Sidecar Sync

Previewing digitalNow 2024, Google NotebookLM, and xRx Framework Explained | 49

• Amith Nagarajan and Mallory Mejias • Episode 49

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In this episode of Sidecar Sync, Amith and Mallory dive into the latest AI trends impacting associations. They preview the upcoming digitalNow conference and showcase the impressive keynote lineup, including experts from Google, the US Department of State, and more. The episode also features an exciting exploration of Google Notebook LM, a new tool designed to help users organize and interact with documents using AI, along with an overview of XRX, an open-source framework enabling multimodal AI solutions. Listen in to learn how associations can harness these tools to boost productivity and innovation.

🎉 digitalNow 2024 Contest:

Post about this episode on LinkedIn! Share something you learned or a cool tool you're going to try, tag Sidecar (https://www.linkedin.com/company/sidecar-global), and tag #digitalNow. Each post is an entry, and two winners will receive free passes to digitalNow 2024.

Note: Every post counts as one entry. The contest ends on October 4th.

🔗 https://www.digitalnowconference.com/

🛠 AI Tools and Resources Mentioned in This Episode:

Ascend: Unlocking the Power of AI for Associations ➡ https://ascendbook.org
Join the AI Learning Hub ➡ https://sidecarglobal.com/hub
Google Notebook LM ➡ https://notebooklm.withgoogle.com/
XRX ➡ https://groq.com/xrx-by-8090-powered-by-groq-create-deploy-multimodal-ai-solutions/

Chapters:
00:00 - Introduction
06:45 - Preview of digitalNow 2024 Conference
22:35 - Google Notebook LM Overview and Features
25:43 - Experiment with Sidecar Content
30:18 - More Opportunities for NotebookLM 
41:12 - Insights into XRX Framework and Applications
45:43 - LPU vs. GPU
53:53 - Closing Thoughts and digitalNow Contest

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More about Your Hosts:

Amith Nagarajan is the Chairman of Blue Cypress 🔗 https://BlueCypress.io, a family of purpose-driven companies and proud practitioners of Conscious Capitalism. The Blue Cypress companies focus on helping associations, non-profits, and other purpose-driven organizations achieve long-term success. Amith is also an active early-stage investor in B2B SaaS companies. He’s had the good fortune of nearly three decades of success as an entrepreneur and enjoys helping others in their journey.

📣 Follow Amith on LinkedIn:
https://linkedin.com/amithnagarajan

Mallory Mejias is the Manager at Sidecar, and she's passionate about creating opportunities for association professionals to learn, grow, and better serve their members using artificial intelligence. She enjoys blending creativity and innovation to produce fresh, meaningful content for the association space.

📣 Follow Mallory on Linkedin:
https://linkedin.com/mallorymejias

Speaker 1:

In an age of AI, we have to focus on our humanity more than ever before, as individuals, as teams, as families, and so health, longevity, sleep, restorative benefits that come from all those things are more important than ever, because we're getting busier, not less busy. Welcome to Sidecar Sync, your weekly dose of innovation. Welcome to Sidecar Sync, your weekly dose of innovation. If you're looking for the latest news, insights and developments in the association world, especially those driven by artificial intelligence, you're in the right place. We cut through the noise to bring you the most relevant updates, with a keen focus on how AI and other emerging technologies are shaping the future. No fluff, just facts and informed discussions. I'm Amit Nagarajan, chairman of Blue Cypress, and I'm your host. Welcome back to the Sidecar Sync. We are excited, as always, to have all of you with us to explore the intersection of artificial intelligence and associations. My name is Amit Nagarajan.

Speaker 2:

And my name is Mallory Mejiaz.

Speaker 1:

And we are your hosts. Before we get going on our interesting set of three topics at that intersection of AI and associations, let's take a moment to hear a quick word from our sponsor.

Speaker 2:

Today's sponsor is Sidecar's AI Learning Hub. The Learning Hub is your go-to place to sharpen your AI skills, ensuring you're keeping up with the latest in the AI space. With the AI Learning Hub, you'll get access to a library of lessons designed to the unique challenges and opportunities within associations, weekly live office hours with AI experts and a community of fellow AI enthusiasts who are just as excited about learning AI as you are. Are you ready to future proof your career? You can purchase 12 month access to the AI learning hub for $399. For more information, go to sidecarglobalcom. Slash hub Amit, how's it going?

Speaker 1:

It is going great. You know it's a busy day, but you, but down here in New Orleans, I think there's been a role reversal, because I think you guys are thinking about hurricanes today.

Speaker 2:

I was going to say of our listeners. If you've listened to the Sidecar Sync before and you had to guess which one of us was about to experience a hurricane, you would probably guess Amit, because he lives in New Orleans. But we have a hurricane coming through Atlanta this weekend, I think, maybe hitting like Friday, saturday. I will say I'm not all that worried about it. But on that same note, after having grown up in Louisiana my whole life, there's a part of me that's nagging like do I go stock up on water bottles? You know all the hurricane prep.

Speaker 1:

Yeah, I think the Louisiana thing probably desensitizes you just a little bit to the impending doom of a hurricane maybe, but I don't know. You guys are a little bit inland, so it shouldn't be too too bad and hopefully it won't cause a lot of damage along the way for folks that are in the path on the coastal communities. So we'll obviously be keeping all those folks in our thoughts and hopefully no one who's listening is directly affected, but hurricanes are definitely no joke.

Speaker 1:

But here in Louisiana, and specifically in New Orleans, there's a reason. There's a drink called the hurricane, and it tends to be where people head when hurricanes are headed here, as opposed to doing anything in terms of active preparation for the storm.

Speaker 2:

Exactly. Well, at least for the time being, I don't think we have a podcast planned for during the hurricane, though maybe just for fun times. Maybe we should schedule one.

Speaker 1:

Yeah, seriously.

Speaker 2:

Amit, I'm going to quiz you really quickly. Do you know what number episode this is for us? I'm putting you on the spot.

Speaker 1:

Well, I could cheat and look it up by looking at the show notes that you've prepared, as you always do so helpfully, but it is actually kind of clipped off of my screen so helpfully, but it is actually kind of clipped off of my screen. So I don't know. I think.

Speaker 2:

Are we close to 50? We're really close to 50 today, or well, tomorrow, when this episode is released, we will be releasing episode 49 of the Sidecar.

Speaker 1:

Scene.

Speaker 2:

Podcast.

Speaker 1:

Well, 49 is a great number. It's my favorite team in the NFL.

Speaker 2:

Unfortunately, they're not doing very well at the moment, but that's exciting 49 episodes.

Speaker 2:

It's crazy to think about. We've done one every week, as we've talked about in the past few weeks, and I feel like we've come a long way. I mean, I think the goal and the vision with the podcast is certainly still the same, but we've evolved and grown and I mean, I don't know if I've ever asked you this, but had you done, had you ever had your own podcast before? Is this a first for you? Nope, I have never done a podcast before I. Is this a for you and one colleague? Potentially you could win two passes to Digital Now 2024, which is October 27th through 30th in Washington DC, and we're going to talk a little bit more about that conference, actually as topic one.

Speaker 2:

But here's what you have to do. We're also going to write down the instructions in the show notes. You have to post on LinkedIn about the Sidecar Sync. It could be something you like from this episode, something you learned, a cool tool that you're going to try out. Post about this episode on LinkedIn tag Sidecar and hashtag digital. Now, every post that you make is one entry, so theoretically, you can have unlimited entries if you want to post all day, every day, about the Sidecar Sync podcast on your LinkedIn, and we're wrapping up this contest on October 4th, so you've got a little over a week. We're really excited to launch this and I can't wait to see all your posts.

Speaker 1:

Can posts be AI generated?

Speaker 2:

I will leave that to the discretion of our viewers and listeners, but I would say they should probably be AI generated. If you're a really good listener, they should probably be AI generated.

Speaker 1:

For the record, I'm all in favor of that.

Speaker 2:

Well, today, as I mentioned, first and foremost we're going to talk about Digital Now, that event that is coming up for us next month, believe it or not Now, that event that is coming up for us next month, believe it or not. And then we're going to talk about Google Notebook LM and share kind of a fun experiment we ran with it at Sidecar. And then, finally, we are talking about XRX. So, first and foremost, digital Now. We've mentioned it a few times, many times on this podcast before, but Digital Now is our flagship annual in-person event for Sidecar. We bring Silicon Valley and executive level content to the association space and it is going to be for the first time ever in Washington DC. I can't believe it's the first time ever in Washington DC because, as we all know, there are many associations there, but we are thrilled to be bringing it to the capital of our nation there. But we are thrilled to be bringing it to the capital of our nation. The theme this year is Exponential Associations Building a Foundation for the Future. So we're going to be pulling on a lot of the same topics that we talk about on this podcast, but the idea of kind of re-evaluating what it means to be an association right now, what that might look like in the future and the steps you have to take to become that exponential association so you can not only survive in the future but thrive as an organization. So to give you kind of an event overview, the event kicks off on October 27th, which is a Sunday. We've got a registration period and then a welcome party and then we have two full days of sessions on Monday, october 28th and Tuesday, october 29th. We've got some fantastic keynote speakers that I'm going to go through really quickly here. Amit, you'll be kicking off the event as our first keynote speaker. We've got Thomas Altman, who's the co-founder of Tassio Labs and one of the creators of several products that we've mentioned on this podcast, like Betty, bot and Skip. We've got Sharon Guy joining us on the keynote stage, who is an AI and e-commerce expert who formerly worked at the Alibaba Group. Denise Turley, who's the VP of Corporate Systems at the US Chamber of Commerce.

Speaker 2:

On day two, we've got Gio Altamirano-Rayo, chief Data Scientist at the US Department of State. Robert Plotkin, who's an AI patent attorney. Neil Hoyne, who's been on the podcast along with Robert, actually, and Sharon. Neil Hoyne is the chief strategist at Google. We're so excited to have him joining us at Digital Now this year. Dr Parham Dedia, who's an integrative medicine physician and sleep specialist We'll talk a little bit about that in just a second. And then we also have John Spence joining us, who's a leadership expert and executive coach.

Speaker 2:

We have a keynote panel on both days with an excellent facilitator and consultant in the association space named Mary Byers, and then in the afternoons on both days, we've got some exciting breakout sessions lined up. I've jotted down the names of a few just to give you a little teaser. One of those is Bridging the Gap Integrating IT and Data Strategy for Transformative Business Outcomes. Another is Need for Speed you Might Not Be Thinking Big Enough From Buzz to Impact. Practical Strategies to Elevate your Value, innovate the Lean Way, getting Non-Dues Revenue Right. And then we will also have an exciting interview lined up with Dale Sear and Juan Sanchez from Intellios, along with Mary Byers, who we've also had on the podcast in a previous episode.

Speaker 2:

On Tuesday, october 29th, we have our download party at a nearby venue called the Roofers Union. That'll be a great couple hours that we spend together, socializing, networking, enjoying some good food and drinks. And then, wednesday morning, we have an AI innovation showcase where we're highlighting associations that are doing really innovative work with AI, and a key takeaway session to consolidate everything you've learned from those fantastic keynote speakers and breakout sessions and take it back to your organization. So, amit, that was kind of a big overview. What was your inspiration for bringing Digital Now into the Sidecar world?

Speaker 1:

So, mallory, I have been part of Digital Now as a speaker or sponsor prior to when we acquired the company and brought it into Sidecar, and I always had the highest level of regard for what the founders of Digital Now had done Two gentlemen by the name of Don D and Hugh Lee, who had been consultants and advisors to the association communities for many, many years, who I had tons of respect for, and they built this program to really try to bring things into the association community that were at the forefront of technological disruption, leadership change, and I think they did a fantastic job for 20 years. And as those guys were heading towards the latter part of their career on a full-time basis and also the pandemic hit at the same time, sidecar was starting to really grow, it just seemed like an awesome fit. So I think we were a great place for that conference company and really the event to land. And there's a cultural alignment between Sidecar and Digital Now. Both have always been focused on how do you bring new ideas and innovative concepts into the association community, so it was a very natural fit. So we did that acquisition back in during the beginning of the pandemic really. So Digital Now has occurred. This will be the 24th year beginning of the pandemic really. So Digital Now has occurred. This will be the 24th year, and Digital Now has gone on every year, except for the year 2020 when the pandemic went on. So that was the year that was virtual. Only, we were not involved that year, but we took over in 2021.

Speaker 1:

We did the event in Nashville. The first year we ran it. The pandemic was kind of winding down, but it was still a thing, and so that was a bit on the risky side. Our goal simply was just to have the event and do it safely and hopefully have some people come together and really resuscitate it. And then 2022, we did it here in New Orleans, which was super fun. And then last year, in 2023, we held it in Denver.

Speaker 1:

This year we thought you know what Digital Now? The founders of the event. Originally they always held it in either Orlando and they took it to a couple of other spots, but they had a special relationship with the folks at Disney, so they were doing it in Orlando a lot. We thought, you know, no one's ever run this thing in DC, so you know, there's, as you said, there's a couple of associations in DC. So hey, let's see what happens when we bring it to DC. So, but getting back to the inspiration it really was how do we add more emphasis to innovation in this space? And, of course, we've been deeply embroiled in the world of AI for over a decade now, and so AI was not news to us and it was always part of the agenda for Digital Now when we acquired the company, but certainly since the ChatGPT moment in late 22,. We've been hyper-focused on that at Sidecar and, of course, digital Now has been focused really, really heavily on AI in the years since we've been running it.

Speaker 2:

I'm sure some of our audience listening to those keynote speakers we mentioned someone from Google, someone from the US Department of State, someone from the US Chamber of Commerce they might be thinking, wow, it's exciting to bring in speakers from outside of the association space, but perhaps these individuals don't have a great grasp Maybe I'm just spitballing that of how associations work. So I'd like to hear a little bit of your thought process from bringing in outside speakers to Digital Now.

Speaker 1:

Yeah, it's a great question and I totally agree with you. The context of associations, or whatever your industry is, is so important to connect with people. I mean that's why associations exist. Right, there's associations in all these hyper specialized, narrow categories and subspecialties, and that's because the more specific you are with your approach to engagement, with content, with learning, the more effective you are at conveying the content. The issue with people who are only in the association market is you get a bit of an echo chamber after a while, and so we like to bring in new ideas, things that are from different industries, because there's a lot of great content from fellow association travelers, so to speak. So you think about all the great work the folks at ASAE do, the work that Chicago Forum does and all the other regional SAEs and a number of other organizations that produce great association content.

Speaker 1:

The reason we started Sidecar was we wanted to plug a gap that we felt existed in the ecosystem of thinking about things from radically different sources that could be applied in this sector but really weren't being talked about enough. So it's really part of the founding of Sidecar going back six years plus now, and digital now was always like that as well. So for me it is about getting new ideas, sparking new conversations, but also, of course, blending association expertise in. So part of it has to do with how we prepare our keynotes, how we vet them to begin with, if they're willing to make an investment in spending the full conference with us. So our keynotes hang out with us the whole time. They get to know our attendees. They really add a ton of value by having conversations and we do a lot of prep work with these keynotes to make sure they have a really good understanding.

Speaker 1:

So a lot of times keynote speakers are parachuted in, they give a canned talk and then they literally exit out the door as quickly as they possibly can to catch their next flight. We don't do that. We bring in some very significant speaking talent. Obviously, as you just went over, we're really excited about the folks coming in and appreciative of them, but they're committed to helping this community and we want people that are aligned with purpose. I think it's a great combination. Also, as you mentioned earlier, our good friend, mary Byers is facilitating conversations with some of the keynotes each day and that helps thread in deep association expertise with people who might have less experience in the space. So that's how I've always thought about it and I think it's an opportunity each year for people to learn about what's happening outside of the association bubble.

Speaker 2:

Yep, I agree with you. Mary does such a fantastic job of pulling out insights and challenge questions and things out of speakers, so I'm really excited to see how that plays out. I did mention Dr Parham Dedia, who is the integrative medicine physician and sleep specialist, amit, I'm sure some of our listeners and viewers are thinking, huh, how does that fit in with AI and associations? So can you speak to Dr Dedia a little bit?

Speaker 1:

with AI and associations. So can you speak to Dr Dedi a little bit? Well, parham is an amazing guy. He's an engaging speaker. I think people are going to find him fascinating on a number of levels, and my perspective is this is that in an age of AI, we have to focus on our humanity more than ever before, as individuals, as teams, as families, and so health, longevity, sleep, restorative benefits that come from all those things are more important than ever. Because we're getting busier, not less busy. Even though AI is helping us, we somehow are getting busier.

Speaker 1:

I'm hopeful that AI will perhaps change that balance over time, but in the meantime, we have a big task ahead of us as leaders in and around the association market, we have to figure out how to us, as leaders in and around the association market, we have to figure out how to embrace this incredibly exciting but also incredibly disruptive technology. Not just AI, by the way. That's what I'm talking about, but there's plenty of other things, which is, by the way, a little preview into my keynote, which is about exponential everything. It's not just AI, it's a whole bunch of other stuff that I'll be talking about on stage, and the point is this is that we have to take care of ourselves, and it's a little bit non-traditional for digital now, and probably for most conferences, to try to balance that out a little bit. But we thought we'd pull in one keynote speaker who could really think more broadly and more holistically about success. So, if you start with success from an individual perspective, from your own platform as an individual, which has to be rooted in good practices around sleep and other things, he's a sleep expert, so I tend to think about sleep Not that his talks put me to sleep, because he's a very engaging speaker, but he is world-renowned in sleep specifically.

Speaker 1:

But he'll be sharing some insights that I think people will find very practical. He's not dogmatic. He's not one of these people that comes in and tells you to do eight things, and he's not someone who says you have to do perfect this and perfect that. He's a much more practical guy.

Speaker 1:

I've gotten to know him personally over the years and he's just an amazing individual, deeply cares about helping people and he's excited about Digital Now as a platform to help innovative thinkers in our space hopefully learn some techniques that will help them and their families and their colleagues in their life journey, which will, of course, make them happier and healthier, but also make them more successful or more likely to be successful in adopting big changes like implementing AI. So that's how it ties together in my mind. I'm an entrepreneur, I like taking risks. So that's how it ties together in my mind. I'm an entrepreneur, I like taking risks, I like doing things that are different, and so bringing in someone who's kind of off program, so to speak, it's like bringing in a folk singer to a rock and roll concert or something. It's not something people are going to expect, but it might be really cool. So hopefully it'll be the latter.

Speaker 2:

Absolutely, amit. You invited Parham to our leadership summit, which we actually talked about on the last episode, but I think it was two years ago at this point and Parham's session across the board was one of the best ones rated in the survey feedback and I still think back to tips and tricks he shared with us from two years ago. So I'm thrilled to bring him to Digital Now this year and I'll let you all know his session is called High Yield Health the Foundation for Exponential Times and I love that.

Speaker 1:

What a cool tie-in. Yeah, so cool. And I knew what would happen when we have our Leadership Summit annually, which is our private event for Blue Cypress family companies. There's a bunch of companies in the families you guys have probably heard us talk about over time and we invite the senior leadership from all the different companies and the families you guys have probably heard us talk about over time and we invite the senior leadership from all the different companies and Blue Cypress HQ to come together once a year up in the mountains of Utah and learn together and hang out and build relationships. We actually just finished doing this year's installment last week. It was a ton of fun and we invited Parham and I knew that.

Speaker 1:

I was pretty sure that he'd get largely really, really positive reviews, but I also knew that I was almost certain anyway, mallory, that we would get some criticism, that some of the people coming together would say what the hell are you guys doing telling us about health? This is a business conference. It's none of your damn business what I do with my health and with my body and I'm okay. Well, no one's telling you what to do. We're trying to provide things that hopefully will be helpful.

Speaker 1:

Not every session is helpful to everyone and I kind of view it with digital now in a similar fashion that some people attending will be surprised, maybe in some way unfortunately offended, but I kind of look at it and say the vast majority of people I think are going to get maybe at least one useful thing from Parham probably many, I know. Every time I hear him speak even though I've heard him speak bunches of times I learn at least one new thing. So that's the nature of risk. Right, you can't please everyone all the time and if you try to do that you end up becoming something generic, like you turn into a toaster. There's totally undifferentiated.

Speaker 2:

You make me remember. Yes, it was the most polarizing session because across the board it was the favorite by a long shot, but we actually got some of the most negative feedback about it as well, so that's really interesting. Anyway, come to Digital Now.

Speaker 1:

If you're curious to see how that plays out, that's how Sidecar has always been and that's how Digital Now has always been, which is another reason we brought the two companies together a few years ago, so very excited about Digital Now this year.

Speaker 2:

For sure, can you give us a quick sneak peek of your session?

Speaker 1:

Sure, well, exponential associations is our general theme, and I'm going to be talking about exponentials Exponentials in the context of AI, but also other fields that are experiencing similar phenomenon. So we think about the world of energy, we think about the world of material science, synthetic biology. My goal is to share what's happening from a macro lens across a number of exponentially growing categories and then talk about how they're converging and how they're feeding off of each other. So, for example, ai is begetting more advanced material science and more advanced material science is going to beget, over time, better AI and there's multiple you know chains of effects that come from that.

Speaker 1:

I'm going to talk about it from that general perspective and then I'm hoping to zoom in and talk about how each of these advancements could help specific professions or sectors, how the associations that serve those professions or sectors need to stand up to help those areas, those sectors, adjust, and then, of course, how associations internally would need to adjust as these changes unfold. So it's the broad thematic approach that we're taking with the whole conference around exponentials, and AI is a big, big, big part of that, but there are other things on the horizon. I also plan to talk just a touch about quantum computing and how. That's kind of like another layer of crazy on top of all the crazy. So hopefully it'll be a lot of fun, but I'm hoping to kick off the event with just a bunch of ideas on what's happening in the world and get people excited about it.

Speaker 2:

Can't wait for it. All right. Next up, we're talking about Google's latest release, notebook LM. Notebook LM allows users to upload documents, create notebooks and interact with their content sources using AI. Of course, it can summarize information, answer questions and generate new ideas based on uploaded sources. Users can upload up to 50 sources, including Google Docs, pdfs, text files, google Slides and web URLs. It doesn't look like at this point you can upload video, but I imagine that will be something you can do very soon.

Speaker 2:

Notebook LM is powered by Google Gemini's 1.5 Pro and, as I mentioned, it creates summaries of your uploaded documents and highlights key topics, suggests questions and it can also generate audio, which we're going to share a little bit of, based on the sources that you upload. You can ask specific questions about your documents. You can have Google Notebook LM help you create an FAQ section or a brief. I'm going to share my screen in just a minute so you can see what I'm talking about here. And it operates as a closed system, so it doesn't perform web searches beyond the uploaded content and, as a note, user data remains private and is not used to train its algorithms. So right now I'm going to share my screen and, for listeners only. I'll try to walk you through exactly what I'm seeing. So right now I'm in Google Notebook LM and of course, as you probably all expected, we decided to use the second edition of our Ascend book for this experiment and I also linked the Sidecar website. So those were the two sources that I added. I could have added a ton more probably, but I was trying to run through this pretty quickly and what I got out of it for such a quick experiment, I will say was very impressive to me. So you can upload sources, you can do as I mentioned. Google docs slides, a link to your website copy text up to 50, which is quite a bit. I will show you the chat interface, so kind of like a chat GPT. It's still loading here.

Speaker 2:

If you click this notebook guide here, you will see that it summarized all of the content that I provided to it, and I can ask Notebook LM to help me create the FAQs, study guide, table of contents, timeline, briefing, doc. And I can also essentially ask it to help me create whatever I want. So one example that I ran yesterday was asking it to create an outline for five podcast episodes from Ascend 2nd Edition, and it did a really good job of this. I imagine it scrubbed our website and maybe pulled some context from there about the podcast, but other than that, I didn't give it previous episode outlines or anything like that.

Speaker 2:

If I had added a few of those in as additional sources, I imagine what I would have gotten out of it would have been much better. You can see there are suggested questions here and then also you see an option to generate an audio overview. So this is essentially a nine minute quick podcast that was created about Ascend second edition. It was a man and a woman speaking. I can load it here, but actually I'll just cut that out and I'm going to play a couple clips from that audio for you right now.

Speaker 3:

All right, everyone ready to dive into some really cool stuff for associations. We're talking AI and we've got this book Ascend, unlocking the Power of AI for Associations. That's basically like a cheat sheet for well, the future.

Speaker 4:

I like that, a cheat sheet. Yeah, you know, that's what struck me too reading this. They come out strong, saying AI is going to be as big as get this the invention of flight.

Speaker 3:

Yeah, I mean, when I read that, I was like whoa, this isn't just some tech upgrade, right, this is huge. We got to be ready or we're going to be left behind, and they back it up too, which I appreciated.

Speaker 4:

They get into the whole history of big tech changes like think printing press, even the internet, and how those totally shook things up.

Speaker 3:

Exactly. It's about the big picture, not just the shiny new tools. And speaking of which, let's be real. People are nervous about AI, especially when it comes to jobs.

Speaker 4:

Totally and give them credit. Ascend doesn't shy away from that at all. They tackle it head on, saying look used right. Ai doesn't replace us.

Speaker 3:

It actually makes us better at our jobs. Like, imagine ditching all those spreadsheets and emails that bog us down. Right, ai handles that and we're free to actually think, strategize, build relationships. You know the stuff AI can't do.

Speaker 4:

Exactly, and that's where Sidecar, the group behind the book. They get it Free AI webinars, a whole learning hub, even an AI mastermind group. They're meeting people wherever they are on this whole AI journey.

Speaker 3:

Love that because, let's be real, we're all over the place with this right. Some folks are just dipping their toes in, others are like knee deep. Already Speaking of that, learn, experiment, slash. Then they lay out. That was huge for me.

Speaker 4:

So practical it's like don't freak out, just start small, learn the basics, try some stuff out, see what works, then go from there.

Speaker 3:

Love that. And it gets real specific too on what you can do, like right now, like marketing no more generic emails, we're talking totally personalized messages to each member.

Speaker 4:

And they name drop some really cool AI tools too. Dle MidJourney Even if you can't draw, you can make awesome visuals for your content now.

Speaker 3:

It's like having a whole design team at your fingertips. And then okay, this one blew my mind AI agents. They're talking about a skip for every association analyzing member data, even helping make decisions.

Speaker 4:

All about that data right. That's the foundation. They stress that Can't build a house on sand. They say so true.

Speaker 2:

Amit, I shared with you that generated audio podcast of sorts yesterday and you gave it a listen and you were pretty impressed, and you obviously we both deal with this stuff all the time. Can you talk a little bit about why you were so impressed?

Speaker 1:

Sure, I was really impressed. I had a holy crap moment because I looked at it and said it's synthesizing kind of a higher order product, which is a podcast from all this source material, a number of iterations that you went through with the tool, and I thought the quality of the content just the transcript that fed into the podcast was really good. It was conversational. It was two different people speaking to each other, as listeners have heard from the little clips that you just played, and it sounds really natural to the quality of the voice synthesis was really sounds really natural too. The quality of the voice synthesis was really really good and it had emotion, it had tone, it was really good.

Speaker 1:

I mean, I could definitely see us using this tool as a part of the sidecar sync. That's unnecessarily replaced what we do, because of course, that's super awesome, but we definitely want to look at creative ways to augment it. One of my favorite podcasts on the really technical side is this thing called Latent Space, which I think I've told you about Mallory. It's really about AI engineering, so it's more like at the code level how people are putting together systems and they talk about model training, all this really cool stuff. Well, anyway, those guys have. First of all, I think I'm pretty sure it's sooner they use for like a theme song which is kind of fun.

Speaker 1:

I don't know if we'll do that and then they have an AI co-host. So I think it's two founders of this podcast that have conversations. Sometimes they bring in guests, but they have an AI co-host that essentially reads scripts. That kind of are introductions and conclusions, but also really interesting interludes between segments of the show. So I could see Notebook LM operating in all of those areas and I thought, the multimodalities we've talked a lot on this podcast and in the book about how AI is becoming multimodal and how we're on this progression through the doubling curve of roughly six-month doubling in capability in AI and we're seeing that because the voice capability here is dramatically different. On that note, as a little side note, just today I was able to access the new ChatGPT advanced voice mode. I don't know if you've played with that yet.

Speaker 2:

No, I haven't. What was that like? It was what was demonstrated.

Speaker 1:

When GPT-4.0 was first announced and was only available to a small number of people. No one I know had direct access to it, but today they rolled it out. You may have to actually delete the ChatGPT app from your phone and then reinstall it to get it right away, but they say they're rolling it out over the next few days to everyone, and I found it to be far more natural than the last version of voice. It's not quite as good as the demo so far in terms of its latency. It does have a little bit of a lag to it, but it's fine and it's way more useful than previously because you can interrupt, you can really have a conversation with the thing, but it's a very natural feeling voice. So I think that the Google Notebook LM is another good example of that.

Speaker 1:

Computers for a long, long time have been hard for people to use because you've had to comply with the computer's way of thinking, which is screens and mouses and clicks and all this other stuff where we've tried to approximate a good user interface or user experience. And now we're moving to natural interfaces where we can have language interaction. In our language we can speak to the computer, the computer can see us and see not only what we're saying but how we're feeling, if we want to share the video, and soon we'll be able to see the AI avatar in real time and be able to understand more from what the AI is saying. So I find all of this exciting. I think Google's work is often underrated in the area of AI, which is still shocking considering their longtime leadership in the discipline. But they haven't done a great job commercializing it. So the onus is on them to shift gears.

Speaker 1:

I think this tool is a good example of where Google shines, where they've taken their underlying model, which is the Gemini Pro 1.5, as you mentioned, which is a good model. It's nowhere near as good as GPT-4.0 or Anthropix 3.5, claude Sonnet, probably about on par with the Lama 405B product or model, but it's a good model. But they've built some really cool software around it and they've stitched it together in a way that has some novel use. So creating that audio file took you a handful of clicks. You could have done that with these other tools, but it would have taken you more and more steps to produce all the different pieces and then go to 11 labs and connect it all together. It might've taken you a few hours, so there's a lot of opportunity for engineering good solutions and for creating a nice user experience. That's easy. So you know, hats off to Google. I think they did a great job.

Speaker 2:

I agree. If you all tuned into previous episodes, you probably heard my stance on this, at least personally, which is, for now, I will choose to consume human generated content for fun and or like human plus AI, but mostly human. I will say this is the first time I've listened to totally AI generated audio and thought, wow, this is entertaining. It was casual, it was friendly. They kind of have like this back and forth rapport with one another and I thought, okay, now I can kind of see this more than I did previously. So I was incredibly impressed with this. I think in theory it seems a lot like a custom GPT. Obviously, with custom GBTs we don't have the ability to generate that nine minute audio. Also, as a side note, it generated that in maybe five minutes or so, five minutes or less of processing time. But this is impressive and I think it's a great point you made that maybe the underlying model isn't necessarily better than anything we're seeing, but the way that they've packaged this up is exciting.

Speaker 1:

And that's where I think a lot of upside is that I often tell audiences that I speak to on AI that even if the models that we have today do not get better at all for a decade or longer, it's going to take us about that long to figure out all the creative ways we can use the technology as it is today. We can do by combining and recombining and layering and all these other cool things. We've talked about agent systems, which is basically actually what this is. It's a multi-agentic type of solution. I don't know what's under the hood, but it basically is that conceptually, it's amazing what you can do just by building on top of the foundational capability of these models that we've had access to really only for a handful of years now. So I'm pumped about it.

Speaker 1:

I think this is a great example. Associations can create their own notebooks, they can put their content in there, they can share them with different people. This is a very early product, so I wouldn't necessarily build a product strategy around that, but it should be a prototyping environment where you're thinking, hey, what would it look like if I had some of my content maybe tailored for particular use cases in this kind of environment? What I do like about Google's commitment to not ever training on your data is that the other companies aren't being that direct about it.

Speaker 2:

You can protect your data by way of opting out of training with some other AI platforms, but with Google, they're saying up front we will not use anything you share for model training, which I think is good source documents as they relate to whatever department that you work in membership, marketing, finance even and then create kind of this notebook, essentially, where this new hire can go in and ask questions and you know that it's creating answers based on those source materials only, taking all your member requests and emails and even transcripts from phone calls, dropping those in here, you could do that in a few hours and then you have kind of this really neat resource that you can keep going back to and asking questions to.

Speaker 2:

But something a little bit I guess it's maybe not so far out of the association sphere that I think is exciting is the idea that students can drop in maybe the chapter from the textbook that they're reading and maybe their notes from the lesson, the teacher's lecture, and then create not only study guides from that but even an audio, like a nine-minute audio, of whatever you're learning in school. Amit, I'm curious do you think your kids would be interested in something like that if you showed it to them?

Speaker 1:

I think they might be. My kids are warm and cold. Not hot and cold, but warm and cold about.

Speaker 1:

AI, depending on the day and I think they're starting to see more about the usefulness of AI. I don't know if it's broadly generational or age-based. My kids are kind of in the mid-teens right now, but they generally look at AI as something that's kind of putting people out of jobs is their mindset, particularly my daughter. My son not quite as much, but he just is looking at going. I don't know if I need this thing or not, so it's kind of interesting because they're just not super excited about it. I think this tool might change their mind a little bit because it has a lot of utility for students, as you mentioned, and probably in a way that educators might look at as a positive development, because it's going to help them create new ways of learning, as opposed to replacing learning. It's interesting. It happens to be that this morning I was over at my son's school. I was asked by the administration over there to give a talk to their faculty on AI and I was happy to do that and I told them. I said, look, I'm a fish out of water here because I don't know anything about education. I mean, I work with associations all the time. They provide professional education, but that's very different than K-12. But I did my best. I shared some of the general broad themes that we talk about a lot on this podcast and with the association community. Some super interesting conversations came out of that. There were, of course, the predictable concerns with respect to students cheating, but a lot of what we talked about actually was the use cases for teachers, where teachers are going to see an incredible opportunity to improve their efficiency and connect with their students more. You know, you think about like, where does AI leave the rest of us in terms of what we do with our time? And the opportunity for improved human connection I think is unbelievable. So with teachers, the real magic of it is when they're able to spend more time, particularly one-on-one or in small group settings, with the students. That's where they're able to deliver life-changing value in some cases and where I think they also get a lot of purpose from it. But there's less and less of that because there's so much administrative work, there's so much lesson planning, there's so much grading. And think about the medical profession. You have doctors that spend a smaller and smaller fraction of their time with patients and with each patient. It's a tiny amount of time that is super rushed when you actually visit your doctor. And what if we could change it, where the doctors have way more time to spend 30 minutes or an hour or an hour and a half with you and they're not rushed? And similarly, if the teacher had all the time to spend, you know, with each individual student, to get to know them and connect with them and have all these super powerful tools behind them to be able to do personalized learning and create really engaging experiences for each child in that process or each person in that process for adult ed. That changes their outcomes dramatically. So that's exciting. So we ended up talking about that a lot.

Speaker 1:

I think that we didn't talk about this particular tool, but every industry, every sector is going to go through so much change. And this particular tool I'd encourage people to go check it out. I actually haven't played with this one myself yet. I was really excited when you showed me that example because I haven't had a chance to look at this one. But it's definitely worth spending an hour or two.

Speaker 1:

And my parting comment, with pretty much all the talks I give, is a call to action where I say listen, the one thing that you can do, all of you, no matter how busy you are and no matter how advanced or early you are in your AI journeys, you can allocate a small sliver of time every week, put it on your calendar and make it non-negotiable as a learning block. So it can be 15 minutes, it can be an hour. If you can do it more frequently, a couple times a week or even daily, that's awesome. But even if you just said, look, let's just start off with 15 minutes once a week and what we're going to do with that 15 minutes, it's a non-negotiable block of time on the calendar. We're going to learn something about AI, right, and so this is the perfect type of thing to go play with for 15 minutes. You'll learn a lot from it.

Speaker 1:

And, of course, if you can go with higher frequency, a little bit longer durations, that's great. But it's kind of like telling someone who's never gone to the gym that they should start working out six days a week. It's not going to happen. But if you say, hey, once a week, take a 10-minute walk, then go up from there, it's the same kind of approach I'm trying to take. So, in any event, I think this is a great example. Build your own personal backlog of AI learning, ai experiments that you want to do, keep a list somewhere and this should go right onto that list.

Speaker 2:

And if you have a ton of time on your hands, you can start a podcast, because for me, that's what keeps me super accountable is knowing. Hey, I want to talk about this tool. I always, always do my best if it's something I know how to use and think I can use efficiently to test it out so I can at least give you all a firsthand insight. All right for topic three. We're talking about XRX, which is an open source development framework created through a partnership between 8090 and Grok and that is Grok with a Q. It enables developers to build multimodal AI solutions with seamless integration of voice, text and image outputs. So, honestly, the term XRX is something that you may not remember, but if I break it down into what it means, it might help you. So the first X refers to any modality input. The R, which is a capital R, refers to reasoning, and then the last X is any modality output. So, xrx any modality input. Add in some reasoning any modality output. What are the key features? It allows for the creation of AI applications that can handle input and output modalities like voice, text and images. At its core, it incorporates a robust reasoning system which enables complex AI-powered interactions, powered by Grok's LPU AI inference technology, xrx, delivers instant inference and superior performance, making it suitable for real-time applications and, as we mentioned, the framework is open source, which allows developers to freely use and contribute to its development. So all of that is a little on the technical side. I wanted to talk a bit about what this looks like in practice and, instead of reinventing the wheel, I went to LinkedIn to a post that Amit actually shared with me. This post is by someone named Benjamin Klieger, who is an AI applications engineer at Grok, and he says quote need an AI agent to ask and collect patient information through voice calls? Done. Can the agent be interrupted and wait for the person to respond? Yes. Can it interpret information out of order? Yes. Can it correct information if the patient interrupts it to revise a previous answer? Yes. Can it interpret information out of order? Yes. Can it correct information if the patient interrupts it to revise a previous answer? Yes.

Speaker 2:

What about an AI using casual language to take pizza orders? Done. Can it use casual language like a pizza shop worker? Can it navigate customers through the menu at the same time? Yes to both. Can it confirm the total purchase price with the customer and then submit a real pizza order through Shopify yes, so when you start to hear some of those use cases and examples and there also is a short video that we'll link to you in the show notes as well on LinkedIn that shows just how real time the real time inference is, you'll see how impressive this could be. You'll see how impressive this could be. So, amit, we've talked about Grok several times on the pod, but I want to say the episode where we talked about the LPUs it was a while back, so can you talk a little bit about the difference between Grok's LPUs versus traditional GPUs?

Speaker 1:

Sure, Well, you know we. So we had, I think, a whole episode on this, maybe 20 episodes ago or something, so we'll definitely link to it in the show notes.

Speaker 1:

It's still relevant. The information about the share is in much more detail in that pod, but the basic idea is that GPUs have been used for both training AI models and also running them. In the AI world, we typically call running the model, like when you interact with chat, GPT. It's called inference, and so training versus inference are very different computationally and their requirements in terms of memory, access to data and actual you know computations. The fundamental ideas behind each of those processes are very different. So the idea basically is that, rather than using GPUs for both training and inference, what if we had specialty hardware that was incredibly good at inference? So Grok's innovation is the Language Processing Unit, or LPU as they call it, and that is essentially purpose-built hardware that is designed just for inference. It is not used for training at all. So GPUs, primarily from NVIDIA at the moment, are used for training most AI models. You can also use NVIDIA GPUs for inference, but LPUs are much more performant at inference.

Speaker 1:

So it's kind of like I don't know if you ever actually those of you in DC have probably seen this like in some cities that have riverfronts. You'll see these like tourist bus things, things that they tool around the city streets and they show people what's going on and they turn into boats. So in the Potomac in DC it's pretty cool. You'll sometimes see these things just going to the river and they're not particularly great as buses, they're not particularly great as boats, but they can do both kind of sort of Right. So, similarly, a GPU is a general purpose thing. That's not what G stands for. It's graphics originally, but it's basically AI workloads doing really high-scale parallel computations, which is great for all sorts of different things, but it's kind of like the general purpose workhorse in a sense in the AI realm, Whereas LPUs are like a speedboat on the water. That thing's not going to go anywhere on land, but all it can do is go really really fast in that one category right. So it does one thing and that one thing that it does. It does it really really well. And if you were going to design a speedboat versus if you're going to design this kind of amphibious bus thing, you have optimization opportunities. You can make the hull a lot more hydrodynamic, you can put a lot more powerful engines in it, you can approach a lot of different design decisions differently because it's single purpose rather than multipurpose. So that's the basic idea is that LPUs are specifically built for just inference and they've done a lot of interesting things in the hardware design in terms of memory architecture. That eliminates a lot of the choke points that GPUs suffer from on the inference side.

Speaker 1:

But that's more of a technical discussion. That, first of all, is not even my area of expertise. I only know it at a surface level and, secondly, it's probably not super interesting to the audience, so we won't go into a lot of detail there. It's best to just categorize it as specialty hardware used for running AI models, and it does it at ridiculously fast speeds.

Speaker 1:

There will be other technologies like Grok stuff, but right now Grok is the clear leader in terms of inference. They are inferencing the LAMA 3.1 70 billion parameter model, which is the medium size model, at something over a thousand tokens per second, which is many, many times faster than human perception can possibly consume Even those of us that read and hear and listen at incredibly fast rates. That's probably 200, 300, 400 tokens per second is what we can consume at most, and this thing's already many times faster. So, coming back to the commentary about real-time applications, anything that you're thinking about with AI, that you want to have very low latency on. Grok is an amazing platform to build on, so we're super fans of what they've built, really because of the benefits. I think the company's cool. The people who work there seem awesome, but the technology just is in its own league at the moment.

Speaker 2:

And to set the stage, are we seeing Grok chips power, other frontier models? You mentioned Lama, but what does the landscape look like across the board?

Speaker 1:

So at the moment, grok availability for people other than those who are building massive data centers is you inference. If you want to inference with Grok LPUs, you do it through the Grok cloud, which you can sign up for as a developer, get an API key and start building stuff, and it's super cool. They've got great customer support teams Highly recommend that. And then you have your choice of models. They're not a model company, so they have a couple of Mistral models. They have models from the Lama family and several other things that they have, like the Whisper model from OpenAI, which is the voice to text and text to voice open source model that they have. So that's kind of the infrastructure that's powering XRX and I think that's interesting because that enables this kind of real-time opportunity that other AI platforms really can't match at the moment.

Speaker 1:

And then the reasoning the R in the middle that you were describing earlier, mallory, is really important because we talked a lot on this podcast a few weeks ago, right before OpenAI released its O1 model, which was previously Strawberry, and how that was kind of the first like truly reasoning-enabled model.

Speaker 1:

Well, you know, the R is going to be whichever model you want to plug in, because it's an open-source model agnostic framework. So building multi-agentic kind of voice-to-voice model or applications, I should say, are now a lot easier. It's still not like, oh, click a button and it's built for you. But when you overlay what we're talking about here with XRX as an open source framework and then you think about plugging it into infrastructure like Member Junction, which we've talked about, or really anything else, it makes it so much easier to start thinking about how you're going to construct applications to meet both current needs but also future ideas, because you know again with the pace of advancement here, that R in XRX becomes more and more and more powerful over time and you can plug in even more complex decision making.

Speaker 2:

So Skip is an AI data analyst. Skip is an AI data analyst for associations. This is my first time actually thinking through this, but are you all considering and can you share, making Skip multimodal in the sense that you could just talk to Skip? Skip responds low latency, easy conversation.

Speaker 1:

Totally so. Skip and Betty, which are both multi-agentic solutions for associations. Skip, as you mentioned, is a data analyst and Betty is a knowledge assistant. These are both AI chatbots that Tassio Labs actually mentioned Thomas earlier, one of our keynotes at Digital Now this year he's one of the founders and he's been involved in building those solutions are text-to-text right now, so they're multimodal in that they can interpret images and video, but they're interacting with the user text-to-text.

Speaker 1:

It's on the near-term roadmap to enable voice and to also have potential other modalities, and what I mean by that is imagine a world where, in the context of analytics, you might say something like even a member might be able to ask questions that result in Skip fetching data, doing whatever transformations are necessary and responding. Obviously, there's a bunch of different security layers that you have, but this is an enabling technology that would make it easier for a product like Skip to support that kind of capability. It's not necessarily required, but the idea is that, you know, xrx is a tool set that makes it possible for associations and anyone else for that matter to build solutions like that. That's why I find it exciting.

Speaker 2:

And you said the key earlier is the low latency. That's the piece that's impressive here. Can you think of any other use cases off the top of your head where low latency might be important? I guess member calls to a call center is what I'm thinking, anything else.

Speaker 1:

Sure, anything where people are interacting. It's a synchronous form of communication. So, phone calls, video conferencing If you want to have an AI avatar, join us on this Zoom call and have it interact with us in a meaningful way and see that in a full 3D type of avatar that is photorealistic and talking to us. That would be something that you need real-time inference for. There's a lot of applications where real-time makes a lot of sense. There's certainly applications where it's less important. You might have, actually, skip is a great example. A lot of times people go to Skip and they say, hey, I want you to predict which of my members are not going to renew, and Skip goes off and does all sorts of data crunching and runs machine learning models for you and comes back with a spreadsheet as an answer to that type of question, and you might not care if it takes five or 10 minutes for something like that, or if it took, you know, 30 minutes, it really doesn't matter that much. But that's an example where an asynchronous interaction is totally fine. But for synchronous communication, which can even include things like text messaging or interacting through apps like WhatsApp, those are all scenarios where I think this becomes really, really important.

Speaker 1:

The other thing to remember is models are getting more compact, which makes them faster to run. So model capabilities that would have required the biggest frontier models last year are now packed into these small to medium-sized models, which inference much faster on any hardware and will definitely inference really really fast, as we talked about on Grok. So I think that what would have been possible a year ago, even if you had the same hardware you have today, you would have had a lesser model running on that hardware, and now you have something dramatically better. So that's part of what makes this exciting, because if the real-time interaction is with a model that's kind of dumb, then you can have the best multimodal real-time interaction, but the thing in the middle you're talking to is not very useful and that's no longer the case. And it's the convergence of all these capabilities that, for the first time, ordinary organizations that are run by people who aren't Netflix, amazon, openai can build stuff like this. And that's exciting because that's the dead center for the association market.

Speaker 2:

Well, when we can communicate voice to voice with Betty and Skip, we'll have to bring one or both of them on the pod and we can interview them ourselves.

Speaker 1:

That'd be fantastic.

Speaker 2:

Well, everyone, thank you all for tuning in and reminder about the contest we're running. If you want a free registration to Digital Now for you and your colleague, post on LinkedIn about this episode, something that you learned. Maybe it's going to try Notebook LM, maybe it's about XRX Tag, sidecar Hashtag, digital Now, and every post is an entry. We'll see you all next week.

Speaker 1:

Thanks for tuning in to Sidecar Sync this week. Looking to dive deeper? Download your free copy of our new book Ascend Unlocking the Power of AI for Associations at ascendbookorg. It's packed with insights to power your association's journey with AI. And remember Sidecar is here with more resources, from webinars to boot camps, to help you stay ahead in the association world. We'll catch you in the next episode. Until then, keep learning, keep growing and keep disrupting.