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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.

A brain implant changed her life. Then it was removed against her will.

Sticking an electrode inside a person’s brain can do more than treat a disease. Take the case of Rita Leggett, an Australian woman whose experimental brain implant designed to help people with epilepsy changed her sense of agency and self.

Leggett told researchers that she “became one” with her device. It helped her to control the unpredictable, violent seizures she routinely experienced, and allowed her to take charge of her own life. So she was devastated when, two years later, she was told she had to remove the implant because the company that made it had gone bust.

The removal of this implant, and others like it, might represent a breach of human rights, ethicists say in a paper published earlier this month. And the issue will only become more pressing as the brain implant market grows in the coming years and more people receive devices like Leggett’s. Read the full story.

—Jessica Hamzelou

You can read more about what happens to patients when their life-changing brain implants are removed against their wishes in the latest issue of The Checkup, Jessica’s weekly newsletter giving you the inside track on all things biotech. Sign up to receive it in your inbox every Thursday.

If you’d like to read more about brain implants, why not check out:

+ Brain waves can tell us how much pain someone is in. The research could open doors for personalized brain therapies to target and treat the worst kinds of chronic pain. Read the full story.

+ An ALS patient set a record for communicating via a brain implant. Brain interfaces could let paralyzed people speak at almost normal speeds. Read the full story.

+ Here’s how personalized brain stimulation could treat depression. Implants that track and optimize our brain activity are on the way. Read the full story.

The must-reads

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

1Chipmaker Nvidia is hurtling towards a trillion dollar valuation
The AI boom has sent the company’s value skyrocketing. (WP $)
It’s gaining ground on the likes of Apple and Microsoft. (FT $)
But Nvidia is still reliant on third parties to actually manufacture its chips. (WSJ $)
These simple design rules could turn the chip industry on its head. (MIT Technology Review)

2 Neuralink has FDA approval to study brain implants in humans
But the company is still under investigation for how it conducted trials in animals. (Reuters)
The agency refused Neuralink permission to start testing in humans last year. (WP $)
Elon Musk’s Neuralink is neuroscience theater. (MIT Technology Review)

3 North and South Korea are locked in a new space race
They want to use spy satellites to gain an edge on each other. (WSJ $)

4 The success of mRNA vaccines could pave the way for cancer jabs
But experts are, understandably, still treading very cautiously. (Knowable Magazine)
What’s next for mRNA vaccines. (MIT Technology Review)

5 Deep sea mining is threatening newly-discovered species
It could devastate the precious eco-systems before we have the opportunity to protect them. (Motherboard)

6 US authorities are demanding Big Tech hands over migrant data
But we don’t know how often the platforms comply with the subpoenas. (The Guardian)

7 Our organs are aging at different rates
Aging clocks can help us to keep an eye on our deterioration—but they don’t always provide a full picture of health. (Proto.Life)+ A test told me my brain and liver are older than they should be. (MIT Technology Review)

8 How the internet birthed a new pan-Asian beauty ideal
And erased facial asymmetry along the way. (Wired $)
The fight for “Instagram face” (MIT Technology Review)

9 Sergey Brin’s not giving up on his airship dreams
It’s been a passion project for years—but costs are mounting. (Bloomberg $)

10 It’s time to break free from push notifications
They’re intrusive and annoying, so why not get rid? (The Atlantic $)

Quote of the day

“There will be an awful lot of losing lottery tickets.”

—Trevor Greetham, an investment strategist at Royal London Investment Management, tells Reuters why investors rushing to make a quick buck on AI-themed stocks would do well to remember the lessons of the dotcom crash.

The big story

Yann LeCun has a bold new vision for the future of AI

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By: Rhiannon Williams
Title: The Download: brain implant removal, and Nvidia’s AI payoff
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Published Date: Fri, 26 May 2023 12:10:00 +0000

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What if we could just ask AI to be less biased?



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This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

Think of a teacher. Close your eyes. What does that person look like? If you ask Stable Diffusion or DALL-E 2, two of the most popular AI image generators, it’s a white man with glasses. 

Last week, I published a story about new tools developed by researchers at AI startup Hugging Face and the University of Leipzig that let people see for themselves what kinds of inherent biases AI models have about different genders and ethnicities.

Although I’ve written a lot about how our biases are reflected in AI models, it still felt jarring to see exactly how pale, male, and stale the humans of AI are. That was particularly true for DALL-E 2, which generates white men 97% of the time when given prompts like “CEO” or “director.”

And the bias problem runs even deeper than you might think into the broader world created by AI. These models are built by American companies and trained on North American data, and thus when they’re asked to generate even mundane everyday items, from doors to houses, they create objects that look American, Federico Bianchi, a researcher at Stanford University, tells me.

As the world becomes increasingly filled with AI-generated imagery, we are going to mostly see images that reflect America’s biases, culture, and values. Who knew AI could end up being a major instrument of American soft power?
So how do we address these problems? A lot of work has gone into fixing biases in the data sets AI models are trained on. But two recent research papers propose interesting new approaches.

What if, instead of making the training data less biased, you could simply ask the model to give you less biased answers?

A team of researchers at the Technical University of Darmstadt, Germany, and AI startup Hugging Face developed a tool called Fair Diffusion that makes it easier to tweak AI models to generate the types of images you want. For example, you can generate stock photos of CEOs in different settings and then use Fair Diffusion to swap out the white men in the images for women or people of different ethnicities.

As the Hugging Face tools show, AI models that generate images on the basis of image-text pairs in their training data default to very strong biases about professions, gender, and ethnicity. The German researchers’ Fair Diffusion tool is based on a technique they developed called semantic guidance, which allows users to guide how the AI system generates images of people and edit the results.

The AI system stays very close to the original image, says Kristian Kersting, a computer science professor at TU Darmstadt who participated in the work. 

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This method lets people create the images they want without having to undertake the cumbersome and time-consuming task of trying to improve the biased data set that was used to train the AI model, says Felix Friedrich, a PhD student at TU Darmstadt who worked on the tool.

However, the tool is not perfect. Changing the images for some occupations, such as “dishwasher,” didn’t work as well because the word means both a machine and a job. The tool also only works with two genders. And ultimately, the diversity of the people the model can generate is still limited by the images in the AI system’s training set. Still, while more research is needed, this tool could be an important step in mitigating biases.

A similar technique also seems to work for language models. Research from the AI lab Anthropic shows how simple instructions can steer large language models to produce less toxic content, as my colleague Niall Firth reported recently. The Anthropic team tested different language models of varying sizes and found that if the models are large enough, they self-correct for some biases after simply being asked to.

Researchers don’t know why text- and image-generating AI models do this. The Anthropic team thinks it might be because larger models have larger training data sets, which include lots of examples of biased or stereotypical behavior—but also examples of people pushing back against this biased behavior.

AI tools are becoming increasingly popular for generating stock images. Tools like Fair Diffusion could be useful for companies that want their promotional pictures to reflect society’s diversity,

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By: Melissa Heikkilä
Title: What if we could just ask AI to be less biased?
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Published Date: Tue, 28 Mar 2023 08:22:40 +0000

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Proactive and predictive tools for transformation



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Supply chain. Finance. Accounting. Inventory. Manufacturing. Procurement. HR. Name a mission-critical application that operates in the background to keep businesses running, and it falls under the umbrella of enterprise resource planning (ERP).

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Until recently, the sprawling, interconnected sets of ERP modules that ran these essential functions were configured and managed manually. In the context of an organization whose IT systems were relatively static and running in a consistent, predictable environment, this might not be a problem.

Those well-established conventional IT systems, however, can no longer be taken for granted. Companies are accelerating their digital transformation efforts, automating, optimizing, and reinventing their business processes. The pace of change continues to accelerate: Deloitte reports, for example, that 58% of organizations have stepped up their modernization plans due to the covid-19 pandemic.

v2 MIT Del SAP ITStat

Many ERP apps are now being moved to public cloud services, such as AWS, Azure, or Google Cloud, while others are being replaced with SaaS-based alternatives, including Salesforce and Workday. The previously monolithic ERP platform is being deconstructed.

Enterprises now find themselves with a mixed-bag, hybrid cloud environment: some legacy core applications remain on premises, while new applications are cloud native and run in containers or as microservices.

This new ERP landscape is more distributed and more complex than ever before. And failure to effectively monitor these ERP apps could result in business outages that can cost the company dearly. Shawn Windle, founder and managing principal at ERP Advisers Group, puts it bluntly: “The intrinsic value of these systems is that they run the business. Without these apps, you don’t have a business.”

Download the report

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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By: MIT Technology Review Insights
Title: Proactive and predictive tools for transformation
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Published Date: Mon, 05 Jun 2023 15:00:00 +0000

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The Download: making sense of tech, and Apple’s AR ambitions




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.

Overwhelmed by the rapid pace of new tech? Let us help.

It’s been a busy year. Over the past 12 months, we’ve witnessed the explosion of generative AI, the collapse of crypto, and a whole lot of promises from lawmakers pledging to slow the march of climate change. While it’s easy to feel overwhelmed by all this rapid change, we’re here to help.

Our MIT Technology Review Explains section is dedicated to untangling the complex, sometimes messy, world of science and technology to help you understand what’s happening.

Our series of explainers cut through the noise and get to the heart of the issues that really matter, covering everything from biotechnology and cryptocurrency to quantum computing and what’s going on in China’s tech industry.

Take a look over some of our fascinating explainers:

+ Our quick guide to the 6 ways we can regulate AI. A handy guide to all the most (and least) promising efforts to govern AI around the world. Read the full story.

Ethereum moved to proof of stake. Why can’t Bitcoin? There is no technical obstacle to making the notoriously energy-hungry cryptocurrency far more efficient—just a social one. Read the full story.

+ ChatGPT is everywhere. Here’s where it came from. OpenAI’s breakout hit was an overnight sensation—but it is built on decades of research. Read more about its fascinating history.

+ Everything you need to know about the wild world of alternative jet fuels. Find out more about how trash, cooking oil, and green electricity could power your future flights. Read the full story.

+ How to log off. Sick of spending all your time staring at your devices? Here’s how to strike a healthier balance. Read the full story.

Is there a particular topic you’d like to see our writers tackle in the future? Get in touch with your suggestions! 

The must-reads

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

1 Apple wants to make you care about augmented reality
In theory, it’s got a better shot at success than companies that lack its elusive cool factor. (The Verge)
Its rumored new mixed reality headset is worrying the competition. (Wired $)
The launch could be a much-needed shot in the arm for VR startups. (FT $)
The metaverse is still fundamentally uncool, though. (NYT $)
The metaverse is a new word for an old idea. (MIT Technology Review)

2 A new antibiotic is thwarting resistant bugs
If approved, it’d be the first of its kind to be green-lit in more than two decades. (New Scientist $)
The next pandemic is already here. Covid can teach us how to fight it. (MIT Technology Review)

3 ChatGPT has pumped the tech industry back up 
But the AI boom has been far from good news for everyone. (WP $)
It could take over 10 years for some economies to reap the rewards. (FT $)
ChatGPT is about to revolutionize the economy. (MIT Technology Review)

4 A biotech company mistakenly told 400 patient they may have cancer
It’s a harrowing example of the dangers of over-relying on detection tech. (FT $)

5 China has had enough of AI-driven fraud
Its tight internet restrictions mean it could be relatively successful in cracking down on it, too. (WSJ $)

6 We still can’t seem to quit coal
It’s a lifeline for Asia, in particular—and demand is likely to grow. (Economist $)+ Climate scientists are worried about the cooling upper atmosphere. (Wired $)

7 Bitcoin enthusiasts are agonizing over what to do with memecoins
Purists argue the system is being abused by a proliferation of junk coins. (Bloomberg $)

8 An Irish town has banned children from owning smartphones
It’s a voluntary system that can only really work if everyone agrees. (The Guardian)

9 Takeout customers are increasingly picking up their orders themselves
The apps’ high delivery fees are to blame. (Insider $)

10 Recycling is rarely as simple as it should be
A new AI system makes it easier to tell whether that container should be chucked in the trash instead. (Axios)
Why you might recycle a battery—and how to do it. (MIT Technology Review)

Quote of the day

“They know how to build a religion.”

—Inga Petryaevskaya, CEO of virtual and augmented reality startup ShapesXR, tells the Wall Street Journal why Apple might give her industry a much-needed boost.

The big story

The FBI accused him of spying for China. It ruined his life.

Read More


By: Rhiannon Williams
Title: The Download: making sense of tech, and Apple’s AR ambitions
Sourced From:
Published Date: Mon, 05 Jun 2023 12:10:00 +0000

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