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The Glasgow climate talks will fall short. Here are other ways to accelerate progress.

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The Glasgow climate talks will fall short. Here are other ways to accelerate progress.


Thousands of delegates will amass in Glasgow, Scotland, in the coming days for the annual UN climate conference, where they’ll spend two weeks squabbling over a lengthy list of action items that add up to a single question: How much faster will the world move to prevent catastrophic warming this century?

If history is any clue, it won’t be by much.

After 25 such summits over the last three decades, global greenhouse-gas emissions have continued to rise, aside from a few dips during economic downturns. Climate pollution is expected to sharply rebound in 2021, to nearly the peak levels of 2019, as the economy surges back from the pandemic.

Six years after nations adopted the landmark Paris climate agreement, countries haven’t committed to, much less enacted, the necessary policies to reduce emissions anywhere near as much as required to achieve the accord’s stated goal: preventing 2 ˚C of global warming this century while striving to limit the increase to 1.5 ˚C. And rich countries are still tens of billions of dollars short of the $100 billion in annual funds they agreed to provide to help developing nations address climate change.

If countries do no more than fulfill the loose pledges they’ve made for 2030 under the agreement, the planet is likely to heat up by around 2.7 ˚C this century, according to the UN Environment Programme’s “emissions gap report,” released earlier this week. If all they do is abide by domestic climate policies already in place, temperature increases could exceed 3 ˚C.

In a 3 ˚C warmer world, coral reefs likely disappear, the ice sheets begin to collapse, hundred-year droughts will occur every few years across vast stretches of the globe, and sea-level rise could force hundreds of millions of people to relocate, according to various studies.

“If the goal is to maintain a safe, livable climate for the majority of the world’s population, the grade is an F-,” says Jessica Green, an associate professor of political science at the University of Toronto who focuses on climate governance. “We’re not there; we’re not even close.”

Given the near-term calculations of geopolitics, which are dominated by considerations of political strength, international advantage, and domestic growth, the lack of progress isn’t terribly surprising.

Any treaty that involves nearly all the world’s nations, from the Kyoto Protocol to the Paris accord, has to be watered down to the point that it simply doesn’t demand much. Under the 2015 Paris agreement, emissions targets are self-determined, voluntary, and nonbinding. There is no real penalty for failing to set ambitious goals or achieve them, beyond international tsk-tsking.

National leaders and their people are being asked to voluntarily pay now for benefits that will largely accrue decades later—and won’t come at all if other nations fail to follow through on their commitments. The climate agreements also ask poor countries that have produced small fractions of the emissions generated by rich ones to tamp down their growth and curtail their citizens’ access to energy and a higher quality of life, with only vague, unaccountable promises of assistance.

As leaders and negotiators gather in Glasgow, many observers hold out hope that the world will rebuild momentum behind and faith in the Paris agreement. But at the same time, there’s a growing school of thought that the loose international framework will never drive major emissions reductions, and may even be pulling attention away from other models that could do more.

We might soon know who is right. As the US climate czar, John Kerry, recently told the BBC, the UN conference is the “last best hope for the world to get its act together.”

Limited progress

To be sure, the world has achieved some progress on climate change, as more nations shift away from coal and embrace increasingly cost-competitive renewables and electric vehicles. Global emissions do seem to be at least flattening, which could allow us to sidestep the worst-case warming scenarios from a few years ago, of around 4 ˚C or higher.

But countries need to make much faster progress from this point forward to avoid still extremely dangerous outcomes. The conference will be a revealing test of the international resolve to do so, because most nations are supposed to raise their Paris commitments for the first time this year.

In April, President Biden stepped up the US’s target, from 26% to 28% below 2005 levels by 2025 to a 50% to 52% reduction by 2030. Similarly this summer, European Union nations formally approved the European Climate Law, creating a binding requirement that members cut emissions 55% by 2030, with the goal of becoming “climate neutral” by 2050.

All told, nearly 90 countries plus the EU had submitted new 2030 targets as part of the UN process as of mid-September, according to Climate Action Tracker, an independent scientific research group. More than 70 nations, however, had not at that time.

Meanwhile, Russia’s Vladimir Putin pledged to achieve carbon neutrality by 2060, joining a list of now more than 100 countries that have pledged to zero out emissions from at least the primary greenhouse gas by around midcentury. China previously committed to hit the same 2060 mark, recently announced the nation will stop building coal plants overseas and reiterated its plan this week to achieve peak carbon dioxide emissions by 2030. Over the weekend, Saudi Arabia announced plans to achieve net-zero emissions by 2060 and plant 450 million trees over the next nine years.

But Kelly Sims Gallagher, director of the Climate Policy Lab at Tuft’s Fletcher School, said that midcentury goals can serve as “a distraction from near-term action.” She also stressed that nations aren’t doing enough to enact domestic policies that provide a credible path to fulfilling their 2030 pledges.

Earlier this month, the International Energy Agency highlighted the gaps between national climate policies, Glasgow pledges, and what’s still needed to zero out emissions by midcentury.

In fact, it’s hard to see how the US will meet its 50% target after a key measure to drive down emissions from the power sector was reportedly removed from the budget bill. An analysis published last week, led by energy researchers at Princeton and Dartmouth, found that if every other climate policy in the pending budget and infrastructure bills passes, the nation will still come up nearly 350 million tons shy.

Such shortfalls will reduce Kerry’s leverage at the upcoming talks, leaving it harder for him to make the case that other nations must step up their climate pledges or policies.

Meanwhile, the 2030 commitments announced in advance of the event still don’t add up to nearly what’s required. The UN Environment Programme report estimates nations will need to eliminate another 28 billion tons of carbon dioxide pollution in the next nine years to hold warming at 1.5 ˚C this century, or 13 billion tons to limit it to 2 ˚C.

“I don’t want to categorically trash the [UN process] and throw the baby out with the bathwater, but it’s time to be realistic about what it can and can’t do,” Green says.

Why isn’t it working?

The fundamental problem is that climate change is an enormously complex and expensive problem to solve. And for the most part, international agreements have failed to address the underlying economic and domestic political challenges, scholars argue.

Combating climate change means overhauling nearly every aspect of how the world generates energy, produces food, manufactures goods, and moves them and people around the world. It requires shutting down or retrofitting trillions of dollars’ worth of plants, factories, machines, and vehicles that would otherwise continue operating profitably for decades.

So despite the declining costs of renewables, batteries, and electric vehicles, rapidly shifting to zero-carbon sources still imposes giant costs on nations and businesses, whatever the eventual returns from creating new industries and reducing the risks of accelerating climate change. And it creates existential risks for powerful emitting industries.

In a recent essay in Foreign Affairs, Yale economist William Nordhaus argues that the decades of international climate negotiations have failed for three key reasons: Most of the world hasn’t put any real cost on climate pollution. We’re not investing enough to drive innovation in cleaner technologies. And UN agreements haven’t solved what’s known as the “free rider” problem. Basically, most nations will reap the same benefits from global action to slash emissions, whether they contribute meaningfully to the effort or not. So why would they bother?

Emissions cuts won’t happen at the speed and scale required until nations, trade pacts, or treaties create incentives, penalties, or mandates that are generous or strict enough to bring them about. And there is little sign that most countries will suddenly agree to meaningful versions of those at Glasgow.

Innovation

How else can the world accelerate international progress on climate change?

While stressing that the UN conference is “huge deal,” Varun Sivaram, a senior advisor to Kerry, said that the most important role the US can play in driving down emissions beyond its borders is in developing cheaper, better low-carbon technologies.

By heavily funding research and development efforts, the US will make it easier and more politically feasible for other nations to decarbonize, he said during a discussion at MIT Technology Review’s EmTech conference late last month. That will be particularly true for emerging economies that will account for most of the emissions growth in the coming years.

“The number one tool the US has to speed the energy transition around the world is innovation,” he said.

Others stress the importance and potential spillover effects from local efforts.

In an essay late last year in Boston Review, Charles Sabel of Columbia Law School and David Victor of the University of California, San Diego, highlighted the need for, and early successes of, what they describe as “experimentalist governance.”

In this model, smaller institutions that don’t need to achieve global consensus, like states or sector-specific regulatory agencies, can set strict and binding standards that bring about broader changes in particular polluting industries. They’re also able to adapt their tactics over time based on results.

The hope is that a variety of governments or regulators trying a variety of approaches can provide critical lessons on what does and doesn’t work, and drive a process that makes it cheaper and easier for other areas to enact emissions reduction policies and adopt cleaner technologies.

Islands In Maldives Build Defences Against Rising Sea Levels
Tourists walk by sandbags in the Maldives, a nation of low-lying islands where coastlines have been heavily effected by erosion as ocean levels rise.

ALLISON JOYCE/GETTY IMAGES

The article points to California’s strict and evolving rules on vehicle air pollution and carbon emissions. The state’s regulations compelled the auto industry, which doesn’t want to produce different models for different markets, to figure out ways to produce ever more fuel-efficient vehicles. They also helped accelerate the development of electric vehicles, the authors argue.

Another example is Germany’s aggressive renewable-energy policies and investments in research and development, which helped create an early market for solar panels while driving down costs for the rest of the world.

Victor says that the Paris agreement does play a role: it puts some pressure on companies and governments, and provides a compass that’s guiding the world toward “goals that aren’t achievable” but are roughly in the right direction.

But as he and Sabel argued in the piece, its role is a “considerably smaller one” than proponents believe.

“What if … the only practical way to get to a workable global solution is to encourage and piece together partial ones?” they wrote. “What if the best way to build an effective consensus is not to ask who will commit to achieving certain outcomes no matter what, but instead by inviting parties to start by solving problems at many scales?”

Climate clubs

There is also a growing belief that smaller groups of governments or institutions need to enact rules or create trading blocs that compel climate action through clear benefits or sharp penalties.

Victor, Nordhaus, and others have argued for the importance of marketplaces, known as “climate clubs,” that are initially small enough to set stricter rules but include incentives that can attract more members and encourage them to commit to increasingly aggressive targets.

This approach could take a variety of forms, including regional carbon markets, trade pacts among a few nations with common emissions commitments, or joint programs to pursue technology innovation in key areas.

One example is the tightening set of climate rules within the European Union. In addition to setting a binding emissions reduction target among member nations, the European Commission is taking steps to increase the cost of carbon pollution, reduce free carbon allowances for industrial sectors like cement and steel, and set up a carbon border tax that would impose fees on goods from countries or companies that are heavier polluters.

Combined with stricter climate policies, R&D funding, and government-backed purchase agreements within certain European nations, these regulations are starting to produce real and relatively rapid shifts in heavy industry in Europe. That progress includes a growing variety of green hydrogen and green steel projects.

A crucial feature of any climate club is that it’s attractive enough to draw in more members over time, Nordhaus said in an email. The major carrot is the potential for other nations and their companies to sell their products within the market on similar terms. That should incentivize other countries or foreign companies to adopt the standards required for admission, whether that means a common carbon price or relatively similar policy ambitions.

Obstructionism

There are some obvious challenges involved in this approach.

It is time-consuming: crafting one complex trade pact, much less many, can easily take years, and the world needs to make rapid emissions cuts now. It could produce myriad sets of conflicting rules that prove difficult to mesh together. It means that while some groups of nations are doing a lot, others may not be doing much at all. And it could create increasingly fragmented trade alliances around the world, with blocs of “good” and “bad” climate actors that trade mostly among themselves.

Those pacts could deepen international divisions, and even increase hostilities that might manifest in other potentially dangerous ways.

There are also clear global equity issues in demanding that poor nations—which haven’t emitted nearly as much historically, and can’t afford to decarbonize as rapidly—be held to the same standards as richer ones, or subjected to carbon border taxes that threaten to slow their economic growth.



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Why I became a TechTrekker

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group jumps into the air with snowy mountains in the background


My senior spring in high school, I decided to defer my MIT enrollment by a year. I had always planned to take a gap year, but after receiving the silver tube in the mail and seeing all my college-bound friends plan out their classes and dorm decor, I got cold feet. Every time I mentioned my plans, I was met with questions like “But what about school?” and “MIT is cool with this?”

Yeah. MIT totally is. Postponing your MIT start date is as simple as clicking a checkbox. 

Sofia Pronina (right) was among those who hiked to the Katla Glacier during this year’s TechTrek to Iceland.

COURTESY PHOTO

Now, having finished my first year of classes, I’m really grateful that I stuck with my decision to delay MIT, as I realized that having a full year of unstructured time is a gift. I could let my creative juices run. Pick up hobbies for fun. Do cool things like work at an AI startup and teach myself how to create latte art. My favorite part of the year, however, was backpacking across Europe. I traveled through Austria, Slovakia, Russia, Spain, France, the UK, Greece, Italy, Germany, Poland, Romania, and Hungary. 

Moreover, despite my fear that I’d be losing a valuable year, traveling turned out to be the most productive thing I could have done with my time. I got to explore different cultures, meet new people from all over the world, and gain unique perspectives that I couldn’t have gotten otherwise. My travels throughout Europe allowed me to leave my comfort zone and expand my understanding of the greater human experience. 

“In Iceland there’s less focus on hustle culture, and this relaxed approach to work-life balance ends up fostering creativity. This was a wild revelation to a bunch of MIT students.”

When I became a full-time student last fall, I realized that StartLabs, the premier undergraduate entrepreneurship club on campus, gives MIT undergrads a similar opportunity to expand their horizons and experience new things. I immediately signed up. At StartLabs, we host fireside chats and ideathons throughout the year. But our flagship event is our annual TechTrek over spring break. In previous years, StartLabs has gone on TechTrek trips to Germany, Switzerland, and Israel. On these fully funded trips, StartLabs members have visited and collaborated with industry leaders, incubators, startups, and academic institutions. They take these treks both to connect with the global startup sphere and to build closer relationships within the club itself.

Most important, however, the process of organizing the TechTrek is itself an expedited introduction to entrepreneurship. The trip is entirely planned by StartLabs members; we figure out travel logistics, find sponsors, and then discover ways to optimize our funding. 

two students soaking in a hot spring in Iceland

COURTESY PHOTO

In organizing this year’s trip to Iceland, we had to learn how to delegate roles to all the planners and how to maintain morale when making this trip a reality seemed to be an impossible task. We woke up extra early to take 6 a.m. calls with Icelandic founders and sponsors. We came up with options for different levels of sponsorship, used pattern recognition to deduce the email addresses of hundreds of potential contacts at organizations we wanted to visit, and all got scrappy with utilizing our LinkedIn connections.

And as any good entrepreneur must, we had to learn how to be lean and maximize our resources. To stretch our food budget, we planned all our incubator and company visits around lunchtime in hopes of getting fed, played human Tetris as we fit 16 people into a six-person Airbnb, and emailed grocery stores to get their nearly expired foods for a discount. We even made a deal with the local bus company to give us free tickets in exchange for a story post on our Instagram account. 

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The Download: spying keyboard software, and why boring AI is best

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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.

How ubiquitous keyboard software puts hundreds of millions of Chinese users at risk

For millions of Chinese people, the first software they download onto devices is always the same: a keyboard app. Yet few of them are aware that it may make everything they type vulnerable to spying eyes. 

QWERTY keyboards are inefficient as many Chinese characters share the same latinized spelling. As a result, many switch to smart, localized keyboard apps to save time and frustration. Today, over 800 million Chinese people use third-party keyboard apps on their PCs, laptops, and mobile phones. 

But a recent report by the Citizen Lab, a University of Toronto–affiliated research group, revealed that Sogou, one of the most popular Chinese keyboard apps, had a massive security loophole. Read the full story. 

—Zeyi Yang

Why we should all be rooting for boring AI

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. It hopes they could improve intelligence and operational planning. 

But those might not be the right use cases, writes our senior AI reporter Melissa Heikkila. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases. 

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. The DoD’s best bet is to apply generative AI to more mundane things like Excel, email, or word processing. Read the full story. 

This story is from The Algorithm, Melissa’s weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The ice cores that will let us look 1.5 million years into the past

To better understand the role atmospheric carbon dioxide plays in Earth’s climate cycles, scientists have long turned to ice cores drilled in Antarctica, where snow layers accumulate and compact over hundreds of thousands of years, trapping samples of ancient air in a lattice of bubbles that serve as tiny time capsules. 

By analyzing those cores, scientists can connect greenhouse-gas concentrations with temperatures going back 800,000 years. Now, a new European-led initiative hopes to eventually retrieve the oldest core yet, dating back 1.5 million years. But that impressive feat is still only the first step. Once they’ve done that, they’ll have to figure out how they’re going to extract the air from the ice. Read the full story.

—Christian Elliott

This story is from the latest edition of our print magazine, set to go live tomorrow. Subscribe today for as low as $8/month to ensure you receive full access to the new Ethics issue and in-depth stories on experimental drugs, AI assisted warfare, microfinance, and more.

The must-reads

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

1 How AI got dragged into the culture wars
Fears about ‘woke’ AI fundamentally misunderstand how it works. Yet they’re gaining traction. (The Guardian
+ Why it’s impossible to build an unbiased AI language model. (MIT Technology Review)
 
2 Researchers are racing to understand a new coronavirus variant 
It’s unlikely to be cause for concern, but it shows this virus still has plenty of tricks up its sleeve. (Nature)
Covid hasn’t entirely gone away—here’s where we stand. (MIT Technology Review)
+ Why we can’t afford to stop monitoring it. (Ars Technica)
 
3 How Hilary became such a monster storm
Much of it is down to unusually hot sea surface temperatures. (Wired $)
+ The era of simultaneous climate disasters is here to stay. (Axios)
People are donning cooling vests so they can work through the heat. (Wired $)
 
4 Brain privacy is set to become important 
Scientists are getting better at decoding our brain data. It’s surely only a matter of time before others want a peek. (The Atlantic $)
How your brain data could be used against you. (MIT Technology Review)
 
5 How Nvidia built such a big competitive advantage in AI chips
Today it accounts for 70% of all AI chip sales—and an even greater share for training generative models. (NYT $)
The chips it’s selling to China are less effective due to US export controls. (Ars Technica)
+ These simple design rules could turn the chip industry on its head. (MIT Technology Review)
 
6 Inside the complex world of dissociative identity disorder on TikTok 
Reducing stigma is great, but doctors fear people are self-diagnosing or even imitating the disorder. (The Verge)
 
7 What TikTok might have to give up to keep operating in the US
This shows just how hollow the authorities’ purported data-collection concerns really are. (Forbes)
 
8 Soldiers in Ukraine are playing World of Tanks on their phones
It’s eerily similar to the war they are themselves fighting, but they say it helps them to dissociate from the horror. (NYT $)
 
9 Conspiracy theorists are sharing mad ideas on what causes wildfires
But it’s all just a convoluted way to try to avoid having to tackle climate change. (Slate $)
 
10 Christie’s accidentally leaked the location of tons of valuable art 🖼📍
Seemingly thanks to the metadata that often automatically attaches to smartphone photos. (WP $)

Quote of the day

“Is it going to take people dying for something to move forward?”

—An anonymous air traffic controller warns that staffing shortages in their industry, plus other factors, are starting to threaten passenger safety, the New York Times reports.

The big story

Inside effective altruism, where the far future counts a lot more than the present

" "

VICTOR KERLOW

October 2022

Since its birth in the late 2000s, effective altruism has aimed to answer the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer.

It’s no surprise that effective altruisms’ ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story.

—Rebecca Ackermann

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Watch Andrew Scott’s electrifying reading of the 1965 commencement address ‘Choose One of Five’ by Edith Sampson.
+ Here’s how Metallica makes sure its live performances ROCK. ($)
+ Cannot deal with this utterly ludicrous wooden vehicle
+ Learn about a weird and wonderful new instrument called a harpejji.



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Why we should all be rooting for boring AI

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Why we should all be rooting for boring AI


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

I’m back from a wholesome week off picking blueberries in a forest. So this story we published last week about the messy ethics of AI in warfare is just the antidote, bringing my blood pressure right back up again. 

Arthur Holland Michel does a great job looking at the complicated and nuanced ethical questions around warfare and the military’s increasing use of artificial-intelligence tools. There are myriad ways AI could fail catastrophically or be abused in conflict situations, and there don’t seem to be any real rules constraining it yet. Holland Michel’s story illustrates how little there is to hold people accountable when things go wrong.  

Last year I wrote about how the war in Ukraine kick-started a new boom in business for defense AI startups. The latest hype cycle has only added to that, as companies—and now the military too—race to embed generative AI in products and services. 

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. 

The department sees tons of potential to “improve intelligence, operational planning, and administrative and business processes.” 

But Holland Michel’s story highlights why the first two use cases might be a bad idea. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases.  

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. Everyone agrees that humans should make the final call, but that is made harder by technology that acts unpredictably, especially in fast-moving conflict situations. 

Some worry that the people lowest on the hierarchy will pay the highest price when things go wrong: “In the event of an accident—regardless of whether the human was wrong, the computer was wrong, or they were wrong together—the person who made the ‘decision’ will absorb the blame and protect everyone else along the chain of command from the full impact of accountability,” Holland Michel writes. 

The only ones who seem likely to face no consequences when AI fails in war are the companies supplying the technology.

It helps companies when the rules the US has set to govern AI in warfare are mere recommendations, not laws. That makes it really hard to hold anyone accountable. Even the AI Act, the EU’s sweeping upcoming regulation for high-risk AI systems, exempts military uses, which arguably are the highest-risk applications of them all. 

While everyone is looking for exciting new uses for generative AI, I personally can’t wait for it to become boring. 

Amid early signs that people are starting to lose interest in the technology, companies might find that these sorts of tools are better suited for mundane, low-risk applications than solving humanity’s biggest problems.

Applying AI in, for example, productivity software such as Excel, email, or word processing might not be the sexiest idea, but compared to warfare it’s a relatively low-stakes application, and simple enough to have the potential to actually work as advertised. It could help us do the tedious bits of our jobs faster and better.

Boring AI is unlikely to break as easily and, most important, won’t kill anyone. Hopefully, soon we’ll forget we’re interacting with AI at all. (It wasn’t that long ago when machine translation was an exciting new thing in AI. Now most people don’t even think about its role in powering Google Translate.) 

That’s why I’m more confident that organizations like the DoD will find success applying generative AI in administrative and business processes. 

Boring AI is not morally complex. It’s not magic. But it works. 

Deeper Learning

AI isn’t great at decoding human emotions. So why are regulators targeting the tech?

Amid all the chatter about ChatGPT, artificial general intelligence, and the prospect of robots taking people’s jobs, regulators in the EU and the US have been ramping up warnings against AI and emotion recognition. Emotion recognition is the attempt to identify a person’s feelings or state of mind using AI analysis of video, facial images, or audio recordings. 

But why is this a top concern? Western regulators are particularly concerned about China’s use of the technology, and its potential to enable social control. And there’s also evidence that it simply does not work properly. Tate Ryan-Mosley dissected the thorny questions around the technology in last week’s edition of The Technocrat, our weekly newsletter on tech policy.

Bits and Bytes

Meta is preparing to launch free code-generating software
A version of its new LLaMA 2 language model that is able to generate programming code will pose a stiff challenge to similar proprietary code-generating programs from rivals such as OpenAI, Microsoft, and Google. The open-source program is called Code Llama, and its launch is imminent, according to The Information. (The Information

OpenAI is testing GPT-4 for content moderation
Using the language model to moderate online content could really help alleviate the mental toll content moderation takes on humans. OpenAI says it’s seen some promising first results, although the tech does not outperform highly trained humans. A lot of big, open questions remain, such as whether the tool can be attuned to different cultures and pick up context and nuance. (OpenAI)

Google is working on an AI assistant that offers life advice
The generative AI tools could function as a life coach, offering up ideas, planning instructions, and tutoring tips. (The New York Times)

Two tech luminaries have quit their jobs to build AI systems inspired by bees
Sakana, a new AI research lab, draws inspiration from the animal kingdom. Founded by two prominent industry researchers and former Googlers, the company plans to make multiple smaller AI models that work together, the idea being that a “swarm” of programs could be as powerful as a single large AI model. (Bloomberg)

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