Meet the Latest AI Darling: Reddit

Summary

Summary of WSJ Tech News Briefing – "Meet the Latest AI Darling: Reddit" (December 12, 2024)

Hosted by Belle Lin for The Wall Street Journal, the December 12, 2024 episode of WSJ Tech News Briefing delves into two major topics: Amazon's latest foray into warehouse automation and Reddit's burgeoning role as a pivotal data source for artificial intelligence (AI) companies. Below is a comprehensive summary of the key discussions, insights, and conclusions from the episode.

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1. Amazon's Most Automated Warehouse Yet Still Relies on Human Labor

Overview: Amazon has unveiled its most automated warehouse to date in Shreveport, Louisiana. This facility integrates robotics and artificial intelligence (AI) at every step of the fulfillment process. Despite the high level of automation, Amazon continues to employ thousands of people to ensure smooth operations, especially during the bustling holiday season.

Key Insights:

• Limitations of Automation:

  • Dexterity and Flexibility: Robots struggle with tasks requiring the dexterity of the human hand. As Liz Young, WSJ reporter, explained at [01:55], “...robots can't do what a human hand does to reach into a bin full of items, but both identify what it's looking for and then correctly pick up that item.”
  • Handling Diverse Products: Amazon's vast inventory includes over 400 million products varying in size, weight, and fragility. Teaching robots to handle such a diverse range— from soft dog toys to heavy toaster ovens—requires immense training data and complex programming. Liz Young highlighted this challenge at [02:50]: “Here's how you pick up a dog toy and here's how you pick up a toaster oven... that's really challenging to teach that robot.”

• Facility Specifications:

  • Size and Employment: The Shreveport facility spans over 3 million square feet and is projected to employ 2,500 individuals. As of the episode's release, Amazon had hired approximately 1,400 workers in just over two months after opening.
  • Operational Goals: The integration of more automation aims to reduce labor costs, accelerate operations, and enhance workplace safety. Liz Young noted at [04:25] that the robots “carry a stack of totes directly over to workers... so people don't have to bend over, for example.”

• Economic Impact:

  • Cost and Speed Efficiency: Although Amazon has not disclosed exact figures, the company asserts that the automated facility has reduced fulfillment costs by 25% and increased order fulfillment speed by the same percentage compared to less automated sites ([04:38] Liz Young).

Conclusion: While automation significantly enhances efficiency and reduces costs, Amazon acknowledges that human workers remain indispensable for tasks that require adaptability and nuanced handling. The Shreveport warehouse exemplifies the synergistic relationship between advanced robotics and human labor in optimizing fulfillment operations.

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2. Reddit's Data: A Goldmine for AI Companies and a New Revenue Stream

Overview: Reddit has emerged as a crucial data provider for AI companies like OpenAI and Google. Transitioning from previous frustrations with AI interactions, Reddit now leverages its extensive and diverse user-generated content to fuel AI advancements. This strategic move has not only propelled Reddit towards profitability but also opened new avenues for revenue through data licensing.

Key Insights:

• Value of Reddit's Data for AI:

  • Extensive and Diverse Content: With nearly two decades of active user engagement, Reddit boasts a rich repository of over 5.3 billion pieces of content in the first half of the year alone—a 20.5% increase from the previous year ([09:45] Sarah Needleman). The platform's organization into more than 100,000 subreddits ensures coverage of an almost limitless array of topics, making it an invaluable resource for training AI models.
  • Quality Signals: Unlike other social platforms that rely heavily on algorithms to surface content, Reddit employs a system of upvotes, downvotes, and karma points to highlight high-quality and relevant information. As Sarah Needleman explained at [06:43], “...users can respond to those comments with an upvote or a down vote... AI companies look for high quality information...”

• Revenue Growth from Data Licensing:

  • Financial Impact: Reddit reported its first quarterly profit as a publicly traded company, partly attributed to lucrative data licensing deals with AI giants like OpenAI and Google. The revenue from these deals surged from $12.3 million to $81.6 million in just nine months ([08:40] Sarah Needleman), signaling a substantial growth trajectory.
  • Investment Appeal: The rapid increase in data licensing revenue presents a promising long-term opportunity for investors, as these deals offer high-margin returns without significant additional costs.

• Challenges and Considerations:

  • Data Quality and Bias: While Reddit's data is extensive, it is primarily generated by everyday users, which means the content can sometimes be biased or of varying quality. Sarah Needleman pointed out at [10:37], “...some of the data it's being trained on is just flawed or biased.”
  • Content Limitations: Private messages and chats are excluded from the data shared with AI companies, limiting the comprehensiveness of the dataset. Additionally, Reddit's user base of 97 million daily users, while substantial, is smaller compared to platforms like Snapchat with 443 million daily users ([10:28] Sarah Needleman).

Conclusion: Reddit's strategic data licensing has transformed the platform into a significant player in the AI industry. By providing AI companies with diverse and high-quality data, Reddit not only enhances AI training but also diversifies its revenue streams. However, the quality and potential biases in user-generated content pose ongoing challenges that Reddit and its partners must navigate to maximize the benefits of this symbiotic relationship.

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Final Thoughts: The December 12th episode of WSJ Tech News Briefing underscores the evolving dynamics between advanced technology and human labor in Amazon's automated warehouses, as well as Reddit's pivotal role in the AI ecosystem through its vast data resources. These discussions highlight the continuous interplay between innovation, efficiency, and economic growth within the tech industry.

Transcript

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[Belle Lin]

Welcome to Tech News briefing. It's Thursday, December 12th. I'm Belle Lin for the Wall Street Journal. Amazon just opened its most automated warehouse yet. But underneath all the robotics and artificial intelligence, the facility will still rely on thousands of people. We'll find out why the E Commerce behemoth can't do without humans yet and then AI companies were one of Reddit's biggest frustrations last year. Now they're a key source of growth for the social media platform. Our reporter Sarah Needleman tells us why OpenAI and Google are hankering for Reddit's data. But first, Amazon said its new warehouse in Shreveport, Louisiana, is its first to use automation and AI at every step of the fulfillment process. Yet it still needs thousands of people to keep it running smoothly, especially in the midst of the frantic holiday retail season that pushes millions of added shipments through fulfillment networks. So what can't Amazon's robots do? WSJ reporter Liz Young has been following the story, and she joins us now with more. Liz, why does Amazon need humans at an automated factory that's filled with robots?

[Liz Young]

Basically, Amazon has been able to incorporate more automation throughout their warehouse, so they're able to do that to help speed up fulfillment, get packages to you at your house faster. But in the process, there's still a lot of things that robots can't do. It's difficult for robots, for example, to do what a human hand does to reach into a bin full of items, but both identify what it's looking for and then correctly pick up that item. Same with loading and unloading trucks. These are tasks that just haven't been able to be fully automated yet. When you think about it, Amazon sells, they say, more than 400 million products, and those range in size, weight, and fragility. So you know, you have everything from like a soft dog toy to a toaster oven that's really big, heavy, but also easily breakable. So it's really challenging to then teach that robot. Here's how you pick up a dog toy and you here's how you pick.

[Belle Lin]

Up a toaster oven and the amount of time and training data required to teach it on those 400 million items. That's gotta be huge.

[Liz Young]

Yeah, absolutely. They're working on training the AI so that the AI can identify damage. For example, is another part of this that they want to be able to look at it and say, okay, is this broken in a way that a human can quickly look at something and say, oh, that dog toy's falling apart. A robot is still learning how to do that reliably every single time to say, we can't send that to a customer.

[Belle Lin]

All right, Liz, give us a sense of this new Amazon warehouse in Louisiana. How big is this facility?

[Liz Young]

Yeah, absolutely. It's more than 3 million square feet. And the building is going to employ eventually 2,500 people picking orders, loading, unloading trucks, managing the robotics, all that good stuff. So far, they've been open a little over two months. They've hired about 1,400 people. So they're still ramping up operations there. And the idea here is that they want to incorporate more automation to help save on labor costs, speed up operations, and to make warehouses safer.

[Belle Lin]

So for doing things like lifting heavy objects repetitively, are those what robots are being used for now?

[Liz Young]

Yeah, so there's some automation at every different point that serves different kinds of functions. But one of the things they have these robots that are able to roll across the ground, kind of like a Roomba, and what they carry is they carry a stack of totes directly over to workers. And Amazon says that the robot is able to provide a tote to a worker at an ergonomic height so that people don't have to bend over, for.

[Belle Lin]

Example, Liz, do we have any idea how much of a bottom line impact these robots can have? And especially during the upcoming holiday season, can they simply pack millions more of these boxes?

[Liz Young]

Amazon has not disclosed what a difference this makes, but they do say that it helps speed things up. Amazon said that this building has cut fulfillment costs 25% and is fulfilling orders 25% faster than some of its less automated sites.

[Belle Lin]

That was our reporter, Liz Young. Coming up, it turns out years upon years of Reddit posts are excellent fodder for training AI models. We'll find out why and what that means for Reddit's revenue.

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[Belle Lin]

AI companies need data so their apps can respond to users questions and prompts with accurate results and in a conversational tone. Enter Reddit, whose text heavy platform and growing collection of online human interactions fit the bill. Plus, Reddit's willingness to sell its data to AI companies makes it stand out because there's only so much data out there to gobble up for free or purchase. Reddit recently reported its first quarterly profit as a publicly traded company, thanks partly to data licensing deals it made in the past year with OpenAI and Google. For more on Reddit's newfound wealth and the limits of its data, we're joined by WSJ reporter Sarah Needleman. Sarah, we know there's a lot of text on Reddit, but why is that data so, so interesting and valuable to AI companies?

[Sarah Needleman]

Well, there are a number of reasons. The platform has been around for about 19 years and during that time people have posted a lot of comments. And what's interesting about Reddit, or at least what makes it a little bit different than some of its peers, is that users can respond to those comments with an upvote or a down vote. They can also accumulate what's called karma, which are essentially like points that show you've been a good contributor to the platform. And that's, you know, with the up and down vote. That's different than what you might see on other platforms where the content is organized by an algorithm. But when posts on Reddit get a lot of upvotes, those are the ones that you're more likely to see than the ones that are voted down because they are considered higher in quality. And that's the sort of thing that AI companies look for. They want high quality information and they're looking for a wide variety of information too. So Reddit is divided into more than 100,000 so called subreddits and these are dedicated to all sorts of topics, just about everything you can possibly think of. And they can be very specific specific or they can be general. And that's really helpful for AI because it really covers a lot of ground, whereas other social platforms may cater to a specific group of people. So for example, Discord is known for being popular among video game enthusiasts, Strava is popular for fitness fans. But Reddit is for just about everybody on earth and its demographics are really spread out. There is one other thing about Reddit that makes it attractive for the AI companies. And that is that because users are mostly pseudonymous, they just go by like a fake username, they tend to be more candid in what they post. And that's again something that's helpful for an AI tool that wants to be able to take users queries and respond with accurate information and in a conversational tone. The way that we talk, not a robot.

[Belle Lin]

For Reddit's business, this seems to be pretty great. How much money has Reddit made from some of these deals?

[Sarah Needleman]

Reddit has made a good chunk of change from these deals. It's still the amount of money that comes in from the data licensing is still much smaller than their main bread and butter, which is advertising sales. But that being said, with the first nine months of this year, Reddit's revenue category that includes the licensing deals we're talking about grew to 81.6 million and that's up from 12.3 million a year earlier. So this is like a category that's blown up. And so even though collectively it's still small compared to the broader picture of Reddit's revenue pie, the fast growth is really interesting and it's really exciting for investors because this could be a long term opportunity. We don't know exactly how long these deals are for, but the companies are looking for more than just what people have written in those past 19 years. They also want what's coming in right now, day after day. It's an ongoing. Their thirst can never be quenched. They're constantly drinking from this fountain that is Reddit and we're talking about a relatively high margin business. So they didn't have to put out a lot of costs to make this happen.

[Belle Lin]

Yeah, absolutely. Can we quantify how much data Reddit really has?

[Sarah Needleman]

Reddit did say that in the first half of this year, people posted more than 5.3 billion pieces of content to Reddit and that's a 20.5% increase from the second half of 2023. And that seems like a pretty beefing amount. I will say, however, that private message and chats, that content is not shared with the AI companies, so we wouldn't be counting that. And that does account for a large part of the 5.3 billion pieces of content I just mentioned. Also, keep in mind, Reddit is not as big as some of its other social media peers. So while that number does seem big, and it is big, keep in mind Reddit has something like 97 million daily users. Snapchat, for example, had 443 million daily users in both cases we're talking about as of the end of September.

[Belle Lin]

Are there any downsides for OpenAI to be training on Reddit's data or for any AI company to be training on Reddit's data?

[Sarah Needleman]

Reddit's data is based on what regular people are posting day in and day out. And these aren't necessarily experts. They have opinions that are wide ranging. And just because something is voted up as being very popular doesn't necessarily mean it's high in quality. Oftentimes that is the case. It is a logical conclusion, but that isn't always a guarantee. And so it's possible that some of the data it's being trained on is just flawed or biased. And that is true of a lot of content on the Internet. And so there's some judgment calls or some editing they may have to make along the way to correct that. But again, we have, you know, the signals, the up votes and downvotes, the karma. These are all signals that help AI companies get a sense of what is high quality. And a lot of the AI companies, when they spit out results, they have some sort of language that warns readers, don't necessarily take this verbatim, but anyone with common sense should not take anything verbatim from the Internet and assume it to be true.

[Belle Lin]

That was our reporter Sarah Needleman. And that's it for Tech News Briefing. Today's show was produced by Julie Chang with supervising producer Kathryn Millsop. Logging off. I'm Belle Lynn for the Wall Street Journal. We'll sign back in this afternoon with TNB Tech Minute. Thanks for listening.

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