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Scroll through the livestreaming videos at 4 a.m. on Taobao, China’s most popular e-commerce platform, and you’ll find it weirdly busy. While most people are fast asleep, there are still many diligent streamers presenting products to the cameras and offering discounts in the wee hours.

But if you take a closer look, you may notice that many of these livestream influencers seem slightly robotic. The movement of their lips largely matches what they are saying, but there are always moments when it looks unnatural.

These streamers are not real: they are AI-generated clones of the real streamers. As technologies that create realistic avatars, voices, and movements get more sophisticated and affordable, the popularity of these deepfakes has exploded across China’s e-commerce streaming platforms.

Today, livestreaming is the dominant marketing channel for traditional and digital brands in China. Influencers on Taobao, Douyin, Kuaishou, or other platforms can broker massive deals in a few hours. The top names can sell more than a billion dollars’ worth of goods in one night and gain royalty status just like big movie stars. But at the same time, training livestream hosts, retaining them, and figuring out the technical details of broadcasting comes with a significant cost for smaller brands. It’s much cheaper to automate the job.

Since 2022, a swarm of Chinese startups and major tech companies have been offering the service of creating deepfake avatars for e-commerce livestreaming. With just a few minutes of sample video and $1,000 in costs, brands can clone a human streamer to work 24/7.

From deepfake to e-commerce

Synthetic media have been making headlines since the late 2010s, particularly when a Reddit user named “deepfake” swapped faces into pornography. Since then, the technology has evolved, but the idea is the same: with some technical tools, faces can be generated or manipulated to look like specific real humans and do things that the actual human has never done.

The technology has mostly been known for its problematic use in revenge porn, identity scams, and political misinformation. While there have been attempts to commercialize it in more innocuous ways, it has always remained a novelty. But now, Chinese AI companies have found a new use case that seems to be going quite well.

Founded in 2017, Nanjing-based startup Silicon Intelligence specializes in natural-language processing, particularly text-to-speech technologies like robocall tools. But Sima Huapeng, its founder and CEO, says his company first started to see AI’s potential as a livestreaming tool in 2020.

Back then, Silicon Intelligence needed 30 minutes of training videos to generate a digital clone that could speak and act like a human. The next year, it was 10 minutes, then three, and now only one minute of video is needed.

And as the tech has improved, the service has gotten cheaper too. Generating a basic AI clone now costs a customer about 8,000 RMB ($1,100). If the client wants to create a more complicated and capable streamer, the price can go up to several thousands of dollars. Other than the generation, that fee also covers a year of maintenance.

Video of an AI streamer generated by Silicon Intelligence.SILICON INTELLIGENCE

Once the avatar is generated, its mouth and body move in time with the scripted audio. While the scripts were once pre-written by humans, companies are now using large language models to generate them too.

Now, all the human workers have to do is input basic information such as the name and price of the product being sold, proofread the generated script, and watch the digital influencer go live. A more advanced version of the technology can spot live comments and find matching answers in its database to answer in real time, so it looks as if the AI streamer is actively communicating with the audience. It can even adjust its marketing strategy based on the number of viewers, Sima says.

These livestream AI clones are trained on the common scripts and gestures seen in e-commerce videos, says Huang Wei, the director of virtual influencer livestreaming business at the Chinese AI company Xiaoice. The company has a database of nearly a hundred pre-designed movements.

“For example, [when human streamers say] ‘Welcome to my livestream channel. Move your fingers and hit the follow button,’ they are definitely pointing their finger upward, because that’s where the ‘Follow’ button is on the screen of most mobile livestream apps,” says Huang. Similarly, when streamers introduce a new product, they point down—to the shopping cart, where viewers can find all products. Xiaoice’s AI streamers replicate all these common tricks. “We want to make sure the spoken language and the body language are matching. You don’t want it to be talking about the Follow button while it’s clapping its

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By: Zeyi Yang
Title: Deepfakes of Chinese influencers are livestreaming 24/7
Sourced From: www.technologyreview.com/2023/09/19/1079832/chinese-ecommerce-deepfakes-livestream-influencers-ai/
Published Date: Tue, 19 Sep 2023 07:45:00 +0000

Tech

This US startup makes a crucial chip material and is taking on a Japanese giant

Thintronics PCB jpg

It can be dizzying to try to understand all the complex components of a single computer chip: layers of microscopic components linked to one another through highways of copper wires, some barely wider than a few strands of DNA. Nestled between those wires is an insulating material called a dielectric, ensuring that the wires don’t touch and short out. Zooming in further, there’s one particular dielectric placed between the chip and the structure beneath it; this material, called dielectric film, is produced in sheets as thin as white blood cells.

For 30 years, a single Japanese company called Ajinomoto has made billions producing this particular film. Competitors have struggled to outdo them, and today Ajinomoto has more than 90% of the market in the product, which is used in everything from laptops to data centers.

But now, a startup based in Berkeley, California, is embarking on a herculean effort to dethrone Ajinomoto and bring this small slice of the chipmaking supply chain back to the US.

Thintronics is promising a product purpose-built for the computing demands of the AI era—a suite of new materials that the company claims have higher insulating properties and, if adopted, could mean data centers with faster computing speeds and lower energy costs. 

The company is at the forefront of a coming wave of new US-based companies, spurred by the $280 billion CHIPS and Science Act, that is seeking to carve out a portion of the semiconductor sector, which has become dominated by just a handful of international players. But to succeed, Thintronics and its peers will have to overcome a web of challenges—solving technical problems, disrupting long-standing industry relationships, and persuading global semiconductor titans to accommodate new suppliers.

“Inventing new materials platforms and getting them into the world is very difficult,” Thintronics founder and CEO Stefan Pastine says. It is “not for the faint of heart.”

The insulator bottleneck

If you recognize the name Ajinomoto, you’re probably surprised to hear it plays a critical role in the chip sector: the company is better known as the world’s leading supplier of MSG seasoning powder. In the 1990s, Ajinomoto discovered that a by-product of MSG made a great insulator, and it has enjoyed a near monopoly in the niche material ever since.

But Ajinomoto doesn’t make any of the other parts that go into chips. In fact, the insulating materials in chips rely on dispersed supply chains: one layer uses materials from Ajinomoto, another uses material from another company, and so on, with none of the layers optimized to work in tandem. The resulting system works okay when data is being transmitted over short paths, but over longer distances, like between chips, weak insulators act as a bottleneck, wasting energy and slowing down computing speeds. That’s recently become a growing concern, especially as the scale of AI training gets more expensive and consumes eye-popping amounts of energy. (Ajinomoto did not respond to requests for comment.)

None of this made much sense to Pastine, a chemist who sold his previous company, which specialized in recycling hard plastics, to an industrial chemicals company in 2019. Around that time, he started to believe that the chemicals industry could be slow to innovate, and he thought the same pattern was keeping chipmakers from finding better insulating materials. In the chip industry, he says, insulators have “kind of been looked at as the redheaded stepchild”—they haven’t seen the progress made with transistors and other chip components.

He launched Thintronics that same year, with the hope that cracking the code on a better insulator could provide data centers with faster computing speeds at lower costs. That idea wasn’t groundbreaking—new insulators are constantly being researched and deployed—but Pastine believed that he could find the right chemistry to deliver a breakthrough.

Thintronics PCB 1 jpg

Thintronics says it will manufacture different insulators for all layers of the chip, for a system designed to swap into existing manufacturing lines. Pastine tells me the materials are now being tested with a number of industry players. But he declined to provide names, citing nondisclosure agreements, and

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By: James O’Donnell
Title: This US startup makes a crucial chip material and is taking on a Japanese giant
Sourced From: www.technologyreview.com/2024/04/11/1091143/thintronics-ajinomoto-dielectric-chip-semiconductor-competition/
Published Date: Thu, 11 Apr 2024 16:04:55 +0000

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Tech

The Download: AI is making robots more helpful, and the problem with cleaning up pollution

This is today’s edition of The Download our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Is robotics about to have its own ChatGPT moment?

Henry and Jane Evans are used to awkward houseguests. For more than a decade, the couple, who live in Los Altos Hills, California, have hosted a slew of robots in their home.

In 2002, at age 40, Henry had a massive stroke, which left him with quadriplegia and an inability to speak. While they’ve experimented with many advanced robotic prototypes in a bid to give Henry more autonomy, it’s one recent model that works in tandem with AI models that has made the biggest changes—helping to brush his hair, and opening up his relationship with his granddaughter.

A new generation of scientists and inventors believes that the previously missing ingredient of AI can give robots the ability to learn new skills and adapt to new environments faster than ever before. This new approach, just maybe, can finally bring robots out of the factory and into our homes. Read the full story.

—Melissa Heikkilä

Melissa’s story is from the next magazine issue of MIT Technology Review, set to go live on April 24, on the theme of Build. If you don’t subscribe already, sign up now to get a copy when it lands.

The inadvertent geoengineering experiment that the world is now shutting off

The news: When we talk about climate change, the focus is usually on the role that greenhouse-gas emissions play in driving up global temperatures, and rightly so. But another important, less-known phenomenon is also heating up the planet: reductions in other types of pollution.

In a nutshell: In particular, the world’s power plants, factories, and ships are pumping much less sulfur dioxide into the air, thanks to an increasingly strict set of global pollution regulations. Sulfur dioxide creates aerosol particles in the atmosphere that can directly reflect sunlight back into space or act as the “condensation nuclei” around which cloud droplets form. More or thicker clouds, in turn, also cast away more sunlight. So when we clean up pollution, we also ease this cooling effect.

Why it matters: Cutting air pollution has unequivocally saved lives. But as the world rapidly warms, it’s critical to understand the impact of pollution-fighting regulations on the global thermostat as well. Read the full story.

—James Temple

This story is from The Spark, our weekly climate and energy newsletter. Sign up to receive it in your inbox every Wednesday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Election workers are worried about AI 
Generative models could make it easier for election deniers to spam offices. (Wired $)
Eric Schmidt has a 6-point plan for fighting election misinformation. (MIT Technology Review)

2 Apple has warned users in 92 countries of mercenary spyware attacks
It said it had high confidence that the targets were at genuine risk. (TechCrunch)

3 The US is in desperate need of chip engineers
Without them, it can’t meet its lofty semiconductor production goals. (WSJ $)
Taiwanese chipmakers are looking to expand overseas. (FT $)
How ASML took over the chipmaking chessboard. (MIT Technology Review)

4 Meet the chatbot tutors
Tens of thousands of gig economy workers are training tomorrow’s models. (NYT $)
Adobe is paying photographers $120 per video to train its generator. (Bloomberg $)
The next wave of AI coding tools is emerging. (IEEE Spectrum)
The people paid to train AI are outsourcing their work… to AI. (MIT Technology Review)

5 The Middle East is rushing to build AI infrastructure
Both Saudi Arabia and the UAE see sprawling data centers as key to becoming the region’s AI superpower. (Bloomberg $)

6 Political content creators and activists are lobbying Meta
They claim the company’s decision to limit the reach of ‘political’ content is threatening their livelihoods. (WP $)

7 The European Space Agency is planning an artificial solar eclipse
The mission, due to launch later this year, should provide essential insight into the sun’s atmosphere. (IEEE Spectrum)

8 How AI is helping to recover Ireland’s marginalized voices
Starting with the dung queen of Dublin. (The Guardian)
How AI is helping historians better understand our past. (MIT Technology Review)

9 Video game history is vanishing before our eyes
As consoles fall out of use, their games are consigned to history too. (FT $)

10 Dating apps are struggling to make looking for love fun
Charging users seems counterintuitive, then. (The Atlantic $)
Here’s how the net’s newest matchmakers help you find love. (MIT Technology Review)

Quote of the day

“We’re women sharing

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By: Rhiannon Williams
Title: The Download: AI is making robots more helpful, and the problem with cleaning up pollution
Sourced From: www.technologyreview.com/2024/04/11/1091100/the-download-ai-is-making-robots-more-helpful-and-the-problem-with-cleaning-up-pollution/
Published Date: Thu, 11 Apr 2024 12:10:00 +0000

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Tech

Scaling individual impact: Insights from an AI engineering leader

team with flag

Traditionally, moving up in an organization has meant leading increasingly large teams of people, with all the business and operational duties that entails. As a leader of large teams, your contributions can become less about your own work and more about your team’s output and impact. There’s another path, though. The rapidly evolving fields of artificial intelligence (AI) and machine learning (ML) have increased demand for engineering leaders who drive impact as individual contributors (ICs). An IC has more flexibility to move across different parts of the organization, solve problems that require expertise from different technical domains, and keep their skill set aligned with the latest developments (hopefully with the added benefit of fewer meetings).

team with flag 1

In an executive IC role as a technical leader, I have a deep impact by looking at the intersections of systems across organizational boundaries, prioritize the problems that really need solving, then assemble stakeholders from across teams to create the best solutions.

Driving influence through expertise

People leaders typically have the benefit of an organization that scales with them. As an IC, you scale through the scope, complexity, and impact of the problems you help solve. The key to being effective is getting really good at identifying and structuring problems. You need to proactively identify the most impactful problems to solve—the ones that deliver the most value but that others aren’t focusing on—and structure them in a way that makes them easier to solve.

People skills are still important because building strong relationships with colleagues is fundamental. When consensus is clear, solving problems is straightforward, but when the solution challenges the status quo, it’s crucial to have established technical credibility and organizational influence.

And then there’s the fun part: getting your hands dirty. Choosing the IC path has allowed me to spend more time designing and building AI/ML systems than other management roles would—prototyping, experimenting with new tools and techniques, and thinking deeply about our most complex technical challenges.

A great example I’ve been fortunate to work on involved designing the structure of a new ML-driven platform. It required significant knowledge at the cutting edge and touched multiple other parts of the organization. The freedom to structure my time as an IC allowed me to dive deep in the domain, understand the technical needs of the problem space, and scope the approach. At the same time, I worked across multiple enterprise and line-of-business teams to align appropriate resources and define solutions that met the business needs of our partners. This allowed us to deliver a cutting-edge solution on a very short timescale to help the organization safely scale a new set of capabilities.

Being an IC lets you operate more like a surgeon than a general. You focus your efforts on precise, high-leverage interventions. Rapid, iterative problem-solving is what makes the role impactful and rewarding.

The keys to success as an IC executive

In an IC executive role, there are key skills that are essential. First is maintaining deep technical expertise. I usually have a couple of different lines of study going on at any given time, one that’s closely related to the problems I’m currently working on, and another that takes a long view on foundational knowledge that will help me in the future.

Second is the ability to proactively identify and structure high-impact problems. That means developing a strong intuition for where AI/ML can drive the most business value, and leveraging the problem in a way that achieves the highest business results.

Determining how the problem will be formulated means considering what specific problem you are trying to solve and what you are leaving off the table. This intentional approach aligns the right complexity level to the problem to meet the organization’s needs with the minimum level of effort. The next step is breaking down the problem into chunks that can be solved by the people or teams aligned to the effort.

Doing this well requires building a diverse network across the organization. Building and nurturing relationships in different functional areas is crucial to IC success, giving you the context to spot impactful problems

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By: Grant Gillary
Title: Scaling individual impact: Insights from an AI engineering leader
Sourced From: www.technologyreview.com/2024/04/11/1090504/scaling-individual-impact-insights-from-an-ai-engineering-leader/
Published Date: Thu, 11 Apr 2024 14:00:00 +0000

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