Alice Albrecht is the founder and CEO of re:collect, a software tool that helps knowledge creators focus and connect. Alice’s background is in cognitive neuroscience and machine learning. In this conversation, we explore how tools for thought such as re:collect can help augment our thinking.
Show notes
- Alice Albrecht (LinkedIn)
- re:collect
- @recollect_ai (Twitter)
- RENDER(); Tools for Thinking conference
- Alice’s re:collect demo at the RENDER() conference (Vimeo)
- Instapaper
- Obsidian
- Roam Research
- Every
- Readwise
- Substack
- GPT-3
- Stable Diffusion
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Transcript
Jorge: Alice, welcome to the show.
Alice: Thank you! Thanks for having me.
Jorge: I’m excited to have you in the show. I saw you present recently at the Tools For Thought conference, but I expect that a lot of folks listening in might not know who you are. Would you mind, please, introducing yourself?
About Alice and re:collect
Alice: Absolutely. Yeah, so my name’s Alice Albrecht. I’m the founder and CEO right now of a company called re:collect. Our product helps you to take all of the information that you come across online or your notes and bring them to you at the moment that you want to ideate or create with it. And we use lots of machine learning in the background to help that process out. I’m sure we’ll get into that piece. And before this, I had a career as an academic. I was in cognitive neuroscience, and then I spent about a decade in tech doing machine learning and data work.
Jorge: When you say that the product allows you… I don’t remember exactly how you said it, but the sense I got was like, as I’m navigating online, I’m capturing what I’m seeing. What kind of stuff am I capturing?
Alice: Right now, they are articles and tweets. So things you’re reading right now. We have plans to expand that as we grow.
Jorge: So, mostly text-based?
Alice: Mostly text-based now, yeah.
Jorge: When I think of that space, I think of tools like Instapaper or Pocket. Some folks might not be familiar with them; I guess it might be worth describing. In the case of Instapaper, for example, there might be an extension to your web browser or a bookmarklet where you run across an article you want to read later, you “clip it,” and then afterward, when you’re going through your stuff, you have a queue of things to read that are nicely formatted or whatever. I gather that re:collect is different than that.
Alice: Yeah. Actually, when you onboard, you can bring in Instapaper and Pocket. So, if you have that information, we’re happy to have you bring that in. And so, we are quite different than that. The crossover there that’s been really interesting is we’re there really to help you make use of all this information. I call those “save it for later” tools or “read it later” tools. Bookmarks work in a similar way.
So, we take in information from there; we take it in as you’re browsing. We can do that automatically, so you don’t have to remember to do that. But we’re really… our goal is once you have all that information, then we’re there to help you do something with that information.
One interesting piece we’ve seen… we’re in private alpha right now, but with our early customers say they have an open tab that they haven’t quite read or they saved something to Instapaper or Pocket earlier, the way our product works, it will come to you when it’s useful. So it, in a sense, can help you to know: okay, read it later, “when.” This is sort of read it “now.” So if you’re working on something, and you use re:collect, you can bring back that information in that moment, which gives you a cue — even if you haven’t read it — to read it now.
Jorge: You say, “come to you when it’s useful,” can you give an example of a use case for that?
How re:collect works
Alice: Yeah. So if you are in our web app or really even online and you highlight any text and click “recall,” we bring back everything in re:collect at the sentence level that’s connected to that. So, say today I was getting ready for this podcast and I was either on re:collect on the web and I was looking at your background or people that you’ve interviewed or tools that you’ve talked about, or really the tools for thought space in general, and I highlight a sentence about that. What I would get back is at the sentence level connected information to that.
Those could be articles that I haven’t read before, though. Those could be things that I saved for later. Those could be open tabs that I had that I wanted to get to someday, but today is the day, right? I’m thinking about this topic. I’m focusing on this this morning; now is the time, really, to get that information.
So once you get the sentence back, you can expand it and see the original article. Or you can go to the original article if you want. So, when I say, “save for later/ the time is now,” it’s really context-based; you’re thinking about something right now. If I bring you in a thing that’s related to it… and even if you haven’t read it before, then this is the time — if you have it — to dig in and read it.
Jorge: This is one of these, “it’d be easier if this was a video show rather than an audio show,” because we could show it. So to describe it to folks, the way that I grokked it — and I am in the alpha, so I’ve test driven it, but I’m not a proficient user; I’ve only just started — and the sense I get is that if I’m reading something online and I have the re:collect browser extension installed, and I have already populated it with some articles — I imported my Instapaper; all of my Instapaper stuff, [and] I have been using Instapaper for many, many years; there’s a corpus there that it can now feed off of. And then, if I have the extension installed, I can select any text on any webpage and say, “show me things that might be related to this from the stuff that I’ve saved before,” right?
Alice: Right. Or you could — even from the browser extension — you can do that same process, but you could write your own sentence there. So, if you just have a thought, you can remove the text from the recall box, and you can generally say what you’re thinking about. So really, it’s very simple but counterintuitively harder to explain.
But all of this uses a lot of natural language processing on the back end. So really. Any full sentence anywhere: it could be on the web, it could be in the app, it could be a thing you just wrote — any sentence, we can show you what’s related to that sentence and what’s connected for you. And it’s your data, your Instapaper that you brought in, and some of your browsing history now.
Designed with the mind in mind
Jorge: The re:collect website says that the tool is grounded in science and that it’s designed with your mind in mind. And you said that your background is in cognitive neuroscience. I was hoping that you’d tell us a bit more about what that means. What does it mean for it to be grounded in science?
Alice: Yeah. I sort of came to this space from a slightly different angle, given my background. When I was a graduate student and a postdoc, I mostly actually focused on vision, but I did work a lot in this area of attention and memory to some extent.
So, when I say it’s grounded in science, what we’re doing at re:collect is we’re designing these machine learning models on the back end to connect all this information, but my goal is to connect it the way your mind would. We have this notion of something you’ve attended to; we have this notion of memory. And really, the core of it is: how would you remember something? How do you connect information when it comes in, and you put it in your own memory, in your mind?
I am from a design perspective, and the principles we use, I’m trying to do everything I can to minimize the distraction. To minimize the things that you would do that would take your thinking off track. In part, that’s why there’s really nothing for the customer to do during the collection process. There’s not a lot of intentional organizing or storing, and I really don’t want you to get distracted; going to try and hunt for that information when it’s useful later.
So, there are these principles that I don’t want you to get distracted. I want you to be in this creative flow state, as it were. So, everything I can do from a technology perspective. That would be the models or the design of the product; I want everything to be in that direction.
And then, from the modeling perspective, really, that’s like the big, big thing, the big moonshot piece there. If I can craft these machine learning models to mimic your attention or your memory in a way that’s useful to you, I feel like that gets us to a better place overall if what we’re really trying to do is augment your thinking.
Memory augmentation
Jorge: The augmentation we’re talking about is memory augmentation, primarily. Yeah?
Alice: Right. So, it’s memory, to start. I firmly believe that one of the bigger unsolved problems right now is that we don’t have our information accessible to us. We can’t remember where we stored it; we can’t remember to store it. There are a lot of these blockers right now. Eventually, I really am — as a later goal — looking to augment your creativity. So, to bring you things that are not exactly related. They’re sort of “one hop out,” as it were, so it’s connected, but it’s inspirational. We’ve already started to build that into the product, also.
Jorge: I’d want to riff on what you were saying there about the challenges that we have in collecting stuff online. And again, [as] someone who’s been using Instapaper for a long time, something that happens to me is I will come across an interesting article online. And I just see the length of the thing, and I go, “I don’t have time for this right now,” so I clip it into Instapaper.
And then, invariably, what happens is that time passes, and when I circle back — usually it’s in a flight or something — I’ll circle back to my Instapaper queue. And I might remember why I had clipped the thing, to begin with, but maybe the time has passed, or the context isn’t clear, or I have other things to go through at this point.
And the sense that I get from re:collect is that one of the advantages it has over a system like any of these “read-it-later” apps is that it’s allowing me to suss out the more granular insights that might be present in those things. So, it’s kind of like spelunking in the content somehow. Is that a fair read?
Alice: It is a fair read, yeah. That’s why the sentence level. I really feel like even a title of an article might be misleading. They might have a really good point in paragraph seven, let’s say, that, unless you’d read the article and saved that intentionally, you may have never even seen [it]. So I think it’s definitely fair to say we kind of do that spelunking for you.
But I think even beyond that, there’s sort of like read for later. We’re trying as much as we can not to keep you in this loop of consumption. So, we could have gone a path where we really just gave great reading recommendations. Like, you know, if you’re on that flight or if you have this two-hour window where you really just want to be reading. So part of the sentence level is also, “can we get you the information you need without necessitating more consumption?”
Like, if we’re pushing you towards this synthesis and creation point — which is really where we shine — you don’t need to read the whole article right now. You really just need this part. So we’re trying to reduce the amount of information at every step too.
Jorge: One dilemma that I find present in a lot of tools for thought is that they have tremendous promise for — you mentioned synthesis and creation, this notion that it’s going to somehow allow me to model my ideas and maybe connect them to sources in a way that you can’t do by just writing things down linearly on paper. But for you to get to the point where there’s a viable corpus for you to do that, you have to feed the system, right?
And when I went through the onboarding for re:collect, it asked me — like you were saying — to import my stuff from Instapaper, which — I think it was Instapaper and Pocket, if I remember correctly, and I chose to do in Instapaper. And I was very grateful to see that feature because I thought a system like this wouldn’t be very useful if it’s completely empty, right? You have to have the sentences in there for it to make sense.
Adding content to the corpus
Alice: Yeah, and we really want to set people up at the beginning for that. So we’re always working on more integrations, more ways to get that information in really easily. We also take, if you want, your browsing history for the last ninety days. We’ll take the stuff that you’ve already done as long as you agree to have those pages in.
So, that’s absolutely right. And I think that is a potential shortcoming of products where you sign up, and then you have this sort of blank database that you’re meant to populate. And then, eventually, something is supposed to emerge out of that. But personally, I don’t know that I’ve ever gotten to the place where I was dedicated enough to spending the time and energy to populate it to actually have something emerge that’s useful.
Jorge: Especially in note-taking tools, right? Like, you get these hypertext note-taking tools, things like Obsidian and Roam, and there’s tremendous promise there, but you actually have to take notes, and you actually have to link things for these insights to emerge.
Alice: Right. And our goal too, in bringing this information in — you know, Instapaper, Pocket — as I said, we’re working on other integrations — I feel like people tend to move from tool to tool when in the note-taking space or when in the “save it for later,” any kind of collection tool, probably because none of them fully meets someone’s needs and a new thing comes up, they want to try it. But what we end up with are these sort of half-abandoned pockets of information in different places. So, I might have started with one tool. Then a new one comes out; it looks more promising, and I transition to that one.
Part of the hope with re:collect is we’re not really in the business of “let’s be your sole information collection tool.” But we would really want to make sure we get all that information and then kind of centralize it for you so that you can do this synthesis and the creation with us. So I think that’s the other problem is people migrate from tool to tool to tool over time.
Jorge: Yeah. And a lot of these tools make it relatively easy for you to export your stuff, but it’s one thing for you to export the content, and it’s another to export the graph. And the graph, it’s like, “what are you going to import it into?”
I think you mentioned that you could explicitly import things, or the tool can import just the pages that you are looking at. Is that true?
Alice: Yeah. So, right now, if it’s a place where you like to do… like, I like Every as a publication source. So when I’m on there, I have the extension where — you’ll see this if you use it — but you slide it over, so every time I open an Every page, it’ll just bring that in for me. I think that kind of as a principle of the way we’re designing the product; we’ll continue to expand. But for now, it’s really there to make sure I don’t have to click every time and remember, “Okay, this has to go somewhere.” just removing that one step of “let’s store this.” And assuming that I can trust that re:collect has pulled it in for me.
Jorge: So that’s a toggle on a per-publication basis. It’s not that it’s looking at everything that you’re navigating and pulling it in, right?
Alice: No, it’s really per publication. That’s part of the sort of alpha testing right now is really getting feedback from people on what they want from that; how much information do they want to come in automatically.
Privacy and business model
Jorge: I’m asking because that was clear to me during the onboarding process, but for folks listening in, you know, it’s important to know that you do put… I don’t know if to call it guardrails, or you get to choose what gets indexed, right? I imagine that you would want to be careful with Gmail or something like that, right?
Alice: Absolutely. Right. And we have a list that we just don’t bring in. We don’t even try. So we know some of those sites that we definitely don’t want to even… you know, even if someone toggled it over, we have guardrails on that way in terms of user error. We also really do value people’s privacy and really want them to have full access to what’s in re:collect, so at any point, someone can go in, and they can see everything that we’ve got in re:collect. They can manage that. They can delete everything from a certain hostname. They can remove certain articles. So it’s all transparent in that sense. We really do try to make people feel very comfortable in bringing their information in, can always bring it out. It’s not opaque or anything like that.
Jorge: So that brings me to something else that folks might be wondering about. And it might be… like you said, it’s in alpha, so it might be very early days, and it might be unclear yet, but I’m wondering about the business model, right? Is it going to be something that you’re thinking of offering subscriptions for? Are you going to be mining that information to show advertising? I mean, what’s the story there?
Alice: Yeah. Eventually, this will be a paid product; otherwise, we will not exist. So we’ll have a subscription business model. Right now, we’re really B2C, so business-to-consumer model. Over time as in any company, those specifics of the business model may change. So I’m not promising that forever-ever. But in terms of advertising, we have no plans to mine the data, to throw advertisements into re:collect. It goes against this idea of helping you to focus and helping you to stay in that flow state. So, I really don’t see advertising as a viable business model for us.
Why Now?
Jorge: So why are we seeing this now? What’s going on? I mean, there’s a lot of excitement, I think, around the tools for thought space, you know? This idea that we have these amazing new tools and services. Why are tools like re:collect appearing now?
Alice: Yeah, I think it’s really threefold. I think we’ve seen a change in the way people are using technology, I’d say, over the past ten years or so. I think now, more than at any other point in time, people have access to more information than they ever have, so they’re actually quite overwhelmed by that. So I think part of the reason for this is people are seeking out — as customers and as creators of these products — tools to help them deal with that kind of information overload that they’re coming across. So I think that’s one piece.
You’ve mentioned, I think, something about only seeing things that are recent but things that are farther back; it’s harder to find. The way some of the algorithms on other products have been developed, we’re really only getting sort of information on Twitter or even Substack — any kind of publication — that’s very new. So, like, it came out a week ago, maybe, and sort of after that, it really dies off. And I think people need that information or are struggling in terms of ways to re-access it. So that’s one. Lots and lots of information. Information overload is really kind of hitting a breaking point, I think, for a lot of people.
The second piece, I think, is a shift societally in terms of the way we’re working. So I spend a lot of time working in — like I said, about ten years in tech data and machine learning — really until recently, I think a lot of the work in machine learning was centered around, “how do we learn to automate human processes? How do we learn to automate things that, in a big company, people don’t need to do?” People sometimes call this another industrial revolution.
As we’re seeing that, and people’s work is changing, thought work is becoming much more important and their creativity is becoming much more important. So, my ability to know things and access that information, and bring them up in the right context at the right time in a business is really critical. So I think, again, from the sort of changing in the way we work, people really, really need tools that’ll give them easy access to their ideas.
And the third piece there is really on the machine learning front. Just a few years ago, we saw with transformer models and, you know, these pre-trained models that are readily available, this huge shift in terms of what was possible. And so, if folks listening have seen, I guess, demos of like GPT-3 that generate text or even these Stable Diffusion demos that, this week, everyone’s very excited about, where they generate images. We’re starting to see the fruits of storing and producing all of this text electronically… for, again, over a decade now. And the models are now able to utilize that in a different way. Or, as practitioners, we’re able to do really interesting things with text information.
So, I really feel like at this moment for, you know, all three of those things are coming together, and I hope that that enables us to have better access and be able to better use some of this technology. So, I’m really excited about that and the changes.
Creating as knowledge work
Jorge: I think that those three points do sound essential. And the three are related, right? Like, they’re intimately related. But in the second one, you said that people are seeking out tools. I think that there’s also — and I think that you touched on this; I just want to emphasize it — there are tools that allow us to better process the stuff that’s coming in, right? Like that’s somehow the inputs or whatever. Better filtering, better… you know, when we have so much available to us, we have to get better at curation. And we’ll see what we pay attention to. But then there’s also the fact that we are creating more and sharing more. You know, you talked about the Twitter integration, and it feels like work for people who are knowledge workers does not just entail managing the inputs. It also entails sharing smartly.
Alice: Right.
Jorge: And that seems like a big sea shift as well.
Alice: It really is. And I think, to your first point, we are creating more. We’re really calling on people that weren’t traditional authors or traditional journalists to be creating a lot of the content that fuels a lot of these platforms. So that’s a huge shift. So, yeah. Thank you for putting that piece out too.
But even, you know, knowledge workers is such a big term, but I really think about knowledge creators, people that put ideas together as an important part of their job, they’re doing a lot of consumption. But the lines between work and your personal persona online, what space do you occupy in this online universe? Those lines seem to be blurring a bit over time, too. So it’s not just that I only share my ideas inside of my traditional work organization. A lot of us are sharing our ideas outside generally. We find community that way. We find our next job that way. We build sort of a persona online.
And if knowledge is this token that’s really important in this newer economy, then being able to, like, really get that out there in a way that you feel comfortable with and you feel proud of is going to be increasingly important too. So that will increase the generation too, I think, as we go. So we’re seeing this increase now. I think it’s going to expand beyond that.
Synthesis and creation
Jorge: The focus of the tool right now, like you were saying, is to help you find the gems, maybe, in the things that you have come across that might be connected to an idea that you’re interested in or focused on right now. I can either do it by selecting a text or by typing a sentence myself, right? And it’ll look through my history, through the things that I’ve imported, and pull out kind of sentence-level texts that might match the model that the AI is building in the backend. That’s how I understand it, anyways. And I’m wondering if we could unpack how the process of identifying these granular insights that I might have come across in some text might support the process of… particularly the process of creation, right? Like, I’m writing a book right now. How would it help me to be able to do that?
Alice: The way I think about this is it starts with synthesis along the way, right? If you’re creating something as big as a book. So our customers tend to be people that write often. Some of them are writing books, newsletters, even people that want to get, like, tweets out often. So for me, when you are thinking through your ideas, you’re doing some ideation for the book — maybe you have an outline; everyone’s process is very different there — but at some step along the way, you are taking your current idea, maybe you are trying to bring in your own past ideas.
You’re synthesizing information that way; you’re bringing it together. Or maybe you are looking at what other people have thought about what you’re working on or what you’re writing about right now and so you want to bring that and bring those things together. And so, for me, the synthesis process is ongoing. It’s always taking two or more pieces of information, trying to put them together, and develop really either more clarity or sort of the next step in that thinking or the next step in that writing.
So the creation side of it, really, most of what we’re building is… you know, again, I wish this was visual, but we have what we call a playground. So you can take your ideas there in cards. You can start to put them together visually. You can… I always encourage people to start to synthesize that information as soon as possible. So you can make a new note card and synthesize, say, a couple of cards.
But eventually, this is building towards an output of sorts. And like I said, that output could be really a lot of different things that are text-based. But pushing you more and more towards that creation towards “okay, you have all of this information; let’s help you make use of it. Let’s help you bring it to a place… we’re bringing the materials to you. We’re encouraging that synthesis. We’re encouraging you to create and share that with other people.”
Modalities of interaction
Jorge: To be clear for folks — and again, this conversation, more than any I’ve had before, has made me think maybe this should be a YouTube thing so that we could show people — but the way that I see it as an early user, it feels to me like there are a couple of modalities in which I interact with a tool. One is this kind of contextual interaction where, like we were saying earlier like I’m either in the context of reading a webpage or Twitter or whatever, and I select something, and I can have re:collect bring to me text snippets that might be related somehow to that text. That’s one modality. The other modality is this playground that you’ve been talking about. And playground, the way that I understand it, allows me to create spatial relationships between these ideas that I’m exploring, somehow.
Alice: Right. So the things I think about a lot are like, how do we make all of this information — for lack of a better word — accessible to you, and then how do we help you manipulate it? So, if you think about the web extension as you’re reading or even as you’re in the playground or you’re in the web app, we’re trying all the time to make it more accessible. We’re trying to connect the right ideas for you; we’re trying to help you synthesize those. But then, what do you do — again — once you have those materials?
So the playground is really our attempt… so for folks — obviously, they can’t see it right now — the playground is this infinite canvas. You can put your cards on, and you can organize them however you like. To me, that was really important as one of the components of this product because it’s very difficult to just get “disembodied,” as it were, snippets of information. And then what do you do? Do you just put them in a linear Google doc and try to put them together?
No matter how you slice it, I think people are moving their information around as they find these connections. So this sort of 2-D environment for now on this spatial canvas is the best place for us to give you really this playground, again, to manipulate your ideas. To do something with them, please, to move towards that creation.
Jorge: I’ve actually interviewed people on the show who have been writing books, and they use things like sticky notes, right? To map out the ideas and maybe start formulating the outline for the book. And I get the sense that the playground is a way for me to do something like that, where It’s almost like they’re sticky notes, but they’re sticky notes with a superpower, which is that I can pivot from the idea on that card or on that note to references in my corpus that might somehow be related to it, right?
Alice: Right. It’s as if you had a buddy there with you while you’re writing that is giving you really relevant sticky notes, right? Like you’re starting with a sticky note, and you’re like, “what about this?” And that buddy next to you is handing you, “okay! These five sticky notes are really important!” You get to put those together, right? Even in an analog state, if I’m writing something and I have sticky notes out, I don’t get that superpower. So I find that really exciting about our application.
The impact on your work
Jorge: Yeah, I love that image of the buddy — a kind of smart buddy — handing you relevant sticky notes. So with that in mind, I’m wondering the degree to which you yourself have been using this approach in your own work and in your own life. And if so, what results have you seen? How has it changed the way that you work?
Alice: Yeah, that’s a great question. So, I, as an individual, don’t tend to be terribly well organized. I have lots of things I’m doing at once. I have lots of books I read at once. I have lots of open tabs. So I tend to feel a bit scattered. I have never really found any tool or set of tools that can help me to streamline this process that can help me to bring this stuff together.
So for me, what I use this for is any kind of presentation I’m giving, honestly. So I’ve given talks. I’ve put the talk together in this — just short of putting… you know, making the slides that I’m going to present. I’ve used this to write articles. So some of those will be coming out soon. I use this as a founder for putting my ideas together for the product. How do we think about, what are the areas we’re really focused on? As a machine learning person, I’ve used this to put together; how do I think about connecting these different concepts and machine learning or these different models even to create this bigger thing. As a machine learning person or developer, that’s another place I’ve used it.
I’ve also used it as a general place to kind of have this scratch pad. So, if I am going to put a tweet out about something, I’ll go in there first and say like, “Okay, what do I know about this or that? What should I add?” We added something recently where you can tweet directly from the playground. So I can just get those out. So, that’s been huge for me in terms of somebody who needs to be visible in public. I need to be getting information out, and it would take me much longer to put all of this together, to collect all of my materials — again, not a super organized person — and to get that out. So it has really empowered me in that way.
Jorge: That’s very exciting. And I did not know about tweeting directly from the playgrounds. I’m going to have to play a bit more with it.
Alice: Very neat, yeah.
Jorge: And I’m guessing that the best way to do that… and now I’m going to be selfish and ask for personal advice here. So, as I said, I’m writing a book, and I do like to engage on Twitter and stuff like that. So the use cases that you’re discussing here are use cases that I have. And I’ve started by importing, as I said, my Instapaper queue from many, many years, but that only represents a fragment of the information that I find relevant. What would you recommend to someone like myself who wants to use the tool more and wants to have it give me relevant results? Like, what would be the most effective way for me to do that relatively quickly?
Alice: And so I understand… you’re thinking of getting more information, and like, Instapaper isn’t all of your information?
Jorge: Yeah, for example, the book, right? So I’m working on this book, and I’ve got a lot of notes that I’m keeping in Obsidian. Things that I’ve read on my Kindle, I import into Obsidian via Readwise. I have a lot of granular notes there. I have lots of PDFs from journals and academic papers and stuff like that. And I kind of wish that I had all of this stuff in re:collect that I could play around with it.
Alice: Yeah, this is great. So, first of all, if… you’re using it as an early tester. If other folks are using it or they get on, we have a waitlist. Please join, and you can always send us a note if you want to get bumped up. It’s quite long now. But you know, that kind of feedback is really important to us. But on the specific point, so we actually yesterday launched PDF capabilities. So if you have PDFs, you can just open those up in your browser and bring them in. And a next step for us would be to be able obviously to do that in a bulk way. So, you know, coming soon!
We’re big fans of Readwise. We’re actually working on a Readwise integration. It’s on our very near future roadmap. And then, in terms of things like Obsidian, we’ve been thinking about this a lot. And sort of how to bring people’s notes and information they have in Obsidian because it’s really mixed, and it has this big hierarchy. How to bring that in an effective way, that’s really the place that… it’s sort of like we would love feedback and information from people that are using that tool to think about, like what’s the best way to design bringing them in. But PDFs and Readwise… The PDFs are there today. Readwise is very soon to come in. So I hope that’s good news in terms of getting more in.
Closing
Jorge: Well, that’s good news. And you’ve just opened the door for me to give you more feedback, which I will do because I do plan to continue using the tool. This sounds really promising and exciting. Where can folks see for themselves and maybe sign up for being in the alpha?
Alice: If you want to join our waitlist, you can go to re-collect.ai. There’s a hyphen between re and collect. And you can always find us on Twitter. So we’re pretty good about posting small videos of what we’re working on there. So Twitter is the same; it’s @recollect_ai on Twitter. You can reach out to us if you have thoughts or feedback. I think the email’s on our website. There are definitely ways to join the waitlist to check out what we’re doing online.
Jorge: Great. I’ll include those in the show notes. I feel like we might have short-changed listeners by saying, “this should be a video!” Are there videos that we can point them to? Have you all uploaded any that show the tool in action?
Alice: I don’t think we have a public demo video yet. We’ve been thinking a lot about this and how we could put one on the homepage. So maybe by the time this comes out, there’s something on there. But yeah, there are little videos on Twitter. We definitely release one of those often when we release a new feature so they can see pieces of that there. I gave a demo again at the Tools For Thought conference you were at. I think there’s a public video of that, but the lighting was a little bit hard to see.
Jorge: Well, I look for that when compiling the show notes. In the meantime, folks can go on Twitter and see these shorter videos. But I do think that it’s worth looking into because it is a very promising tool. Thank you so much for being here, Alice.
Alice: Thank you so much for having me. It’s been a pleasure.