Category: Science & Tech

Orange distributes its translations via an app called emaqi (a pun on “emaki,” the ancient Japanese illustrated scrolls that are considered a precursor to manga). It also wants to be a translator-for-hire for US publishers.

But Orange has not been welcomed by all US fans. When it showed up at Anime NYC, a US anime convention, this summer, Japanese-to-English translator Jan Mitsuko Cash tweeted: “A company like Orange has no place at the convention hosting the Manga Awards, which celebrates manga and manga professionals in the industry. If you agree, please encourage @animenyc to ban AI companies from exhibiting or hosting panels.”  

Brienza takes the same view. “Work in the culture industries, including translation, which ultimately is about translating human intention, not mere words on a page, can be poorly paid and precarious,” she says. “If this is the way the wind is blowing, I can only grieve for those who will go from making little money to none.”

Some have also called Orange out for cutting corners. “The manga uses stylized text to represent the inner thoughts that the [protagonist] can’t quite voice,” another fan tweeted. “But Orange didn’t pay a redrawer or letterer to replicate it properly. They also just skip over some text entirely.”

EMAQI

Everyone at Orange understands that manga translation is a sensitive issue, says Kuroda: “We believe that human creativity is absolutely irreplaceable, which is why all AI-assisted work is rigorously reviewed, refined, and finalized by a team of people.”  

Orange also claims that the authors it has translated are on board with its approach. “I’m genuinely happy with how the English version turned out,” says Kenji Yajima, one of the authors Orange has worked with, referring to the company’s translation of his title Neko Oji: Salaryman reincarnated as a kitten! (see images). “As a manga artist, seeing my work shared in other languages is always exciting. It’s a chance to connect with readers I never imagined reaching before.”

If consumers don’t have confidence that the AI tools they’re interacting with are respecting their privacy, are not embedding bias and discrimination, that they’re not causing safety problems, then all the marvelous possibilities really aren’t going to materialize. Nowhere is that more true than national security and law enforcement. 

I’ll give you a great example. Facial recognition technology is an area where there have been horrific, inappropriate uses: take a grainy video from a convenience store and identify a black man who has never even been in that state, who’s then arrested for a crime he didn’t commit. (Editor’s note: Prabhakar is referring to this story). Wrongful arrests based on a really poor use of facial recognition technology, that has got to stop. 

In stark contrast to that, when I go through security at the airport now, it takes your picture and compares it to your ID to make sure that you are the person you say you are. That’s a very narrow, specific application that’s matching my image to my ID, and the sign tells me—and I know from our DHS colleagues that this is really the case—that they’re going to delete the image. That’s an efficient, responsible use of that kind of automated technology. Appropriate, respectful, responsible—that’s where we’ve got to go.

Were you surprised at the AI safety bill getting vetoed in California?

I wasn’t. I followed the debate, and I knew that there were strong views on both sides. I think what was expressed, that I think was accurate, by the opponents of that bill, is that it was simply impractical, because it was an expression of desire about how to assess safety, but we actually just don’t know how to do those things. No one knows. It’s not a secret, it’s a mystery. 

To me, it really reminds us that while all we want is to know how safe, effective and trustworthy a model is, we actually have very limited capacity to answer those questions. Those are actually very deep research questions, and a great example of the kind of public R&D that now needs to be done at a much deeper level.

Let’s talk about talent. Much of the recent National Security Memorandum on AI was about how to help the right talent come from abroad to the US to work on AI. Do you think we’re handling that in the right way?

It’s a hugely important issue. This is the ultimate American story, that people have come here throughout the centuries to build this country, and it’s as true now in science and technology fields as it’s ever been. We’re living in a different world. I came here as a small child because my parents came here in the early 1960s from India, and in that period, there were very limited opportunities [to emigrate to] many other parts of the world. 

Virologists have been especially worried about the virus making its way into pigs, because these animals are notorious viral incubators. “They can become infected with swine strains, bird strains and human strains,” says Brinkley Bellotti, an infectious disease epidemiologist at Wake Forest University in North Carolina. These strains can swap genes and give rise to new, potentially more infectious or harmful strains.

Thankfully, we haven’t seen any other cases in pig farms, and there’s no evidence that the virus can spread between pigs. And while it has been spreading pretty rapidly between cattle, the virus doesn’t seem to have evolved much, says Seema Lakdawala, a virologist at the Emory University School of Medicine in Atlanta, Georgia. That suggests that the virus made the leap into cattle, probably from birds, only once. And it has been spreading through herds since.

Unfortunately, we still don’t really know how it is spreading. There is some evidence to suggest the virus can be spread from cow to cow through shared milking equipment. But it is unclear how the virus is spreading between farms. “It’s hard to form an effective control strategy when you don’t know exactly how it’s spreading,” says Bellotti.

But it is in cows. And it’s in their milk. When scientists analyzed 297 samples of Grade A pasteurized retail milk products, including milk, cream and cheese, they found viral RNA from H5N1 in 20% of them. Those samples were collected from 17 states across the US. And the study was conducted in April, just weeks after the virus was first detected in cattle. “It’s surprising to me that we are totally fine with … our pasteurized milk products containing viral DNA,” says Lakdawala.

Research suggests that, as long as the milk is pasteurized, the virus is not infectious. But Lakdawala is concerned that pasteurization may not inactivate all of the virus, all the time. “We don’t know how much virus we need to ingest [to become infected], and whether any is going to slip through pasteurization,” she says.

And no reassurances can be made for unpasteurized raw milk. When cows are infected with H5N1, their milk can turn thick, yellow and “chunky.” But research has shown that, even when the milk starts to look normal again, it can still contain potentially infectious virus.

The most concerning development, though, is the rise in human cases. So far, 55 such cases of H5N1 bird flu have been reported in the US, according to the US Centers for Disease Control and Prevention (CDC). Twenty-nine of those cases have been detected in California. In almost all those cases, the infected person is thought to have caught the virus from cattle or poultry on farms. But in two of those cases, the source of the infection is unknown.

In this exclusive webcast, we delve into the transformative potential of portable microservices for the deployment of generative AI models. We explore how startups and large organizations are leveraging this technology to streamline generative AI deployment, enhance customer service, and drive innovation across domains, including chatbots, document analysis, and video generation.

Our discussion focuses on overcoming key challenges such as deployment complexity, security, and cost management. We also discuss how microservices can help executives realize business value with generative AI while maintaining control over data and intellectual property.

Deeper Learning

Inside Clear’s ambitions to manage your identity beyond the airport

Clear is the most visible biometrics company around, and one you’ve likely interacted with already, whether passing security checkpoints at airports and stadiums or verifying your identity on LinkedIn. Along the way, it’s built one of the largest private repositories of identity data on the planet, including scans of fingerprints, irises, and faces. A confluence of factors is now accelerating the adoption of identity verification technologies—including AI, of course, as well as the lingering effects of the pandemic’s push toward “contactless” experiences—and Clear aims to be the ubiquitous provider of these services. In the near future, countless situations where you might need an ID or credit card might require no more than showing your face. 

Why this matters: Now that biometrics have gone mainstream, what—and who—bears the cost? Because this convenience, even if chosen by only some of us, leaves all of us wrestling with the effects. If Clear gains ground in its vision, it will move us toward a world where we’re increasingly obligated to give up our biometric data to a system that’s vulnerable to data leaks.  Read more from Eileen Guo.

Bits and Bytes

Inside the booming “AI pimping” industry

Instagram is being flooded with hundreds of AI-generated influencers who are stealing videos from real models and adult content creators, giving them AI-generated faces, and monetizing their bodies with links to dating sites, Patreon, OnlyFans competitors, and various AI apps. (404 Media)

How to protect your art from AI

There is little you can do if your work has already been scraped into a data set, but you can take steps to prevent future work from being used that way. Here are four ways to do that. (MIT Technology Review)

Elon Musk and Vivek Ramaswamy have offered details on their plans to cut regulations