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Scientists advance cloud-seeding capabilities with nanotechnology

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Scientists advance cloud-seeding capabilities with nanotechnology


Dr. Zou leads a groundbreaking research project using nanotechnology to develop cloud-seeding materials. Cloud seeding is a form of weather modification that mimics what naturally occurs in clouds but enhances the process by adding particles that can stimulate and accelerate the condensation process. However, Dr. Zou explains, “The cloud-seeding materials used today have been around for many decades. The information and techniques are out of date and their effectiveness is not well understood.”

Cloud seeding has strict requirements. To be successful, scientists need the right air temperature, the right humidity, a surface that attracts water and keeps it, and then the correct size material to allow condensation to form on the particle.

“Through the advancement in nanotechnology and nanoscience, nowadays we are working to design and engineer cloud-seeding materials with optimal properties to ensure water vapor condensation will occur effectively and maximize the rainfall achieved,” explains Dr. Zou.

Related materials

Full transcript

Laurel Ruma: From MIT Technology Review, I’m Laurel Ruma, and this is Business Lab. The show that helps business leaders make sense of new technologies coming out of the lab and into the market place.

Our topic today is cloud seeding to increase rainfall. Although cloud seeding has been around since the 1940s, climate change and population growth are driving scientists to take a closer look at the technology, which could offer a viable cost-effective supplement to existing water supplies, particularly in arid and semi-arid regions, like the United Arab Emirates.

To help advance the science, in 2015 the UAE government launched a new initiative, the UAE Research Program for Rain Enhancement Science. The aim is to get other innovative projects from scientists in the field of rain enhancement from all over the world, with the winning ideas obtaining a grant of $5 million to work and improve on concepts for a period of three years. Two words for you: nanoengineered materials.

My guest today is Dr. Linda Zou, who is a professor of civil and environmental engineering at Khalifa University of Science and Technology. Dr. Zou leads a groundbreaking research project using nanotechnology to develop cloud seeding materials.

She was awarded a grant by the UAE Research Program on rain enhancement science from 2016 to 2019. Dr. Zou’s research interests include applying nanotechnology and membrane science to the development of low energy and high efficiency novel desalination and water purification solutions. This podcast is produced in partnership with the UAE Pavilion Expo 2020 Dubai. Welcome, Dr. Zou.

Dr. Zou: Thank you, Laurel.

Laurel: You were one of the first scientists in the world to explore the use of nanotechnology in cloud seeding. Why are you interested in this type of research?

Dr. Zou: The cloud seeding materials used today have been around for many decades. The information and techniques are out of date and their effectiveness is not well understood. Through the advancement in nanotechnology and nanoscience, nowadays we are working to design and engineer cloud seeding materials with optimal properties to ensure water vapor condensation will occur effectively and maximize the rainfall achieved.

Laurel: Cloud seeding is a form of weather modification that mimics what naturally occurs in clouds but enhances the process by adding particles that can stimulate and accelerate the condensation process. Could you explain in more detail how cloud seeding works?

Dr. Zou: In the natural water cycle on the earth, the sun irradiates on the surface of our planet and the water on the surface is evaporated by the heat as the vapors. The tiny vapors rise into the atmosphere without condensation nuclei, which are small particles. They remain as vapors in the air and move higher and further.

The natural occurring condensation nuclei are such as dust particles, volcano flash, or pollens. Unfortunately, such material is unpredictable, where and how much available. On the other hand, cloud seeding practice is to release artificial seeding materials as nuclei to initiate the water vapor in the cloud to condense into droplets and promote the formation of large droplets until they grow big enough to fall as rain.

The key factors of a successful cloud seeding operation include, first, identifying the suitable cloud for seeding. Second, having the efficient seeding material for water droplet formation.

Laurel: To successfully cloud seed, you need a number of things: the right air temperature, the right humidity, a surface that attracts water and keeps it, and then the correct size material to allow condensation to form on the particle. Is that correct?

Dr. Zou: Yes. Yes.

Laurel: Although cloud seeding has been around for decades, how does today’s technology move it toward a greater success rate?

Dr. Zou: As we know, the global water shortage has continuously intensified by rapid population growth and economic development around the world. Conventional water resources such as rivers, lakes, and groundwater have become very limited, which is driving scientists and engineers to look for alternative water resources.

Atmospheric water is one such alternative resource. At the moment, all possible solutions that could resolve the water shortage issue should be examined carefully.

Nanotechnology can engineer material and design the material with well controlled size, shapes, and properties. So it has a huge possibility to improve its efficiency.

Laurel: Your research focuses on the cloud seeding material itself, specifically the nanomaterials as you mentioned, which is a more effective tool in generating rain from existing clouds. What are conventional cloud seeding materials, and then how does nanotechnology come into play?

Dr. Zou: The conventional cloud seeding materials include mostly hydroscopic salt mixture, which can change from salt crystals into water droplets at the right condition. The delivery of this salt is to vaporize them by ignition by a flare device. This salt vapor then will recondense as very small particles. Because the process is random and uncertain, the form and size of the particle cannot be controlled and most are probably too small to be effective cloud seeding materials.

The conventional cloud seeding material can only be activated at a very high relative humidity in atmosphere in the cloud, such as greater than 75% relative humidity. In my project, we have changed the surface of the material to make it more reactive so it can work at a lower and wider relative humidity to make it more likely to happen.

To achieve this, we use the nanotechnology to deposit titanium dioxide nanoparticles as a shell layer and sodium chloride crystal core. This nanoengineered shell core structured material can be activated at much broader relative humidity conditions such as about 65%. Because the coated nanolayers are more hydrophilic and porous, the water can be absorbed easily and increase the local relative humidity of the crystals and increase the probability of forming water droplets. So it is a synergistic effect.

Laurel: You’ve also developed another kind of technology, ice nucleating particles. How do those compare to cloud seeding materials?

Dr. Zou: Yes. As you know, cold clouds with sub-zero temperatures are also present in the atmosphere. They are made of many super cooled water vapors, so although they are below zero, they remain as vapor. Once such cloud encounters the ice nucleation particles, they rapidly form a large number of ice crystals and bypass the liquid water phase. So they form super cool vapor and crystallize into ice particles.

Ice nucleation is important. It will initiate from the thin water layer formed on the surface of the ice nuclease, and the ice will grow rapidly at the expense of the water vapor in the cloud. We designed and fabricated a porous nanocomposite of 3D reduced graphite oxide and silica dioxide nanoparticles. This material can initiate ice nucleation followed by rapid growth starting from a temperature of minus 80 degrees. This temperature is much higher than most other known ice nucleate material. Often they require minus 25 degrees or even lower.

Laurel: This is very critical because the cloud seeding materials go very high up into the atmosphere where it is very cold, correct?

Dr. Zou: Yes. The higher you move up to the atmosphere, quickly moving into subzero and very cold.

Laurel: In the past, one of the challenges scientists encountered when researching cloud seeding was the lack of a simulation environment. You took this on as part of your research. What did you develop and how will it facilitate future research?

Dr. Zou: It is a challenge area and I have collaborated with the Cloud Microphysics Modeling International team. The innovation of my project is the characteristics data we obtained from the experiment. This data describing my new seeding materials property and their interactions in atmosphere. So we can use them as input to develop one-dimensional and three-dimensional modeling of precipitation enhancement caused by cloud seeding, and the results prove quite successful.

Laurel: Could you describe that weather chamber that you used in your experiments? What are the challenges with then deploying the material out in the real world?

Dr. Zou: The cloud chamber is a three-dimensional experimental environment. They vary in size. There’s a small one, a medium one, and a large one. The small one could be 20 meters and the large one could be like a building. I used an eight cubic meter chamber with controlled humidity and temperature. A device at the top of the chamber releases the seeding materials.

Immediately after the seeding is released, the electronic equipment, which are electronic optical cameras, will quickly take many, many photos to record the image while the seeding material’s falling. Then we can later analyze at what stage the droplets formed and at what number and size of the droplets. We can do a spectrum analysis and to find out their vapor condensation, the droplet formation, and the size and the number of the droplets. Using this information is very good to compare the performance of different materials, and we did that extensively.

Laurel: Then in the real world where we don’t have this controlled chamber, it’s not quite as easy necessarily to measure that kind of success.

Dr. Zou: Yes, you are right. In the open environment, it’s more challenging.

Laurel: Your research signifies a milestone toward achieving greater water security in the world. What kind of effect can cloud seeding potentially have on a country, like the UAE, which typically only records four inches of rain in a year?

Dr. Zou: Yeah. UAE is in the arid climate zone, and the government has already taken the initiative of this UAE research program for re-enhancement science. We call them UAEREP [United Arab Emirates Research Program for Rain Enhancement Science]. My research work has been supported in their first cycle and received excellent worldwide exposure.

Today, together with the National Center of Meteorology of the UAE, we can see the application of these new seeding materials in real operations very quickly across UAE to increase the rainfall.

Laurel: Back to your technology, you filed a patent on the cloud seeding material itself. What are you working on now, and what are you thinking about next?

Dr. Zou: Yeah. One patent is filed on the titanium dioxide, sodium chloride material for warm cloud seeding, and another patent is filed for porous graphite oxide, silica dioxide, nano compensated for cold cloud seeding.

At the moment, I’m working collaboratively on a project to evaluate the effects of these materials in the open air. A team of pilots is conducting an investigation by releasing the seeding materials and in real time capturing and analyzing them. It’s very promising to know more about the effects of this seeding material.

On the other hand, I am also dedicated to the scale up of the production, reduce the cost, and the application of the materials. We are looking forward to moving the seeding materials from laboratory to the commercial venture for not only cloud seeding applications, but wider applications, such as different weather modification efforts, including agriculture or crop protection, hail, or storm suppression, and the artificial snow making at the ski resort. Yes, such type of applications.

Laurel: Certainly, a number of possible commercial ventures. You are also pursuing funding initiatives at this point too, for your research. Is that correct?

Dr. Zou: We want to move the materials, as I mentioned, from laboratory already and scale up, so it has a chance of reaching the market and to reach many different parts of the world as well, because there are so many countries worldwide that practice weather modification.

Laurel: Dr. Zou, thank you so much for being with us here on the Business Lab. This has been an absolute, fantastic conversation.

Dr. Zou: Thank you for having me.

Laurel: That was Dr. Linda Zou, a professor of civil and environmental engineering at Khalifa University of Science and Technology, who I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review, overlooking the Charles River.

That’s it for this episode of Business Lab. I’m your host, Laurel Ruma. I’m the Director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print on the web and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com.

This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Collective Next. Thanks for listening.

This podcast episode 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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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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