At this point, everyone knows batteries are essential to EVs, but what about the broader effort to electrify everything else?

Batteries can provide the grid, or individual buildings like hospitals and factories, with reliable backup power and also help smooth out the use of renewables, which generate energy intermittently—e.g., when the sun is shining or the wind is blowing.

• Many of the solutions for supporting the energy grid today rely on fossil fuels, such as “peaker plants,” which are often powered by natural gas and come online during periods of high demand.
• Batteries offer a cleaner alternative for responding to demand and creating a lower-emission, more-resilient grid.

Battery build-out: While the vast majority of today’s existing energy storage is handled by pumped hydro projects, lithium-ion batteries are currently the most common tech being used to add new capacity, making up about 93% of all stationary storage installations in 2020, according to the IEA.

• Last year, about 25 GWh of energy stationary storage (ESS) capacity was added globally, Iola Hughes, research manager at Rho Motion, told Emerging Tech Brew.

Although the demand for ESS batteries is growing substantially—more than 100GWh of new capacity has been announced for this year and next year—the market is concentrated in just a few regions, Hughes said.

“In terms of new installations in 2021, for example, the US was far ahead of both China and the European market. But it’s worth noting that over 50% of that was coming from California,” she said.

Looking ahead: The world will need nearly 600 GWh of battery energy storage by the end of the decade in order to achieve net-zero emissions by 2050, per IEA estimates. In 2021, there was less than 60 GWh of battery storage capacity, according to estimates from energy research firms Rho Motion and Wood Mackenzie.

There’s a lot more to cover here—read the full breakdown.—GD

If you’re unsure about whether you’re in the wrong, you may turn to a friend, a family member, or some other confidant to talk it through. But nearly 4 million people have another go-to: r/AmItheAsshole, one of the most famous communities on Reddit.

• Posts typically describe a personal situation and ask the community to decide whether the original poster is the one at fault—issuing a judgment of “YTA” (you’re the asshole) or “NTA” (not the asshole).

WTTDOTM, an internet artist whose real name is Morry Kolman, and Alex Petros, an independent developer, decided to automate that experience by training an AI text-generation model on thousands of r/AITA posts.

• On the corresponding website, released today, users can type out their own questionable experiences, and the AI will respond with a determination of whether they’re at fault.

Why it matters: In the interest of educating users on how AI really works, Kolman and Petros didn’t just train one model—they trained three: one using all the Reddit post data, one solely on posts where the Redditor was deemed at fault, and one solely on posts where the Redditor was absolved. The goal is to show users how different training data can influence a model’s answers—and how, at the end of the day, AI is about imitating learned patterns.

To train their own language models, Kolman and Petros used OpenAI’s GPT-3, a headline language model now licensed by Microsoft. GPT-3, BERT, and other large language models serve as a key foundation for billion-dollar businesses ranging from customer service to automated copywriting.

Emerging Tech Brew chatted with Kolman and Petros about what sparked the idea, their favorite AITA-inspired answers so far, and what they hope people learn from the project.

Read the full conversation here.—HF

When Zoom calls and phone convos replace in-person meetings, some of the subtleties of communication—like body language and tone—are bound to get lost.

Companies that make “emotion-recognition” algorithms have cropped up in a controversial attempt to help solve this issue, selling software that they claim can parse emotions on video and phone calls.

• Last week, Protocol reported that Zoom is planning to add emotion-recognition software to its product, for now focused on helping sales teams.
• And Uniphore, a startup that sells emotion recognition tech to sales, HR, education, and health care customers, raised a $400 million Series E in February.

But, but, but…The technology’s efficacy is dubious, some researchers say, and others argue that even if it did work, this sort of tech is a bad idea due to privacy risks and potential discrimination.

For its part, Zoom rolled out a limited version of this tech last week, called Zoom IQ for Sales. It analyzes sentiment after a meeting concludes, rather than in real-time.

• But the company is researching how to incorporate emotion-recognition tech into forthcoming projects, and cited studies to Protocol that suggest some improvements have been made in the field.

Big picture: A key concern among critics is that emotion-recognition AI will be used by managers to surveil and discipline employees. And, even more controversially, students.

It’s not a misplaced fear: In general, worker surveillance software has exploded with the rise of remote work. Pre-pandemic, just 30% of companies had adopted such tech, per Gartner data—by the end of 2021, that figure had doubled to 60%.

Click here to view on-site.—DM

Snap poll: Would you feel comfortable with an organization (employer, school, etc.,) using “emotion recognition” software on you?

Yes

No

Only with explicit consent

Stat: Nearly 20% of HR professionals using AI tech said qualified candidates were inadvertently excluded by automated hiring software, per a new survey from SHRM cited by HR Brew.

Quote: “Dumping mmWave is smart…mmWave is an attempt to make use of the spectrum that nobody wants, but that spectrum is free because it has terrible range and signal characteristics.”—Ron Amadeo, reviews editor at Ars Technica, on the 5G band that is supposed to deliver the next-gen standard’s most dazzling performance (h/t Android Authority)

Read: When a model learns a thing from data created by a machine…that’s amore synthetic data.

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For smart analysis about a dumb news cycle: Stratechery breaks down what it could mean to actually “unlock” the potential of Twitter.

For flavor-enhancing tech: Presenting…Chopsticks that use an electrical current to make food taste 1.5x saltier than it actually is. Rumor has it that if you eat anchovies with them, you will instantly pickle.

For “little signals:” Google released a very ASMR-y video highlighting a project to make tech notifications less intrusive—check it out here.

Results from last Wednesday’s snap poll are in and, among Emerging Tech Brew readers, new health features for wearable devices hold quite a bit of appeal.

By the numbers…Among 2,224 respondents, just over half (51%) said the addition of new health features (e.g., Fitbit’s new atrial-fibrillation algorithm) would make them more likely to buy a wearable device.

• Under one-quarter (23%) were unmoved by the idea of new health features.
• And just over one-quarter (26%) said they don’t want wearables anyway. Fancy health features or not.

Zoom out: A lot of wearables get sold every year—in 2021, nearly 534 million units of wearables were sold globally, per Statista estimates. That was a 20% increase from 2020. For comparison, 1.35 billion smartphone units were sold in 2021, per Statista.

Catch up on the top Emerging Tech Brew stories from the past few editions:

• Rate design could help the grid handle the electrification of everything
• A primer on synthetic data, which is gaining steam for AI
• After a decade of declines, why battery prices could increase in 2022