The Pixelmator Photo 1.4 update brings ML Super Resolution to the iPad. This is the feature introduced on macOS that lets you upscale images using machine learning. “Today’s update also adds a very awesome comparison slider, letting you quickly compare your edited image with the original in a split-screen view. And it works all around the app, so when using the Repair tool, you can turn on and move the comparison slider to see just the changes made with that tool. When the Color Adjustments tool selected, you’ll see just the color changes, and so on. Super useful.” Finally, the company has raised the app’s price to US$7.99, up from US$4.99.
A report on Friday says that China would rather TikTok be shut down instead of being sold to a U.S. company.
However, Chinese officials believe a forced sale would make both ByteDance and China appear weak in the face of pressure from Washington, the sources said, speaking on condition of anonymity given the sensitivity of the situation.
ByteDance said in a statement to Reuters that the Chinese government had never suggested to it that it should shut down TikTok in the United States or in any other markets.
Here’s what I think this means. China is all about the AI, and based on reports its algorithms seem to be more advanced than even invasive Facebook. China doesn’t want the U.S. to know just how more advanced it’s algorithms are. Read: China export ban of such technology.
Apple has launched an AI/ML residency program that invites experts to build machine learning and AI powered products and experiences.
John Giannandrea, Apple’s Senior Vice President for Machine Learning and AI Strategy, and Bob Borchers, VP of Product Marketing, spoke with Ars Technica about Apple’s AI strategy and beliefs.
When I joined Apple, I was already an iPad user, and I loved the Pencil,” Giannandrea (who goes by “J.G.” to colleagues) told me. “So, I would track down the software teams and I would say, ‘Okay, where’s the machine learning team that’s working on handwriting?’ And I couldn’t find it.” It turned out the team he was looking for didn’t exist—a surprise, he said, given that machine learning is one of the best tools available for the feature today.
Here’s something cool that Google has created: A web tool called “Fabricius” that uses machine learning to decrypt hieroglyphs.
So far, experts had to dig manually through books upon books to translate and decipher the ancient language–a process that has remained virtually unchanged for over a century. Fabricius includes the first digital tool – that is also being released as open source to support further developments in the study of ancient languages – that decodes Egyptian hieroglyphs built on machine learning.
Apple has acquired machine learning startup Inductiv, Inc to improve Siri, machine learning, and Apple’s data science endeavors.
Now here’s a cool article I found last night. Simon Willison found the SQLite database that Apple Photos uses. It contains photo metadata as well as the aesthetic scoring system that the machine learning uses. Further, there are numeric categories used to label content within photos. For example, Category 2027 is for Entertainment, Trip, Travel, Museum, Beach Activity, etc. I think the quality scores are particularly interesting. There are scores for noise, composition, lively color, harmonious color, pleasant lighting/pattern/perspective, and a bunch more. I bet Apple’s acquisition of Regaind contributed to this.
Apple has acquired an AI startup called Voysis, which could be used to enhance Siri’s commerce capabilities.
The Joint Photographic Experts Group (JPEG) is exploring methods to use machine learning to create the next JPEG image codec.
In a recent meeting held in Sydney, the group released a call for evidence to explore AI-based methods to find a new image compression codec. The program, aptly named JPEG AI, was launched last year; with a special group to study neural-network-based image codecs.
Bryan Chaffin and John Kheit discuss the difference between artificial intelligence (AI) and machine learning, including the state of both today. They also talk about their new Macs— John got a new 28-core Mac Pro, while Bryan has a new iMac—and whether or not they like their new purchases. The cap the show by catching up on The Curse of Oak Island TV show on History.
Shortly after acquiring AI company Xnor.ai, Apple canceled its contract with Project Maven that would use algorithms to analyze military drone imagery.
Apple acquired artificial intelligence company Xnor.ai, which specializes in “low-power, edge-base tools” like image recognition.
Dr. Mac has discovered something approaching the holy grail of image-processing—a way to enlarge (or reduce) an image with fewer visible artifacts and jagged edges, and less blurriness and other unwanted elements.
In the latest update Pixelmator Pro adds a machine learning feature called ML Super Resolution as a way to enhance small, blurry images.
Adobe announced a couple of features in Photoshop for iPad today, including Select Subject, optimizing cloud documents, and more.
Google started an initiative called Project Understood. It’s partnering with the Canadian Down Syndrome Society to ask people with Down syndrome help train its voice recognition algorithms to understand them better.
“Out of the box, Google’s speech recognizer would not recognize every third word for a person with Down syndrome, and that makes the technology not very usable,” Google engineer Jimmy Tobin said in a video introducing the project. Google is aiming to collect 500 “donations” of voice recordings from people with Down syndrome, and is already more than halfway toward its goal.
A worthy project.
Australia will soon install a camera system powered by machine learning that is designed to spot mobile phones in cars.
To let drivers adjust, warning letters will be sent to those spotted using phones by the cameras for the first three months. Australia uses a points system for drivers — unrestricted driver’s licenses have 13 points. After the first three months, drivers caught using their phones illegally will lose five points and be issued a $344 fine. During other periods, the penalty could increase to 10 points. If a driver loses all of their points, they could lose their license.
Distracted driving is absolutely a serious problem, but I don’t think more surveillance infrastructure is the answer.
Apple has rebuilt its privacy site to show off “everyday apps designed for your privacy.” They’re Apple’s own apps showing privacy features.
A company called Seed wants to build a database of 100,000 poop photos so an AI can learn to tell the difference between healthy and unhealthy poop.
Ara Katz, co-founder and co-CEO of Seed, hopes that the poop project is just one of the company’s many future contributions to our understanding of health. “It’s projects like this [that] allow people who are not scientists to participate in citizen science. By crowdsourcing data, we can help researchers and technologies like auggi in order to help people identify different conditions.”
Take a poop pic and submit it at seed.com/poop.
The New York Times has a nice feature out today about how a mother found photos of her kids in a machine learning database.
None of them could have foreseen that 14 years later, those images would reside in an unprecedentedly huge facial-recognition database called MegaFace. Containing the likenesses of nearly 700,000 individuals, it has been downloaded by dozens of companies to train a new generation of face-identification algorithms, used to track protesters, surveil terrorists, spot problem gamblers and spy on the public at large. The average age of the people in the database, its creators have said, is 16.
I can’t imagine the gross feeling you get when you see your kids in a database like this.