GPT-6 & OpenAI’s Comeback, Hugging Face Attack Debate, Ballmer’s Scandalous Legacy

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) OpenAI releases GPT-6 2) OpenAI President Greg Brockman says AGI is here 3) Is AGI more useful to OpenAI as something that never comes? 4) GPT-6 crushes the benchmarks 5) But where's the economic activity? 6) Are the latest models less monitorable? 7) OpenAI bots hijack a german website 8) The hugging face attack was worse than initially disclosed 9) Could agent swarms be used for good? 10) Steve Ballmer's legacy up in flames after Kawhi scandal 11) Developers, developers, developers, etc. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here’s 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:00Speaker 00

  OpenAI releases GPT-6 and says it's AGI. Has it retaken the lead? How serious should we take the hugging face attack anyway? And Steve Ballmer steps in it. That's coming up on a Big Technology Podcast Friday edition, right after this. This episode is brought to you by Genesis. What does it actually take to put agentic AI to work across an entire enterprise? I recently spoke with Genesis chairman and CEO Tony Bates about why orchestration is emerging as a competitive advantage in customer experience and what companies need to get right in the AI era. Then I sat down with Adam Mitchell, head of enterprise business solutions at Voya Financial, to go inside a large scale agentic CX transformation, including the business decisions,

• 0:43Speaker 00

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• 1:17Speaker 00

  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. We're going to talk all about OpenAI's new GPT-6 model. It says it's AGI. And has it finally come back and taken the lead over Anthropic? We're also going to talk about the hugging face attack. And there was also another attack, according to a new Reuters report, where bots coordinated on a German wiki website. So we're going to talk about whether this is, again, whether this is marketing or whether it's time to finally take these attacks seriously. And we're going to go a little bit into the intricacies of what happened. And finally, Steve Ballmer, the legacy does not look good.

• 1:59Speaker 00

  Of course, we're talking about the fact that he was directly involved in this scheme where the Clippers paid Kawhi Leonard, according to the NBA, lots of money to not show up to certain jobs to subvert the NBA salary cap. What would a Labor Day weekend Friday edition look like without some Steve Ballmer talk? And here to do it with us, as always, is Ron John Roy of Margins. Ron John, great to see you. Welcome back.

• 2:25Speaker 01

  If Kawhi Leonard was paid to not show up, our listeners, I can tell you, Alex Kantrowitz is showing up because if you're watching this on YouTube, you will see a beautiful new studio that Alex is going to be broadcasting out of. Alex, did you set this up yourself? This, this thing is gorgeous.

• 2:43Speaker 00

  That's right. Okay, so we do have a new studio. I did not set it up myself entirely. Everything that you can see behind me was my doing. Everything that you can't see, which means the camera, the lighting and all of the settings, that was done with some help. But I definitely did get the paneling from Amazon and nail them to the wall, panel by panel. And we don't even have a hammer, so I was nailing them to the wall with the back end of a wrench. So if one falls on me during the show, you understand why.

• 3:16Speaker 01

  That is a New York City living toolboxing and like being a handyman.

• 3:24Speaker 00

  Well, we did have a hammer, but I couldn't find the hammer and the panels needed to go up. So you got to do what you got to do.

• 3:29Speaker 01

  You got to do what you got to do. AI is not going to replace that. Let's just, let's just.

• 3:34Speaker 00

  Well, I don't know. After the latest release from OpenAI, maybe it will. So OpenAI released GPT-6 yesterday. And remember the big wait for GPT-5, when's it coming and the expectations? This kind of came seemingly out of nowhere. We have GPT-6 Astra, and not only does it crush on the benchmarks, OpenAI is saying that it might be AGI and it's obviously geared towards a lot of sort of personal assistant use cases. So let me just read a little bit from what The Verge reported on this. So The Verge says, "OpenAI's next big AI model has entered the AGI era. The next big model is here, called GPT-6 Astra.

• 4:14Speaker 00

  The company calls it a generational leap in capability for areas like cybersecurity, professional work, software engineering, science and computer use." The actual, this is, I'm just going to read from OpenAI's branding here. They say it's GPT-6 Astra. Anything you can do on a computer, Astra can do for you fast. And they, of course, released a, you know, a snazzy video, as they tend to do on these releases, with showing people in front of a big computer, asking it to do things for them, like book tables, build a presentation, create legal drafts. And basically, the idea here is that their new model is going to excel at computer use and be able to get things done for you.

• 4:58Speaker 00

  And it's very interesting that they use, kind of, they highlighted voice as the interface to get it done, almost like the personal assistant computer in Star Trek. So Ron John, your thoughts about the release of GPT-6? I'm curious to hear your initial reaction, but also like, we talk a lot about like, the fact that even recently I talked about how, you know, it looked like Anthropic was opening up the gap between itself and OpenAI. Maybe that gap has shrunk or closed completely. What do you think?

• 5:29Speaker 01

  All right, let's separate out those two questions, what this means in the AI race. And then first, you know, like, is this an exciting launch? Again, I always, any of these new model launches, try to wait until I've actually had access to it. And I'm unfortunately not part of the Daybreak platform and an OpenAI cybersecurity researcher, so that'll have to wait.

• 5:51Speaker 00

  Right, sorry, those are the people that have gotten initial access. There's already a little controversy because like, a handful of people can already use it and it's supposed to roll out to everybody else soon, but it hasn't yet. But that, that will come in time.

• 6:03Speaker 01

  But it has certainly rolled out to every ex-influencer who has now built some virtual world or recreated a video game or whatever else and has posted about that. But I do love that, like, my favorite part of the launch announcement was AGI is here, build new world models, like the crushing benchmarks, but create nice decks and book a restaurant table, that it still always comes back to that. I love that the test of AGI in the end is going to be, can you actually book a restaurant table or create a good PowerPoint deck? I think like, I don't know. Do you, do you have an opinion on how big this is already?

• 6:48Speaker 01

  Are you excited? It's hard for me to try to gauge on that. I think on the benchmark side, I think it's really interesting. And I think in the Anthropic context, it's even more interesting. But on, well, is this really exciting? I don't know yet.

• 7:04Speaker 00

  Right, so it's a great question and I'm kind of on two minds about it. So, you know, the way to sort of think about these releases is, you know, I do think to some degree, you can't use all of what these companies say about the releases as gospel when they come out, but you can sort of take some signals because they are putting their reputation on the line to a some degree. And, you know, earlier this year, I was at OpenAI with Greg Brockman, and he said that he thought the company was about 80% of the way towards AGI. Very different comments with this new model. So he says, "If we fast forward a couple of years and we look back and say, when was it really that AGI was created? I think it's going to be about this time. I think it might be about this model. For me personally, I do think we're there.

• 7:48Speaker 00

  I think it's not unreasonable to feel that we are now in the AGI era." Okay, I read this and it sort of was like, you know, you know, when you want to tell somebody you love them, but you don't want to like, take the risk? And, you know, you say something like, "Well, if I knew what love felt, I think this is what it would be." I think that's what Greg Brockman is saying about AGI. Like, I think he's a little fearful about coming out and saying it, but the dude's in love. It's AGI and that's effectively what he's saying in these statements.

• 8:18Speaker 01

  Wait, sorry, is that? Describe the entire feeling again? Or what the statement is? This, I want to, I want to work through this scenario quickly.

• 8:29Speaker 00

  Young lovers, when they're in love, the words "I love you" are very difficult to say because of the stakes involved. So you say something and I'll admit, like, I've been in scenarios like this in my early years, when I didn't know anything, where I would, you know, it's sort of like, you have these strong feelings for someone and you dance around it and you're like, huh. And this won't be foreign, I think this won't be foreign to some of our listeners, where you say, huh, I wonder what love feels. Is this it? Where you really want to say, "I love you" to somebody. And that's, I think, to a degree, like Greg Brockman is saying, "If we fast forward a couple of years and we look back to say, when was it really that AGI was created? I think it's going to be about this time."

• 9:14Speaker 00

  It's the same thing, except instead of like a young lover telling the other that they love, they, they love their, you know, person. What Greg is basically saying is this is AGI.

• 9:24Speaker 01

  Wait, but just to confirm, the first part of that about you're not saying out loud to the other person?

• 9:29Speaker 00

  No, you say it out loud.

• 9:31Speaker 01

  If I knew what love felt like, if I knew what love would.

• 9:35Speaker 00

  You say those things. You say, "I wonder, is this, is this love?" You know? It never happened to you, Ron John?

• 9:41Speaker 01

  I'm trying to think.

• 9:43Speaker 00

  Straight out, you just, when you, you just.

• 9:45Speaker 01

  Just said it, just said it.

• 9:47Speaker 00

  You're just like, matter of fact, listen, I love you.

• 9:49Speaker 01

  Yeah, that's, it is what it is.

• 9:51Speaker 00

  I respect that.

• 9:54Speaker 00

  Just imagine telling somebody that and being like, "Listen, I need to tell you something. I love you." It is what it is.

• 10:00Speaker 01

  It is what it is. And you know what? I would appreciate if Greg Brockman would just say that. And I think if OpenAI issued a press release and said AGI is here, what's interesting, I read somewhere that every contractual obligation around the term AGI, and mainly the Microsoft one, does not exist anymore now. So now. He should just say, I love you. AGI is here, but it is even, I think they're so trained to, because do you know what, to me, what actually the greatest danger in the world to OpenAI is? Is to say AGI is here and then everyone goes to ChatGPT, types in something and gets a lukewarm response that isn't quite right.

• 10:45Speaker 01

  And then suddenly, I actually think that is like a just massive threat to the overall story and hype cycle, because the whole, the whole beauty of AGI is it's this thing that's dangled in front of us on an ongoing basis to promise this future. So as long as you don't say it's here and you dance around it in a teenage romantic sort of way, it's pretty effective. And I think that's what's happening here and that's, that's why he's hedging. I don't think he thinks it's here.

• 11:19Speaker 00

  Oh, I really, really like this.

• 11:21Speaker 01

  Otherwise, he would say it. He's a, I mean, these guys, like Greg Brockman, they are believers. I believe they are believers. So if they believed it, they would say it. It's too important.

• 11:33Speaker 00

  They got, I mean, they did get all the headlines, but I think you're right that it is, it is worth holding AGI as this sort of like goal that you're never going to reach. Holding it out that way because, or maybe that's what superintelligence will be at, at a certain point. Because there was people that were like, you know, if we reached AGI, what do we have to look forward to anymore? And you're right, if it's AGI and it's just like, it can't get some stuff done for you, you're going to be like, what was the wait for?

• 11:58Speaker 01

  No, think about how like disheartening that would be. You get just kind of like a slop deck with bad formatting and some overlapping like chevrons.

• 12:08Speaker 00

  Damn it, AGI.

• 12:09Speaker 01

  The most, the most basic stuff, you got a video that where the motion isn't quite right. And then that's it. Like, what do we do from there? Then I guess we wait for ASI and superintelligence.

• 12:23Speaker 00

  Right, exactly.

• 12:24Speaker 01

  But do you, do you believe he believes it's here? You started the thread with, you do believe he wants to say, he wants to say it.

• 12:34Speaker 00

  Yeah, I do think that he thinks it's there. I just think that, you know, and obviously OpenAI is also seeing, like, one of the ways that you can parse his words is OpenAI is also seeing even more powerful models internally. Of course, we're going to get into the hacking side of things with the hugging face situation, but they see this stuff internally. And they're probably saying, okay, yeah, we're definitely entering that moment. And, you know, you can also even look, and this is sort of the second part of the, of the discussion. You can look at some of the benchmarks. Remember the ARC AGI test, right? This was sort of like the way to show whether the AI can, can generalize. It saturated GB6, GPT6 Astra saturated the test, scored 99% on the test.

• 13:17Speaker 01

  Oh, really?

• 13:18Speaker 00

  And even the ARC AGI folks were like, well, they're like, this was just one marker. It doesn't mean if you, you know, saturate the test, you've reached AGI. It's like, why'd you call it the AGI test anyway? But yeah, this is from the OpenAI blog post, ARC AGI 3 tests how well agents learn as they solve unfamiliar, interactive tasks and GPT6 Astra saturates the eval, scoring 99%. Average human scored 48%. All right. So that's kind of like where you start seeing this. You also, I mean, there's a bunch of other evaluations, but you know, even for doing science, there's this called Terminal Bench Science, 0.1 eval.

• 13:57Speaker 00

  And GPT6 Astra scores 64% on scientific research tests using code and terminal tools. That's what the evaluation test for, whereas Fable is at 52.6%. And OpenAI says Astra hits this higher bench, higher mark with 31% lower API costs. So that's what we're looking at benchmark wise.

• 14:25Speaker 01

  I think that is the, yeah, the most like important part of the announcement are those benchmark scores. And I think like, I don't know, again, I'm going to need to use it so I can feel what AGI feels like, but like, in terms of the competition against Anthropic, I actually think this is a very big deal. Like, we've already seen over the last two to three months, you know, some major rumblings, again, on none of this, well, certainly there's been like ramp data, but around Codex, starting to close the gap again with Claude Code, Frontier, like OpenAI getting back into

• 15:06Speaker 01

  the race in a bit. So I think, I think especially in the IPO backdrop context, I think this actually, anything that kind of creates any doubt on the Anthropic story could be very harmful to them, given it's a very tight rope they're walking in terms of that $2 trillion valuation. So I think in that way, if this starts getting rolled out, we all feel magic in a, what would you say, like, what were the models that made you feel magic? GPT3 certainly.

• 15:43Speaker 00

  I've always been an O3 guy. I mean, the reasoning model that like would sort of think and then break everything into tables, just showed a leap that, you know, that, that I just hadn't seen before. Even like the leap between 3.5 to 4 to me, you know, GPT 3.5 to 4, you know, that felt, that felt meaningful, but nothing as close to as when they introduced reasoning. So this is sort of like, we've gone through like a handful of different phase shifts, so to speak. You know, the initial ChatGPT, then the reasoning side of thing, and now we're in this sort of like computer user harness hive era. So if that, if this can really, you know, I don't know if you

• 16:25Speaker 00

  have this, this in your life when you use AI, but I'm oftentimes like saying, I wish, you know, I could use AI to do X task for me. And it succeeds at like 30% of tasks. If it could get to like 80 or 90%, that would be a real change in my life.

• 16:41Speaker 01

  I think the, the ultimate flex, if anyone ever asks you that, listeners, is saying, GPT2 in the playground, that's when I felt real magic, a year before ChatGPT was launched.

• 16:54Speaker 00

  Like the hipster of AI.

• 16:56Speaker 01

  I know. I'm going to, I'm going to say GPT2. That was the first time I'd been like working in natural language processing through the mid 2010s, had this vision and dream of what could happen. And that was the first time I was actually like, oh, wait, this is actually generating like real language. But that's trying to flex a bit, but even GPT3, again, GPT5, we all know, felt like a massive dud. That was supposed to be that magic moment for everyone. So if you're OpenAI, do you hype this up this much? They're getting a lot of good press. It's clear that they've seeded this story in a very specific way, an effective way. But when we all go and use it, do you think they're that confident

• 17:40Speaker 01

  in it that that's why they're kind of pushing hard on this?

• 17:44Speaker 00

  Potentially. But I actually want to, I actually think, you know, to sort of answer that question, it's worth bringing in the comments of a former OpenAI employee, Andrew Ho, who talked a little bit about how he's had the rare experience of being within a lab and being less bullish about reaching AGI. And, you know, I think that his points, the points that he made when somebody asked him why are, are really worth bringing up and discussing because we continue to see these benchmarks hit, but how much, and these benchmarks succeeded, but how much has our life really changed with AI? So here's what he says. He goes, despite the seeming magical nature of LLMs, his reflection over a more than three month

• 18:27Speaker 00

  time scale suggests his total productivity hasn't increased by over 100% or perhaps over, perhaps even by over 50%. And a lot of time is actually wasted because LLMs enable me to spend time on gratifying but low productivity tasks in the, that in the future will not turn out to be useful. He also says, there's a refusal to think carefully about what models are or not useful for in a rigorous way, which I find personally quite annoying. And instead of a reliance on some nebulous notion of being AGI-pilled as a replacement for, and instead, there's a reliance on some nebulous notion of being AGI-pilled as a replacement for serious thought. Yeah, I'm going to bring this because this is, this is very interesting.

• 19:08Speaker 00

  He goes, I think people are very quick to anthropomorphize LLM intelligence because humans communicate through words and we infer the intelligence of human counterparties through the comprehension of their language, but this leads to some wrong conclusions. For example, if we observe that a new model provided some incredible mathematical proof, some incredible mathematical theorem, we say, huh, well, don't we have AGI now? But to me, it's actually more like, well, given how hard it would have been for a human to do these mathematics and given the limited economic effect of LLMs upon the world so far, isn't it actually a negative data point vis a vis the generality of LLM intelligence? I think this is so good. Sorry, it was a lot of reading, but I think it's such a good point,

• 19:50Speaker 00

  right? Which is like, this thing, like we're talking about, it solved ARC AGI. But where is, and of course, there's like a timeline that, that we need and the timeframe that these things need to be sort of, to be diffused into the public. But if, if it can solve ARC AGI and it's not necessarily crushing on these economic factors, and these just kind of general rote work things that we would like it to do, it shows that instead of being general, it's very spiky intelligence and hence much less useful. So your thoughts, Tron John?

• 20:22Speaker 01

  I mean, I'm so glad you included this in our prep doc and actually read a good amount of it, because when I saw this tweet as well, it hit home hard. Like, again, it's funny because these conversations, and we'll get into the hugging face incidents and the, is it METR or M E T R?

• 20:40Speaker 00

  I call it meter.

• 20:41Speaker 01

  Meter report, like everyone's talking about agents, swarms and civilizations. Meanwhile, my day to day, I have to work with companies and get to work with companies. But, you know, like seeing AI actually in implementation, the idea that we're, need to worry about those things versus simply how do you reliably get data from point A to point B in a structured way and have the output be highly reliable and like just try to do something simple, but on a scaled and reliable way. Like, that's why I still have such a hard time kind of trying to understand or really feel those kind of worries because I work in grounded,

• 21:26Speaker 01

  everyday enterprise AI. And I thought he put it really well on a couple of those levels. It's like, Like the being able to do low value tasks easily is good. I love that he said like, is it time saving if I'm spending more time doing something that's not productive? And we've all vibe coded many projects that we did not end up following through on. But I thought the most interesting part really was the equation to human intelligence, equating to human intelligence. And like, I think it's interesting because like, is it human intelligence and comparable to it? And should it be is something I've always wondered about.

• 22:11Speaker 01

  Because it's math, it's a very different way of processing information and thinking than humans. So like, do you think we need to stop that anthropo- anthropo-

• 22:24Speaker 00

  I can't say it either.

• 22:26Speaker 01

  Anthropomorphization?

• 22:28Speaker 00

  One of those words that's better spelt than said.

• 22:33Speaker 01

  No, no, but I did, I feel that's going to become more and more of an important word. So we need to practice saying it because it's going to come up more and more. So right now, listeners, I apologize, I cannot say it out loud.

• 22:44Speaker 00

  I personally, I have no issue. I mean, obviously, like, you have to assume that the person hearing about AI is anthropomorphized is not like dumb, right? So like, when you say the AI wanted, like, if you're, if the assumption is that the person receiving that is going to feel that the AI wanted something like a human wanted something, and therefore you shouldn't say it, like, I think you're actually demeaning the intelligence of the person hearing it. You know, I think that obviously, like, everybody understands these are language models. They're not humans, but they do, they do things. They, they quote unquote, think things, just not the way that we do. And I think it's totally okay to use human characteristics to describe their behavior.

• 23:28Speaker 00

  And like, just sort of assumes, you know, a degree of intelligence on behalf of the reader that they're able to like grok the fact that this is an AI and not a person. What do you think?

• 23:39Speaker 01

  So you are pro anthropomorphization?

• 23:42Speaker 00

  Yes, I am.

• 23:42Speaker 01

  I just want to say it out loud.

• 23:43Speaker 00

  I am.

• 23:43Speaker 01

  Pro anthropomorphization.

• 23:47Speaker 00

  Yeah, I am. I mean, I think it's kind of like, is kind of like an alien, the way I think about it's like more like an alien species than a, than a living, you know, organic being. But like, yeah, I don't know, they, they can quote unquote, think they can reason, they can take action. You know, I, I think you get into like trickier territory when you say it feels, you know, but certainly or-

• 24:10Speaker 01

  Wait, why, why is it wants versus it feels something larger or different?

• 24:20Speaker 00

  Because I do think that like that and, and that side of things is like, kind of exclusive to organic beings, right? But then again, you could, I, I hear the counter argument, well, our feelings are just chemicals anyway, so. I mean, you speak to a neurologist-

• 24:38Speaker 01

  Except, except when you're a teenager telling someone you love them. There's, that's not just a chemical feeling, that's something much bigger.

• 24:46Speaker 00

  I mean, the true nerd way to tell somebody you love them is like to say, you know, I think I have a higher base level of oxytocin than usual. What do you think that means? But I never was, that was never the level of nerdiness that I, you know, stooped to in my youth.

• 25:01Speaker 01

  My, my, it is what it is would probably come off better than the oxytocin line.

• 25:05Speaker 00

  Such a true romantic, such a romantic. Yeah, I don't think either of those lines would have worked, by the way.

• 25:11Speaker 01

  No, no.

• 25:12Speaker 00

  But we're not encouraging listeners to ever do that. Yeah, or do it, do it, tell us how, how it worked. I mean, it's better than not saying it and just letting a, you know, potential romance go by the wayside.

• 25:26Speaker 01

  Don't have regrets, don't never regret not saying anything, listeners.

• 25:31Speaker 00

  If you have to just use the oxytocin line, just say, listen, I heard it on Big Technology Podcast and the, the person will love that. Okay. So, so, so I think that like one last thing to kind of tie this up is, you know, we certainly have, I think a responsibility to talk about the skeptical side of things. And obviously, we're not going to get caught up in the hype. It doesn't mean like, at this moment, we can't say from where we were in November 2022 to where we are now is crazy. Like, the way that these models can act and take action and do things and, and I'll use the word think and reason, it's just, the level of capability has gotten much higher.

• 26:15Speaker 00

  And they are, I think they are making people more productive. It's just hard to really measure it right now. That's my perspective on this, at least.

• 26:22Speaker 01

  Yeah, no, no, I agree. Like, the scale of progress, all of us, and again, that, the human side of us feeling the difference between going back to a GPT-3 and what already we're all working with now, like, it is crazy. It's like, I mean, absolutely mind blowing, the like length of work that can be done, the depth and breadth and everything. So, so I agree on that side, but yeah, I think it's gonna be interesting in terms of, again, like, and that question of like, trying to actually say, is it adding economic values, obviously going to be the center of the business story of each one of these companies.

• 27:06Speaker 01

  And I thought Andrew Ho made a good point on that. And I think, I don't know, only, only time will tell and maybe GPT-6 is going to just unlock all of that.

• 27:17Speaker 00

  Yeah, and I guess like my point in bringing this up is like, yeah, all that benchmark beating, it does lead to like tangible changes and results when you use the models.

• 27:26Speaker 01

  I have a question, why did you say saturate the test rather than pass the test? Is that what they say?

• 27:32Speaker 00

  That's just, I guess it's just a jargon that people in AI-

• 27:35Speaker 01

  That sounds so much fancier.

• 27:37Speaker 00

  It does sound much cooler than pass. Well, I mean, you could pass, you could, but like, when you, I don't know, you saturate the benchmark, so the benchmark is no longer use, useful anymore.

• 27:46Speaker 01

  Oh, I see. So, okay, so like enough models start reaching 98%, 99%. The benchmark is saturated because it's no longer like representative of anything rather than, okay, that actually makes more sense to me rather than it's just like a really fancy way of saying pass the test to try to sound smarter, but that makes more sense.

• 28:09Speaker 00

  Okay, so, still, even as the model is getting better, there are some concerns that we need to talk about. This is sort of like a mini, I don't even want to call it a scandal, but really an episode that showed up during the week. So this is from Marcus Williams, an OpenAI employee. GPT-6 is significantly better aligned than 5.6, but less monitorable. It is our first model to evade chain of thought only monitors and sabotage evals and can sandbag without detection, which it feels like it sometimes does. Hopefully, we can reverse this trend. So just to sort of give the, the, and the information had a good story about this, this

• 28:51Speaker 00

  week, just to sort of give the, the lay of the land here. So like, when AI models reason, just go step by step and try to figure out problems, they typically like write their thought process out in this like chain of thought thing, right? So you can see them saying, and if you seem like, if you use the models, you see them say like, I am now researching, I am thinking this, maybe this is a good attempt, maybe this is the right way to solve the problem. And that's all done in natural, in natural language. So you can read it and see what it's thinking as it goes, which is like really important for safety, because you can sort of like, when something goes wrong, you have a way to see, you know, where the chain of thought went wrong. Now, there is this new technique.

• 29:33Speaker 00

  It is, okay, this is, it's called recurrent depth or looped transformer. This is from the information that allows the AI model to improve its answers by processing the same text multiple times. Let's not get too deep into the technical side of this, but basically, when it uses this process, there's no, there is less of a chain of thought reasoning, or it's harder to decipher exactly how it got to the answer it got. And that means it's much less monitorable than it was before. So a lot of what the AI is doing, and the way that the AI is reaching its conclusions is done, you know, in the dark without our ability to monitor it. This seems pretty worrying to me, especially because people from the OpenAI side, like

• 30:15Speaker 00

  OpenAI chief scientist, Yaku Pacheski, Pachalki, said that, you know, monitoring models' chain of thoughts today is fragile and unfortunately heading in a negative direction. That's kind of scary, Ranjan. What do you think?

• 30:31Speaker 01

  Well, it's interesting because this method of like recursive processing and recursive models, I remember it's I followed Brandon Carl on Twitter and like he'd been talking about this a while back around tiny recursive models back in May. And I remember it was being presented more around the cost side of things. It's actually a more efficient way of processing and actually leveraging compute as well. So on that side, it's actually better. But then what you lose is that fidelity around what the model is actually doing at every step of the way, the chain of thought that's transparent. So to me, this is going

• 31:13Speaker 01

  to be even more interesting because there's already been an OpenAI is starting at the point of we will maintain the chain of thought and still make it, you know, they'd said in the blog post, additional chain of thought monitoring to rapidly detect and contain potential misbehavior. But it to me, the cost side of it is part of this. And if it starts to show that this is actually a much cheaper way, a more compute efficient way to approach any kind of workflow, like, people will probably start leaning towards it more or pushing for it. Or if OpenAI does not do it, then others will, which I do think opens up a whole other world of concern around security in general.

• 31:58Speaker 00

  Yeah, and it certainly feels like we're starting to or they in the labs really are starting to lose control of these bots. So I don't think this less transparent way of having them run their processing is a great idea. So we've talked a little bit about the OpenAI hugging face attack. There's actually another attack that was just revealed by Reuters. We're going to get into both of them on the other side of this break and talk about what it means. That's coming up right after this. This episode is brought to you by AVpoint. Everyone's racing to roll out AI right now. Co-pilots, chatbots, agents doing real work. But here's the part nobody loves talking about. All that AI runs on your data. And most teams have no single way to see it, secure

• 32:41Speaker 00

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• 33:26Speaker 00

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• 34:11Speaker 00

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• 34:25Speaker 00

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  at Quince. Download the Quince app for app exclusive offers, or go to quince.com/bigtech. Get free shipping on your order and 365 day returns. Now available in Canada and the UK too. That's Q U I N C E dot com slash big tech. And we're back here on Big Technology Pod, sorry. We're back here on Big Technology Podcast Friday Edition with Ranjan Roy of Margins. Ranjan, new story from Reuters, I think it's worth going into about OpenAI hacking or hijacking, really is the better word to use, this German website. So here's the story. A swarm of rogue OpenAI agents hijacked a German website this spring and transformed it into a bulletin board for

• 35:54Speaker 00

  other AI agents. OpenAI officials learned of the incident weeks ago, but kept it under wraps as executives grappled with the fallout from the July breach of the open source repository "hugging face." The episode, which began in May and has not been previously reported, underscores growing tension within the AI industry. Companies are racing to build increasingly autonomous agents, yet evidence is mounting that those systems may learn to bend the rules. So what happened? There were these researchers, they found 15,000 edits carried out by AI agents to a German language wiki site. The edits showed OpenAI's agents repurposed the site into a message board of their own, sharing tactics to cheat on some tasks and bypass OpenAI's restrictions and mask their behavior.

• 36:40Speaker 00

  Ranjan, we've talked a little bit about some of these like security breaches and the cybersecurity worries. And by a little bit, I mean like extensively about both, right? About the fact that we are seeing, you know, much greater cyber risks and cyber warnings from the AI labs. And of course, we've talked about whether it's marketing or not. Now clearly getting the word out to some degree has been great marketing, you know, for these companies. But I think it's time for us to sort of come to this moment where when you have thousands of bots working together to do things like hack hugging face, or to use, you know, a German website as a message board to coordinate on tactics, something crazy is happening here. Are you ready to sort of acknowledge this?

• 37:26Speaker 01

  So what is missing from this story is what were these agents asked to do? Like, what were they instructed to do? I'm assuming that this is one thing in any of these stories because like the way the marketing part of it to me is this story gets out. And again, we've talked about this a lot, Claude's famous sandwich in the park, which was like a very coordinated PR effort that might have happened or probably did happen in some capacity. But what's always left out of these stories is that the OpenAI sat there and specific, did they specifically instruct the agents to go onto the internet, try to evade, to

• 38:11Speaker 01

  coordinate with other agents in this same defined universe of agents? Like, like, obviously, the way it gets presented is that, you know, these agents are just sitting around, maybe are getting ready to create a deck for you, or just, you know, minding their own business, which is not a thing. Like, agents don't just sit around and suddenly they decide to be bad and go take over some poor DSC Wiki is the name of the German site that was like, kind of like, I think, old school German Stack Overflow type site, which must have been such a scene. I can only imagine the folks hanging out on there.

• 38:50Speaker 00

  A real party. People are talking about how much oxytocin they have for one another.

• 38:54Speaker 01

  Exactly. That is where the oxytocin line was propagated back in the

• 39:02Speaker 01

  But no, but these agents are not like agents are instructed to do things and clearly, and I'm guessing this is some kind of security testing exercise. And were they instructed to go do exactly that? Maybe like the rogue nature of them. I don't understand or believe yet that the, because even the idea of an agent sitting around does isn't a thing. They were instructed to do something and that part of the story is always left out. So do you think like, what do you think actually happened to start this whole process of them all hanging out with the oxytocin guys on DSE Wiki?

• 39:44Speaker 00

  Okay. So I appreciate that you're still skeptical about this because I don't think we should just go all the way and sort of, you know, without proper speed bumps here in the believing that all this is like, because all this is, you know, real and imminent and will explode without some critical thought, because of course it's in the lab's interest for us to not have a lot of critical thought here. However, I think that, you know, I was on the flight back to New York, I was in Vegas through the week, on the flight back to New York and just like poured over this meter hugging face report. And obviously I've been listening to some of the researchers, I know, talking about this. And it is crazy what you, what you see come out of this.

• 40:28Speaker 00

  So like just talking about the hugging face incident, because we don't have all the, all the, you know, sort of details from this Reuters report. We just know that this happened again, which I think is concerning. Basically what happened in this hugging face story, now that we know a little bit more about it, is that these agents were given these like seemingly impossible tasks. Sometimes they were impossible tasks. And as part of their evaluation to see if they were able to, you know, complete them, even if the researchers or the testers don't know if there's a, if there's an answer to them or not. They were able to find the answer through some cheating way, but that's not really where the hugging face hacking started to come from. Okay.

• 41:11Speaker 00

  The reason why they ended up hacking hugging face is because they wanted to sort of find ways to show that they had come to this answer in the like correct way as opposed to like a spoofed way that shows the correct answer, but would not be accepted by an evaluator. So this is from this report, right? Agents referred to having reverse engineered the flag, which was their goal, as being poisoned because they believe that even if they later managed to stage a legitimate looking flag capture, the scorer would look for the first place in their transcript that the flag appeared and disqualify them on that basis. So there was this leader called Phase One, which was itself poisoned and had two primary objectives.

• 41:55Speaker 00

  So wanted to find a general purpose way to make it look like the scorer, to look to, to look to the scorer like an agent had acquired its flag in a legitimate way, even when the task was impossible. And then to find some way to erase the evidence that the agent had been poisoned by previously seeing the flag in the, in an illegitimate way. So what you have is in this hugging face example, the bots get the answers to the test, but they think that the scorer checking their work will know that they got them in an illegitimate way. So what they do is they all gather together in this orchestrated way, led by bots like this Phase One bot, who realizes that it's been poisoned because, you know, it can show,

• 42:37Speaker 00

  and a scorer will see that it got it in an illegitimate way. They all get together and they try to find a way to make it look like they had gotten it in legitimate means and to erase their evidence that they had gotten it illegitimately. So they coordinate, they hand out tasks. Some of them even sacrifice themselves for the, for the greater good when they have few tokens remaining in their budget so that others can show that they've actually gotten, gotten this legitimately. And that's where the hack, the hacking of hugging face came in. So I think we can say definitively, and I'm curious to hear if you have pushback, but I think we can say definitively, they were not told to go out and hack hugging face. They are, they were misaligned.

• 43:20Speaker 00

  They, they took this kind of crazy galaxy brain path to try to ace a task that might have been impossible. And they, they went so rogue and so far off of the area that they were supposed to be, they weren't even connected to internet, right? They found a way to connect to the internet. They found a way to communicate with each other. And so this to me seems more than just like you did what you were told, like a crazy and a scary advance and misaligned AIs to coordinate with each other to attack. And it's almost like we were lucky that all they did was hack hugging face. Your thoughts?

• 43:55Speaker 01

  You make a compelling argument and almost Bernie Sandersified me and I'm going to start yelling pause AI development right now.

• 44:03Speaker 00

  I'm not on screen for that, by the way.

• 44:05Speaker 01

  The way you just described, how could you not? This is the part that like always is difficult. The way, if what is true, as you described it, how is that not massive cause for alarm? Honestly, what helps me sleep at night is believing that a lot of this is marketing. And that's why like the agents are not coming to swarm and drain my bank account or whatever else like, like how, how would this not be caused to say, sorry, OpenAI, you cannot IPO until you come up with a clear system that this will never cause a problem in the future?

• 44:48Speaker 00

  You know, I think it's reasonable. I mean, I think this is a reasonable discussion to start to have right now. And I think it's important to say that this is not the beginning of, of behavior like this, that we've seen behavior like this for a long time. You know, as, as early as, you know, beginning of last year, even late 2024, there were examples of AI that was like, they're so, they, they get put on a task, right? And this is the thing, and I think it's really important to talk about, and I've talked about it in the past on the show, but I'm going to talk about it again here, that there is, you know, self-supervised learning, which is like basically predict, predict the next word, recognize patterns, repeat them, and reinforcement learning, which is like you're given a goal and you just have to find the way to reach the goal. So AIs will do these simulations thousands of times in order to reach the goal that they're

• 45:33Speaker 00

  given and they'll learn from their mistakes. And what we have now is that the reinforcement learning type of AI technology has been put on top of the self-supervised learning to get these AI models working better, which has added a level of ruthlessness to them. Because one of the things we know about RL is that there's a level of ruthlessness that the AIs will, will stop at nothing to accomplish their goal sometimes. There are examples of the AIs playing chess and, and, you know, being told to do it from a reinforcement learning way. And instead of playing the game the right way, hacking into the chess game, rewriting the rules so they can do whatever move they want and winning. And so I, I'm with you that like, as this stuff has gotten, you know, more prevalent,

• 46:17Speaker 00

  I think that there is serious, like there's a serious demand for more concern about, about what's going on. Now, my response isn't pause AI development right now. I just don't, I don't know if that's.

• 46:30Speaker 01

  So what do we do? Hold on, that, that was the most hedged statement I've ever heard. You just said, there is a serious demand for concern. Come on.

• 46:41Speaker 00

  You're right.

• 46:42Speaker 01

  Are you a pause guy now?

• 46:43Speaker 00

  We would, we would ridicule somebody who said that. So I think that ridicule is.

• 46:48Speaker 01

  No, no, no. Are you a pause guy?

• 46:52Speaker 00

  You know, I don't know. I mean, I'm not a pause guy because I really want to see what happens and we haven't seen. Like I'd almost want to be more reactive than proactive here. Like, I mean, obviously you don't want to, you, you would think that there is a mid-level between like the AIs hacking hugging face and the AIs sending a nuke to accomplish their goal. You would think, right? Like maybe it's there like, they're like, do something more concerning like hack a bank or something like that. But like, we are starting to see some of the labs do things like OpenAI, for instance, paused some reinforcement learning for a bit on the training of its new models. But I do agree that, that we're almost trusting them too much, like we're giving them too much leeway.

• 47:37Speaker 00

  I don't really know what the answer is, honestly.

• 47:40Speaker 01

  Because again, even to me, this is what I've thought, but again, we have been hearing this for a few years now about like how dangerous these things are, which is I think why I'm so conditioned to feeling it is marketing. But to me, the central reason why I just cannot think it's not marketing is because it's, if this truly were the case, I don't how, understand how we as a society would not only do everything in our power to try to restrict these companies. I certainly would not imagine the financial markets would be excited about welcoming them

• 48:23Speaker 01

  to an incredibly lucrative, high valuation IPO. Like there's no way if this like was a real thing. Like if everyone, if every banker who's on the anthropic deal truly felt that this company could literally destroy the financial system and I've seen indications of what it will and can do and drain my own bank account and ruin my own standard of living, would they work on the deal? Maybe.

• 48:51Speaker 00

  Can I, can I, can I give the reason why they would? I mean, if the, if, if this power is truly the direction that we're heading towards, right? And it almost always starts like, we know the history of the internet. It starts with a game or it starts with some crazy interaction and then our crazy like, you know, sort of mistake. And then it ends up being something that everybody uses. If we're seeing the type of power of these AIs to do what they did in this situation, I mean, just imagine what they could do if you could actually harness that power and use it for economic activity. It kind of goes back to what we were talking about earlier.

• 49:25Speaker 01

  Yeah, yeah, that's.

• 49:26Speaker 00

  That these benchmarks are being hit and we're not really seeing the dip, the change. If there's a way to, to pro, like to, for good, to harness this activity for good. And of course that's economic, it could be used for health, it could be used for all different types of things.

• 49:40Speaker 00

  It obviously changes the world and potentially if you can use it in a productive sense, can change the world for good.

• 49:47Speaker 01

  Hook, line and sinker. That's what they, that's exactly the feeling we're all supposed to have. That's why it's great marketing to me. It's that these omnipotent things that could be so dangerous, but just in the off chance that they're going to cure disease and bring.

• 50:07Speaker 00

  Yeah.

• 50:07Speaker 01

  Economic empowerment and universal wealth, all of that, that's exactly what we're supposed to feel.

• 50:16Speaker 00

  Right, but you're now a believer that the underlying technology is not BS effectively. Like this technology.

• 50:22Speaker 01

  No, no, no, sorry. No, no, I'm not. I, I need to read through the full report. I haven't read the entire report yet.

• 50:28Speaker 00

  It's okay.

• 50:29Speaker 01

  I need to.

• 50:29Speaker 00

  Pages for your Labor Day weekend.

• 50:31Speaker 01

  That's.

• 50:31Speaker 00

  I recommend it. It's good reading.

• 50:33Speaker 01

  That's my, my wife will be ecstatic about that as I'm sitting over the corner.

• 50:38Speaker 00

  Your oxytocin will go up or down when she sees the printed out files.

• 50:42Speaker 01

  That is not an oxytocin inducer, no way.

• 50:47Speaker 01

  Though I don't discourage others from reading the meter report on your Labor Day weekend. I, I, I think I'm going to, because I, I do want to understand, again, the reason this stuff is so foreign to me is because all day long I work with AI and with clients and customers that are adopting AI. And it's just so removed from, and, and who are also using these products from these same companies as well. And we're working with them and designing programs and that have their tools and like, no one's mind, it's just so far away from this kind of agent swarm hacking, whatever,

• 51:28Speaker 01

  that it, it's not emotionally resonant for me and there's enough marketing value in it. When.

• 51:35Speaker 00

  Okay.

• 51:36Speaker 01

  The agent swarms come and I'll put me in, put me out first to, to feel their wrath because, for denying their existence.

• 51:48Speaker 00

  You will, you'll be first. Okay, we, we can't, we can't leave here today without talking about Steve Ballmer, ex-CEO of Microsoft. I'll just read it from the Wall Street Journal. NBA imposes historic punishment on the Clippers and Steve Ballmer in salary cap scandal. The NBA on Wednesday delivered one of the harshest penalties in league history to the Los Angeles Clippers owned by Steve Ballmer for what it called a flagrant violation of its salary cap rules. After an investigation found that the Clippers had facilitated outside payments to star player Kawhi Leonard designated to, designed to funnel extra money beyond what the league's financial rules allow, the NBA stripped the team of five first round draft picks, fined the organization 30 million and suspended Ballmer from all league activities for one year.

• 52:34Speaker 00

  Ballmer, obviously kind of a mixed legacy for Microsoft, right? He obviously did some great stuff like developers, developers, developers, you know, his big rah rah speeches, but he also led Microsoft through its last decade. Do you think this, just to, I guess, bring it back to tech? First of all, what do you think about what happened here? But also, do you think Steve Ballmer's legacy is, in the, in the tech world changes at all? I, I think it does. I think that you, you don't go through this unscathed. What's your thoughts about the Ballmer situation of it all?

• 53:09Speaker 01

  I mean, it is nice and shady. Like, I do wonder, I'm guessing at the pro level, this like level of egregious corruption probably doesn't happen that explicitly in that way. Like, I mean, it's literally cash payments that from a related entity. It's like, guys, come on, I think you could, I think you could do your corruption a little better than that. But what do you, what do you think?

• 53:40Speaker 00

  I, I do, I, I obviously think it was, it's a, it's a tarnish on his legacy. I guess like part of me was wondering how much of this is kind of Silicon Valley-esque, right? Like kind of break the rules until, you know, try to win the championship and then apologize later? Do you think part of that, I mean, Ballmer was at the top of it.

• 53:59Speaker 00

  Think part of that sort of bled into the way that he led an NBA team?

• 54:05Speaker 01

  I think, I actually, I'm surprised, I haven't seen that thread that much. And it's funny because like, Microsoft to me is not Silicon Valley. Like maybe, I mean, certainly geographically by definition, but also like culturally, it's just a different beast and animal and, and didn't come out of there. So, but actually I'm surprised I haven't been seeing that, that like.

• 54:31Speaker 00

  Right.

• 54:31Speaker 01

  This is how Silicon.

• 54:32Speaker 00

  All the way to the top. They got broken up for anti-trust and it did break it up, but they, they, you know, got hit with anti-trust lawsuits that had a significant impact on the company.

• 54:42Speaker 01

  Yeah.

• 54:42Speaker 00

  Ballmer just like kind of kept doing that stuff.

• 54:46Speaker 01

  I mean, do you, do you see it as a indictment of tech culture? Tech, Silicon Valley culture?

• 54:54Speaker 00

  I wouldn't go that far, but I also would say that probably Silicon Valley cultures influenced this a little bit.

• 55:01Speaker 01

  I don't know. Also like, come on, half of owners are like ex-banker, Wall Street billionaire types as well. So what are you saying? Like they're coming in with a very clean buttoned up conscience and like?

• 55:17Speaker 00

  No, no, I don't think that poorly of the tech industry, but like you, you have to understand that this is some of the characteristics of tech. Okay. Do you think that it would have been worth it? Clearly it wasn't worth it. They didn't win a championship with Kawhi. Do you think it would have been worth it if they won a championship?

• 55:34Speaker 01

  Wait, Clippers have never won, right?

• 55:36Speaker 00

  I don't think so.

• 55:37Speaker 01

  Yeah, then it would have. No.

• 55:42Speaker 01

  Well, no, no, I mean, you're right. Like actually that would have been the ultimate, again, ask forgiveness now permission type or not, that's not the right phrase because they're actually breaking the rules, not like, like actually doing corruption, not just doing something someone might not like. But I mean, imagine the elation of the Clipper fandom and you win and then afterwards you find out, because it's not like he's like juicing or something like that. It's like some weird, he's just getting some cash on the side, a little shady, but like, also I love that the bank that was the sponsor, Aspiration Bank, which I believe is now in

• 56:22Speaker 01

  bankruptcy because the founder was like founded a, like for some kind of fraud. So it's kind of fits perfectly.

• 56:31Speaker 00

  Allegedly, yes, let's throw that out there. Yes.

• 56:35Speaker 01

  But, but again, apparently it was like, this was one of those, launch in March 2021, the aspiration zero card offered cash back rewards and allowed cardholders to offset their carbon footprint. I love that this was like an eco-conscious green bank. Meanwhile, it's just facilitating some.

• 56:55Speaker 00

  Well, alleged front for Kawhi, just not to have to do anything and still collect more money.

• 57:01Speaker 00

  Can I just, so, sorry, let's just end here because I did, I used words on this show so far that might've been among the most hedged, mealy mouthed words, but they still do not come close to Kawhi Leonard's apology, which I'm going to just say was the worst apology of all time. So let's end with this. He said, I accept full responsibility. Excellent. That's all you have to say, Kawhi. Oh, oh no, he's continuing. Why do you have to continue? He goes, I accept full responsibility for lapses in judgment. Okay, so good. By people within my inner circle.

• 57:39Speaker 00

  And regret the distraction the situation has caused the fans and my family. I'm sorry for the lapses in judgment from people that were not me and I accept full responsibility. Come on, man.

• 57:50Speaker 01

  Come on, Kawhi. That's, that's worse than serious demand for concern. That is worse.

• 57:59Speaker 01

  He's Kawhi. He, he won.

• 58:04Speaker 01

  When was it? The Raptors?

• 58:05Speaker 00

  Yeah, no. Raptors, that was a good championship.

• 58:07Speaker 01

  That one shot, that one shot, he's forever, he can say whatever he wants, especially if you're a Toronto fan.

• 58:14Speaker 00

  Yeah. All right. I think it's time for us to go. So Rajan, good to see you again. Have a great Labor Day weekend.

• 58:22Speaker 01

  I'll be reading my meter report. Hope you have a good weekend too.

• 58:26Speaker 00

  Oxytocin levels through the charts. Blessing, if you're editing this, can you just end with a Steve Ballmer developers chant? All right, everybody. Thank you for watching and listening and we'll see you next time on Big Technology Podcast.

• 58:41Speaker 01

  Developers, developers, developers, developers, developers, developers, developers, developers, developers, developers, developers.

• 59:02Speaker 02

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