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Meet Dean and Alexis Indot, TikTok’s hottest finance couple

Meet Dean and Alexis Indot, TikTok’s hottest finance couple

Tech-news

If you’ve been on finance TikTok lately, you’ve probably seen Dean Indot answer his wife Alexis’s finance questions to the tune of millions of views.

Dean, a commercial banking exec and Pepperdine MBA, and his wife Alexis went viral from one of their first-ever videos. It wasn’t long before Dean’s reading-chair rant on why you might not want to use your debit card very often got 14.5 million views. Now, their TikTok account, @alexisanddean, has 1.7 million followers.

We sat down with Alexis and Dean to discuss why their content struck such a chord, when they started making big money from it, and why educational content is so important.

Alexis and Dean Idot
Credit: Mashable composite: Zooey Liao; Instagram/ Getty Images

How did you guys come up with the specific concept for your videos?

Dean: Alexis is pretty active on social media. I’m not at all. I use LinkedIn for work, and my company manages that for me. And I use Twitter or X for my investment news feeds and data. That’s about the extent of my usage of social media. 

She always asks me questions, just as a couple, about finance stuff. It’s just how we talk. We sit down and we hang out, and it’s always questions. Right after the mini financial crisis in ’23, I’m immersed in that because I’m a banker. So all the bankers out there were heavily immersed in that for those two to three weeks of chaos. The long story short is: she asked me to explain it. She wanted to know what was going on because the average person didn’t understand what it means when banks go out of business. Why? So she asked me a question, and then I explained, and that was the first video.

Were you uncomfortable at all with the idea of answering her questions on camera?

Dean: No. I didn’t realize it was being recorded [at first]. I’m not uncomfortable at all. And fun fact: I don’t watch any of my videos. I would only watch the videos in case there are editing requirements or some comment that says I said something untoward or wrong. But I never watch my videos.

Do you edit them? 

Dean: Alexis does everything. She comes from digital marketing and is an entrepreneur. She had her own business for many years, all of which was marketed and driven by social media. I have no idea what happens after she takes the video.

Alexis: I film everything in one take. If it’s for a brand [and] if a brand requires edits, I will do it in CapCut, but all of our organic content is filmed in one take, and then I post it directly on TikTok. I just add a little title to it through the TikTok app, but I don’t edit our content whatsoever.

Dean: If you see the setup here, you’d know there is no production here. I don’t even have a mic. It’s her iPhone.

Alexis: Everything’s done on the iPhone camera.

Dean: Not even a stick or a stand. She just holds it. And that has not changed since day one.

Why do you think viewers gravitate toward that?

Dean: Authenticity. What you see is what you get,

Alexis: [We get] comments [about how people] feel like they’re sitting at a table with us.

Where do you both come up with inspiration or ideas for your videos? 

Dean: I’m very active in paying attention to news, to the economy, to markets. I’m an active trader — not by trade, but for personal reasons. I’m literally sitting here every morning before the market opens, listening to news all day until it closes. I’m a news hound. That’s just how I am. What I do is interpret the news for the masses on social media who don’t want to read or don’t have the time to read. So the content ideas just come organically. If it’s not a brand deal, it’s usually organic. It’s something interesting out there that I want to talk about, or she thinks it’s really interesting that people don’t understand.

Alexis: There’ll be a headline in the news, and Dean will be going off about it. And it makes perfect sense to Dean, but I have no idea what’s going on. I might ask questions that seem elementary to him, but I kind of represent our audience in a way that not everyone understands what’s going on. So sometimes it’ll be me asking questions, just trying to get an explanation on current events. 

Can you sort of walk me through how you go from ideation to publishing a post?

Alexis: I ask Dean the question, [and] I’ll get the content that I need. And then, as far as posting it, sometimes I will backlog content. We’ll film a bunch of stuff in one day. Dean’s really busy, so we’ll have filming days where we do a bunch of content in one day. If it’s a hot topic, we’ll film it that morning and post it right away. 

Mashable Trend Report

When I’m ready to post that piece of content, I upload it to the TikTok app. It’s very important to use hashtags on TikTok. Not so much Instagram, but cataloging your content on TikTok is really important. So I make sure that I use as many relevant hashtags as I can think of. Some of our favorites are #FinancialLiteracy and #FinancialEducation. Dean doesn’t know anything about hashtag strategy.

Dean: No idea.

Alexis: I make sure that I always hashtag relevant hashtags. Then I tag the location, and then we upload it. I don’t keep anything in the drafts; I just keep it like on my camera roll in my phone. And it’s really straightforward and simple. There really isn’t much of a process other than we film.

How many videos are you posting on average every day?

Alexis: On average, we post three times a week. One thing that we just started is Financial Literacy Fridays. I can film a bunch of content that’s not time sensitive with Dean and then keep it as a backlog. That way, I’m posting every single Friday, no matter what. We just did the first one, and we got almost a million views. So it seems to be well-received. And that’s hopefully a new cadence for us moving forward. 

When did you realize you could generate a significant income from this? 

Dean: The first video [we posted] went viral, but I didn’t really pay attention to it at all. I would say six months into it.

Alexis: Dean thought it was kind of a joke in the beginning, but we got a million views on the first video, and then that same week, we got something with like three or four million views, and nothing was getting under 300,000 [views]. And I knew that was a really big deal. [It took us] two months to get into the TikTok Creator Fund.

Dean: They started paying out really well on engagement. Once it passed five figures in revenue, that’s when I [said], “Wait a minute, this is bonafide. This is not a joke.”

You were getting five figures from the Creator Fund?

Alexis: No, not [at first]. Only this year. 

Dean: In the beginning, we had small brand deals here and there, what I call “funny money.” It’s gas money.

Alexis: But we’re really only two-and-a-half years in, and to see how much we’ve grown has been really kind of crazy.

Which monetization methods do you use? 

Alexis: The Creator Fund. There is something called Specialized Rewards on TikTok, where they reward creators who make what they call educational learning content. And we’ve been selected to be in that program as well. So that’s been really great for brand deals. 

Dean: We have a couple of longer-term contracts, but again, we’re very picky about that, too, about the brand deals. I view this business not just as about making as much money as I can as fast as I can; it’s more about helping the community… I would never do a brand deal if it’s a product that I wouldn’t use or that I haven’t used already. I’m very, very strict about that.

Alexis: Even if it’s a product that I think is a good product. If Dean’s like, “It’s a good product, but it’s not something that fits my lifestyle,” we still won’t. It has to be something that we personally use and enjoy. 

Is that mostly brands coming to you? 

Dean: No, they all come to us. 

Alexis: I have a manager, but I would say 98 percent of everything is inbound to us. 

How quickly you became successful on TikTok is quite an anomaly, right? It’s not that common to have your first video go viral. Was this your first attempt at virality?

Dean: It wasn’t even a try.

Alexis: I had other channels.

Dean: She thought it was funny.

Alexis: Well, no, I had a small business that I would advertise on Instagram that I’ve spent years building, and I never had the success that I had with this channel. 

[For this project],I filmed one video and I introduced myself and [said] what I was gonna be posting. And then that same night, I posted the very first question I asked Dean, and out of the gate, it did really well. It wasn’t an idea that I had recycled and had to try multiple times. It just worked the first time. I think it was a combination of the content style and the topic that we picked. It was such a hot topic at that time. I’ve realized that the content that does the best on our channel sometimes is a hot topic. Being on it with what’s relevant works really well with TikTok. The algorithm seems to like it. 

What advice would you give to someone who’s starting out in content creation and is looking to build a career or grow their following similar to yours?

Dean: What you see is what you get. I’m not trying. I’m not doing anything that isn’t normally me. 

Alexis: What Dean just said. When people ask me, “How can we replicate what you guys have done?” I just tell people to be themselves. When you’re creating content, if you’re not filming with a partner in the way that we are, I tell people to act like you’re on FaceTime with your friends. TikTok feels like a little community, a small family, people that you talk with every day, and engage with your comments. Film as if you’re talking to your friend on FaceTime. 



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Waiting in line for a midnight game release or scrambling to find a sold-out gaming headset at your favorite electronics store feels far less appealing in a world where instant digital access is just a click away. Today’s gamers are done chasing physical stock and juggling dozens of store accounts. Instead, they’re seeking out a more streamlined, cost-effective way to buy gear and titles, often without ever leaving their chair.

Digital marketplaces have exploded in popularity among gaming enthusiasts aiming to make every dollar and minute count. For those new to this shift, sites like Eneba.com have made a strong mark by combining everything from rare peripherals to discounted digital game codes in one convenient space. With fierce competition driving prices lower and generous selection on offer, these platforms now rival traditional game shops, yet offer far more flexibility, whether it’s a late-night shopping urge or a flash sale on the latest blockbuster.

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The Big Draws: Price, Speed, and Selection

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Amanz/Unsplash

What drives players to trust digital marketplaces over the tried and tested big-name stores? Savings are a major factor: prices for both hardware and digital game keys can dip well below official retailer listings. Flash sales or limited-time discounts mean buyers can seize deals at odd hours, no camping out, no extra fees for international shipping.

But it’s not just the cost that wins people over. Instant access is non-negotiable for gamers who want a new release the second it drops, or need to replace a mic in time for tonight’s match. Digital codes and direct-to-home shipping let buyers skip wait times entirely. On top of that, curated stock and real-time availability mean less hunting around, which saves effort. Every moment not spent scrolling is one more minute playing.

Security and Transparency Keep Gamers Loyal

A son and dad gaming

Skepticism around digital goods is only natural when you’re entering codes worth fifty or even a hundred dollars. Digital marketplaces have worked hard to build trust by publishing clear security guarantees, requiring third-party merchant verification, and setting strict standards for compliance and sourcing. Buyers know that when issues arise, support teams are ready to step in, a far cry from faceless classified ads or auction sites.

Transparency is a dealbreaker for many. Region-locked codes? Out-of-stock hardware? Sites that label everything clearly and show purchase history on demand find it easier to retain picky shoppers. Gamers remember who wasted their time and who made the experience simple.

Flexibility for Modern Gaming Lifestyles

Physical games and hardware still have a place, but the digital approach caters to how gamers actually live and play. Swapping consoles with friends, jumping from PC to mobile, and redeeming codes while traveling all become easier with digital ownership. The global reach of digital marketplaces makes it possible to find rare or region-specific gear and content not available locally.

With the cycle of new releases and old favorites never ending, staying ahead of the next hot thing is less stressful when your shopping list can be satisfied in one place. Digital marketplaces like Eneba, offering deals on all things digital, continue to reshape how players discover, buy, and enjoy what they love most.

#Savvy #Gamers #Embracing #Digital #Marketplaces #Gear #GamesAndroid Gaming,console gaming,desktop gaming

Wednesday was a big day for the tech industry with Meta, Google, Amazon and Microsoft all reporting earnings at the same time in the afternoon. Out of the four, though, Meta was the clear loser with its shares down more than 7% even though revenue increased 33% this past quarter, the company’s fastest since 2021.

It’s probably because the company upped its already outrageous spending expectations for the year. Meta said that 2026 capital expenditures would be at least $10 billion more than expected and could top $145 billion. While emphasizing his “confidence in this investment,” CEO Mark Zuckerberg said that most of this increase was due to “higher component costs, particularly memory pricing.”

The AI boom has led to an unprecedented data center buildout that has constrained the global memory chip supply and increased prices for these valuable chips. The result has been a global memory crisis that has impacted not only Meta and the rest of the AI industry but also caused the prices of consumer electronics like laptops and smartphones to soar.

Meta’s $145 billion is a dramatic increase from the $72 billion capital expenditure it recorded just last year, and Zuckerberg is betting it all on an AI turnaround effort.

Meta has been left behind in the AI race as industry rivals like Google have soared past. Roughly 10 months ago, Zuckerberg acknowledged the situation and announced a major catch-up effort that saw him commit billions upon billions of dollars to research and development, and to poach talent from all over the industry, including bringing in Scale AI’s founder Alexandr Wang to lead the new Meta Superintelligence Labs AI division.

Many have been reasonably nervous about this commitment, considering that the company’s latest big bet in emerging tech, the Metaverse, has flopped dramatically. In Wednesday’s earnings report, Meta said that the Reality Labs division, which had helmed the Metaverse efforts, notched an operating loss of more than $4 billion, while only cashing in $402 million in sales. That adds to the whopping $80 billion and more the division has lost in the past six years.

But experts are somewhat more hopeful about the AI bet because, earlier this month, the tech giant debuted the first fruits of that investment with the AI model Muse Spark, a proprietary model that the company plans to open-source in the future. It’s a step in the right direction, but Meta still has to do more before it can confidently say the catch-up effort is successful.

“This was the first release from Meta Superintelligence Labs, and it shows that our work is on track to build a leading lab,” Zuckerberg assured investors in the company’s earnings call. “Now that we have a strong model, we can develop more novel products as well.”

Those novel products will include two agents, one for personal and the other for business uses, according to Zuckerberg.

“We’re already testing an early version of business AIs and weekly conversations have grown 10x since the start of this year,” Zuckerberg said.

One way that AI is clearly showing up to benefit Meta is internally. Meta CFO Susan Li said that over half a billion users weekly on Facebook and Instagram each are now watching videos translated and dubbed by AI. The company is also incorporating the new AI model into parts of its core business, like ads, and particularly into its recommendation system. The goal is to have the AI hyper-personalize feeds for users.

“Since our recommendation systems are operating at such large scale, we’ll phase in this new research and technology over time,” Zuckerberg said. “But the trend over the last few years seems clear that we are seeing an increasing return on the amount that we can improve engagement for people and value for advertisers.”

AI is also taking over internally at Meta. The company is laying off 10% of its workforce and reportedly offering voluntary buyouts to 7% of its U.S. staff, in what seems to follow a purportedly AI-driven trend that has taken Silicon Valley by storm.

On the call, executives wouldn’t say if the layoffs had to do with automation of jobs, but Li did say that a “leaner operating model” would help “offset the substantial investments we’re making.”

#Meta #Spend #Billion #Year #DueArtificial intelligence,Mark Zuckerberg,Meta">Meta Could Spend 5 Billion This Year Due to AI Wednesday was a big day for the tech industry with Meta, Google, Amazon and Microsoft all reporting earnings at the same time in the afternoon. Out of the four, though, Meta was the clear loser with its shares down more than 7% even though revenue increased 33% this past quarter, the company’s fastest since 2021. It’s probably because the company upped its already outrageous spending expectations for the year. Meta said that 2026 capital expenditures would be at least billion more than expected and could top 5 billion. While emphasizing his “confidence in this investment,” CEO Mark Zuckerberg said that most of this increase was due to “higher component costs, particularly memory pricing.” The AI boom has led to an unprecedented data center buildout that has constrained the global memory chip supply and increased prices for these valuable chips. The result has been a global memory crisis that has impacted not only Meta and the rest of the AI industry but also caused the prices of consumer electronics like laptops and smartphones to soar. Meta’s 5 billion is a dramatic increase from the billion capital expenditure it recorded just last year, and Zuckerberg is betting it all on an AI turnaround effort. Meta has been left behind in the AI race as industry rivals like Google have soared past. Roughly 10 months ago, Zuckerberg acknowledged the situation and announced a major catch-up effort that saw him commit billions upon billions of dollars to research and development, and to poach talent from all over the industry, including bringing in Scale AI’s founder Alexandr Wang to lead the new Meta Superintelligence Labs AI division. Many have been reasonably nervous about this commitment, considering that the company’s latest big bet in emerging tech, the Metaverse, has flopped dramatically. In Wednesday’s earnings report, Meta said that the Reality Labs division, which had helmed the Metaverse efforts, notched an operating loss of more than billion, while only cashing in 2 million in sales. That adds to the whopping billion and more the division has lost in the past six years. But experts are somewhat more hopeful about the AI bet because, earlier this month, the tech giant debuted the first fruits of that investment with the AI model Muse Spark, a proprietary model that the company plans to open-source in the future. It’s a step in the right direction, but Meta still has to do more before it can confidently say the catch-up effort is successful. “This was the first release from Meta Superintelligence Labs, and it shows that our work is on track to build a leading lab,” Zuckerberg assured investors in the company’s earnings call. “Now that we have a strong model, we can develop more novel products as well.” Those novel products will include two agents, one for personal and the other for business uses, according to Zuckerberg. “We’re already testing an early version of business AIs and weekly conversations have grown 10x since the start of this year,” Zuckerberg said. One way that AI is clearly showing up to benefit Meta is internally. Meta CFO Susan Li said that over half a billion users weekly on Facebook and Instagram each are now watching videos translated and dubbed by AI. The company is also incorporating the new AI model into parts of its core business, like ads, and particularly into its recommendation system. The goal is to have the AI hyper-personalize feeds for users. “Since our recommendation systems are operating at such large scale, we’ll phase in this new research and technology over time,” Zuckerberg said. “But the trend over the last few years seems clear that we are seeing an increasing return on the amount that we can improve engagement for people and value for advertisers.” AI is also taking over internally at Meta. The company is laying off 10% of its workforce and reportedly offering voluntary buyouts to 7% of its U.S. staff, in what seems to follow a purportedly AI-driven trend that has taken Silicon Valley by storm. On the call, executives wouldn’t say if the layoffs had to do with automation of jobs, but Li did say that a “leaner operating model” would help “offset the substantial investments we’re making.” #Meta #Spend #Billion #Year #DueArtificial intelligence,Mark Zuckerberg,Meta

fastest since 2021.

It’s probably because the company upped its already outrageous spending expectations for the year. Meta said that 2026 capital expenditures would be at least $10 billion more than expected and could top $145 billion. While emphasizing his “confidence in this investment,” CEO Mark Zuckerberg said that most of this increase was due to “higher component costs, particularly memory pricing.”

The AI boom has led to an unprecedented data center buildout that has constrained the global memory chip supply and increased prices for these valuable chips. The result has been a global memory crisis that has impacted not only Meta and the rest of the AI industry but also caused the prices of consumer electronics like laptops and smartphones to soar.

Meta’s $145 billion is a dramatic increase from the $72 billion capital expenditure it recorded just last year, and Zuckerberg is betting it all on an AI turnaround effort.

Meta has been left behind in the AI race as industry rivals like Google have soared past. Roughly 10 months ago, Zuckerberg acknowledged the situation and announced a major catch-up effort that saw him commit billions upon billions of dollars to research and development, and to poach talent from all over the industry, including bringing in Scale AI’s founder Alexandr Wang to lead the new Meta Superintelligence Labs AI division.

Many have been reasonably nervous about this commitment, considering that the company’s latest big bet in emerging tech, the Metaverse, has flopped dramatically. In Wednesday’s earnings report, Meta said that the Reality Labs division, which had helmed the Metaverse efforts, notched an operating loss of more than $4 billion, while only cashing in $402 million in sales. That adds to the whopping $80 billion and more the division has lost in the past six years.

But experts are somewhat more hopeful about the AI bet because, earlier this month, the tech giant debuted the first fruits of that investment with the AI model Muse Spark, a proprietary model that the company plans to open-source in the future. It’s a step in the right direction, but Meta still has to do more before it can confidently say the catch-up effort is successful.

“This was the first release from Meta Superintelligence Labs, and it shows that our work is on track to build a leading lab,” Zuckerberg assured investors in the company’s earnings call. “Now that we have a strong model, we can develop more novel products as well.”

Those novel products will include two agents, one for personal and the other for business uses, according to Zuckerberg.

“We’re already testing an early version of business AIs and weekly conversations have grown 10x since the start of this year,” Zuckerberg said.

One way that AI is clearly showing up to benefit Meta is internally. Meta CFO Susan Li said that over half a billion users weekly on Facebook and Instagram each are now watching videos translated and dubbed by AI. The company is also incorporating the new AI model into parts of its core business, like ads, and particularly into its recommendation system. The goal is to have the AI hyper-personalize feeds for users.

“Since our recommendation systems are operating at such large scale, we’ll phase in this new research and technology over time,” Zuckerberg said. “But the trend over the last few years seems clear that we are seeing an increasing return on the amount that we can improve engagement for people and value for advertisers.”

AI is also taking over internally at Meta. The company is laying off 10% of its workforce and reportedly offering voluntary buyouts to 7% of its U.S. staff, in what seems to follow a purportedly AI-driven trend that has taken Silicon Valley by storm.

On the call, executives wouldn’t say if the layoffs had to do with automation of jobs, but Li did say that a “leaner operating model” would help “offset the substantial investments we’re making.”

#Meta #Spend #Billion #Year #DueArtificial intelligence,Mark Zuckerberg,Meta">Meta Could Spend $145 Billion This Year Due to AIMeta Could Spend $145 Billion This Year Due to AI Wednesday was a big day for the tech industry with Meta, Google, Amazon and Microsoft all reporting earnings at the same time in the afternoon. Out of the four, though, Meta was the clear loser with its shares down more than 7% even though revenue increased 33% this past quarter, the company’s fastest since 2021. It’s probably because the company upped its already outrageous spending expectations for the year. Meta said that 2026 capital expenditures would be at least $10 billion more than expected and could top $145 billion. While emphasizing his “confidence in this investment,” CEO Mark Zuckerberg said that most of this increase was due to “higher component costs, particularly memory pricing.” The AI boom has led to an unprecedented data center buildout that has constrained the global memory chip supply and increased prices for these valuable chips. The result has been a global memory crisis that has impacted not only Meta and the rest of the AI industry but also caused the prices of consumer electronics like laptops and smartphones to soar. Meta’s $145 billion is a dramatic increase from the $72 billion capital expenditure it recorded just last year, and Zuckerberg is betting it all on an AI turnaround effort. Meta has been left behind in the AI race as industry rivals like Google have soared past. Roughly 10 months ago, Zuckerberg acknowledged the situation and announced a major catch-up effort that saw him commit billions upon billions of dollars to research and development, and to poach talent from all over the industry, including bringing in Scale AI’s founder Alexandr Wang to lead the new Meta Superintelligence Labs AI division. Many have been reasonably nervous about this commitment, considering that the company’s latest big bet in emerging tech, the Metaverse, has flopped dramatically. In Wednesday’s earnings report, Meta said that the Reality Labs division, which had helmed the Metaverse efforts, notched an operating loss of more than $4 billion, while only cashing in $402 million in sales. That adds to the whopping $80 billion and more the division has lost in the past six years. But experts are somewhat more hopeful about the AI bet because, earlier this month, the tech giant debuted the first fruits of that investment with the AI model Muse Spark, a proprietary model that the company plans to open-source in the future. It’s a step in the right direction, but Meta still has to do more before it can confidently say the catch-up effort is successful. “This was the first release from Meta Superintelligence Labs, and it shows that our work is on track to build a leading lab,” Zuckerberg assured investors in the company’s earnings call. “Now that we have a strong model, we can develop more novel products as well.” Those novel products will include two agents, one for personal and the other for business uses, according to Zuckerberg. “We’re already testing an early version of business AIs and weekly conversations have grown 10x since the start of this year,” Zuckerberg said. One way that AI is clearly showing up to benefit Meta is internally. Meta CFO Susan Li said that over half a billion users weekly on Facebook and Instagram each are now watching videos translated and dubbed by AI. The company is also incorporating the new AI model into parts of its core business, like ads, and particularly into its recommendation system. The goal is to have the AI hyper-personalize feeds for users. “Since our recommendation systems are operating at such large scale, we’ll phase in this new research and technology over time,” Zuckerberg said. “But the trend over the last few years seems clear that we are seeing an increasing return on the amount that we can improve engagement for people and value for advertisers.” AI is also taking over internally at Meta. The company is laying off 10% of its workforce and reportedly offering voluntary buyouts to 7% of its U.S. staff, in what seems to follow a purportedly AI-driven trend that has taken Silicon Valley by storm. On the call, executives wouldn’t say if the layoffs had to do with automation of jobs, but Li did say that a “leaner operating model” would help “offset the substantial investments we’re making.” #Meta #Spend #Billion #Year #DueArtificial intelligence,Mark Zuckerberg,Meta

Wednesday was a big day for the tech industry with Meta, Google, Amazon and Microsoft all reporting earnings at the same time in the afternoon. Out of the four, though, Meta was the clear loser with its shares down more than 7% even though revenue increased 33% this past quarter, the company’s fastest since 2021.

It’s probably because the company upped its already outrageous spending expectations for the year. Meta said that 2026 capital expenditures would be at least $10 billion more than expected and could top $145 billion. While emphasizing his “confidence in this investment,” CEO Mark Zuckerberg said that most of this increase was due to “higher component costs, particularly memory pricing.”

The AI boom has led to an unprecedented data center buildout that has constrained the global memory chip supply and increased prices for these valuable chips. The result has been a global memory crisis that has impacted not only Meta and the rest of the AI industry but also caused the prices of consumer electronics like laptops and smartphones to soar.

Meta’s $145 billion is a dramatic increase from the $72 billion capital expenditure it recorded just last year, and Zuckerberg is betting it all on an AI turnaround effort.

Meta has been left behind in the AI race as industry rivals like Google have soared past. Roughly 10 months ago, Zuckerberg acknowledged the situation and announced a major catch-up effort that saw him commit billions upon billions of dollars to research and development, and to poach talent from all over the industry, including bringing in Scale AI’s founder Alexandr Wang to lead the new Meta Superintelligence Labs AI division.

Many have been reasonably nervous about this commitment, considering that the company’s latest big bet in emerging tech, the Metaverse, has flopped dramatically. In Wednesday’s earnings report, Meta said that the Reality Labs division, which had helmed the Metaverse efforts, notched an operating loss of more than $4 billion, while only cashing in $402 million in sales. That adds to the whopping $80 billion and more the division has lost in the past six years.

But experts are somewhat more hopeful about the AI bet because, earlier this month, the tech giant debuted the first fruits of that investment with the AI model Muse Spark, a proprietary model that the company plans to open-source in the future. It’s a step in the right direction, but Meta still has to do more before it can confidently say the catch-up effort is successful.

“This was the first release from Meta Superintelligence Labs, and it shows that our work is on track to build a leading lab,” Zuckerberg assured investors in the company’s earnings call. “Now that we have a strong model, we can develop more novel products as well.”

Those novel products will include two agents, one for personal and the other for business uses, according to Zuckerberg.

“We’re already testing an early version of business AIs and weekly conversations have grown 10x since the start of this year,” Zuckerberg said.

One way that AI is clearly showing up to benefit Meta is internally. Meta CFO Susan Li said that over half a billion users weekly on Facebook and Instagram each are now watching videos translated and dubbed by AI. The company is also incorporating the new AI model into parts of its core business, like ads, and particularly into its recommendation system. The goal is to have the AI hyper-personalize feeds for users.

“Since our recommendation systems are operating at such large scale, we’ll phase in this new research and technology over time,” Zuckerberg said. “But the trend over the last few years seems clear that we are seeing an increasing return on the amount that we can improve engagement for people and value for advertisers.”

AI is also taking over internally at Meta. The company is laying off 10% of its workforce and reportedly offering voluntary buyouts to 7% of its U.S. staff, in what seems to follow a purportedly AI-driven trend that has taken Silicon Valley by storm.

On the call, executives wouldn’t say if the layoffs had to do with automation of jobs, but Li did say that a “leaner operating model” would help “offset the substantial investments we’re making.”

#Meta #Spend #Billion #Year #DueArtificial intelligence,Mark Zuckerberg,Meta

Elon Musk returned to the witness stand on Wednesday to continue telling his side of the story in his legal battle against OpenAI and its CEO Sam Altman. Under cross-examination from OpenAI’s lawyers, Musk was pressed on all the ways he tried to squeeze the organization over a 2017 power struggle that he ultimately lost. Around this time, Musk tried to hire away OpenAI researchers and stopped sending it funding he had previously promised, according to emails presented as evidence in the case.

As the cross-examination began, tension rippled through the courtroom. Judge Yvonne Gonzalez Rogers started the day by reprimanding someone in the gallery for taking a picture of Musk. OpenAI president and cofounder Greg Brockman sat behind his lawyers with a yellow legal pad in his lap, giving Musk a cold stare as he testified. Musk grew visibly frustrated on the witness stand, pausing frequently to tell OpenAI’s lawyer, William Savitt, that he saw his questions as misleading. Meanwhile, Savitt’s cross-examination was derailed by objections, technical issues, and Musk continuously claiming he doesn’t recall key details of OpenAI’s history.

Savitt showed the courtroom emails from September 2017 between Musk, Brockman, and researcher Ilya Sutskever discussing the formation of what would become OpenAI’s for-profit arm. In the thread, Musk demanded the right to choose four members of its board of directors, giving him more voting power than his cofounders, who would be left with three in total. “I would unequivocally have initial control of the company, but this will change quickly,” said Musk in one message. Sutskever wrote back rejecting the idea because he said he feared it would give Musk too much power.

Months before these negotiations started, Musk had halted payments to OpenAI, which was particularly difficult for the organization because he was then its main source of funding. Since 2016, Musk had been sending $5 million payments to OpenAI quarterly as part of a broader $1 billion pledge he made at the organization’s launch. But in the spring of 2017, he stopped sending the money. In another email from August 2017, the head of Musk’s family office, Jared Birchall, asked Musk if he should continue withholding it. Musk responded simply, “Yes.”

Around the time Musk lost the power struggle, emails show that he held discussions with executives at Tesla and Neuralink, his brain-computer interface company, about hiring OpenAI employees. At the time, Musk was still a board member of OpenAI.

Musk sent an email to a Tesla vice president in June 2017 about hiring an early OpenAI researcher, Andrej Karpathy. “Just talked to Andrej and he accepted as joining as director of Tesla Vision,” Musk wrote. “Andrej is arguably the #2 guy in the world in computer vision … The openai guys are gonna want to kill me, but it had to be done.”

On the stand, Musk argued that Karpathy was already interested in leaving OpenAI when he tried to recruit him to Tesla. “Andrej had made his decision. If he’s going to leave OpenAI, he might as well work at Tesla,” Musk said.

In October 2017, Musk also wrote to Ben Rapoport, a cofounder of Neuralink. “Hire independently or directly from OpenAI,” said Musk. “I have no problem if you pitch people at OpenAI to work at Neuralink.”

When pressed about this by Savitt, Musk argued that it would have been illegal for him not to allow Tesla and Neuralink to hire from OpenAI. “It’s illegal to restrict employment. It would be illegal to say you can’t employ people from OpenAI. You can’t have some cabal that stops people from working at the company they want to work at,” Musk said.

#Elon #Musk #Squeezed #OpenAI #Gonna #Killmodel behavior,artificial intelligence,elon musk,openai,sam altman,lawsuits">How Elon Musk Squeezed OpenAI: They ‘Are Gonna Want to Kill Me’Elon Musk returned to the witness stand on Wednesday to continue telling his side of the story in his legal battle against OpenAI and its CEO Sam Altman. Under cross-examination from OpenAI’s lawyers, Musk was pressed on all the ways he tried to squeeze the organization over a 2017 power struggle that he ultimately lost. Around this time, Musk tried to hire away OpenAI researchers and stopped sending it funding he had previously promised, according to emails presented as evidence in the case.As the cross-examination began, tension rippled through the courtroom. Judge Yvonne Gonzalez Rogers started the day by reprimanding someone in the gallery for taking a picture of Musk. OpenAI president and cofounder Greg Brockman sat behind his lawyers with a yellow legal pad in his lap, giving Musk a cold stare as he testified. Musk grew visibly frustrated on the witness stand, pausing frequently to tell OpenAI’s lawyer, William Savitt, that he saw his questions as misleading. Meanwhile, Savitt’s cross-examination was derailed by objections, technical issues, and Musk continuously claiming he doesn’t recall key details of OpenAI’s history.Savitt showed the courtroom emails from September 2017 between Musk, Brockman, and researcher Ilya Sutskever discussing the formation of what would become OpenAI’s for-profit arm. In the thread, Musk demanded the right to choose four members of its board of directors, giving him more voting power than his cofounders, who would be left with three in total. “I would unequivocally have initial control of the company, but this will change quickly,” said Musk in one message. Sutskever wrote back rejecting the idea because he said he feared it would give Musk too much power.Months before these negotiations started, Musk had halted payments to OpenAI, which was particularly difficult for the organization because he was then its main source of funding. Since 2016, Musk had been sending million payments to OpenAI quarterly as part of a broader billion pledge he made at the organization’s launch. But in the spring of 2017, he stopped sending the money. In another email from August 2017, the head of Musk’s family office, Jared Birchall, asked Musk if he should continue withholding it. Musk responded simply, “Yes.”Around the time Musk lost the power struggle, emails show that he held discussions with executives at Tesla and Neuralink, his brain-computer interface company, about hiring OpenAI employees. At the time, Musk was still a board member of OpenAI.Musk sent an email to a Tesla vice president in June 2017 about hiring an early OpenAI researcher, Andrej Karpathy. “Just talked to Andrej and he accepted as joining as director of Tesla Vision,” Musk wrote. “Andrej is arguably the #2 guy in the world in computer vision … The openai guys are gonna want to kill me, but it had to be done.”On the stand, Musk argued that Karpathy was already interested in leaving OpenAI when he tried to recruit him to Tesla. “Andrej had made his decision. If he’s going to leave OpenAI, he might as well work at Tesla,” Musk said.In October 2017, Musk also wrote to Ben Rapoport, a cofounder of Neuralink. “Hire independently or directly from OpenAI,” said Musk. “I have no problem if you pitch people at OpenAI to work at Neuralink.”When pressed about this by Savitt, Musk argued that it would have been illegal for him not to allow Tesla and Neuralink to hire from OpenAI. “It’s illegal to restrict employment. It would be illegal to say you can’t employ people from OpenAI. You can’t have some cabal that stops people from working at the company they want to work at,” Musk said.#Elon #Musk #Squeezed #OpenAI #Gonna #Killmodel behavior,artificial intelligence,elon musk,openai,sam altman,lawsuits

his side of the story in his legal battle against OpenAI and its CEO Sam Altman. Under cross-examination from OpenAI’s lawyers, Musk was pressed on all the ways he tried to squeeze the organization over a 2017 power struggle that he ultimately lost. Around this time, Musk tried to hire away OpenAI researchers and stopped sending it funding he had previously promised, according to emails presented as evidence in the case.

As the cross-examination began, tension rippled through the courtroom. Judge Yvonne Gonzalez Rogers started the day by reprimanding someone in the gallery for taking a picture of Musk. OpenAI president and cofounder Greg Brockman sat behind his lawyers with a yellow legal pad in his lap, giving Musk a cold stare as he testified. Musk grew visibly frustrated on the witness stand, pausing frequently to tell OpenAI’s lawyer, William Savitt, that he saw his questions as misleading. Meanwhile, Savitt’s cross-examination was derailed by objections, technical issues, and Musk continuously claiming he doesn’t recall key details of OpenAI’s history.

Savitt showed the courtroom emails from September 2017 between Musk, Brockman, and researcher Ilya Sutskever discussing the formation of what would become OpenAI’s for-profit arm. In the thread, Musk demanded the right to choose four members of its board of directors, giving him more voting power than his cofounders, who would be left with three in total. “I would unequivocally have initial control of the company, but this will change quickly,” said Musk in one message. Sutskever wrote back rejecting the idea because he said he feared it would give Musk too much power.

Months before these negotiations started, Musk had halted payments to OpenAI, which was particularly difficult for the organization because he was then its main source of funding. Since 2016, Musk had been sending $5 million payments to OpenAI quarterly as part of a broader $1 billion pledge he made at the organization’s launch. But in the spring of 2017, he stopped sending the money. In another email from August 2017, the head of Musk’s family office, Jared Birchall, asked Musk if he should continue withholding it. Musk responded simply, “Yes.”

Around the time Musk lost the power struggle, emails show that he held discussions with executives at Tesla and Neuralink, his brain-computer interface company, about hiring OpenAI employees. At the time, Musk was still a board member of OpenAI.

Musk sent an email to a Tesla vice president in June 2017 about hiring an early OpenAI researcher, Andrej Karpathy. “Just talked to Andrej and he accepted as joining as director of Tesla Vision,” Musk wrote. “Andrej is arguably the #2 guy in the world in computer vision … The openai guys are gonna want to kill me, but it had to be done.”

On the stand, Musk argued that Karpathy was already interested in leaving OpenAI when he tried to recruit him to Tesla. “Andrej had made his decision. If he’s going to leave OpenAI, he might as well work at Tesla,” Musk said.

In October 2017, Musk also wrote to Ben Rapoport, a cofounder of Neuralink. “Hire independently or directly from OpenAI,” said Musk. “I have no problem if you pitch people at OpenAI to work at Neuralink.”

When pressed about this by Savitt, Musk argued that it would have been illegal for him not to allow Tesla and Neuralink to hire from OpenAI. “It’s illegal to restrict employment. It would be illegal to say you can’t employ people from OpenAI. You can’t have some cabal that stops people from working at the company they want to work at,” Musk said.

#Elon #Musk #Squeezed #OpenAI #Gonna #Killmodel behavior,artificial intelligence,elon musk,openai,sam altman,lawsuits">How Elon Musk Squeezed OpenAI: They ‘Are Gonna Want to Kill Me’

Elon Musk returned to the witness stand on Wednesday to continue telling his side of the story in his legal battle against OpenAI and its CEO Sam Altman. Under cross-examination from OpenAI’s lawyers, Musk was pressed on all the ways he tried to squeeze the organization over a 2017 power struggle that he ultimately lost. Around this time, Musk tried to hire away OpenAI researchers and stopped sending it funding he had previously promised, according to emails presented as evidence in the case.

As the cross-examination began, tension rippled through the courtroom. Judge Yvonne Gonzalez Rogers started the day by reprimanding someone in the gallery for taking a picture of Musk. OpenAI president and cofounder Greg Brockman sat behind his lawyers with a yellow legal pad in his lap, giving Musk a cold stare as he testified. Musk grew visibly frustrated on the witness stand, pausing frequently to tell OpenAI’s lawyer, William Savitt, that he saw his questions as misleading. Meanwhile, Savitt’s cross-examination was derailed by objections, technical issues, and Musk continuously claiming he doesn’t recall key details of OpenAI’s history.

Savitt showed the courtroom emails from September 2017 between Musk, Brockman, and researcher Ilya Sutskever discussing the formation of what would become OpenAI’s for-profit arm. In the thread, Musk demanded the right to choose four members of its board of directors, giving him more voting power than his cofounders, who would be left with three in total. “I would unequivocally have initial control of the company, but this will change quickly,” said Musk in one message. Sutskever wrote back rejecting the idea because he said he feared it would give Musk too much power.

Months before these negotiations started, Musk had halted payments to OpenAI, which was particularly difficult for the organization because he was then its main source of funding. Since 2016, Musk had been sending $5 million payments to OpenAI quarterly as part of a broader $1 billion pledge he made at the organization’s launch. But in the spring of 2017, he stopped sending the money. In another email from August 2017, the head of Musk’s family office, Jared Birchall, asked Musk if he should continue withholding it. Musk responded simply, “Yes.”

Around the time Musk lost the power struggle, emails show that he held discussions with executives at Tesla and Neuralink, his brain-computer interface company, about hiring OpenAI employees. At the time, Musk was still a board member of OpenAI.

Musk sent an email to a Tesla vice president in June 2017 about hiring an early OpenAI researcher, Andrej Karpathy. “Just talked to Andrej and he accepted as joining as director of Tesla Vision,” Musk wrote. “Andrej is arguably the #2 guy in the world in computer vision … The openai guys are gonna want to kill me, but it had to be done.”

On the stand, Musk argued that Karpathy was already interested in leaving OpenAI when he tried to recruit him to Tesla. “Andrej had made his decision. If he’s going to leave OpenAI, he might as well work at Tesla,” Musk said.

In October 2017, Musk also wrote to Ben Rapoport, a cofounder of Neuralink. “Hire independently or directly from OpenAI,” said Musk. “I have no problem if you pitch people at OpenAI to work at Neuralink.”

When pressed about this by Savitt, Musk argued that it would have been illegal for him not to allow Tesla and Neuralink to hire from OpenAI. “It’s illegal to restrict employment. It would be illegal to say you can’t employ people from OpenAI. You can’t have some cabal that stops people from working at the company they want to work at,” Musk said.

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