NVIDIA Vs. The Media ft. GamersNexus

Summary

Better Offline Podcast Summary: "NVIDIA Vs. The Media ft. GamersNexus"
Released on June 25, 2025

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Introduction

In this episode of Better Offline, host Ed Zitron engages in a candid discussion with Steve Burke from GamersNexus. The focus centers on Nvidia's evolving relationship with the media, particularly its influence over tech reviewers and the broader implications for the tech industry.

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Computex Conference Overview [03:14]

Ed and Steve kick off the conversation by reflecting on their recent attendance at Computex, Taipei's premier computer hardware and technology trade show.

• Ed Zitron [03:47]: “Computex is like a much better CES.”
• Highlights:
  • AI Dominance: This year, AI technologies overshadowed traditional consumer hardware, leading to consumer manufacturers being pushed to secondary booths.
  • Innovations Observed: Features like an AI-powered computer case and advanced cooling solutions, including immersion cooling and thermosyphons from Noctua, were prominently displayed.
  • GPU Announcements: Nvidia subtly introduced its 5060 series, while AMD unveiled details about the 9060 XT, targeting the more affordable consumer GPU segment.

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Nvidia's Pressure on Media and Reviewers [05:39]

A significant portion of the episode delves into Nvidia's interactions with tech media, focusing on alleged pressures to influence editorial content.

• Ed Zitron [05:39]: “Nvidia wanted more coverage of MFG, which is part of their DLSS technology suite.”
• Key Points:
  • MFG Technology: Multi-Frame Generation (MFG) is an AI-driven feature aimed at increasing frame rates by generating additional frames, complementing Nvidia's DLSS (Deep Learning Super Sampling).
  • Editorial Influence: Nvidia reportedly pressured reviewers to feature MFG in benchmarks, arguing it enhances performance metrics. Ed and Steve felt this was misleading as MFG can introduce visual inconsistencies.
  • Steve Burke's Observation: “Nvidia sort of buried its 5060 launch,” indicating a strategic downplay of higher-end products in favor of broader market appeal.

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Understanding Nvidia’s MFG Technology [09:02]

The discussion deepens with an analysis of MFG technology and its implications for gaming performance and visual quality.

• Ed Zitron [09:02]: “MFG interpolates frames using AI, which can result in inconsistencies and visual artifacts.”
• Insights:
  • Performance vs. Quality: While MFG boosts frame rates, it can compromise visual fidelity, causing issues like garbled text and misplaced UI elements in games.
  • User Experience: In titles like Final Fantasy, the artificial frame generation led to noticeable blurriness and interface glitches, detracting from the gaming experience.

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Nvidia's Allocation Policies and Partner Relations [22:16]

Ed sheds light on Nvidia's GPU allocation strategies and their impact on partners and the broader market.

• Ed Zitron [22:16]: “Nvidia used allocation as leverage, restricting what partners could do with their products.”
• Examples:
  • EVGA Partnership: Nvidia's top partner EVGA faced restrictions that limited creative freedoms, such as modifying power connectors, leading to public disputes and eventual severance of the partnership.
  • Market Control: With a 92% market share in consumer GPUs, Nvidia's allocation policies can stifle competition and innovation among smaller manufacturers.

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Shift Towards AI and Its Implications [26:08]

The conversation shifts to Nvidia's strategic pivot towards AI, exploring potential benefits and drawbacks.

• Ed Zitron [26:08]: “Their concentration on AI could decimate consumer GPU development, potentially harming the broader tech ecosystem.”
• Discussion Points:
  • AI as a Revenue Stream: Nvidia is heavily investing in AI technologies, aiming to capitalize on high-growth sectors like machine learning and data centers.
  • Consumer GPU Neglect: There's concern that Nvidia's focus on AI might lead to reduced resources and innovation in consumer-grade GPUs, affecting gamers and content creators.

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Impact of AI on Media and Society [33:21]

Ed and Steve address the broader societal implications of AI, particularly in media and information consumption.

• Ed Zitron [33:21]: “AI can aid in areas like medical research, but the potential for misuse and manipulation is high.”
• Key Concerns:
  • Content Manipulation: AI-generated comments and content can create misleading narratives, making it difficult to discern authentic opinions from automated or biased inputs.
  • Corporate Control: Large corporations controlling AI technologies could manipulate information flows to serve their interests, undermining public trust and media integrity.

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Challenges for New Entrants in the GPU Market [30:23]

The duo discusses the formidable barriers new companies face when attempting to enter the GPU market.

• Ed Zitron [31:39]: “New companies face immense hurdles, from securing silicon allocations to matching the investment power of established players.”
• Insights:
  • Fabrication Costs: Building or accessing fabrication facilities (fabs) requires billions in investment, making it nearly impossible for startups to compete with giants like Nvidia and AMD.
  • Intel's Struggle: Intel's foray into consumer GPUs highlights the difficulties new entrants face, despite being an established player in the CPU market.

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Nvidia’s Relationship with Cryptocurrency [44:26]

Ed touches upon Nvidia’s fluctuating stance towards cryptocurrency mining and its impact on GPU availability.

• Ed Zitron [44:26]: “Nvidia’s pendulum has swung back and forth between catering to miners and focusing on gamers.”
• Details:
  • LHR (Low Hash Rate) GPUs: Nvidia introduced LHR GPUs to deter crypto miners, aiming to make more cards available to gamers.
  • Market Dynamics: Despite these efforts, residual effects of crypto mining remain, affecting GPU supply and pricing.

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Future of AI and Ethical Considerations [35:39]

Ed shares his thoughts on the future trajectory of AI and its ethical implications for society.

• Ed Zitron [35:39]: “The integration of AI in media can lead to misleading comments and reduced trust in online interactions.”
• Ethical Concerns:
  • Manipulation Risks: AI's ability to generate convincing content poses risks of misinformation and manipulation.
  • Responsible Use: Emphasizing the need for ethical guidelines to prevent AI from being exploited by powerful corporations for biased narratives.

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Notable Quotes with Timestamps

1. Ed Zitron [07:38]: “They wanted more coverage of MFG and pressured us to include it in our benchmarks, which we felt was misleading.”
2. Ed Zitron [22:16]: “Nvidia used allocation as leverage, restricting what partners could do with their products.”
3. Ed Zitron [26:08]: “Their concentration on AI could decimate consumer GPU development, potentially harming the broader tech ecosystem.”
4. Ed Zitron [33:21]: “AI can aid in areas like medical research, but the potential for misuse and manipulation is high.”

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Conclusion

The episode offers a critical examination of Nvidia's influence over technology media and its strategic shifts towards AI. Ed and Steve highlight the tensions between corporate interests and independent media integrity, the challenges facing new market entrants, and the broader societal implications of AI integration. The discussion underscores the necessity for transparency, ethical practices, and balanced innovation to ensure a healthy tech ecosystem.

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Further Resources

• GamersNexus: Explore Steve Burke's in-depth tech reviews and analyses.
• Better Offline Website: Visit betteroffline.com for more podcast episodes, links, and resources.
• Discord & Reddit: Join the community discussions on Discord and Reddit under r/betteroffline.

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This summary captures the essence of the "NVIDIA Vs. The Media" episode, providing listeners with a comprehensive overview of the key discussions, insights, and concerns raised regarding Nvidia's role in the tech industry.

Transcript

[Ed Zitron]

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[Steve Burke]

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[Steve Burke]

Have you?

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[Ryan Seacrest]

Hello and welcome to Better Offline. I'm your host Ed Zitron and this week we're joined again by the wonderful Steve Burke of Gamers Nexus. How are you doing, Steve?

[Ed Zitron]

Doing well. How about you?

[Ryan Seacrest]

Doing great. So you were just at Computex, right?

[Ed Zitron]

Yes, yeah, we were over there for a couple weeks.

[Ryan Seacrest]

So for the listeners who don't know, because there's a fair amount you don't know every conference. So what is Computex and what makes it so important?

[Ed Zitron]

Computex is the. I think it's the largest computer hardware and computer technology trade show. So that's hosted in Taipei every year. And it's like a much better ces people may know ces and is it.

[Ryan Seacrest]

More focused on enterprise stuff or consumer stuff?

[Ed Zitron]

This year, weirdly, they AI commandeered the entire main hall. So there were a lot of pissed off consumer hardware manufacturers who were sort of evicted and driven out of the main hall and put into the lesser one with consumer hardware.

[Ryan Seacrest]

What were they even showing with the AI stuff as well?

[Ed Zitron]

I mean, one company had an AI computer case.

[Ryan Seacrest]

Oh, how did that. What's the AI doing there?

[Ed Zitron]

Absolutely no idea.

[Ryan Seacrest]

Sick. It's so cool that this is absorbed. It's also kind of brutal. That's literally absorbing space.

[Ed Zitron]

Yes.

[Ryan Seacrest]

Did you see anything cool there though? Anything you're excited about?

[Ed Zitron]

Yeah, there's a lot of cool stuff. There was some immersion cooling, which is always nice to see where they actually literally immerse the system in fluid for cooling. There was a thermosyphon from Noctua, which is just a really cool use of. It's another cooling technology. Lots of computer case and cooling solution development. And then on the GPU side, I mean, Nvidia sort of buried its 5060 launch and then AMD more formally announced the information for its 9060 XT. And both of those are sort of the slightly more affordable consumer class GPUs.

[Ryan Seacrest]

Yeah. So Nvidia also was doing some funny business with you recently. You did that wonderful video. So walk us through what happened there because they tried to big dog you, so to speak.

[Ed Zitron]

Yeah. So I mean, the Problem we had with them and we talked about was for several months there had been this. I felt sort of pressure from Nvidia with where. So Nvidia for context, for people. Nvidia sends out GP review samples. We and other reviewers are not entitled to them. That's fine, we can buy them ourselves as well. But they send out samples for product reviews. And in the past, Nvidia has been in hot water for asking another outlet called Hard Run Box to I believe the quote was or paraphrase was change your editorial direction. Yeah, and so that was several years ago.

[Ryan Seacrest]

And what did they, what did they ask them to do back then?

[Ed Zitron]

Back then it was seeking more coverage of real time ray tracing in video games, which at the time was more or less only found in any kind of meaningful performance on Nvidia hardware But also. And the reason at least we weren't ready to fully do testing for real time ray tracing yet was because it wasn't ready yet. I mean, there weren't that many games with it.

[Ryan Seacrest]

You couldn't really test it because you couldn't use it.

[Ed Zitron]

Yeah, I mean, they launched and if I remember correctly, there were actually zero games that supported this technology and the only thing available were sort of tech demos. And so anyway, that was what they wanted. Then they kind of went away, at least as far as we know publicly, didn't try to push reviewers in a particular direction with their narrative or their editorial style. And then over the last several months we were getting this pressure of basically. So we do a bunch of interviews with engineers and technical people at Nvidia and I felt they were starting to use that as a lever to be like, oh, it sure seems like you like talking to the thermal engineers. It'd be a shame if something happened to us.

[Ryan Seacrest]

And you did that very long one over with Nvidia, right? You went and kind of looked at how the thermal stuff worked.

[Ed Zitron]

Yeah, yeah, we did. I mean, they're great educational content, the engineers are awesome. And I've spent years working with mostly are in different departments or don't work there anymore to get Nvidia on the same page where I'm like, look, we're not looking for a marketing puff piece. We're looking for actual engineers who just want to talk about the stuff they make and people can learn about it. But it's not like, obviously, yes, it can support the product by nature of if it's good and the engineers explain it well, then people will like it. But the objective is not just like, come on our show and use Us as a platform to sell things. We want engineers, not marketers. Yeah. And so that was great. And the like I said lever that it became was they wanted more. Nvidia wanted more coverage of this thing called mfg, which is multi frame generation, which is something that Jensen Huang, the CEO, talks about on stage as being part of their technology suite. That is big surprise, AI accelerated that effectively multiplies the frame rate to be used as a smoothing technology. So it's stiff.

[Ryan Seacrest]

Is this different to like DLSS and things like that or is that it.

[Ed Zitron]

Is part of the DLSS or the Deep Learn super sampling technology suite. So it's sort of, it's almost like a subset of dlss.

[Ryan Seacrest]

Right. And so it basically just looks better at higher resolution. It fills in the frames. I'm guessing just trying to simplify.

[Ed Zitron]

Yeah. So yes, the simplest version of it is MFG sort of interpolates frames. So it's able to add in or insert additional, effectively artificial or generated frames, if you're trying to be charitable with it, that are not literally built by the game engine. And so the GPU is working with its own software to construct these frames and construct pixels based on what it thinks is going to happen next. And we actually tested it and there's situations where it's not bad, there's situations where it's awful like with any technology. But what it does is on a chart, if you just look at the number that comes out, the so called frame rate, or the amount of frames in a given period of time, that looks higher with this technology. But it's not measuring the same thing as something without this technology. So it's effectively you're comparing apples and oranges if you try to put real frames that are rendered in the traditional way up against these generated AI frames that are effectively guessing at what they should look like.

[Ryan Seacrest]

And do they look bad as well?

[Ed Zitron]

They can, they can look really bad. I mean we've done some testing where in some of the games it's just like text, for example, will get completely garbled text on screen. Yeah. Interface. Interface issues will draw the interface in the wrong area. You could have really bad blurry, insanely.

[Ryan Seacrest]

Bad for like any RPG of any kind or any kind of like Twitch. I don't know.

[Ed Zitron]

Yeah.

[Ryan Seacrest]

Feels like anything you'd be doing ever would be ruined by that.

[Ed Zitron]

Yeah. So there's scenarios where it works. Okay. But the RPG example you brought up, so Final Fantasy was one of the games we tested where there's just areas. I mean it just, I Personally would turn it off, it looks worse. And I'd rather have a lower quote unquote frame rate than have this sort of potential blurry mess every now and then.

[Ryan Seacrest]

So strange. Low quality as well. Just a very strange thing to push out the door.

[Ed Zitron]

Yeah. And I think sort of finish the editorial narrative thing. No, I mean, it's fine, but I'll finish that first and I'll come back to your comment you just made because that's also interesting. But on the editorial side, they wanted more coverage of MFG and we disagreed from an objective standpoint. I kind of made the case to them several times over several calls over several months of why we think it just doesn't belong on the same charts as normal benchmarking, normal objective testing. And so there's just a disagreement, which is fine. The problem came in when I felt repeatedly on various calls with the Nvidia people that they were almost sort of holding hostage the idea of working with engineers again where it's. Well, the way we're able to make this happen is by you covering things like mfg, you know, sort of that type of conversation.

[Ryan Seacrest]

Yeah. So. And they mentioned something about like budgets in, in the video, I remember.

[Ed Zitron]

Yeah. I mean there was like discussion of one of the Times specifically the statement was that this is how we can secure budget for these types of things. And like to be clear for listeners, we don't take money for interviews. Yeah. And in fact, I've paid now over five figures to visit Nvidia on numerous occasions for said interviews. Personally, like I have paid and I.

[Ryan Seacrest]

Can say this from the PR side and not work with Nvidia or anyone associated got firewall that it's like no one talks about budgets. No one is like, oh, I can't visit a journalist due to budget. And certainly not Nvidia, a company that had $39 billion, I believe in revenue just from the center portion last quarter.

[Ed Zitron]

Kind of farcical multi trillion dollar market cap. I think if I try to take devil's advocate, maybe there's some internal budgeting, whatever, like the marketing department needs to budget time from the engineering department or something. But we're talking like a couple hours of time max normally, you know, especially when I'm traveling to them. So it just seemed like I don't know it, I didn't buy it. And also that was only one of the, the numerous calls, you know, like that the, the defensible reason for them changed. It felt like each time where it's like, oh, let's try this angle. Let's try this angle.

[Ryan Seacrest]

So did they end up blocking you? Are they just. How did that situation resolve itself?

[Ed Zitron]

I have not spoken with anyone there since we posted our video, talking about it. And part of the challenge with posting that video is it's like the first couple times this came up, I assumed that it was just sort of, okay, maybe the guy phrased it wrong. I've worked with these people for a while, and maybe it just came out wrong after a couple times. I did call one of my reps after the meeting where they kind of pushed this. You testing this technology that you think is not appropriate to share on charts with competitors, that's how we get you these interviews. I called a rep and said, hey, if you guys say this to people, this is going to be taken the wrong way. And I'm still assuming it's not meant this way.

[Ryan Seacrest]

Really trying your hardest there.

[Ed Zitron]

But if I hear this again, I have to start assuming it's the way it sounds. And it did come up again. And part of the challenge with making the video we made was we want to blow the whistle on it in case other people are facing that pressure and also in case consumers are watching or reading content which may be influenced without their knowledge. The problem is, I think Nvidia may now be in a situation where let's just assume everybody makes up and it's fine at some point. I don't know that they will ever be able to put an engineer on camera anytime in the near future with anybody without the audience questioning it. And for good reason, because that was what we felt was being used as the lever against us. And so it's just kind of. I don't know. We tried to. You know, I explained it to them several times why this is a problem and why the phrasing is a problem. And the more you hear it, the more it's like, okay, I mean, at some point, like, I think you're saying what it sounds like you're saying, and I'm gonna stop.

[Ryan Seacrest]

It's good that you did it, though, because it's. GN's got well over a million subscribers, so who knows what they're doing to much smaller outlets as well.

[Ed Zitron]

Yeah, I mean, and that's what I'm really concerned about is I've had conversations with Nvidia in the past that we'll probably get into in a future video, but about their strategy for newer creators. And I don't like what I've heard. I mean, it sounds very much like, where are going to sort of try and shape these newer creators. And I think the problem is as especially old guard media as in people like OGs. Before us retire or move to other industries, there's openings to change how media interfaces with these companies in general because you've got newer people who don't have the historical background with these companies to know what to expect. And so it's easier to kind of slowly creep that goalpost where it's it's less independence and it's more marketing arm of the companies. And that's what I'm really worried about is if they get in any of these companies with newer creators early and are able to change the expectancy of the relationship. So change it From Independent reviewer analyzing large companies device into more of a hey, we're all friends. We're all working together to try and benefit the consumer when if you're talking about a multitrillion dollar company, their motives are far different from like the guy in his bedroom who's trying to do hardware reviews.

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[Ryan Seacrest]

It's just so weird as well, because they're already so successful. Is this histo? It sounds like historically Nvidia has been a bit draconian like this, though not necessarily pressuring in this way.

[Ed Zitron]

I mean, I certainly think Nvidia is one of the most vindictive companies in the space. They the stories we've heard and told, in some instances of their partners, not reviewers, but actual business partners like board vendors, people who make the video cards that Nvidia GPUs go on those stories would seem to indicate a sort of vindictiveness.

[Ryan Seacrest]

Can you give an example?

[Ed Zitron]

Yeah. Allocation. So GPU allocation is the concept of how many of a high demand GPU can you as a partner get to then attach to a product to then sell to a consumer? And there's a limited amount of these because they're going to sell 100% of them. And allocation is typically measured by percent. So company A might get 25%, company B might get 5% of the GPU supply, whatever that is. And that allocation, we've been told in the past, has been used also as sort of a lever. And so an example would be back in the EVGA days, which EVGA sort of famously was.

[Ryan Seacrest]

And that was a graphics card company, correct?

[Ed Zitron]

Yeah, they were Nvidia's number one partner. And they were. So Nvidia favored that they only made Nvidia video cards. They did not work with any competitors.

[Ryan Seacrest]

Right.

[Ed Zitron]

And they famously cut that relationship publicly. And we ran a story about that. But one of the things that they were unhappy about was Nvidia slowly tightening the screws, which is a direct quote from an Nvidia PM I spoke to. Jesus. Slowly tightening the. Tightening the screws is the quote. But on what the partners were allowed to do with their products. And slowly, over time, they're losing some of this creative freedom.

[Ryan Seacrest]

When you say they lose creative freedom, like what are they being constrained to do?

[Ed Zitron]

One that's public is we did an interview with a famous overclocker who used to work for evga. Kingpin is his username and his name is on video cards that are world famous. We did a video with him and he talked about how he wanted to add two power connectors to a card to basically make it more fun to overclock with for consumers. And so it'd be able to pull more power and it would also be able to do so safer because the current power connector has this issue of burning and catching on fire sometimes. And so he wanted to do two of them to kind of resolve some of that. And in the public discussion we had with Kingpin in the video, he said paraphrasing, but the conversation was he said they wouldn't allow it or they restricted it or something like that. And I said who is they? And he said they. Yeah, like we, we. There was only one they. There could be.

[Ryan Seacrest]

Who could it be?

[Ed Zitron]

Yeah, but there's plenty of examples like that where the another one would be a couple generations ago, the cheaper cards like the 200, $300 models, they were, those models were difficult for the partners to actually make and still make any money. And so there were times where we were told about how this MSRP level video card, meaning the number that Nvidia says is the msrp that would only exist for a fixed period of time because it was simply impossible to afford to make it. But Nvidia really wanted them to exist at this certain msrp. It allows them to advertise a lower price and so they're pushed to make these cards. That allows them to potentially get things like more access to allocation or whatever privilege they may get.

[Ryan Seacrest]

So on a much larger level, what do you think is going on with Nvidia as a company right now? I'm not asking for stock analysis like that, totally not that. But just as a company that both makes consumer graphics cards and underpins whatever the AI thing is how, like what do you think is going on there right now?

[Ed Zitron]

I, I think there's definitely a focus on AI to try and get money. I mean, there was a. Jensen Huang was in an interview, I don't know, last year sometime I think, or early this year, and made a comment about how they use AI to write their own driver software now or their own software or something like that. And it's their number one focus. It's what they're making the most, I guess, investor money on. So they're focused on it. The concern I have is it's one thing to sort of let the consumer hardware side dwindle or get less competitive effort. It's another thing to in my opinion, sort of drag the entire industry down with it as they shift focus to the higher revenue AI side. Right.

[Ryan Seacrest]

When you say drag Them down. How do you mean?

[Ed Zitron]

I mean things like trying to, in my opinion, control the media narrative and shape it like that to me goes beyond, okay, we don't care much about consumer. We're going to focus on making money with AI that gets into. We are going to actively damage the credibility of independent media and also potentially harm consumers who are influenced by that media, which has been shaped with a certain corporate narrative to push. And that's my concern. So that's where I draw the distinction between, as we said in our video, if you want to just focus on AI and if they want to just sell all the GPUs to big enterprise companies, go for it, but don't screw all the rest of us over at the same time.

[Ryan Seacrest]

And do you think that they're abandoning consumer or is it just they are focusing on the shiny object of the day?

[Ed Zitron]

I don't know Jensen Huang personally. My read on him though, I feel like it's unlikely he would want to abandon something he already has.

[Ryan Seacrest]

Right.

[Ed Zitron]

Even if it's only out of maybe sort of pride. And so I don't think they'll abandon it. I do think they're focusing on AI, it's just that I don't. I mean they have like 92% market share in consumer GPUs now, according to John Petty research. So it's just like they can. It's a monopoly. I mean that's like. It's just like this is what monopolies look like.

[Ryan Seacrest]

Well, I would say there was an opportunity for someone to come in, but based on everything you've shown with AMD recently, even on the low end, it almost feels like consumer graphics are being not treated with the respect they deserve. Despite PC gaming being a huge industry and so on and so forth.

[Ed Zitron]

Yeah, it's a massive industry and prosumer too. I mean, even just non AI use cases include people who edit videos or make movies or do 3D animations. Yeah, I think Intel's a good barometer here because intel decided to get into consumer GPU and they're new to it and they've had a hell of a time. They're doing much better now with this current generation. But one of the quotes from an intel person I spoke with previously to us was for their last generation was we should be wrapping these with money when we sell them because they were just. They were basically subsidizing the build out of this new division, this GPU division, by undercutting prices from competitors to just try and get their foot in the door. With what at the time was a lesser product. And so yeah, I think they're a good barometer because if you want to be. I mean first of all to have a fab, a fabrication facility costs these days potentially tens of billions of dollars in years to build. So a new vendor would have to be fabless like Nvidia and like amd, unlike Intel. And to be fabless and make a.

[Ryan Seacrest]

Sorry about this, this is just for the listeners. What is a fab in this case?

[Ed Zitron]

Yeah, so a fab, a fabrication plant is basically a factory for silicon. It's highly controlled clean room environment and that means that there's basically absolutely no dust ingress, the small pieces of skin or whatever just working in an environment that's all either captured or controlled. And that's because a single particle of dust on a wafer can destroy at least part of that silicon supply.

[Ryan Seacrest]

Cool, sorry.

[Ed Zitron]

Yeah and so a new vendor would have to be probably fabless unless they're already huge like intel and that means they need to go get supply from most likely tsmc, possibly from intel maybe. I mean the past Samsung has been used. There's really not a lot of options here and everybody wants their silicon. So to even get allocation of these silicon wafers would be difficult. It's just all of the chips are stacked against someone who wants to do this and they would. I think the only way you get in is if you're an existing multi billion dollar company or have obscene amounts of investment.

[Ryan Seacrest]

Well that fucking sucks. Yeah, actually that's a good question though. So this is for the old timers listening. I Remember having a 3Dfx Voodoo 5500 picture of a halo on the box actually don't know what happened there. What happened to all the smaller manufacturers? Did they just get kind of absorbed or did they just fall apart?

[Ed Zitron]

Yeah, they got bought or Yeah, I think 3DFX if I remember correctly was bought by Nvidia and I just checked that. But some of the others, I mean there's like via Cyrix and some of these CPU companies. Yeah, three DFX bought by Nvidia, SGI was another so they.

[Ryan Seacrest]

Oh yeah, I forgot about sgi.

[Ed Zitron]

Yeah SGI is interesting because they sort of pursued heavily I guess at the time what enterprise would have been or at least workstation hardware and they're really invested in workstation. The story I got from someone, I wasn't covering things back then but was that SGI was less interested in consumer and didn't really think consumers could afford video cards which at the time was sort of true. And that's when Nvidia came in and started really kicking ass in the early days. But a lot of them just, they either got bought or they sort of exited that space.

[Ryan Seacrest]

So changing tacks slightly, how do you feel about AI in general? I know that I'm not expecting an industry in that. I'm just from your perspective, at least from what you've told me in watching your videos, it feels like AI is something now being stapled onto the side of literally everything.

[Ed Zitron]

Yeah.

[Ryan Seacrest]

Within your world, do you think there's like, do you use it? Do you have any thoughts on it?

[Ed Zitron]

There's uses. I mean one thing I'm actually worried about long term with AI use cases and the biggest thing I'm worried about is on the media side. We obviously get a lot of comments. I probably read or at least skim tens of thousands of comments a year and mm, I'm seeing more and more AI comments and not just the really obvious YouTube spam bots, but some where you kind of, you read it and you're like ah, that could be real, you know. And I don't want to like, yeah, I don't want to like remove it if it's a valid real comment. But then a few comments down the thread there'll be this discussion amongst what are obvious sort of bots about say some new crypto BS or whatever. And so I'm actually worried about sort of the dead Internet theory I guess the concept of you're the only human in the room and you might not even know it. That's concerning to me. There's a loneliness factor there I'm worried about. But the big one is just how easily people are manipulated by comments that sort of appear to have the prevailing opinion just in general, even from real comments. You then take that and you apply it to potential AI that becomes very convincing in the future. And you then think one step further of who owns these LLMs and the companies that sell so called AI products. And all of them are these multi billion dollar companies that if they want to could tune it to filter the responses in ways that are beneficial to them. And that to me is sort of the dystopian old man yells at clouds, you know, like concern I have.

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[Ryan Seacrest]

21 + terms and conditions apply. But it feels like a more practical one because everyone freaks out about AGI, which is fictional and all of these other things. But yeah, the idea that comments would be filled with people who were just subtly being nudged in different directions. And when you talk about corporate Narratives as well. Who knows that? And I don't usually with LLMs in particular, I try not to lean into anything too conspiratorial. But like, this is a simple one that you're kind of seeing signs of. Even on Blue Sky. I will occasionally get a comment from someone. It'll take me half a second second to go like, what's wrong with you? This doesn't feel like a human being saying this. No one speaks like this. But you sound human adjacent.

[Ed Zitron]

Right.

[Ryan Seacrest]

And I'm. And at your scale, I imagine that becomes a lot harder to moderate slash process.

[Ed Zitron]

Yeah. And it really is just. I mean I'm highly. My job is to be skeptical and you try to do that in a healthy way. You know, it's easy to go way overboard. But this is something where I think there's so much opportunity to be abused. And I was actually looking at. There's that meta story about meta and Facebook pirating all of these books or taking books from pirated materials and integrating them and there's a lawsuit over it. One of the things I was thinking of though, and actually speaking to a copyright attorney about was it really feels like right now the companies that are willing to break the most laws, especially intellectual property laws and steal the most stuff will make so much money that it's like, you know what, we'll just deal with the consequences in five years when it gets through the court and we'll be so far out ahead of anyone who didn't lie, cheat and steal to get here that it won't matter, which is just how the big corporations broadly behave. But applying that to a new area like AI, I don't know. I'm really concerned about it. I think there's absolutely good use cases. And I mean, as an example, internally we've used it to concept things. So like I'll have an idea in my head for art, like for a product, and I can see it, but I'm a terrible artist. And so there's a use case there where I'll sit down with my artist and try to explain it as best I can and he'll take a go at it. And if I'm like, nah, it doesn't really, like, look how it looks in my head, that's when I might try to pull some mid journey thing like, okay, here's like broadly like the style artistically I'm trying to get, you know, then he can take that and actually make something.

[Ryan Seacrest]

So but just to be clear, you would never use any of that stuff in the real it is literally just a concept tool. Just making sure the listeners have a good view on this.

[Ed Zitron]

Yeah. Correct the artist. So Andrew's been working with me forever. He makes it all from scratch, like in Blender normally and actually flattens it into a 2D image for the shirts and things. Cool. So yeah, it is purely used if in the first conversation he can't like quite figure out what I'm trying to explain as a non artist, you know, it's like, okay, let me go try and figure out like I don't, I don't know art words, you know, I don't, I don't know how to.

[Ryan Seacrest]

No, no, I know, I know.

[Ed Zitron]

So yeah, yeah.

[Ryan Seacrest]

How do you deal with the ethical side of that? Because it's just, it is still working on copyrighted material. But I guess if you're not putting it out there, it's just like this, this shit sucks. Even like looking at it feels bad.

[Ed Zitron]

Yeah. I mean it's hard because it's the first step for us. I was always like a Google search to see what's out there already. And so we'll do a Google search if I'm trying to explain something I want and normally that's pretty successful but like now it's the same. It's like you're getting all this AI art surfacing and so at some point it's sort of like the downloading and uploading and downloading, uploading a PNG multiple times. It feels like it's just getting like the quality is getting lost somewhere in that chain.

[Ryan Seacrest]

It is funny. We're also like three years into it and the best we've got as far as like from you, arguably one of the most, like, I don't mean this. I mean this actually is in a good way. Like you would be excited about something cool in tech coming out. Like if something cool happened. And the coolest we've got is. Yeah, sometimes I can't work out what I'm thinking, so I just make one image and hopefully my artist gets it. But the artist, yeah, it's just like that with three years in and that's the best we've got.

[Ed Zitron]

Yeah. And I think we early, early on with GPT when we ran one of the first news stories that we ran about it and I was trying to understand like, what is this thing? I remember feeding it a spreadsheet I had made with our own data and asking it to analyze the results. And it was just like. And keep in mind this was early but it had hallucinated so much That I was just. I was disillusioned. Just like, okay, this is just. It literally just made everything up.

[Ryan Seacrest]

And that was kind of how I was at the beginning as well, because I love my doodads, my gizmos. I was kind of like, okay, everyone's talking about this. And so I tried to do all of the things they talk about you. It could automate your work. I'm a spreadsheet heavy guy and this crap can't even do that. The funniest one for me was that if you have a Manus Manus. You heard of this one?

[Ed Zitron]

No.

[Ryan Seacrest]

They claim to be an AI agent company.

[Ed Zitron]

Okay.

[Ryan Seacrest]

And I asked it, can you go and find all. All of the links that mentioned me for the last two years? Probably over 100 of them. And it takes 11 minutes or so. And it's writing Python for every single step. And it comes back with 11 links or like nine links. I go, hey, you missed some. And it comes back with nine more after, like another 10. And this is. This was about a month ago. It's just what it feels like. They're pushing them up a hill. It's. But back to Nvidia for a second because this will be the last Nvidia one. I think you have done a really good job of kind of tracking Nvidia as they've jumped towards these movements, but they've done this, but they did. How big was their move towards crypto? That's actually something I've had trouble encapsulating before. Did they really shift the company that aggressively in that direction?

[Ed Zitron]

That's a good question. So Nvidia's relationship with crypto is weird. I remember at one point there was some kind of earnings call or something where it was during one of the GPU mining sort of apocalypses where consumers couldn't get cards because they were all being bought by crypto mining. And I remember doing a report in Hardware News on the earnings where it seemed like the amount of revenue for mining was sort of obfuscated. And it was a challenge where the devices are shared with gaming. And so, okay, I could see how it would be difficult to decouple these in a revenue chart if you sell gaming devices and they're used for multiple things.

[Ryan Seacrest]

Right.

[Ed Zitron]

So it's like, I kind of get it, but at the same time they weren't like hiding from making sales to crypto mining. And then later on Nvidia released these LHR low hash rate cards. I think it was the 30 series. And that was done to try and get More cards? Well, they say to try and get more cards to gamers. Now there were bypasses for that, which is a separate story. And it was done at a time when the 30 series, it was really unfortunate covering it because the hardware was pretty good, the prices at the beginning were good, but there's no supply to meet the demand, which was partly because of COVID shutdowns where people were building new computers for home and also partly because of mining. And so they tried a few things like these low hash rate cards to reduce the viability for mining operations. But yeah, I mean it definitely they've kind of that pendulum has swung back and forth I think at Nvidia where it's like okay, we'd sell a lot of these and make a lot of money to. People are really pissed off and we can't get them to consumer users who might actually be repeat customers in the future. And so let's try and restrict it. So it's definitely, I don't know, I mean it's not unexpected behavior I guess for a big corporation where it's just where's the money? And if the pendulum swings back the other way, we need to try and minimize how much both of these potential client groups hate us for. For catering to the other one. So.

[Ryan Seacrest]

So final GPU related question actually, and forgive me if you don't know the answer for this exactly, but assuming the AI bubble burst and you don't have to commit to whether you think that will happen or not, what else can these big enterprise level GPUs actually be used for?

[Ed Zitron]

They can be used for a lot. I mean like some of the. We're talking to a professor at a university for an upcoming piece and they have some very serious machine learning research use cases and I've looked into some of the other ones and as you might expect, there's really promising use cases in medical and pattern recognition and so called AI being able to do early identification of potentially cancerous masses and people that, you know, it's one of those like if you treat it like a tool rather than like the answer then I suppose in this example as someone who knows nothing about, you know, the medical world, but I suppose a skilled doctor might be able to use it to help the process. I think the concern I would have as a skeptic would be okay, but can we keep that doctrine? The mindset of I'm using this to help catch my mistakes or help see things I can't rather than I'm overworked and I need to lean on this to do my job. That would be the concern.

[Ryan Seacrest]

My whole thing is just if they. And I believe they have. This is my personal opinion. I think they've massively overbuilt and oversold these cards. And I. Sorry, cards is inappropriate to refer to like the Enterprise ones. Racks, I suppose. But it's. What do they do next? Is going to be the question eventually. And I mean there's just very clearly not going to be enough use cases for them. But I think that's going to be really interesting. And now I've got two fun questions for you. First of all, did you hear about this $3,600 keyboard?

[Ed Zitron]

I did not.

[Ryan Seacrest]

The Norbauer Seneca. Okay, so I'm going to send you this later. So Nathan Edwards over at the Verge reviewed this $3600 keyboard which I need to send you because I assume you would.

[Ed Zitron]

Norm Bowers Seneca. I see the review. Luxury keyboard.

[Ryan Seacrest]

It's insane. Listeners, I will drop with everything we've been talking about. I'll have links in there. But this thing, it's like precision honed and if he gets it wrong, he has to start again. It takes him a full day to do the things that absorb impact. So cool.

[Ed Zitron]

This is. This reminds me of the. I don't know, probably almost 20 years ago now. There was the super expensive. I think it was like an Optimus keyboard or something like that.

[Ryan Seacrest]

Oh, was it like the DAS keyboard where it had the little screens on each key?

[Ed Zitron]

Yeah, it was screens for every key. And back then, you know, that was before we were putting screens on everything.

[Ryan Seacrest]

Uh huh. I want. That's the thing. I love that this exists because if you look at the Verge story, which I'll link, it's just a guy who literally sits in this garage and just builds these things like an Artesian. I wish we had more weird shit like this. This is what I miss about the tech industry.

[Ed Zitron]

Yeah, the. The weird stuff and the cool stuff and things where. That's what I like seeing at Computex. But it's okay. I could. This isn't a product yet, but I could see it becoming a product or there's pieces of this that could become a, you know, an affordable product. That's the stuff I like. Yeah.

[Ryan Seacrest]

Did you see anything really bizarre like that? There's.

[Ed Zitron]

Yeah. Well, actually most recently this wasn't Computex, but the most sort of bizarre, cool thing I saw and worked with that I was really happy about was the pre built PC made by a small company called Cherry Tree. They make modded computer cases and it's just a computer inside of the husk of a video card.

[Ryan Seacrest]

Okay, that's cool. I love that, that's. That reminds me of the Corsair thousand D case, which I actually have at home where they have. You can fit micro ATX and a regular sized motherboard in there. I love that stuff. Like it's, that's why I, that's the thing I love about tech, the weirdly really dumb kind of niche stuff. And actually with that in mind, what are you actually excited for as we wrap up? Like, what are the things coming out soon that you're kind of pumped up to see?

[Ed Zitron]

I mean, the cases and cooling are really interesting to me. I just think in the computer actually, CPUs have gotten interesting too. So on the silicon side, AMD has done really well to actually get into gear competitively over the last several years. And these, they call them X3D CPUs which have a bunch of extra cache on them, they've been really good for gaming. And that's a, I mean, seeing that.

[Ryan Seacrest]

What does the extra cache allow?

[Ed Zitron]

Yeah, so because you can fit more stuff local to the cpu, you can store more of what the CPU needs to process within the CPU silicon itself. It doesn't have to go out to system memory. So the way it normally works is like if you're playing a game and you need some kind of file for drawing something in the game or whatever, I mean, it'll go into memory of some kind. So it might be GPU memory, it might be system memory. But if we take the system memory example, something goes into system memory, you need that file, there'll be a transaction where you can imagine these bits going down a bus to the memory and going all the way back to the cpu. And that's a long highway to go down. Whereas with extra cache you can store more local to the cpu, it can transact via basically like a shortcut. And that allows in the real world significantly higher performance in gaming or in cache heavy applications.

[Ryan Seacrest]

And so the new AMD ones are.

[Ed Zitron]

Yeah, it's the new, like the 9800X3D for example. So those. I'm really excited about that, how that's gone because that actually you may like this, but that was actually a sort of a skunk works project where this team of engineers in AMD and we ran a story on this too, but they decided, let's just try this idea. And they experimented with it. They got it working and they brought it through management and said, hey, this looks viable. And then they were able to actually make a product that it came from an abnormal path of an underground sort of Skunk Works effort in the engineering department to actually being the leading gaming product for CPUs on the market.

[Ryan Seacrest]

We will have that link in the episode notes as well and we can wrap on the product the AMD Skunk Works product. You mentioned in a recent video that I had not. AMD made a mountain bike at one point. Just wanna what?

[Ed Zitron]

Yeah. So yeah, that was not a good moment for amd. Fortunately. Fortunately it didn't particularly damage their CPU or GPU credibility. Because it was so hard.

[Ryan Seacrest]

I can't imagine so. But why?

[Ed Zitron]

Why did they do what it was during the COVID bike shortages. I don't know if you remember, but like all kinds of bicycles. Yeah. Were difficult to get and yeah, so they made these $300 so called mountain bikes. I think they're like Kent Walmart bike rebrands basically.

[Ryan Seacrest]

Nice. They went real cheap.

[Ed Zitron]

Yeah. And yeah, it was advertised, you know, for mountain biking and off road trails and whatever. And so we took it down a trail and I actually had trouble getting out of the parking lot. That's how messed up the bike was. We had to take it to a shop before I rode it for a safety check because the. The use V brakes and they were going through the spokes. So they definitely would have stopped me.

[Ryan Seacrest]

But Jensen Huang sitting there being like, we could have had a fucking mountain bike, man.

[Ed Zitron]

How do we get. Yeah, if we make a bike, we can get rid of them.

[Ryan Seacrest]

Yeah, they're just like $20 billion shoved into mountain bike race. That would be so good. Steve, it's always such a pleasure having you on here.

[Ed Zitron]

Where can people find you on Gamers Nexus on YouTube?

[Ryan Seacrest]

Thank you so much for being here. I'm a. Of course. Ed Zitron. You've been listening to Better Offline. Have a great week everyone. Steve, thanks for coming on.

[Ed Zitron]

Thank you.

[Ryan Seacrest]

Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Matosowski. You can check out more of his music and audio [e-mail] m a t t o s o wski.com you can email me at ezeteroffline.com or visit betteroffline.com to find more podcast links and of course my newsletter. I also really recommend you go to chat. Where's your ed to visit the Discord and go to R betteroffline to check out our Reddit. Thank you so much for listening.

[Steve Burke]

Better Offline is a production of Cool Zone Media.

[Ryan Seacrest]

For more from Cool Zone Media, Visit our website coolzone media.com or check us.

[Ed Zitron]

Out on the iHeartRadio app, Apple Podcasts or wherever you get your podcast.

[Steve Burke]

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