-tuning of the output artwork.

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Source: Stability AI releases Stable Doodle, a sketch-to-image tool | TechCrunch

Find it at https://clipdrop.co/stable-doodle

Research group develops biodegradable film that keeps food fresh for longer

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a film made of a compound derived from limonene, the main component of citrus fruit peel, and chitosan, a biopolymer derived from the chitin present in exoskeletons of crustaceans.

The film was developed by a research group in São Paulo state, Brazil, comprising scientists in the Department of Materials Engineering and Bioprocesses at the State University of Campinas’s School of Chemical Engineering (FEQ-UNICAMP) and the Packaging Technology Center at the Institute of Food Technology (ITAL) of the São Paulo State Department of Agriculture and Supply, also in Campinas.

The results of the research are reported in an article published in Food Packaging and Shelf Life.

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Limonene has been used before in film for food to enhance conservation thanks to its antioxidant and anti-microbial action, but its performance is impaired by volatility and instability during the packaging manufacturing process, even on a laboratory scale.

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“The films with the poly(limonene) additive outperformed those with limonene, especially in terms of antioxidant activity, which was about twice as potent,” Vieira said. The substance also performed satisfactorily as an ultraviolet radiation blocker and was found to be non-volatile, making it suitable for large-scale production of packaging, where processing conditions are more severe.

The films are not yet available for use by manufacturers, mainly because chitosan-based plastic is not yet produced on a sufficiently large scale to be competitive, but also because the poly(limonene) production process needs to be optimized to improve yield and to be tested during the manufacturing of commercial packaging.

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More information: Sayeny de Ávila Gonçalves et al, Poly(limonene): A novel renewable oligomeric antioxidant and UV-light blocking additive for chitosan-based films, Food Packaging and Shelf Life (2023). DOI: 10.1016/j.fpsl.2023.101085

Source: Research group develops biodegradable film that keeps food fresh for longer

AI System Identified Drug Trafficker by Scanning Driving Patterns

Police in New York recently managed to identify and apprehend a drug trafficker seemingly by magic. The perp in question, David Zayas, was traveling through the small upstate town of Scarsdale when he was pulled over by Westchester County police. When cops searched Zayas’ vehicle they found a large amount of crack cocaine, a gun, and over $34,000 in cash in his vehicle. The arrestee later pleaded guilty to a drug trafficking charge.

How exactly did cops know Zayas fit the bill for drug trafficking?

Forbes reports that authorities used the services of a company called Rekor to analyze traffic patterns regionally and, in the course of that analysis, the program identified Zayas as suspicious.

For years, cops have used license plate reading systems to look out for drivers who might have an expired license or are wanted for prior violations. Now, however, AI integrations seem to be making the tech frighteningly good at identifying other kinds of criminality just by observing driver behavior.

Rekor describes itself as an AI-driven “roadway intelligence” platform and it contracts with police departments and other public agencies all across the country. It also works with private businesses. Using Rekor’s software, New York cops were able to sift through a gigantic database of information culled from regional roadways by its county-wide ALPR [automatic license plate recognition] system. That system—which Forbes says is made up of 480 cameras distributed throughout the region—routinely scans 16 million vehicles a week, capturing identifying data points like a vehicle’s license plate number, make, and model. By recording and reverse-engineering vehicle trajectories as they travel across the state, cops can apparently use software to assess whether particular routes are suspicious or not.

In this case, Rekor helped police to assess the route that Zayas’ car was taking on a multi-year basis. The algorithm—which found that the driver was routinely making trips back and forth between Massachusetts and certain areas of upstate New York—determined that Zayas’ routes were “known to be used by narcotics pushers and [involved]…conspicuously short stays,” Forbes writes. As a result, the program deemed Zayas’s activity consistent with that of a drug trafficker.

Artificial intelligence has been getting a lot of attention in recent months due to the disruptions it’s made to the media and software industries but less attention has been paid to how this new technology will inevitably supercharge existing surveillance systems. If cops can already ID a drug trafficker with the click of a button, just think how good this tech will be in ten years’ time. As regulations evolve, one would hope governments will figure out how to reasonably deploy this technology without leading us right off the cliff into Minority Report territory. I mean, they probably won’t, but a guy can dream, can’t he?

Source: AI System Identified Drug Trafficker by Scanning Driving Patterns

There is no way at all that this could possibly go wrong, right? See the comments in the link.