Is Generative AI Plateauing?, Booming Bluesky, Apple’s Smart Glasses Play

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover 1) Jake Paul vs. Mike Tyson 2) Why researchers believe Generative AI training methods might be plateauing 3) Is the application really what matters? 4) Will reasoning save the day? 5) Writer raises $200 million 6) ChatGPT defeats Chegg 7) Should ad agencies bill by the hour in the age of AI? 8) Ranjan reflects on our interview with Gustav Soderstrom 9) Gratitude for listeners 10) Yes, we're launching video interviews on Spotify 11) Bluesky's longevity potential 12) Apple's smart glasses move 13) Z-Pain makes us unhappy --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. For weekly updates on the show, sign up for the pod newsletter on LinkedIn: https://www.linkedin.com/newsletters/6901970121829801984/ Want a discount for Big Technology on Substack? Here’s 40% off for the first year: https://tinyurl.com/bigtechnology Questions? Feedback? Write to: [email protected] Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Alex Kantrowitz?

  Is generative AI plateauing as training methods top out? Blue sky is booming as an alternative social network and Apple looks into smart glasses. All that and more is coming up on a big technology podcast Friday edition right after this. Welcome to big technology podcast Friday edition where we break down the news in our traditional cool headed and nuanced format. We have a great show for you today covering everything happening in the world of AI. Very big news. There's concern that training methods that have gotten the generative AI field to here are not going to continue to scale. And that's really coming to the fore right now. We're going to talk about that. We're also going to talk about the rise of blue sky, whether it will be sustainable and Apple's smart glasses play, which is quite interesting. Joining us as always on Fridays to break it all down is Ron John Roy of margins.

• 0:45Alex Kantrowitz?

  Ron John, welcome to the show. Great to see you.

• 0:47Speaker 01

  Scaling laws are here, Alex. They've finally come for the industry.

• 0:52Alex Kantrowitz?

  I know you're excited about what's going to happen with this, but I know you're even more excited about the Jake Paul, Mike Tyson fight. Who you got?

• 1:00Speaker 01

  Neither, neither. I think Netflix is genius in promoting their live programming by just bringing out two people that no one wants to see win, but I'll still take Tyson if I have to.

• 1:12Alex Kantrowitz?

  All right, I'm taking Paul. We can put it on the prediction markets and see what happens. My friend group has been saying that this is an exhibition match, basically. And a lot of betting sites are looking at it the same way. The folks are saying that it's rigged. Do you think this is rigged or a real fight?

• 1:26Speaker 01

  I think this is a real fight. I don't think Netflix would go into this fully rigged or making it reality TV, but I think it's a good reminder of the blurred lines between reality TV and actual live programming, but I think it's real.

• 1:40Alex Kantrowitz?

  I'm going to go rigged. Okay.

• 1:42Speaker 01

  So we got a lot.

• 1:44Alex Kantrowitz?

  Had to cover that.

• 1:45Speaker 01

  Paul market contracts to set up right now.

• 1:48Alex Kantrowitz?

  Absolutely. And now we can talk a little bit about what's happening in the AI world where, shall we say, there's another fight going on between the purists that believe that large language models will continue to scale if you add more data and compute and power to the mix. And those that say eventually these models are going to hit a wall. There's been a long brewing battle between these two factions. And this week, I think, has been the week where both sides have started to put their positions in the ground and say, you know what? I've won. And that's really come on the back of this great information report that talks about how OpenAI has basically found that it has hit the limit of improvement when it trains

• 2:31Alex Kantrowitz?

  with more data, more compute and more power. Here's from the story. The number of people using ChatGPT and artificial intelligence products is soaring. The rate of improvement for basic building blocks underpinning these products is slowing down. The challenge that OpenAI is experiencing with its upcoming flagship model codenamed Orion shows what the company is up against. While Orion's performance ended up exceeding that of prior models, the increase in quality was smaller compared to the jump between its last models, GPT-3 and GPT-4. Some researchers at the company believe Orion isn't reliably better than its predecessor in handling certain tasks. This could be a problem as

• 3:15Alex Kantrowitz?

  Orion may be more expensive for OpenAI to run in its data centers compared to other models. Basically, the idea here is that OpenAI has been training subsequent foundational models with more data, more compute, and it's reached the point of diminishing returns to the point that this grand next model that it's supposed to release, we don't even have a sniff of GPT-5 yet, it's calling this Orion, is going to be just a bit better but more expensive. What do you make of this battle?

• 3:47Speaker 01

  I am happy about this. I think I've talked a lot about how I don't need GPT-5 just yet. I think the amount of opportunity there is around actually productizing the current models is so massive right now. Again, like, there's so many little magical moments even with Claude, with ChatGPT, with any of these tools, that you see so much potential, but then actually translating that into helping you do your job better or create certain things better. I think that there's, there's just so much work to be done there that everyone competing to kind of create this next massive foundational model has never made a

• 4:28Speaker 01

  Ton of sense to me before they actually just got a GPT four or Claude three point five OPUS working, you know, kind of pushing it to its limits and making it work as well as possible. So I'm kind of hoping that this actually moves people towards making tools people use rather than just saying AGI and GPT five and whatever, whatever else.

• 4:51Alex Kantrowitz?

  Now, look, I hear you, but I also have to disagree. I mean, the field's potential is so much more if these models continue to improve. And while they're good today, they're not where they've been promised to be. And if this is the limit, then it severely diminishes sort of the potential of these models to change everything we do as the AI industry has been promised. And it's, by the way, it's not just this information report. Lots of people have been saying this. So this is Ilya Sutskever has talked about it. He says to Reuters, results of from scaling up pre-training, the phase of training an AI model that uses a vast amount of unlabeled data to understand language, patterns and structures, it's plateaued.

• 5:33Alex Kantrowitz?

  Ben Horowitz and Mark Andreessen talking on their podcast. Horowitz says, we're increasing the number of graphics processing units used to train AI, but we're not getting the intelligent improvements at all out of it. And Andreessen has been saying that lots of smart people are working on breaking through the asymptote, figuring out how to get to higher levels of reasoning capability. I mean, shouldn't we just put your concern, your concern about building practical applications aside for a moment? I don't think anyone's going to disagree that it's a time to build practical applications. But isn't this like fairly concerning for the progress of the AI industry? If let's say this is about as smart as they're going to get?

• 6:14Speaker 01

  No, I think, first of all, I love Ilya unleashed right now, going on, going to Reuters and now being able to say things like, uh, the vast amounts of unlabeled data to understand language and patterns and structures have plateaued. But I, yeah, I think the focus being kind of distracting by focusing only on these step changes in quality. Quality of the models has distracted from practical applications. Yes, we should be able to have both, but you even see it in the way that an OpenAI is structured as a company and where they invest their resources. We talked a lot about this with Corey Weinberg from The Information that the cost

• 6:56Speaker 01

  structure of OpenAI is still much more heavily towards the R and D and improving the actual models versus building out a good sales force and a sales enablement and customer success team. And these things might sound boring, but if you're actually want these these technologies to be adapted by corporations and companies and just everyday people, they have to be easier to use and more practical. Like, I get the idea that there's a lot of times that if you're using one of these tools, it doesn't work perfectly the first time. And everyone, the kind of natural reaction is, okay, I guess it's not good enough.

• 7:37Speaker 01

  But then you learn, the better you prompt it, the different you structure your workflow, you can get it to do what you want it to do. But instead, I think a lot of these companies are promising the model will get so smart in the next iteration that you don't even have to do that work around prompting and workflow building, that it'll just figure it out and it'll be okay and AGI will be here, et cetera.

• 8:00Alex Kantrowitz?

  But isn't that what they're trying to do? I mean, isn't, aren't you ignoring the business story here? That OpenAI just raised the largest VC round in history, $6 billion. Is it Microsoft or Amazon are hooking up to nuclear power plants? Anthropic is out in the market trying to raise billions of its own. Just from a business standpoint, if these companies cannot advance this anymore, isn't all that money going to come due and sort of crumble the industry?

• 8:25Speaker 01

  I'm not ignoring the business story at all. That is the business story to me. I think like over raising for the R and D side of things rather than the actual like operationalization and building out businesses on top of the existing technology. I mean, again, we've debated this plenty. I think that. Is a huge mistake in that it actually, you know, potentially hampers the long-term development of the industry. So if it actually means this slowdown, you know, puts a little cold water on the promises of GPT-5 and whatever else, and people just get back to work in terms of actually building things that solve problems, I'm happy about that.

• 9:08Alex Kantrowitz?

  I'm trying to pin you down here a little bit on the technology question, and you keep wiggling your way out, which I respect. But I have to ask, like, isn't there just a tad of disappointment on your end if this is sort of the end here, the end of the road in terms of where this is?

• 9:23Speaker 01

  Not at all. I mean, the things I've already been able to do. I just made a little game in Claude the other day. I saw some video of like, uh, it's kind of like, uh, Space Invaders type of game. I coded a Space Invaders type game with these like, custom images myself in an hour, and then hit the Claude limit, which a lot of listeners probably do, and it's kind of annoying even as a paying customer. But like, that was magical to me. And that exists on the existing technology. It's possible. And there's so many other applications. I can imagine if I'm able to do that for fun in an hour, that are not being

• 10:04Speaker 01

  properly explored because all the attention hype is on the much, much bigger thing. So if the Claude business gets built as, you know, actually teaching people how to use the existing technology well, I think that's has, again, much better, longer-term potential than the entire bet on the entire industry is the technology will get step change better in the next year or two.

• 10:31Alex Kantrowitz?

  Yeah, I don't know about that. I mean, they have, that has been the bet, though.

• 10:35Speaker 01

  It has, it has, and I don't think it's the right one. And I think something that pushes us away from that kind of strategy is gonna be a good, it'll shake things up. It'll definitely shake things up. But I think it's, it's healthy for the longer term world of AI.

• 10:53Alex Kantrowitz?

  You know, you've really not played into my game today where I wanted to evoke feeling of one single feeling of disappointment or sadness from you. And you say, yeah, it would be tough. This is how I'm feeling. Gosh, like if this promised, you know, AI revolution ends here, then I don't know how far we get. And then I come in and say, well, actually, maybe we're not done, you know, sort of like that Walter White give, we're done when we say I'm done.

• 11:19Speaker 01

  All right. Well, I'll give you video generation is the one area that I do think we are severely, we're not even close to anything interesting. And we've been promised things that are interesting, i.e. Sora. But we're very, very far away. Even the runway MLs and other tools that I've tried, we're so, that's one area where I see a huge need for technological improvement. But for any content generation, any coding, even data analysis right now, I think the models are pretty damn good at doing what most people need them to do. We just don't know, most people just don't know how to use them correctly.

• 12:02Alex Kantrowitz?

  Well, Ron, John, thank you for playing along. And I have to inform you, we're not done. We're done when we say I'm done. And that is because, that is because, yes, these research houses might have hit some sort of wall. And the reason why they're hitting the wall is obvious that they're using synthetic data because they've run out of data and it's offering less good results. And this has sort of been the issue with these, training these new models. However, In recent times, there has been a development of a new discipline here, which is reasoning. And we talked about it back in the day, and that's what sort of freaked Ilya out and he left OpenAI.

• 12:44Alex Kantrowitz?

  And that really might be the near future of this field, where the models now such as OpenAI's O1 are prompted and they think, and the more they think, the better they get. And this is again from the information. In OpenAI's case, researchers have developed a type of reasoning model, O1, that takes more time to think about the data that LLM trained on before spitting out an answer. This means the quality of O1's responses can continue to improve when the model is provided with additional computing resources, while it's answering user questions even without making changes to the underlying model. And Casey Newton from Platform recited one example from one of OpenAI researcher talking about it.

• 13:29Alex Kantrowitz?

  This OpenAI researcher says, and this was at a TED AI talk, "It turns out that having the bot think for just 20 seconds in a hand of poker, step by step, got the same boosting performance as scaling up the model by 100,000 times and training it for 100,000 times longer." So I think what we're about to see is a pivot in the AI research field, where yes, they might be applying practically some of the models that exist today, but it seems to me like everybody is going to go completely in on this reasoning format, and that is going to be where we see the improvements. And that's why I want to highlight this post from Dan Shipper that I saw this week. He says, "The message that the information headlines convey is at odds

• 14:13Alex Kantrowitz?

  with what people inside the big labs are actually feeling and saying. It is technically correct, but the takeaway for the casual reader that AI progress is slowing is the exact opposite of what I'm hearing." So this might be a combination of spin and reality, but I'm curious how much stake you're putting into reasoning when it comes to being able to advance the status quo.

• 14:35Speaker 01

  Yeah, no, I think both reasoning and how synthetic data is used matter. And I think actually are in almost more promising direction for the industry than just raw processing powder, power and size. I think first on the synthetic data, like we're going to be talking about a company, writer.com in just a little bit, but they, one of the things they did was like create their own foundation models and they apparently trained them for $700,000 total by using really targeted synthetic data to create different models for different kinds of problems. And I think in the coming months and years, we're going to start to see some awkward headlines

• 15:17Speaker 01

  around size matters because smaller will be better in terms of actual models being used. And like, again, one model should not be reliable to solve every problem for everyone at all times versus maybe there is a model focused on financial data analysis and it's, it's actually much better at solving problems around that versus writing poetry or generating images. So I think using really targeted synthetic data for more targeted models is actually a really interesting space. In terms of the actual reasoning side, I think that's really interesting. Like, like rather than coming up with new ways of actually generating the answers using

• 16:01Speaker 01

  the existing information, that could be incredibly promising and solve so many of the ideas, so many, so many of the challenges facing the industry like cost for any kind of new foundation model, like just, you know, viability of these things actually succeeding. So I think, again, today, today I'm positive. Today, these are all good things for me.

• 16:24Alex Kantrowitz?

  Right. And the cost really matters because if you're using a reasoning model, a lot of that can happen in inference versus in the training, which is, I think, less expensive. Before we move on from this, I just want to talk quickly about this AGI thing that we talk about so often, but rarely define and rarely talk about in context, right? That all these labs are trying to push toward artificial general intelligence or human level intelligence. And it seems like some inside these organizations are like full-fledged trying to get there. And others, I don't know, probably like see it as useful marketing so they can sell products today. Actually, I think that a lot of the productization that happened has kind of been an accident in places like OpenAI as they've pushed, you know, the research forward.

• 17:06Alex Kantrowitz?

  But why don't we just take this point in time to just talk a little bit about AGI? Do you think A, it all along has just been this marketing term? And do you think that if we're not going to get there through these current methods, that the magic of that marketing falls away a little bit, making it harder to sell into companies, making it harder to fundraise if all these companies are doing are just sort of productizing what they have today? And I guess B, do you think we'll get there?

• 17:38Speaker 01

  I think I'm going to go with A. And it's because, I guess, how would you define AGI or artificial general intelligence?

• 17:49Alex Kantrowitz?

  I think Jan LeCun's definition is really good, which is basically that it's human level intelligence. It can handle a variety of things just the way that a human can.

• 17:59Speaker 01

  What is human level intelligence, though? Because there's a

• 18:02Alex Kantrowitz?

  Right.

• 18:03Speaker 01

  I don't know. I think ChatGPT can already do a lot of things better than

• 18:09Alex Kantrowitz?

  But it's almost like, yes, it can answer, you know, questions about philosophy the way that a philosophy professor could. But it's almost like the little more nimble things that it really struggles at. ChatGPT, you can't tell ChatGPT to like, you know, go, you know, write a bunch of emails to people you need to communicate and it does it for you well. It's not really able to do that. It's not really able to switch very well between tasks. It's not very well, it's never really able to, you know, learn in the context and get things right the next time. These are all things that I think make human intelligence special is sort of the adaptability and the ability to be, as we say, general. And I don't think AI is there yet.

• 18:48Speaker 01

  Okay, that's, that's a fair definition. And using that definition, I actually think

• 18:56Speaker 01

  It's fine for the industry to not be on the direction of getting there because even what you said, writing a bunch of emails to different people, I think that problem could and should be solved soon in really targeted manners. Like, you know, take your entire existing email history, train something on that, use that to generate new emails and build like a process or workflow where you actually validate them. Like, I mean, really practically, I think solving that problem could be possible pretty soon. And it's just not getting solved because we're still all trying to chase the dreams of AGI. And I, I think for me, and what exactly it is, the human level reasoning makes some

• 19:40Speaker 01

  sense, but it's amazing to me that it, it's always brought up, but there's not one like clear accepted definition or one clear vision that's communicated by the biggest people in the field, the Sam Altman's and everything else. So it remains this murky, kind of like dystopian, robots taking over, who knows what it is, will be a line item in a contract with Microsoft's investment in order to like change the profit structure. I mean, it's such a nebulous term that that's why I think it does represent a distraction from progress.

• 20:18Alex Kantrowitz?

  And I don't know what it says about my life that you're like, imagine the strongest form of artificial intelligence possible. What does it do? And I'm like, yeah, just write a bunch of emails. Like, oh my God.

• 20:29Speaker 01

  Imagine a world where I'm worried about robot takeovers and you're just trying to go to inbox zero here.

• 20:37Alex Kantrowitz?

  Honestly, if an AI could get me to inbox zero, it would be a true, a true miracle. I would really believe in the power of science. It would have to get through. 12,000 unread, but it is interesting that they have billed AGI initially was like a sort of like what I was describing, human level intelligence adept, able to generalize. And now I think it's talked about really in a way that's akin to superintelligence, something that's smarter than humans in almost all fields and can perform things that humans can't. And that's when you hear like the messaging coming out of OpenAI that it can lead scientific discoveries and these type of things. And it's like, okay, that's not really general, that's superintelligence. And, you know, I think that that has led a lot of the investment and a lot of the hype around this that will eventually get

• 21:22Alex Kantrowitz?

  there. But it just doesn't seem like it's going to be through the traditional scaling of LLMs. I guess that's my point here.

• 21:28Speaker 01

  Yeah, I agree on that.

• 21:30Alex Kantrowitz?

  And you're like, I don't care. That's good.

• 21:33Speaker 01

  I don't care. That's good. That's my new philosophy on scaling laws with LLMs.

• 21:38Alex Kantrowitz?

  It's a good tagline. Okay, last thing about this, did you hear that Google, I think this is worth watching, they have a new experimental Gemini model. It's called Gemini EXP1114. And do you know about Chatbot Arena where they test which is the best LLMs? It's currently sitting at the top of Chatbot Arena and kicking the butt of ChatGPT 4.0, 0.1 Preview, 0.1 Mini, Previous Geminis, all the Claude's. Maybe Google's got it figured out. Whatever they're doing there seems to be working. That it's, and this, by the way, folks, this arena is where people will compare responses to different models and pick the best one.

• 22:20Alex Kantrowitz?

  And it's been voted on by 6,000 folks at this point and is at the very top. So it's quite a moment for Google that I don't want to glance over and I think we'll probably be coming back to it when we talk about Google's prowess in the field.

• 22:34Speaker 01

  Yeah, I think, and for listeners, I mean, check out Chatbot Arena. It's honestly a fun thing and it's, it's a blind comparison test. So you don't know, you're given two answers, you select which one you think is better, and then you find out what's the actual model behind it. So it is essentially an unbiased test. Gemini, or I have a question, are you using Gemini in day to day life?

• 22:59Alex Kantrowitz?

  No, I'm still all in on Claude and I'm looking at Chatbot Arena and I'm like, I am not doing it right. I mean, it's interesting because maybe these models can give a better response, but it's also just like. It matters, like UI matters. I mean, this is sort of me agreeing with your argument.

• 23:17Speaker 01

  Are you agreeing with me?

• 23:18Alex Kantrowitz?

  Personality matters, usefulness matters, even if the model is smarter. But I, this is making me think it's time to give Gemini another shot. How about you?

• 23:27Speaker 01

  I, I don't use it very often. I have it bookmarked. But I mean, still Claude perplexity, chat GPT, steady rotation, all for different use cases. I think perplexity is almost one of the best examples of like UI completely transforming how nice it is to use. And by this point, I really thought Gemini should be my entire travel booking, given it's connected to Google Travel, Google Flights and everything, Google Maps. Like, it should be my starting point, and it still isn't. And I still think the answers in the existing form just are not very good. It gets a lot of stuff wrong.

• 24:13Speaker 01

  It doesn't answer a lot of things as well. And I get trying to be a little bit more conservative and risk averse. I still think Google is incredibly well positioned, just given their ecosystem. But it still has not gotten there yet. And I mean, it's, maybe the next experimental model, once it becomes reality, will, will kind of cross that chasm, but we're not there yet.

• 24:39Alex Kantrowitz?

  Yes, and I have to say, I have become a bit of a perplexity guy. I'll admit it. Perplexity is pretty good.

• 24:45Speaker 01

  It's so good. It's my, it's become my kind of like companion for other things. Like, I think chat GPT is more when I have like, I'm sitting and doing something focused. Claude is for a lot of work, a lot of like, more on the coding side and kind of like really the art, using artifacts. Perplexity is when I'm watching a movie, a sports game of any sort. Like, it just is so good in just giving you quick information in a really nice format with additional links to keep exploring and questions that, uh, I think for that like, and which makes me think it's almost, and it still is the biggest competitor to real search.

• 25:25Alex Kantrowitz?

  Yeah, I find it to be really good for research. Imagine trying to sort through a bunch of programs and figuring out what they offer.

• 25:31Speaker 01

  Yeah, I am just making the decision on the Epic Pass versus the Icon Pass for winter skiing. If other, if listeners are making the same decision and all done in perplexity and asking like specific questions, which resorts in Vermont, which resorts in Colorado are there? And like, it was so, so good in doing that.

• 25:53Alex Kantrowitz?

  I do hope that perplexity finds a way to get me into China this winter, which I'm hoping to stop in on the way back from Australia. So finger crossed.

• 26:03Speaker 01

  Where are you looking to go?

• 26:04Alex Kantrowitz?

  Beijing. I want to see that wall.

• 26:07Speaker 01

  See that wall?

• 26:09Alex Kantrowitz?

  I'll report that.

• 26:09Speaker 01

  I was there in 2009. I went to the Great Wall. It was definitely, it was a good time. It was, lived up to the billing.

• 26:17Alex Kantrowitz?

  Nice. So, okay, so let's just take a minute and go through three stories that the two of us kind of found this week that are talking about what you really are interested in, Ranjan, which is the practical application of AI at this stage and how even if we stop right now, which I don't think we will, we're going to have an extremely powerful technology that's going to disrupt industries and really be practically useful. So why don't you kick it off with this Rider fundraising that you talked about right before?

• 26:43Speaker 01

  Yes. So Rider is Generative AI startup. They just raised 200 million at a nearly $2 billion valuation. What's interesting about them is they're, they built their own foundation models. We had just talked a little earlier about how they build more kind of targeted models that are really focused on solving enterprise business problems. And the entire kind of differentiation that they're focused on is kind of exactly what I've been talking about. Like they have a lot of big name enterprise customers going in and like, remember these companies have messy data. They have like lots of really heavy processes that you're not going to just call and make

• 27:28Speaker 01

  an OpenAI API call and solve. Like there's so much other work that needs to be done that I think it's, it represents like more the Salesforce service now world of enterprise software versus OpenAI being, I don't know, just like a more pure, hard, pure tech company. More like, and I think starting to see more companies like that. That represent the actual utilization and application layer of generative AI is going to be a good thing. It's going to be a very good thing.

• 28:02Alex Kantrowitz?

  When Riderly does its job well, talk about like what you could see in helping a company with.

• 28:08Speaker 01

  A writer. Yeah, it's a.

• 28:11Alex Kantrowitz?

  Sorry, writer. Look at me, I'm adding the Lee at the end of the startup like we're in 2000.

• 28:15Speaker 01

  2013 again. What a time, what a time. I think what it would look like is going in and actually taking one large enterprise and then recreating hundreds of existing processes and just making them better. Automating some stuff, adding a generative AI layer to other stuff, like maybe keeping some stuff manual, like, like really rethinking every existing process at a large enterprise and then like actually asking how does generative AI fit into this and then making that happen and actually creating the kind of frameworks and software that allow you to

• 28:58Speaker 01

  do that. I think if any company is going to be able to win on that, that's where the, I mean, the value that's going to be accrued there is going to be massive versus just, again, I was shocked when I saw OpenAI's kind of like vision around its business is still ChatGPT plus subscriptions because I still believe the companies that crack enterprise are going to be the ones that really accrue value in this.

• 29:26Alex Kantrowitz?

  That's pretty cool. Okay, so mine is a little bit different and that is Chegg. What AI has done to Chegg. This is just an example again of like how current AI is going to change things no matter what. And for those folks who don't know, Chegg is an online education business and they actually started with textbooks and then built up like a pretty serious online education business. And when kids would like want to research stories or problems, they would, they would, they would say that they were checking it. And this is a Wall Street Journal story, how ChatGPT brought down an online education giant, basically saying that instead Of checking kids are using chat GPT now and Chegg stock is down ninety nine percent from early

• 30:11Alex Kantrowitz?

  twenty twenty one, erasing some fourteen point five billion of market value. And there are bond traders, they have doubts that the company will continue bringing in enough cash to pay its debts. So even today, we're already seeing this stuff start to really change education. And I think that's like the most obvious place, but we've we've already had a few years to see this run its course and look at what it's already done with Chegg. And I think that's like a sign of where things might go with the rest of industry. Not that every other incumbent company is going to lose ninety nine percent of their value, but it does kind of show how standard it's become already in education.

• 30:48Speaker 01

  Yeah, I think also seeing that ninety nine percent drawdown brought me back to Chegg was definitely one of those twenty twenty one extrapolating into the future, the pandemic, and like anything with the words online education in it just exploded in value. So I think on one hand, some of it is related to just that not being the case anymore. But also, I think this is actually a really good example. If you think about it, like students are the ones, they are, they will take whatever existing technology there is and make it work for them. They will do that work and they will figure out how to answer their homework questions, or maybe write a paper in some

• 31:30Speaker 01

  cases, or whatever else it is. And I think like this is a perfect example of, you know, a space where the user is actually driving the innovation themselves because students like free things or cheap things that help them do better more quickly. So that's a good, that's a good use case.

• 31:51Alex Kantrowitz?

  User driven innovation. I like that. And it's not just students. It's it's ad agencies are starting to use it as well. Like you talk about like trying to find the answers to the test. The added agency, the ad industry is a place where this happens. And this is the last one of the three stories that we're going to talk about in terms of the practical impact today. But again, from the Wall Street Journal, AI saves ad agencies a lot of Should they still charge by the hour? And this is a story basically that ad agencies have been charging by the hour to clients. And now, all of a sudden, they have ChatGPT that's made them far more efficient. For instance, you know, if your job was to write headlines for a brand.

• 32:33Alex Kantrowitz?

  Now, instead of having to come up with 50 unique ones, maybe you can write five unique ones. And ask ChatGPT to extrapolate out. Or do the same thing with creative, like creative resizing is now becoming much easier with generative AI. And all those hours that ad agencies spent doing that work, which was really repetitive and not value add. Now has become pretty automatable with artificial intelligence. And they're trying to find a new way to charge. And some are going to charge now based off of specific results versus hours. And maybe we see that in places like law, right? And other disciplines. So Ranjan, I'm curious, do you think that ad agencies should still charge by the hour?

• 33:15Alex Kantrowitz?

  Given that they were probably not charging for, you know, such valuable work a lot of the time. And now that ChatGPT has all of a sudden made them efficient. They realize that like a lot of the things they were doing weren't really additive to the client. I mean, what do you think the best solution is? And what do you think this story tells us?

• 33:33Speaker 01

  I think first, it's incredible that you just associated innovation and ad agencies. I think every ad agency out there would be ecstatic that someone out there is.

• 33:45Alex Kantrowitz?

  Advertising listeners, shout out to the ad listeners.

• 33:48Speaker 01

  Yeah, I, I think this story is much, much bigger than just ad agencies. And I loved this one because I think the pricing of everything that we got used to could change. You just said it, whether it's ad agencies, law firms will be very similar. Like outcome based pricing. And in healthcare, this has been a conversation for years. The idea of outcome based pricing where like the actual results are where you bill. Rather than the treatment itself is a much, much better way to potentially approach this. So I think first. So many of these industries, the way the entire pricing structure changes, i- it's going to change. And I even think in SaaS, that's going to be the case.

• 34:33Speaker 01

  And there's been a lot of talk around this with even Salesforce's AI agents or in many others is that seat-based pricing doesn't make sense in a lot of ways. Like if you're automating a bunch of workflows, how many people are using it is totally irrelevant. So there's definitely going to be some new pricing structure that's something around outcomes, around the amount of compute that is consumed. Like, like it's, it's actually kind of exciting again, like on the productization side of this, like it's going to completely change the way and different industries price and it'll be better, I think.

• 35:09Alex Kantrowitz?

  Okay. So after me like sticking up a whole fight about the practical applications of this technology at the beginning of the show, I'm starting to see it your way. I do think that like, there's a lot of room ahead in terms of whatever we have today to apply it practically. And I think maybe we should have flipped this, like that's actually the big story and where the models go is sort of now that I'm talking about it out loud, I still care more about the where the models go.

• 35:36Speaker 01

  Actually, no. Are you saying it's time to build?

• 35:40Alex Kantrowitz?

  It's time to build, Ron, John.

• 35:41Speaker 01

  It's time to build.

• 35:42Alex Kantrowitz?

  Time to build, it's time to break through that asymptote, man, and just get going.

• 35:47Speaker 01

  Just break the asymptote, man.

• 35:49Alex Kantrowitz?

  So on Monday, I spoke with Gustav Soderstrom of Spotify and managed to fit in a question about parent mode. But we also spoke a lot about whether generative AI will replace music and whether that is something that can touch someone's heart, whether it was developed by a human or a machine. And, um, you know, I'm looking through our doc and I see that you have inserted that story back into the conversation. And I'm ready to hear your reaction to what happened on Monday.

• 36:22Speaker 01

  All right. So first of all, and I had asked Alex to ask Spotify CTO, CPO about parent mode. And my problem is since I've had kids, my Discover Weekly has been destroyed. I had screenshotted my most recent Discover Weekly when I opened it and the first song is the poop, poop, poop song.

• 36:46Speaker 01

  Yes, and basically, everything in there is a is just something. Number one hit, it's it's kind of a banger, but uh, basically like not being able to separate out what my kid is listening to versus what I'm listening to makes it, it just destroys the algorithm. And there's no like, I want to hit a refresh button. He had made an interesting comment that uh, like, well, making different profiles is actually really bulky and switching. It's kind of a pain. I could make playlists for my kid and then say, do not add these to the algorithm. But I think it's like a reminder that the most complex, advanced recommendation system in the world with basic UI problems does not work. And this is another

• 37:31Speaker 01

  example. I think that's another good example of that, that like, you could have, and I've read stuff for over the years, Spotify, how they populate discover weekly. They're very early to machine learning recommendation, but a simple UI problem makes it so I end up with the poop poop poop song as number one.

• 37:49Alex Kantrowitz?

  Yeah. And I do think that they're good, they're, it's interesting that they're going to look at these signals and try to like, get better at figuring out where your listening doesn't match what you usually listen to and try to exclude that. But it seems like a problem that's going to take some time for sure. So enjoy the poop poop poop song and Wheels on the Bus. I was like, we were talking about it on LinkedIn. I was like, oh, enjoy Wheels on the Bus. You're like, no.

• 38:11Speaker 01

  No, it's much worse. But actually, did you, maybe what could solve it? Did you try the new AI generated playlist feature?

• 38:21Alex Kantrowitz?

  No, but that's pretty cool. So talk a little bit about that. Cause that Gustav and I were talking about that. Then it came out this week.

• 38:26Speaker 01

  So it's basically you enter a prompt and you get a playlist and you get a bunch of recommended songs and you can kind of like plus, plus, plus, and choose a bunch of the songs you'd want. And so I literally was like, one of mine was. You are a frat boy in the year 2002 in Atlanta who wants some party songs. And it literally recreated my early call, my college experience and it was so good. It got the most cheesy, but actually correct and beautiful, beautiful stuff. So then I made a running playlist and I gave it a couple of examples. And again, it nailed it.

• 39:05Speaker 01

  So I, it had me start to start thinking like, imagine if it really can get it to where you just depending at that moment, are in a particular mood and a really, really, really specific mood. And you just tell the system that and it creates this playlist for you. And I, I think this is going to be big for them because I think not everyone is the kind of music listener, which I am like, who spends time making playlists. So this could really solve this problem for a lot of people.

• 39:36Alex Kantrowitz?

  Yeah. And this is what I was trying to speak with Gustav about. It's like, what if you write your prompt and then you actually get AI generated music that will speak to you more than the human generated music? And you actually also dropped this in our document. And I was like, what am I looking at here? And it's a bunch of drone video with this like really lovely song in the background. And the song you later let on totally AI generated.

• 39:59Speaker 01

  Yeah, I, I got a drone recently and have been having some fun making some videos with it. And I was up in Hudson Valley in a town called Cold Spring, New York. And literally just with Suno made a prompt. Uh, it was like, you write a song in a folksy acoustic style about a town named Cold Spring in Hudson Valley and talk about the foliage. So I made this video, put this song as the backing music, shared it with my family in a, uh, Apple Photos shared album that we use. And my uncle was like, this is a beautiful singer. Who is she? And then there was that moment of I'm like, do I divulge? And then I did, I was like, yeah, it's AI, which, which blew some minds, I think. The song was genuinely good.

• 40:44Alex Kantrowitz?

  Yes, it was really, I enjoyed it very much. All right. And also now that we're talking about Spotify, I'll just note that we are now doing our Wednesday shows via video on Spotify. So if you've recently found the show, this is how it goes. We do Wednesday interviews with folks in the tech industry or outsiders trying to change it. And then on Fridays, Ranjan and I talk through the news. So these shows will be audio only across all platforms. The Wednesday shows, video on Spotify. And if you're new here, we appreciate you coming aboard and giving the show a shot. Definitely seen a bunch of new subscribes come in and we appreciate you all. Before we go to the break, just want to say, share some gratitude to a couple of our listeners.

• 41:28Alex Kantrowitz?

  First of all, Context1930 shared a comment on Trump in the reviews of the podcast. And it was a critical review, but it was five stars. We're taking it into account and we appreciate the way that you shared that feedback. It helps us and it helps the podcast. And I think that's the best way to do it. So thank you, Context1930. Also, Luke Squire made a comment about our discussion about polling versus prediction markets on LinkedIn, basically in favor of polling versus the prediction markets. We've got a couple of those. And that's another great way to share feedback and thoughts on the show, share it on LinkedIn. And critical or not, we love to hear what you think about the show. And it obviously gets the word out to others.

• 42:12Alex Kantrowitz?

  So we appreciate that. Thank you, Luke. And then Graham Hyde emailed me with our, on our email address for feedback, which you can find in the show notes, and made a very interesting point. So we had talked a couple of weeks about how the government should build its own Starlink. We talked about that a few weeks ago. And Graham pointed out, and I'm embarrassed to admit that I didn't know this, that the Department of Defense has actually already started work on its own satellite internet company or communication system, working with SpaceX. It's called Starshield. Ranjan, did you know about it? Here's from one story about it. It's a militarized version of SpaceX's Starlink internet satellites with enhanced encryption

• 42:54Alex Kantrowitz?

  and other security features. And unlike Starlink, which is a commercial service, the Starshield satellites would be owned and controlled by the US government. So the government is actually building this.

• 43:04Speaker 01

  I did not know that, but we need to do more space coverage.

• 43:09Alex Kantrowitz?

  That's right.

• 43:09Speaker 01

  I think, I think space for 2025 is going to be a good topic.

• 43:15Alex Kantrowitz?

  All right, Bezos, put us in a spaceship. We'll take our mics and we'll do it.

• 43:20Speaker 01

  And everybody will be happy. Live from Blue Origin.

• 43:22Alex Kantrowitz?

  That's right.

• 43:23Speaker 01

  2025 goals. Yep.

• 43:25Alex Kantrowitz?

  Bezos, we know you listen. So just do it. All right, let's take a break. We're going to talk about Blue Sky. And if we have time, we're going to talk about Apple smart glasses right after this. And we're back here on Big Technology Podcast Friday Edition. Just a few minutes left, but I definitely want to talk quickly about this Blue Sky surge. So Blue Sky is now up to 15 million users. And it is, it's really soaring in the wake of the election. I don't know about you, but I've definitely noticed myself and lots of other folks have talked about how they've seen mass amounts of followers delete their Twitter accounts. And I think Blue Sky and Threads, which Threads has added 15 million users and just since the start of November have definitely

• 44:07Alex Kantrowitz?

  benefited from this. So do you think that this has staying power? Or is it a flash in the pan?

• 44:12Speaker 01

  I think it does have staying power this time. So I went back to the Blue Sky account I'd created like a year and a half ago, maybe. And it was interesting. I actually saw people who I would engage with, with on Twitter all the time, who I hadn't really processed had left, but just kind of hadn't thought about or noticed in a while. And suddenly I was like, oh, wait, they're, they're alive and kicking and just having those same conversations, especially around a lot of like economics topics, finance topics, even in tech as well. I found a lot of the, a lot of tweeters from my past in there. So I think, because again, from a product standpoint, from before even like creating an account, signing in.

• 44:58Speaker 01

  Following was kind of a pain. And then now, when I went back, it's it's pretty much on par with Twitter slash X. And so I think there's there's staying power here because again, the actual technology behind any of these apps is not that complicated. It's purely about the content and the people involved. So I think it does represent a risk this time, but we've said this a few times now, so.

• 45:24Alex Kantrowitz?

  Yeah, and I'm about to pour some cold water on this. Max Reed, who writes Reed Max on Substack, he says, from what I can tell, the users who've been joining Blue Sky en masse recently are members of the big blob of liberal to left wing journalists, academics and lawyers and tech workers, politically engaged email job types who were the early Twitter adopters and whose compulsive use of the site over the years was an important force in shaping its culture and norms. But he says, Blue Sky is really acting more like a large Discord server, a place to socialize bullshit banter and kill time than a proper Twitter replacement. So basically what he's saying is it's inhabited only by those people and it feels a lot like the old Twitter,

• 46:06Alex Kantrowitz?

  but it just doesn't have the user numbers that it used to have. And therefore, the Blue Sky boom might be an illusion. What do you think about that?

• 46:16Speaker 01

  No, so I think when I had gone on it way back, it was like the extreme version of the anti Elon Musk, anti Twitter types. This time, there's a lot of sports highlights on there, which could be my, I mean, there's more kind of normie content on it this time around. And I pretty quickly was able to find a lot of good follows. So I think that that's still kind of how things were. And maybe that's his specific feed. But I think it's different this time.

• 46:49Alex Kantrowitz?

  Let's see. I don't think that it's going to work. One thing we can say for sure is it doesn't look like Threads is working. I mean, Threads added 15 million people since the start of the month. And Michael Leirman, who I work with as an editor, pointed out to me, he's like, "Does it feel like that?" No, it feels like the same thing. It's just people complaining about Threads.

• 47:12Speaker 01

  I can't with Threads. I opened it up again. And yeah, I mean, it's so odd in terms of like, and I've tried to follow a bunch of people on it, but I don't know, it's, it just does not deliver kind of more real time, interesting conversation. I will admit, like, Blue Sky, I actually moved it to my homepage on my iPhone and moved X off of it. And then in New York this week on Thursday, we were looking out our window and you saw smoke coming out of a building in Midtown. I don't know, did you even hear about?

• 47:52Alex Kantrowitz?

  Yes, of course.

• 47:53Speaker 01

  So there was a fire in Hudson Yards. Apparently it was like a mechanical broom blew up or something like that. But, uh, and no one was injured or anything. But, but I actually tested, I went to Blue Sky and searched NYC fire, nothing. I went to Threads, nothing. I went to Twitter and got all the info I needed right away.

• 48:14Alex Kantrowitz?

  Yeah, that's what I think Twitter is going to be, the one that's staying power. It's the network effects. It's very, very, it might be the most difficult to replace social network. Like, we've seen, like, Blue Facebook, at least in the US, start to lose a lot of interest. People are on Instagram now. I just don't see it happening with Twitter because it is just a group of sickos that have been on that platform. And the network effects there is very difficult to displace. Okay, last story of the day. Apple is thinking about smart glasses, was in our doc for like, the last week, but there's been a lot of politics to talk about. This is from Bloomberg. "Apple is exploring a push into smart glasses with an internal study of products currently on the market." The initiative, codenamed Atlas, got underway last

• 48:59Alex Kantrowitz?

  Week and involves gathering feedback from Apple employees on smart glasses. And it's been led by Apple's product systems quality team, part of the hardware engineering division. So it's very interesting to me that smart glasses are already becoming a thing. Meta has a great pair out with the Ray-Bans and Apple has been beaten to the punch here. And I think it's not going to be too long until we see Apple build a product like this of their own. If not one with an enhanced Siri to hit one of your most favorite things. What do you think?

• 49:35Speaker 01

  Yeah, I think I mean, I told you a couple of weeks ago that I'm testing the Snapchat, the Snap Spectacles, which is their new augmented reality glasses that you can get as a developer versus Orion from Facebook. The actual AR glasses are not available for any kind of like general release. But after using the smart, the spectacles, it's they're amazing. And I talked about it like even my son can use them instantly. My mother, like any one of all ages and kind of like technical technological proclivity can just pick them up and use them. And I think this is the, this is the form factor of the future.

• 50:17Speaker 01

  This is like what we're, we are gonna all own some kind of glasses. And Apple's got to get on there quickly and the Vision Pro was not that. And VR.

• 50:29Alex Kantrowitz?

  Yeah. What do you think it says about Apple that they haven't been able to do this? It's not a good sign.

• 50:35Speaker 01

  No, it's not a good sign. I think like Apple Intelligence, I mean, it's if you think about it, we have a bunch of misses in a row. Apple Intelligence, maybe it'll come around, but it is so, so far from anything we have seen, even remotely close to useful. The Vision Pro flop. I mean, and I'm still upgrading my Macs and AirPods and iPhones and all that. But it's just, it's, I mean, and again, at their scale, they need to find that next big winner. We, everyone knows it and it does not feel, maybe Siri will work in a few.

• 51:16Alex Kantrowitz?

  I think Apple's best chance is that. Mark Zuckerberg gets so ahead of himself on his rebranding campaign where now he's like, you know, cool MMA Zuck with the chain and the big T-shirt and the long hair that he distracts from the mission and then gives Apple an opening. And you know, I'm a fan of a lot of Zuckerberg's side projects, but there was one this week that I just didn't think hit and raised some emoji red flags for me. And that was a collaboration that he did with T-Pain to sing a song, Low, it's called Low, it's one of the hit songs back in the day.

• 52:01Speaker 01

  I believe it's Get Low.

• 52:01Alex Kantrowitz?

  Get Low.

• 52:02Speaker 01

  Alex, it might have made it into my Spotify AI playlist from 2000's college party music.

• 52:10Alex Kantrowitz?

  And he worked with T-Pain to record a version of this song. It's quite X-rated and T-Pain wasn't even involved in Get Low back in the day, but this is from Business Insider. The duo, which calls itself Z-Pain, released the Slow Down, Not Safe For Work track on Spotify, and it features a heavily auto-tuned Zuckerberg singing original lyrics about going to a club and getting confronted by a security guard. And it features Zuckerberg singing some lyrics that I'd really never wanted to hear him sing.

• 52:44Speaker 01

  Oh, this was awful. I mean, what I kind of love is thinking about like trillions of dollars of market capitalization potentially swinging on Mark Zuckerberg, sitting down with T-Pain with an acoustic guitar. I can't remember, does he actually play it in the video or but singing?

• 53:07Alex Kantrowitz?

  I'm trauma wiping it from my head.

• 53:09Speaker 01

  Yeah, and singing about sweat in the nether regions. And with, and to me, the most ridiculous part is that, as you said in the Business Insider article said, T-Pain didn't even sing Get Low. It was Lil Jon and the Eastside Boys back in the day. So like, just how this came to be and what this could mean, like, you're going around laying off people, telling them this is the year of efficiency, and then you're trying to... Call yourself Z-Pain and come up with some weird alter ego and swi- oh, man, I, I can't with this one. This one was too much.

• 53:51Alex Kantrowitz?

  Ranjan, I think there's only one thing that's left to do at this point.

• 53:55Speaker 01

  What's that?

• 53:56Alex Kantrowitz?

  Uh, that is to, uh, cue up the song and play about as much of it as we can get away with, without being kicked off of the podcast platforms. So, thank you for coming on the show, Ranjan. Thank you, everybody, for listening. And now to play us out, Z-Pain, Mark Zuckerberg, and T-Pain. We'll see you next time on Big Technology Podcast.

• 54:16Speaker 02

  Three, six, nine, damn, you're fine. Hoping you can sock it to me, baby, one more time. Get low, get low, get low, get low, get low, get low, get low, get low, get low, get low. From the windows to the walls, till sweat drops down my balls, till all these bitches crawl. Oh, skeet, skeet, motherfucker. Oh, skeet, skeet, goddamn. Oh, skeet, skeet, motherfucker. Oh, skeet, skeet, goddamn.