Hello and welcome to the latest episode of Last Week in AI, where you can hear us chat about what's going on with AI. As usual, we will summarize and discuss some of last week's most interesting AI news. And as always, you can also check out our last week in AI newsletter at last week in that AI for articles we did not cover in this episode, I am one of your hosts, Andrey Kurenkov. I finished my PhD at Stanford last year, and I now work at a generative AI startup.
And once again, we do have a guest cohost who? Jerry being on vacation, so I'll let her introduce herself.
Hello everyone. My name is Dalia Liu. In my past life, two years ago, I was a senior data scientist at Amazon. I built machine learning solutions for, Amazon customers. AWS customers, also were to, experimentation a b testing, some areas in a general data science domain. I left my full time job to host my podcast called The Data Scientist Show, talking about data science project in different industries and their career journey.
I also advised data and AI companies, community building go to market. And recently I focus career coaching, helping data scientists find, career paths. That works for them.
That's right. So another experience podcaster and interviewer of many people out there in industry, similar to John Crone from last week. And, as we've chatted, maybe a slightly different background with not as much emphasis on AI and machine learning. So your kind of takes and, additions to a discussion, especially this week, which is very heavy, kind of consumer news that affects all of us and not just we technical folk. Will be fun to hear.
Yeah.
Before we dive in to a news, as usual, I do want to give a call out. Shout out to some nice feedback we got on Apple Podcasts. As always, I do appreciate reviews. Someone said great content presented in a fun, engaging way. We do try to make it fun, although sometimes it can be hard. A bit more technical stuff. Someone so good overview of AI hype that is also appreciated. And yeah, just as always,
appreciate reviews. And we also got a few comments on YouTube, including someone saying that AI theme song was soothing as well. And I am going to start including AI theme songs at the end of every podcast, because that seems pretty fun. We'll keep our usual FEMA at the beginning, so if you are a hardcore listener who goes all the way to the end of a podcast, well, you'll get that nice, fun tidbit to look forward to.
And just a quick FYI of this time, we are going to try and record the video of this. Partially because we will have a bit of a chat at the end where I'll be going into my background so you can go and look for that on YouTube. Hopefully I do wind up editing the video and not just, you know, cutting all of this out.
Yeah. My task straight is to ask people questions about their careers. So I have to do this. Angie.
That's right. Well, let's get into news, starting with our tools and Apps section. And our first story to chat about is, of course, GBG four. Oh, so on Monday, OpenAI had a little video stream where they announced their latest model, GPT four Omni, which is, iteration on GPT four, natively trained to accept audio as input and also output images and text. And they had very impressive demos of what it is capable of.
So they had this, like 20 minutes stream in which they showed basically real time interaction via voice with this assistant. Very much many people compared it to a movie her. And I think that's pretty appropriate. So you can hit a little button, the microphone goes on and you can talk to AI and without almost any latency, it processes your speech input and produces a speech output that is very humanlike.
The intonations of voice, emotion, etc., are very high quality, even maybe beyond what you've seen. With typical speech synthesis. And this is coming with all the intelligence of ChatGPT and GPT four models before it, in fact, on benchmarks. And I'll some of the technical numbers and so on, they, say that it's even better across the board on all these tasks. And even beyond all that, they also announced that this model would be, half the cost and twice as fast as GPT four.
So that's exciting for me as someone and working with it and using the API, like, that's a big deal to have GPT four quality intelligence at twice the speed and half the cast. So very, I think highly discussed. And I thought very impressive. Progress here from OpenAI. I, I'm curious what you thought. Diana.
Yeah. I watch some, demo clips. I think the real time translation looks really cool. And, one feature I'm very excited to try. I'm not sure if it's available right now. The, the capacity to view your screen on your desktop. I think that would be really cool to have, AI companion to see what I'm working on. Maybe call me out. And, I don't know if you feel this way sometime. It's very lonely to work on things by yourself, but if you do something like pair programing or,
I try this. Just have a friend do some co-working with me. Silent. I'm more productive because it just feels like, someone's watching, so I think I might be more productive. Maybe you can just chat with it. Is it it her? Him? I think that's a question. That's a feature I'm excited about. On my phone, I also played with the audio. So it's, I think in the demo, it shows a female's voice. I think they provide a few options. They have males voice. Different type of a male's voice as well.
But I guess the default is female voice, because, I think a female, virtual assistant sounds less threatening psychologically. Yeah. Would you take. Would you would you, if OpenAI developed something like her, would you would you date an AI?
Well, many people already are, things like replica and many other apps. And that's it's all whole own question. And it's true that with the ability to do real time chat and have is very, it's true that the female voice in particular highlighted in the demo, was very friendly and warm and kind of non-threatening. And, some people even characterize it as sexy or, you know, similar to, again, the movie her.
Yeah.
The the plot of a movie is that the main character falls in love with an AI. So yeah, one of the many implications of this announcement is probably people, forming even deeper emotional bonds with AI than they have been. And there's been a lot of people forming strong bonds of AI for a while now.
Yeah. I have ChatGPT open right now. I want to see what was its response if I ask.
Okay, let's.
Try it as it to. Hello. I really like your voice. Would you go on a date with me?
I'm glad you enjoy our conversations. However, since I'm just an AI, I don't have the ability to go on dates or form personal relationships. I'm here to help with any questions or topics you'd like to discuss. What's on your mind today?
So it doesn't.
Not right now, yeah.
Not right now.
That is how you make a lot of money. So hopefully they. I don't know. Keep thoughtful on that question because it is I think it's possible to exploit people. You've seen that before. And I, you know, people, can maybe find a way to still convince it, but we'll see. And, there's some more details, worth noting.
So they did also announce a desktop app, that, they demonstrated, for instance, coding assistance where it's, you can, copy some of the code you're working on and it will go straight to, which has to be the app. So the workflow is a little bit streamlined. There's no need to go to a website. And they presumably will add that ability to look at your desktop and check it out. So yeah, this is a big news of a week I think.
And if you haven't looked at any of the demos, there are quite a few showcasing live translation, showcasing two eyes talking to each other and doing some duet singing. It does have a, built in, image processing capabilities. So they say it's natively multimodal. So another thing they showed is that as you're talking to it, you can show it images, have a video stream of what's in front of you. And with your voice you can ask, okay, what am I looking at?
Or, even just show it equations and say, can you help me work through this equation? Things like that. And that also works seamlessly. So. Yeah, I think not. Some people on Twitter in the community have expressed disappointment, surprisingly saying, oh, this is not a GPT five. This is, arguably OpenAI plateauing because the intelligence and the benchmarks aren't that far off from what we've seen. But personally, I'll say I was very impressed.
Yeah. What, what kind of feature do you think you want to use immediately in your personal life or in your workflow?
That's an interesting question. I think personally, I do use chat bots a lot already via, the text input, and I don't think I will in the near term, kind of want to use the conversational aspect of it in general, but perhaps over time, especially for just random questions and thoughts that are not related to coding. For instance, I might try it out more and see if it's fun to just interact with AI in this way, which wasn't really possible prior to this sort of thing.
Yeah.
And moving on to the next story, which is from Google and very related to read GPT four oh announcement. So just a day after the open AI event, Google held its own big event with a slew of announcements related to AI, which we'll cover, over the next few stories. But the first one we'll start with, and that is most related to GPT four oh, is Project Astra, a real time multimodal AI assistant that can be in almost real time without almost any lag. Listen to your voice.
Look at video inputs, and answer questions about what you're seeing. I am basically describing what you just went over GPT four. Oh, and that's because it is very similar in some ways to GPT four. Oh, so in some of the demo clips Google shared, it wasn't quite as emotive in its, voice output, and it isn't quite as real time was a bit more of a lag going on, but still. It seems like OpenAI and DeepMind have been working on something pretty similar, and OpenAI beat Google to official announcement.
But Google then had the unveiling of this asteroid. And in fact, there were some fun examples on Twitter from people working on it of, for instance, someone chatting with Project Astra as they were watching the live stream of OpenAI, and, people walking around the office of Google with Project Astra and showcasing what it can do. So, you know, now we'll have, two of these types of chat bots coming soon, at least.
And Google has announced Gemini Live, which is a voice only assistant for easy back and forth conversation and a new feature in Google Lens for video based searches. So lots of updates. Astra is still in early prototype phase, so they aren't rolling out as soon as GPT for oh, which is pretty much out to many people already. But again, I was pretty impressed by what Google DeepMind have done here, and very few companies are capable of
something like GPT four. Oh, it seems like DeepMind is, even if they are a little bit behind.
Yeah. How do you think those works? Do they literally have spies in each other's company and pick the same day to do the announcement?
Well, the Google IO announcement, I guess we knew that the event would be happening, that there would be a bunch of an announcement. I do wonder if OpenAI planned to have VR unveiling the day before to steal the thunder from under Google to some extent. But in terms of product development, I'm guessing they just both realized that real time voice interaction seemed like a killer. Next, advance that they should both target, and both of them went for it.
Because from a technical perspective, without getting too much into it, some of the things regarding like real time processing are very impressive. But on the other hand, we've had years and years of research on training multimodal, models that accept multiple modalities beyond just text with text and images and now with audio. So it makes sense that the trend is very much been to have more and more modalities as input, more and more modalities as output, and make sense at both.
OpenAI DeepMind kept pushing in that direction.
Yeah. And I also saw the Gemini 1.5 Pro is going to offer, 2 million token context window, the largest of any chat bot in the world. And the GPT four is at one 28,000 context window. And Google is working towards and and limited context window size. What do you think? Do you think it's useful for consumer use case or it's more for storing all the knowledge in the, in the world. What does it mean for a limited context window.
Right. Well, I guess in practice it probably won't be truly unlimited, right? You can't have an infinitely long input and expect to allow them to. Or now I guess not all of them. Now it's a multimodal model. Expect it to process that correctly, but. Even at 2 million tokens, right? That's a whole bunch of books.
And I do think for less sort of consumer applications, but for many industrial applications and for many jobs, at that point, you can input many documents, like maybe even your entire code base.
Yeah.
And have the AI process that and apply. And that's been one of the limitations I found when working with AI for coding, for instance, is that it doesn't have the context of your current code base and your current company and all this stuff. So if it can process a whole bunch of documents, when processing your input and question, I think it'll be much more
effective. And in that sense, having a longer context window and also in addition to that, maybe retrieval that a lot of people have also worked on is to some extent a game changer. Moving on to the lightning round where we'll try to keep it a bit shorter because there is a lot to still get through. And the first story is another announcement from the Google event and that is regarding their search experience.
Google is now rolling out AI overviews which previously was known as Search Generative experience.
It's a slightly less nerdy moniker there, and it is pretty much similar to what I have been experimenting for a while now where when you do a Google search of these for some queries, there will be, Gemini model to process your input and produce the outputs kind of add to top that is not just links, but an actual AI response that has processed the contents of some websites, produced a response, and then there are some attached links for you to follow.
And they are have been experimenting with a search, generative experience for a while now. They are saying it will start to really roll out to more people and, be in more Google searches. Again, something we I guess knew was coming and something that, you know, will be interesting to see, to what extent people will just stay on Google rather than going into chat bots or things like perplexity, because Google already will have AI will tend.
And then the next announcement, because again, there were many from Google, is that they have unveiled their own Sora type model with video. So they have produced some clips that show it generating pretty high resolution HD videos, for various things. A lot of sort of similar things we've seen from saw, with clips of tracking shots of various kinds, some surreal imagery of like llamas wearing glasses, this
sort of stuff. And the video is pretty smooth, pretty different from most previous AI outputs where, you know, even just a few months ago, or last year, video from my I was clearly AI generated. There are lots of ways to see where it was AI with this it's much more natural and convincing. Although I will say looking at the clips, it's nowhere near the quality saw. In terms of it's still pretty clearly AI from this VR model, even if it is a lot better.
And alongside video, Google has also announced imagine three, the latest iteration of their image text to image model, which, similar to reality free and other things, is producing higher quality outputs and more complex inputs that previously would not have worked as well. Have you taking a look at this or in general when sort of was released, how did you react? Where was your mind blown by how AI video generation is progressing?
Yeah. I guess because there are previously a lot of other AI, you know, video generation products like, PCA and, I don't know, I just I saw people have some comparison, but I got some already and are used to, the quality and, it's it's very interesting, I think when it just, AI generated the video when it was just launched, you definitely feel. Oh, wow, this is a game. And then you saw some YouTubers would add sometimes, kind of similar to like a B-roll. I generated the video. You just feel.
Oh, yeah. So obviously it's, AI generated. I think for our humans perception, if you are able to generate something like cartoon, that's really cool, like 2D anime style and, that's fine. But if you want to make us believe it's real kind of footage, I think there's still a long way to go. It has to be, like, near 100% kind of real, because I think a human eye does the same. If it's just slightly off, it feels just not real. That that's how I feel.
Yeah. And definitely with this video announcement, if you look at the videos, there is just some less consistency between the frames, some sort of weird eye blurring. What happens? Yeah, that is pretty obvious. So saw the some videos were convincing. But again, I agree that in most cases you could still tell that it was AI. So and that's why, you know, we highlight kind of showcases focused more on the surreal. And that's kind of magical.
Yeah.
Very saturated imagery rather than the sort of things we often see in TV and movies. And now one more announcement from Google before we move on were even more we have an ongoing, cover in this, but the last one we will cover is their new music, AI sandbox. So in addition to everything else, they are unveiling a new music making tool. It will accept text inputs and generate short audio clips or stems based on the prompt.
And so this is a little bit more cater towards music making as opposed to videos we've seen that generate entire songs that are more, I would say consumer related. And this again, as we have a lot of announcements from this event isn't being available. It's just a sort of demonstration video, but we're working on it, and it may be a long time until any of us are able to try it, but. Google? Sure, if nothing else. Announced a lot of stuff yesterday.
Yeah. And I. Did you watch the ACM man's interview on the podcast last Friday?
I have it now.
So, one of the hosts asked him about, copyright. I think they he mentioned they're not sure about how to credit artist, and then they're kind of afraid to get into the area. So I think they're not doing any music generation.
Generation. I think it's, in this perspective, might be a bold move for Google because, for example, one of the, topic they discussed was if someone want to generate a song in Taylor Swift's style, even if it's not using any Taylor Swift's music directly, tweeting those music, but learning her style from the news articles, her her maybe her lyrics. Is this what is have any copyright issue related to, you know, Taylor Swift? I think that's, interesting.
And, yeah, I think I might play with this because I have some idea generated some fun songs, though, talking about data science struggles.
Yeah. Yeah. A lot of podcasters I guess. Yeah. Do this and I think it's a good point. And maybe that's why they focused more on these short audio clips or stems and more instrumental things like viola or clapping rather than generating songs of lyrics, because copyright is, especially in music, kind of thorny. And one story of a section that is not about Google and it's about the other big player we often talk about on throwback.
So on topic, did not have any of these sorts of massive announcements going on, but they did have a couple. So first, they have announced a prompt engineering tool that helps you craft the best input to and from Vic Cloud to be able to get the most out of it. They also are launching Anthropic in Europe now, so expanding to a wider user base and we'll get to a new, different announcement related to their company and business in just a short while. But Dropbox still in the race.
But where these announcements of the live voice assistance and almost real time audio input, it does seem like OpenAI and Google are maybe leading the pack right now with the most cutting edge AI.
Yeah. What do you think about the, prom generation?
I think it'll be interesting, because a lot of people. Probably still aren't using chat bots in some sense, and I think this is one of these things that people will learn how to craft the inputs. So this might help with that.
At the same time, what I found is with regards to this topic of prompt engineering and crafting prompts in general, what I found is very in most cases, what you want is just to be very clear and you know, almost the way you would communicate to another person, just like lay out your task in a clear terms and it'll do what you
want. And so in some sense it's intuitive and I'm not sure this is required unless you have some very tricky things where you might need to know some of more advanced strategies.
Yeah. And, I feel as the model is getting better, maybe eventually. Do think we still need, a lot of prompt engineering. And, I remember a couple months ago, the prompt engineer. It's a very hot title. You saw something like 500 K salary. I'm. I'm not sure whether this is just, kind of a research role for the short period of time, I feel as the model is getting better and better, maybe the engineering on the prompt is going to the effort. There is going to be reduce.
Also, I feel, this feature is important if you are doing something very repetitive, kind of tasks. But I also feel it takes away of our ability to think the specific thing you want to ask. So I think, for example, if you want to, doing something like create an architecture for like a workflow or a pipeline, maybe I would say it's a good idea to at least think about it a little bit, because you might get influenced by the prompt generator, which is only trained on previous
data. And maybe it can serve as a tool. If you feel stuck, it can give you some inspiration or you already have some idea about like the type of question you want to ask and then use it to double check. Oh, if I'm missing something.
Right? Yeah. I do think, personally that the idea of prompt engineers a role is was a bit of a fad and not something that will be here long term. Already I still feel that just being a clear communicator is. Enough to be a good crafter of prompts, and that'll be more and more viscous, as these models are trained to be aligned to what humans want them to do. So. That's my take is no, you don't need prompt engineering as a unique skill set.
You need to be a good communicator, which is true in many jobs, as is, and something that isn't easy necessarily for people. So this is just going to make it more important to be good at communication, than it already is.
Yeah.
And now moving on to applications and business. We have some more exciting news, starting with OpenAI AI. And this came out just after a couple, 1 or 2, I think maybe one day after the announcement of GPT four, oh, with the news that Ilya Sutskever, the chief scientist and one of the co-founders of OpenAI, is officially leaving the company.
This is, of course, following up on the drama from last year, where Ilya and several other members of the board, for a brief, window of time made it so Sam Altman was not the CEO of OpenAI. And then Ilya at the time, of course, said that he regretted that action that arguably hurt OpenAI. So now he is departing to do some other ventures. He never did go back to work after that incident, although he was still an employee, and interactions on Twitter at least were
very friendly. There was no big drama, Yulia posted saying.
Yeah, very corporate speaking.
Yeah, yeah, yeah, positive. And it was great to be up to. And Sam Altman responded saying that he is great and that, there's now a new chief scientist replacing, Ilya in that role. And the one bit of drama that did happen that's worth noting is after Julia's announcement, Jen Leakey, who co-leads the Super Alignment team and is one of the people who published the initial alignment paper, at least one of the early ones from OpenAI on RL. A chef also said that he's resigning and
less corporate speak. I will say, yeah, I resign. Yeah, and that's it. So that does indicate maybe some tensions going on. These two more. So then Ilya leaving, which I think is not as surprising.
Yeah. Also on the idling podcast last week, they asked Sam again about, what happened there. I think he didn't provide a lot of more information, but he did say, yes, there was a conflict in terms of, culture. And previously a lot of board members have experience in nonprofit, come from that world. And maybe since OpenAI is not like a nonprofit anymore. So there is he the way he frame it is, culture clash, I think is probably around
AI safety. And although they didn't promote a new chief scientist, I did see they promoted a, now, like, the promotion I did mentioned this guy. He is the director of research. Jacob had Choki. And, are you familiar with this person? I think he's been. It looks like he's been director of research since last October, and, he might take over kind of the chief scientist role or has more influence in the research.
That's right. Yeah. He is announced as the new chief scientist, in fact. And he similar to Ilia, has a pretty strong tracker track record with research. And he's been with OpenAI since 2017. So kind of a long time employee. OpenAI started, I believe, late 2015, 2016. So he's been there from early on before GPT even happened.
Okay. I'm just looking at his LinkedIn. Okay. He joined as a research lead in 2017. Previously was a postdoc fellow at Harvard. He was a software engineer intern at Facebook. And, yeah, I think he did his, college graduate degree in computer science from University of Warsaw.
And the next story is also about employees and who is leading what companies this time with regards to on topic. And the announcement of someone being hired rather than leaving the company. And the person is Mike Krieger, who is now joining on as chief product officer. And he is a pretty notable figure. He was a co-founder and CTO of Instagram and later also artifact, which, was a personalized used app that was acquired by Yahoo!
And he has an announcement was said to oversee product engineering and product management and product design efforts as we work to expand. This is the language from announcement as we work to expand our suite of enterprise applications and bring cloud to a wider audience. So once again, showcasing that now, these are not just research labs, they are very commercial and they are very much seeking growth and seeking income.
And with this announcement, I think, Tropic does position themselves more strongly in that aim. Next up we are moving out to Lightning Round. And finally, a story not about anthropic or Google or OpenAI. This one is a story about unit three, a Chinese robotics company, and they have released details about their second humanoid model with G1 humanoid agents that notably will be priced at $16,000, which is very, cheap.
It's, cheaper than their first iteration, which was 90,000 and presumably cheaper than pretty much any other humanoid you can hope to get. And if you want to look at it, it's it is human in shape and in some ways similar to what we saw from Boston Dynamics, with very wide range of motions being able to rotate its torso all the way around and just doing all sorts of flexibility. Part of why it will be costing less is it is smaller of any human. It's like almost child sized.
And it compared to some of our other humanoids we've seen, the numbers aren't necessarily as impressive where it can't, carry necessarily as much weight in its arms. The battery life will have two hours per charge and etc., but, yeah, definitely notable. We've been talking a lot about humanoids. I don't know if you've seen this brand, Dalian, of a lot of robotics companies being funded and announcing humanoid robots in development. But this one is adding
to that trend. And, I think with the low cost definitely making it seem more possible, we'll be seeing more humanoid robots out in the wild.
Yeah. I think, after I Model Ridge, kind of converge to a level, I think maybe we might talk about it later. The next, I would probably put it in the real, real world. And, I think robotics probably is the next frontier. And, robotics is really hard. I remember reading something, saying, you know, it's easy to do some live some like, something heavy, do those things. But for those tasks, for example, putting things in a dishwasher is extremely hard for, robots to have the,
precision. And, yeah, I think there are still a lot of interesting challenges for researchers to solve. And, I also look at this robot, I think intentionally they design it in a way that not looking like a human so doesn't have a face, doesn't have any skin. I think it's kind of branded as a task focused robot. I'm curious whether I think there are, I saw this robot in Japan. Those, but I haven't seen it from bigger companies to try to develop. Oh, I think Tesla would launch the robot.
But I don't think that looks like a human. I'm kind of curious. Are people. I don't know, that's a weird thing. I don't I think it's.
True that in general, in commercial, like, big businesses. And what we've been seeing, the trend has been when you make a humanoid robot, it looks like a robot. Yeah. It has bare metal and usually only at most, like an abstract face with a screen.
And while there have been demonstrations of things that look a little bit more humanlike, especially from Japanese researchers, that isn't something that companies are seeking to do, I think, and partly because the aim is to, get these things doing tasks and work and not, you know, socially interacting with us. So that's, definitely a bit more far off than having just these robots moving stuff and solving chores for us.
Yeah. And, I think if I hug a human, the human interaction and the release oxytocin, I wonder if there's research on if I should handshake with a robot. Would I release oxytocin, would boost my mental health as a create some sort of connection.
Maybe. And next story. We are moving on to robot Taxis with a few stories on that, starting with cruise. And the news is that they will start testing in the Phenix area with human safety drivers on board. For a little bit of context, cruise had, major incident last year in a crash that essentially halted their efforts and rollout of their self-driving cars for now, quite a while. So this is pretty notable to show them getting back on the roads and slowly trying to roll things out again.
It seems very carefully since they are adding these human safety drivers. So hopefully I'm a fan of robotaxis, so I hope cruise can get back in the game, so to speak. Yeah.
I only tried Waymo like three weeks ago.
For the.
First time. I think I'm yeah, a little bit conservative. And I feel, oh, I want a company to collect more data before I actually try it. And I also, I think, when we evaluate those accidents, we tend to have a higher standards for robotaxi. We don't necessarily compare that to the accident ratio for human drivers. Sometimes you think think about it is like a little unfair for the researchers, but I do think it's necessary to, evaluate those accidents, even if it's statistical speaking, it's
it's safe. But I think understanding the the real costs is important.
Speaking of which, the next story is that the National Highway Traffic Safety Administration is now probing Amazon owned Zoox, which also is developing self-driving vehicles after two crashes. So Zoox, since March, has been expanding its vehicle testing in California and Nevada to include a wider area and be able to drive and higher speeds at nighttime. And it seems that now its vehicles have been involved in two crashes.
And while they were driving, that resulted in minor injuries to motorcyclists. Zoox, unlike Waymo or Cruise, did not try to roll out a commercial offering yet. So they just are testing. And, not too many details on this yet as to whether vehicles cost it or not. But we have been talking with more and more examples of crashes, and this is adding to that trend of, as you say, the standard for self-driving vehicles is high.
And while our story for a section again on robotaxis, lots of stories on that this week. And this time it's about Waymo. And it is also under investigation from that administration after some crashes and mishaps, apparently there have been 22 reports of crashes or potential traffic safety law valuations. And this intersection will aim to evaluate the software's ability to avoid collisions with stationary objects and its response to traffic safety control devices.
This, yeah, is following up two days after the Zoox announcement, so this administration sure has a lot of work to do with regards to self-driving vehicles, it seems. And on to our next section projects and open source. And our first story is going back to Google. They had some announcements on this front as well, in addition to all the product announcements. And what they announced was first a preview of Gemma
two. So Gemma is their main open source, language model that we've covered previously. Now they're saying that in June I'll be rolling out, Gemma two that will have some larger variants and will, presumably be much better. And besides that, the kind of bigger news on this front is that they announced Polly Gemma, which is an open vision language model.
So unlike Gemma, which is just a language model, this can accept image inputs as well as text, and they are now releasing it through all the usual platforms of GitHub and hugging face. People are able to now build on top of this, and this is pretty notable because there are much fewer open source, high quality vision language models compared to open language models, of which we are now many. So yeah. Google. Continuing to push in this direction.
And this is almost now a new competitive front with meta, of course, also releasing a lot of models. Seems like to be, seen. Seriously, this is one of the things they're investing in. And another big story for open source models. The next one is Falcon two, which is the UAE's new AI model release. So I think last year, or even maybe two years ago, Falcon was one of the first large language models to be open sourced.
It at the time was pretty big news to have, language model where that many billions of parameters out there in the open prior to that becoming much more of a thing with things like clamor. And so now they have launched a second iteration of Falcon with Falcon to 11 B and Falcon to 11 B via LM. Another visual language model like poly Jamma. And the numbers are as usual with model releases, pretty good.
They say that Falcon 211 B outperforms It Matters demo three, and performs on par with Google's GEMA for those, sizes of models. And both of these models are open source and provide unrestricted access to developers world wide. So yeah, open source continuing to. Push forward with more and more models that people can build upon and continue to improve. Pretty big news these two combined this week.
Yeah.
And just one more story for this section. And this one is coming from a hugging face. And it is about, software library rather than an actual, model. So as we covered last week, they released, model for robotics, the robot. This week they are announcing Transformers Agents 2.0, which is a framework to make it so you can have agents that can iterate based on past observations to complex, to complete, solve complex tasks.
And they show this agent framework that, for instance, using Lama 370 B instruct agent, it can outperform GPT four based agents in the GUI leaderboard. As with other software announcements, this one is notable just because Huggingface libraries are used very often by people after building software and agents is one of the challenges we haven't quite solved with language models and with AI in general. It's still very much an ongoing effort.
So having this, library for people to build upon could accelerate that significantly. Moving on to research and advancements, which we'll have just a couple stories, not too many, this week. The first one is the platonic representation hypothesis, a pretty interesting conceptual paper, not a new breakthrough and performance, but very interesting ideas.
So the key idea being presented in this paper is that platonic representation hypothesis that says that neural networks trained for different objectives and on different data and modalities, are converging to a shared statistical model of reality in their representation space.
In neural networks, when you give it an image or give it some text that gets mapped to a big set of numbers, the representation and what this paper shows is that across various models trained with different data sets and so on, as you get bigger, as you get more performant, as you get more, able to do multiple tasks, the representations converge and become more and more similar.
And so there is this hypothesis that there is a one true kind of ideal representation of underlying reality, where images and text and so on are just kind of, projections from reality. And they have a lot of details in this paper as to why this initial hypothesis may be true with things like the capacity, hypothesis that if a non optimal representation exists, then larger models that can explore more possible solutions in terms of representations will.
Find that optimal or get closer to that optimal representation. And then in addition to that, if are, where's the multitask scaling hypothesis that an increasing number of tasks, well, be subjected to learn representations that can solve all of those tasks, and the simplicity bias hypothesis, saying that larger models can fit the data in different ways and will generally tend towards the simplest possible solution.
It's a very interesting kind of insight and hypothesis, not quite proven in this, but there are some numbers showing that as you get bigger and as you, get more multitask, the nearness and similarity of these different models gets bigger.
Yeah, it is interesting like there is only the one source of truth is also although it's from different dimension text vision, but it feels like the law of large numbers. If you have, you know, now everything kind of covered in the middle. So.
Right. And it also relates to some extent, to research in neuroscience, where it's been known for a while that representations of images, for instance, do in neural nets do correlate with how representations of images happen in the human brain. And you can actually do a sort of mapping. They're not the same, but there are shared characteristics. And in this paper, they do go slightly into how seems like neural nets are in, for instance, how they represent color are getting more similar to
humans. So that is another kind of point and favor of this hypothesis. Yeah. And next up the other research paper will cover is Sutra scalable and multilingual language model architecture. And in this paper they show how you can train model on over 50 languages while having good performance across most languages, or even being generally much better at English than other languages. And the key technical bit is that we essentially separate language from actual intelligence.
We begin by having a language encoder and then later have a language decoder basically saying in the input phase, we'll take the language and first process the language itself, and then the language model will just learn to think in terms of concepts, so to speak, in a more abstract space where all languages kind of map onto the same thing and the language model reasons on that.
And when they have an evaluation, they show that compared to GPT four, for instance, it's not as good at English or Hindi at all, but it is more consistent across many more languages. So things that GPT four doesn't do quite as well on for instance, Tamil or Telugu. This model does do very well on. And this. I do think it's pretty notable because there are many, many
languages in the world. And if there's an approach that makes it so, model is effective or almost equally effective in all of them, that would be very useful. Moving on to the policy and safety section. And the first story is about a bipartisan Senate bill on AI security.
This is the secure AI act of 2024, and it would require the National Institute of Standards or Technology to update the National Vulnerability Database and the Cybersecurity and Infrastructure Security Agents to update their common vulnerabilities and exposure program.
In addition, the national security agents would be agency would be tasked with establishing an AI security center to provide an AI testbed for research for private sector and academic researchers, and develop guidance to prevent counter AI techniques. It seems like, some of this would go into effect pretty soon. This would have 30 days after the enactment of legislation to evaluate how to do this. And it kind of.
has some emphasis on public private communications to stay updated on threats and safeguard against threats facing infrastructure. We've been talking about a lot of AI bills being introduced in the Senate bill, this one just being the latest one. So it seems like, with AI being as big as it is, there's a lot more efforts going into that on the policy front in the US.
And the next story is about the UK AI Safety Institute, and it has released an open source tool set called inspect that is designed to strengthen AI safety and facilitate the development of AI evaluation. They say that, this is the first AI safety testing platform spearheaded by a state backed body that is released for wider use.
And as part of this, we do release data sets for evaluation, test solvers to carry out with test and scores to evaluate, to work, these, things going through the tests and aggregate the scores into metrics. And this would be open source and possible to expand of more Python packages. So yeah, now, we'll see if the big companies will actually use this and, release metrics on safety and, the kind of metrics that are part of this.
And on to the Lightning round. One more story in the section, and it is about protesters fighting to stop I and how we're split on how to do it. A group of activists called pause AI, what we have covered in the past has protested recently and called for the halt in development of large AI models because they believe it could pose a risk to humanity's future. Family protests have been taking place globally, including San Francisco in New York, Berlin, Rome and Ottawa. And it seems that.
Yeah. I don't know what you know. And this story goes into. Yeah. Not being sure or some members of the movement disagreeing, on the necessary weight. Some people are even considering sit ins at I developers headquarters, with OpenAI being example, where these protesters would just sit outside their offices as
part of a protest. So, still definitely a small effort in general, but I wouldn't be surprised if there's going to be more calls like this by more people to just say, AI is moving too fast. Just stop and let us catch up. Yeah. And to the last section, Synthetic Media and Art. And the first story is once again going back to Google. And they did have one announcement on this front alongside the rest.
The story is that Google's invisible AI watermark will help identify all, identify generative text and video, and this is an expansion on their AI watermarking technology, since I'd may say that, this was first announced in August, but now, Google has enabled Sinfield to inject an audible watermarks into AI generated music. And this will generally expand to any modality, including, potentially text in the near future.
So. Similar to other news you've covered in terms of for a meta open AI, all deciding to include watermarks to be able to detect synthetic imagery. And at least if the metadata is fair, kind of classify it as such.
Yeah. Do you think they need to, unify in one watermark, maybe kind of become like a standard? So every company having the same thing?
I think so, personally, and a lot of companies are. Already doing this with Sea Tupa, where they have a standard that they've collaborated on. Google and the and the meta have not adopted that standard. Exactly. We've, taking a different route and, and possibly it's may not be easy, but it probably would be ideal for there to be a standard that everyone adopts. Next story how one offer pushed the limits of AI copyright. This is about Alisa Shupe, who has successfully registered.
I registered a copyright for a novel she wrote
using OpenAI's chat. GPT this novel is AI machinations down called Webs and Typed Words, and it is among the first creative works to receive a copyright with AI, generate text, and being at least a part of the creation, and the US Copyright Office has granted the copyright registration, but only recognized her as we offer a V selection, coordination, and arrangement of text generated by artificial intelligent intelligence, which means that no one can copy
the book about permission, but the actual sentences and paragraphs themselves are not copyrighted and could theoretically be rearranged and republished as a different book. So yeah, this is still an open question on copywriting stuff. You write with AI, and it seems like we have a bit more clarity of this happening. I'm curious, Diana, for your interviews. Have you started doing any prep for using AI models to generate questions or at least like research background?
Yeah. So because the people I interview, a lot of them don't have any public information online. So it does require me to sometimes do a 30 minute pre-show chat. But, I have a play with a oh, for example, generated a question in the Tim Ferriss style. And, but sometimes the AI generated was a very verbose. I have to, I think I got inspired by the idea. And then I will still probably use a lot of my own, content.
But I do use anthropic sometimes to help me summarize a what would be a good chapter for me to put it on YouTube, highlights because, I don't know, I haven't tested with GPT two for. Oh, but previously I find anthropic has given me better results. When it process like longer context window compared to, to defeat ChatGPT often ignore something in the middle session, only focusing on the beginning and end.
Yeah, it makes sense. A couple more stories before we move on to a bit of an interview section. So the first one is stellaris gets a DLC about AI which features I created voices. Stellaris is a video game and the very latest downloadable content for Machine age uses generative AI technologies to create some assets, including generating voices for an AI and talking Unnest and AI player advisor, which of course, is. This is a controversial topic, especially voiceover and video
games. So this drew some pushback. And the game's director actually had to address it and reassure the players that the AI voice generation, doesn't mean that voice actors, want at least receive royalties for every line created. So pretty significant. And that this is a big game. This is, a big developer, not huge, not like, you know, millions of players, but still, not an indie release necessarily.
And, this is among the first examples I'm aware of, of, commercial professional game studio adopting some AI tools. And the last story we'll be covering is about an AI film festival, the second annual film festival organized by generative AI startup runway that, after it ran, showcased the top ten finalists films, all of which incorporate AI in some form. So, for instance, doing AI generated backdrops, animations, synthetic voiceovers and special effects.
And the title of article says that humanity triumphed over tech because there is some editorial evaluation of the finalists films, and the claim is that the limitations of current AI tools were evident in the films, with some scenes clearly being a product of an AI model, and that some films were constrained by limitations of AI with disjointed scenes and a lack of control over generative models.
But, despite these limitations, some of the films were able to still be good due to strong scripts and performances. So the argument is that human contributions still make the difference, right? We still don't have AI that can generate films that are compelling, and I would argue that that's probably going to remain true for a while. But, we are
still kind of pretty early on. And, I did look at a couple of videos and if not for analysis, it's interesting to see people try to start, and to come up with how to utilize limitations with its current, how do you realize technology with its current limitations to produce something compelling? Alrighty. Well that's it for venues for this episode. Slightly fewer stories. Unusual you do just because you wanted to focus on the exciting new announcements.
So with the remaining time, since television, does host the.
It up the show.
Data science, a show in which she interviews many. People about their paths, throughout their careers and, kind of learnings. Seems like would be fun if Diana did, like, a short little interview of me. So listeners can get a sense for my background and my thinking and I. So let's see how it goes. Diana. You can go ahead and take over.
Yeah. So since we're talking about art, when I was looking at your, personal website, I notice you like, films. You like music. So I'm curious if you didn't become, AI researcher, what would be another career you wanted to get into?
That's a very interesting question. Yeah, I do feel there's a good chance I would have wanted to pursue something in the creative arts. Perhaps with film. I do enjoy, video editing in particular. So I could see myself doing that. And another possible route that I may still pursue at some point is writing fiction. Okay. Because I do enjoy reading a lot, and I've written some short stories and a lot of essays over the years. So I do like writing, even though it can be very hard.
Yeah. I think there's a lot of possible paths for me that are not technical.
Yeah. Have you publish any short stories?
Yeah. Just a couple, a few, in fact, last year and even before the release of ChatGPT, me and a friend started a little newsletter project called stories by AI, where we published one short story per week with the idea to experiment with how we could use AI to aid in the creation of short stories and, still have our kind of control over the short stories and be the authors, but use the tools to, see how
they could help. And as part of that, I did publish, I think about maybe 3 or 4 things I wrote up and we project we stopped around May of last year because it was kind of coming to a point where ChatGPT and these other things were so good, and so many people were creating AI content. It didn't seem like an interesting thing to explore necessarily anymore, but I did have a lot of fun publishing and writing those few things.
Nice. And, what kind of experience do you want people to have when they read your stories or in the future, watch some videos you're created.
I think personally, what I like a lot is when things are interesting, when things sort of like give you a moment of, being taken aback by some new idea or some interesting notion or something you didn't expect. So my if I do write something or make more videos for YouTube, which I did for a while and released a couple of things, I think would be a heavy. Maybe even intellectual component or conceptual component to it and less sort of an action or.
Do you have example?
Well, the short story is I, I have put out, I guess, examples of that where I think the last one I wrote was conceptually, a chronicle of in the near future, a few decades from now. It's kind of a bleak one where it's just dried up, of how humanity descended into decades long wars over resources due to a combination of climate change and, militaries being, continuously more automated with more and more robot soldiers. So essentially, you got into a dynamic where you have
endless war. We have all the sides just manufacturing robots to send out in a battlefield to fight over, resources that are increasingly necessary as climate change and technology racing happens. So that's an example. And there was a little twist of, like, the narrator, of that one was actually an AI that wrote propaganda and was aware of all these secret details and so on. Yeah. So stuff like that.
And it sounds like you do think about like ai a law even in your art creation. So you talk a lot about AI safety. Where where do you stand. Are you more of, you know, Duma or.
Yeah. We've gotten into this with Jeremy, in the past, sometimes. And we are very much it's we have, opposite views of my regular co-host, where my ergo co-host is very concerned about AI, even potentially exterminating humanity. And personally, I'm very skeptical. We should be very worried. For numerous reasons. We had a whole episode, if listeners want to go into that, I think, like later last year on AI safety and alignment.
So personally, I think there are a lot of concerns that are legitimate to have misinformation with scamming, which is already happening, with people, you know, getting addicted to, romance with AI and moving away from human attraction. Yeah, a lot of these very significant things. But I'm very skeptical that there is a real. Pathway. Even if it got to human level, I for that lead to, significant number of people being, as Zoomers say, exterminated.
Yeah, but you're less worried compared to the people on the East Room side. It seems like you're also very excited about the, development.
So in some ways, I think even as someone who's been in the eye for a while. It's come to a point over pace of AI. Progress is a little jarring. And, it's there's so many impacts it will have on so many people like voice actors, like illustrators, like copywriters, and offers in general. And. It's it's hard not to both be excited by things. And I'm someone who uses ChatGPT a lot, and I really like how it helps me do some of my work and some of my writing, but that comes with some costs.
As with previous, technological revolutions. So it's, it's, a sense of excitement at. What people will do with these very powerful tools, combined with some worry about the people who will be hurt by your tools.
Yeah. And you said you have been in AI research for a while. Can you tell us how did you get into AI and what was your journey like?
Sure. It's interesting. It goes back a long while. I guess the starting point, you might argue, was in high school where we had a robotics club where we competed in this, program called first that has various high schools building robots to compete in these kind of sports, like games. And I was part of a software team and a reward some of the very simple AI not not at all like neural nets and so on. So that was my starting point.
And then at that point, I didn't think of myself as like heading towards working in AI and the. Reason I kind of got more into it was later on in college when I took the intro to AI class. I really got excited and curious and impressed by a lot of what I was learning, and that led me to, doing a research internship the summer after that, and then actually joining the lab of a professor as an undergrad researcher and then doing another internship doing research.
So I think it's I sort of naturally gravitate towards it. Then I try to be a software engineer for a while and, and let's say I wasn't quite as excited by it. So I went back to Stanford for a masters and PhD that, also wound up working on AI and robotics. So it's it was a sense of kind of gravitation towards it, you might say.
So you got an internship? After high school, like in college? In a lab. How did you get your first internship?
Right, so they are. I think they're called rescues. Many universities offer research. Summer, internship, including Stanford, for instance. So you can apply as a student to work in, research lab and be guided by graduate students, on a project. And so, one of the big ones, that does this is from CMU and their robotics lab. It's something called, risks. And that's been going on for a while.
So I saw I think I saw a flier for it, like, piece of paper hanging on some professor's door when I walked by to ask him questions and just. Yeah, it really I would not have been aware of it as a possibility. I don't think, had I just not seen that, as I was walking around campus. And that led to a lot of other stuff.
Yeah. I love those stories. And you you from California? You grew up.
I grew up in a mix of places. I was actually born in Ukraine, in Crimea. And when I was five, we moved to Israel. And then when I was 12, my family moved to the US, to Georgia. So my undergrad was at Georgia Tech, and it wasn't until after my undergrad that I moved out to the Bay area, where, you know, a lot of the software jobs and exciting tech stuff
is happening. So now I've been in the Bay area for almost nine years, and given that a lot of AI is here, it seems like I might stick around for a while longer.
Yeah. And, can you tell us a little bit what you're currently working on in your company? Is this the first job you took after you finish your PhD?
Right? Yeah. So this is it. It is a first thing I did after my PhD. In fact, I started there a couple months before my final defense, as I was finishing up. And we are working on a platform where people can create games of AI and publish them for other people
to enjoy. So as someone who has done YouTube videos, podcasts, photography, all these sorts of things, some writing, I one of the things I wanted or considered doing after a PhD was to going to some company that is using very, very impressive advancements in generative AI to enable creativity, for more people to build cool stuff. And I also like video games.
And it just so happened that there was this early stage startup with like eight people that, was founded by a former lab mate who did my, his PhD with the same advisor. So in some way, like my PhD. LED to me being connected to the startup and and led to me having that as an option because they were still tiny, right? I would not have known of our existence had that not led to it. And, I wonder is a little like I've been there a year now and.
We don't have for the listeners of podcasts wondering if they can try it out. Let's just say it's not ready yet. Yeah, it turns out to be a hard problem. But. You know, I think it's good to. Take on hard problems and hopefully in not too long a time frame, I'll be able to share something cool for people to, let them do stuff I would not be able to do without I.
Yeah, that would be awesome. So when you were taking the offer, have you considered, say, joining an AI research lab in Google or Microsoft? OpenAI.
I did think about it. But. I think ultimately I decided to. You could argue, pivot or move away from research towards joining a startup because especially towards the latter years of my time as a PhD student, I enjoyed research, I liked it, and I would probably enjoy working at Nvidia or Google. But I did miss like building something over a longer time horizon in research. Typically you do a project, to write a paper and you work on it maybe eight months, maybe a year, and that's kind of it.
You move on to the next paper, to the next project, and you keep doing that many times over. And so there's a sense where. You don't kind of build something over a long term, or you might, with a succession of papers building on the same topic or questions. But who you're impacting is other researchers and other people trying to ask questions. So I felt like.
I would like to use my skill set of knowledge and and the recent advancements in AI to build something that impacts more people more directly.
Yeah. And. When you started content creation, building a podcast and the news that a while you were at, Stanford. So what made you want to start this newsletter and the podcast?
Yeah, there's a bit of a history behind it where the kind of seed forest that led to the podcast was, I started working in late 2017, actually. And, you know, the motivation at that point was that we were starting to get into a lot of AI hype, and at the time, a decent portion of the coverage in the media was sensationalist or inaccurate. In some ways. This was, you know, just a year after AlphaGo and at that time seemed like a lot of coverage, overemphasized the kind of impressiveness.
Yeah, or in some other ways wasn't quite right and didn't point out that would explain things quite right. So at that point, I started something called Kind of today where we published, overviews of recent, AI headlines where we tried to point out things that were inaccurate and then just provide better explanations that were informed by understanding AI. That, in turn, led to starting the, last week in AI newsletter, because I already needed to be up to date of news to know what to write about.
And at that time, there wasn't really there were some long running AI newsletters already, but nothing had quite aggregated as much. So we started that like mid 2018 actually, and that's still running. And then the podcast happened in. March of 2020, just before Covid hit. Yeah. And the motivation for that was. I guess it seemed like a natural fit. It was at a point where I was starting to roll out and impact more regular people, and not just researchers.
And I had, by that point done YouTube for kind of a while with maybe ten videos and felt that I would enjoy doing a podcast and producing it and and so on. So we started, now over four years ago. Which is kind of crazy, and it's been a lot of fun. So we kept at it just because it is fun and very useful actually, to just for myself to keep track of and use.
Yeah. That's awesome. I remember last time I saw you, I asked you, hey, you work on this newsletter and podcast. I think you are also involved in some other AI related publication, like are you tired? And you're like, oh yeah, I'm so tired, but I don't want to start doing any of those.
Yeah. And it's worth pointing out that, these are like team efforts to some extent. So. And the I newsletter was one of a person who helps out and, on the podcast, there's also co-hosts that help, share their efforts and, yeah. And then my other side project, the gradient, I have sort of taken a bit less of a role to try and make time for other things. So, yeah, I think, it's a challenge sometimes. I did like as part of focusing on this, I
stopped making YouTube videos. The last one I made was late 2020, and that was fun. And, you know, I actually somehow got to like 70,000 views on my last YouTube video so I could see myself doing more of that. But you have to pick your battles and you only have so much time. And I tried to make time for enjoying life as well and not just producing content. So.
Yeah. So what are the things you do to enjoy life?
A lot of it is, appreciating art or entertainment. So lately I've been playing some video games. I've been watching some cool TV shows, for example. Currently I'm watching through Rome on HBO, and that's fun to see. Depiction of a lot of the history and major events of that time. And I'm playing this game called Sky, which is a very wholesome, kind of beautiful game with a lot of nice scenery and social mechanics. And then, I'm a huge fan of films.
So I watch a lot of the classics, and I know a lot of directors names and stuff like that, and, try to make time to go to arthouse theaters in San Francisco, for instance, to see new releases. So that's a lot of it. And, aside from that, I do like. Going to concerts. And. Doing things with friends, you know, going on hikes and so on.
Yeah. So it seems like you do spend a lot of time thinking about the Roman Empire.
Lately? Yes. Lately, yes.
And. So what are something you are struggling with right now?
Yeah. Well. The startup life has its challenges, right? Where I think. Early on. You know, at a point where we are right now where you would say probably pre product market fit, pre growth, pre like knowing if still work you got to be able to sort of live with that certainty of maybe all this work we doing will lead to failure as is the case with most startups. And we just won't be able to solve it.
And that does lead to some stress. And, and, you know, in a startup environment, there's a lot of. Uncertainty and even like. Hi. How you should do things. What things you should do. There's a lot of questions you need to proactively think about. And, take charge of trying to steer the ship. Yeah, when there are very few people. So that's the case. And then. Yeah, it's it's. I'm sad that I can't do more in life, but I can't make YouTube videos. At least.
Currently, if I really tried, I might be able to, but, maybe I have less energy when I was younger than when I was younger. So my output has to some extent decreased where I have not writing much recently, I am not making YouTube videos. I do enjoy doing this podcast a lot, but I do wish I could, or I could manage to carve out more time for creative outlets. Yeah. But you know, yeah, you gotta pick your battles.
Have you missed a week since you started for podcasting?
Yes. We have had some weeks where, just didn't make sense. In fact, we had a hiatus, in late 2021 I believe, or 2022, for a few months, before the release of ChatGPT, where am I? The original co-host of a podcast? Sharon. Joe had to move on. And there was no co-host, so we just paused for a while, but then Jeremy came on as his venue co-host.
Oh, nice. Yeah. Yeah, I can resonate with. I recently also slowed down the production of my own podcast because I'm trying to figure out what are the things I want to do. For example, spend more time with, career coaching course I'm building and learning new, coaching skills and doing personal development for myself. And, also realize I actually want to create more, YouTube videos. I don't have my own channel. Maybe I'll create one for myself.
And it does feel very scary when you have a great momentum and then you all of a sudden stop, you feel like, oh, am I going to disappoint people when I stop a podcast? Am I have quote unquote quitter? But on the side, it also feels oddly freeing in a way that, oh, I don't have to be on this podcast treadmill anymore. Who make the rules? I have to publish every, every week. I'm for for my own podcast. So, yeah, for own case.
Do you feel, oh, maybe you can have other host, so take over for certain weeks and, or do like bi weekly. I mean, right now there are so many I knows weekly they're even daily I podcast. Have you thought of ways to scale the podcast and give yourself more freedom?
Yeah, a little bit. I'm still currently the editor of a podcast as well, so I spend a couple hours each week post recording, doing that. So that's one thing I thought about. I think maybe one of my flaws, or arguably things I could do better at is now that we have some listenership, there's probably a potential for more monetization and sponsors, and I'm taking this as slightly more professional direction, and I really resist that in some
way. Like, I like the idea of just doing this for fun and for the pure motive of, helping people keep up with I. But, we'll see. Maybe I do still enjoy editing it as well and having the full kind of creative control over it, but perhaps in the future I'll find a way to do this a bit more faster and potentially do more like start. Go back to doing interviews in addition to covering news or do YouTube videos or whatever.
Yeah. As I'm preparing this episode with you, I can see how much effort you, you put in. Do you remember particular apple common or I don't know, do people email you, message you, main thing or something that you feel are is so worth it. Do you remember something like that? What do you say?
Yeah, it's. I mean.
You help me get through a pandemic without an audience.
Yeah. I don't know about that, but, there's it's hard to pick one out because, in general. We get a so much like, we covered a few of them in the beginning of the episode, and we do get. I, you know, maybe I'm self-critical. Sometimes when I release something, I'm not sure that this is really that good or it's, you know, we go through like, 35 articles in rapid succession and, there's really not many podcasts out to ever do this kind of thing. Like, usually you cover maybe a few stories.
Right? We are pretty different. And, some times you're not sure that maybe we should do things like, totally differently and we better, but it's nice to see at least a decent number of people like that. We cover a lot, and then they say things like, this is great. This is your top source for I news. This is helping me keep up with I, as a journalist or as, a PhD student, things like that. So. Yeah. That's that's been very.
Nice to see. And, you know, in the first couple years, we were tiny and didn't have much of a listenership, and we just did it for fun. So it's over the past year, pretty much, a year and a half that started happening and been nice to see.
Yeah. I really, you know, respect that you want to keep this simple and pure not to have, sponsorships. I don't know, maybe someone audience, video editor or something. They want to volunteer or help out or, or. I don't know if you're open. I'm sure if people want to do something like buy you a coffee or donation, you can buy better equipment. You can, you know, put it back to the podcast or have a haircut or something.
Yeah. And I will say, we I suspect we've had a good number of paid subscribers on our Substack.
Oh, nice.
Because of the podcast. Partially. And so if you do really want to support and are, you know, a big fan, then one way would be to go over to the last week in that I cite and we do have paid, subscriptions enabled on the Substack. And we don't do like that. That's more pretty much for peer support. We have, an archive of editorials you can get access to if you do that. But aside from that, there's not many perks. We release everything to everyone. Yeah.
Yeah. And if you like, leave a comment. Subscribe, subscribe on YouTube. Five star review. I think those things definitely helps. And speaking of haircut, and before we wrap up, is your hair naturally blond?
No, no. Your hair? No, it's partially bleached. Oh, you can see.
Yeah, it's our signature.
I don't know about that, but. Yeah, I have dyed my hair a few times over the years, and.
They're going for some crazy color.
Not. It's kind of boring. I did dark blue last time. Okay? Like a grayish thing. So I don't think I'll ever go for pink or purple or something, but who knows? I think it's fun. I do try to do a little bit self self-expression.
I can do about gradient. Oh, sorry. Gradient. No pun intended.
That's fun. I think that's probably pretty hard to pull off. Yeah, in terms of process. But aside from bleaching my hair, a fun fact about me is I have how many? Seven tattoos. Oh, wow. So I'm not quite as nerdy as I might seem. Or maybe I am, but.
Do you have anything you can show us? Is it like a, you know, any parts available? Oh. What's that? It's like a tree with a.
Cube of a tree. And then I have this.
Wow. What is this? Also a tree, but like.
Like a neuron tree.
Is this, like, the kind of the brain stem from Westworld?
This is where I just found a photo of a neuron, and.
Yeah.
I did that, so.
Oh, wow. I don't know if that make you more nerdy or less morally nerdy. Cool.
Both. Yeah. Yeah.
Yeah. Awesome. So. Yeah. What is something you're excited in your life or career in the next couple of months?
I'm excited, I think. Hopefully to. Really figure out how to in the startup. We're working on we've had some very productive discussions on, you know, the stuff we've built so far. Maybe in some ways. We underestimated the difficulty of what we were taking on. And so I'm excited to hopefully. Have a lot more insight and manage to build the right thing, so to speak. And then aside from that. I have. Been thinking about maybe getting back to writing more.
Doing some essays and maybe even some short fiction. Just to spread out sort of my focus. So, we'll see. I'll try to see if I can do that.
Yeah. That's. That's awesome. Anything else you want to tell your audience, or do you want them to know?
Not. Not really. I think. I will say, yeah. It's always humbling to think that so many people listen. Yeah. And that a lot of people seem to appreciate this thing a lot. That to me is, just a fun thing to do. Our thing I, enjoy doing. So, I do want to thank people who do reach out or leave reviews and so on because, Charles, nice to have done something that a lot of people are if this in some small way touched by.
Yeah. Cool. Yeah. This is fun. Maybe sometime I invite you to my podcast, or you can interview me or talk more about your journey someday.
Maybe. Yeah. That was fun. But we are getting a bit far into this recording, so I think we'll go ahead. And that is where. And this will be the end of this episode of last week, and I so thank you, Diana, for co-hosting and for doing this fun interview segment that hopefully our listeners will enjoy.
Yeah, thanks for inviting me.
And as we mentioned in our conversation, and as I say at the end, we would like you to share a podcast or leave a review to do those nice things. But more than anything, we do like knowing that people listen and benefit from us doing this. So please do keep tuning in.
I was. Without me and. I'm bringing all the news to you. Me? Too. In. Next time on that island breeze you'll be. Take.
I want you to march on.
I know the angst. And and and and and and.