AI and product management | Marily Nika (Meta, Google)

there is something called the shiny object trap and I'm always telling people hey don't do AI for the sake of doing AI make sure there's a problem there make sure there is a pain point that needs to be solved in a Smart Way once you have identified what that problem is and what that's very very high level solution is then reach out and try to figure out how to actually implement it welcome to Lenny's podcast where I interview world-class product leaders and growth experts to learn from their hard one experiences building and scaling today's most successful companies today my guest is merely Nika merrily teaches the most popular course on Maven on AI and product management to certainly product lead at meta focusing on metaverse avatars and identity prior to meta she was at Google for over eight years working on Google Glass computer vision and machine learning around speech recognition in our conversation we touch on what PMS should be paying attention to when it comes to what's happening in AI we talk about a bunch of resources that'll help you get started in the world of AI how how AI tools available today can already help you do your job better as a PM we also get relatively technical into what exactly is a model our models train all kinds of fun stuff like that enjoy this conversation with merrily Nika after a short word from our wonderful sponsors this episode is brought to you by amplitude if you're setting up your analytics stack but not using amplitude what are you doing anyone can sell you analytics while amplitude unlocks the power of your product and guides you every step of the way get the right data ask the right questions get the right answers and make growth happen to get started with amplitude for free visit amplitude.com amplitude power to your products this episode is brought to you by EPO EPO is a Next Generation a b testing platform built by Airbnb alums for modern growth teams companies like netlify contentful and Cameo rely on Apple to power their experiments wherever you work running experiments is increasingly essential but there are no commercial tools that integrate with a modern grow team stack this leads to wasted time building internal tools or trying to run your experiments through a clunky marketing tool when I was at Airbnb one of the things that I loved about our experimentation platform was being able to easily slice results by device by country and by user stage fo does all that and more delivering results quickly avoiding annoying prolonged analytic cycles and helping you easily get to the root cause of any issue you discover Apple lets you go beyond basic click-through metrics and instead use your North Star metrics like activation retention subscriptions and payments nfo supports tests on the front end the back end email marketing and even machine learning clients check out EPO at geteppo.com get eppo.com and 10x your experiment velocity merrily welcome to the podcast thank you hello thank you for having me it's very much my pleasure we've interacted a little bit on Twitter we've never actually talked before just right now I've seen your course just kind of all over the place your course on AI and PM and so I just thought it'd be really fun to have you on and help us all understand what the hell is happening in Ai and especially Ain product so thanks again for being here yes thank you I'm really excited I would love your help as a former full-time PM slash everyone listening that is a current pm to help us understand what is going on with AI and product Tech in general and tools in general move really fast you know if you're trying to pay attention to like what's happening it's really hard to stay up to date on where things are going and it feels especially hard in AI it feels like there's just something coming out every day and so I have a bunch of questions along these lines the first is just like what media do you pay attention to to stay on top of what's happening and what's new and what's interesting in the world of AI and machine learning as you know very well subscribing to newsletters is something that's really really impactful and of course I sometimes you are a newsletter but I am a big big fan of the download by nyp ecology review or tler and they're not necessarily AI Centric but what I'm advocating for and what I'm telling people is that in the future everything will be AI by default so even if you have something that's technology focused you will see a lot of AI starting to get sprinkled in there I want to follow open what you just said there but maybe I'll save it a little bit maybe going in a different direction first what do you think is over hyped in the space of AI right now what do you think is under hyped and undervalued I would like to discuss tragically which is both under high and over high at the same time I was reading this article this morning where that our writers complaining and they're very very fearful and they think well writing online is gonna die everything will be studying for is going to be says they're going to take your jobs and so on and I'm just like no no no no no and technology is enhancing our work it's enhancing us it does not steal from us so that's what comes across right now and then there are other things that are under high like obviously two DBT is amazing I'm using it day-to-day but there are other things AI can do in an amazing manner like I was reading a research article the other day that said that AI can now detect place so lie detection whether it is for security reasons or at work or anything like that is now possible so I encourage people to go to these newsletters and look at these online blogs then currents and so on and just read what's happening it's not all about Saturday reading there's more there's more about AI but you should read a lot you mentioned they use chat GPT in your work life talk about that what are you actually using it for even when I'm at work and I am trying to come up with a nice mission statement right when were PMS will come up with mission statements it's just a crucial part and it's where the core begins you want to get people excited you want to get people inspired there is nothing I can write that's going to be as good as what it is right so what I do is I literally go to judge with a nice thing re-ride this mission statement from me and it's just even first try produces something which is fantastic so that number two it helps me create user segments in a fantastic way able to sing or user segments that your mind wouldn't even go there like it's just wouldn't go there and it will provide the motivations they will provide the pinpoints and you just come up with ideas as you breathe it and then the last thing that it does is it provides ideas for you but they're AI enhanced so I just use a bay to day even produce my day-to-day workflow but I'm not making it do my job for me I'm asking it after I have already had a mission in my head and what it is so is the way you're approaching it is you just put in come up with a better mission statement then and then you give it your version of the mission statement exactly interesting and you're saying that that comes up with a better mission statement than the one you had it's better because the mission statement is going to be read by all disciplines it's not just going to be read by PMS that already have a lot of context and understand it's gonna be read by leadership like Junior people by stakeholders by other departments by competitors and you needed to be on bullying ending the words that are meant to be understood by everyone you're going to keep going and they would get inspired by an invisible and then you also said to use it for personas how do you actually frame that prompt with jet GPT let's say you're working for a specific product area and you know you want to create some Fitness bands so you would say something like all would be interested in the fitness bands that doesn't have a screen and it will provide a bulleted list of people like hey young professionals that they're interested in but don't have enough time people that do not want to charge their wearables everything then the list goes on it's just fantastic you were talking about how you think the future of AI is it's the default and is what you mean there that it's basically baked into every product we use and it helps the user do better things that helps the product work better is that what you mean or is it something else I believe that both Park monitors will be AI protocols and this is because we see all products needing to have a personal life experience A recommender system that is actually good I mean you cannot watch Netflix you cannot even watch a movie without needing that after you you want white a lot of sort of like stranger things you will want something similar to watch you're not going to want to make a romantic thing to be suggested or recommended to you right also automation is another thing we need to keep improving on society we need to keep making technological advancements you're not going to be able to do that if you don't have an AI Centric view in every sector that you're working on when you say that every PM will be an aipm is you're thinking that you'll be using AI Tools in your job as a PM or that you'll be building AI into everything you're building with how do you think about that I think it's that you need to get comfortable with having a partner that's a research scientist and you will need to understand that these people can produce a smart model they'll be able to do some automation some personalization some recommendations on in a lot of people it's really uncomfortable a lot of people don't know how to approach the researchers a lot of people don't like the uncertainty that research has a lot of PMS are very very used to okay I'm gonna do this on the lines if I'll do this I'm on a lunch whereas when you're working with research it's more like we're gonna try this and then in a year if it doesn't work out we're gonna shut everything down and pick up completely so I feel that if people get more used to uncertainty and research things are gonna be good convenient for them I just thought you were comparing Chad gbt as like a researcher you're working with but you're actually saying people will have PhD researchers on their teams helping them build models into their product to make their product better is that is that what you're saying correct this is exactly what it is interesting and um and from a product perspective like in Imagine like three bumbles in my head so you want to find the intersection of something that's desirable by users something that is going to be a viable business and something that is going to be feasible from a research scientist and Technical perspective and then when you have that it's just going to be a fantastic product launch that you can run with so yeah whenever I say researcher I mean research scientists that can produce an AI machine learning model wow didn't think about how every cross-functional team might end up with a research scientist interesting interesting four PMS who are curious about learning how to do this stuff what are a couple things that PM's today who are have no experience with AI what can they do to start learning how to build AI tooling into their products understand what the hell is happening in the space of AI this is a good question and I guess the the message that I want to pass is you should then be overwhelmed by these Technologies if you don't have a technical background because you can learn these things and as a PM you'll never need to actually train or code also even if you want to trade there are no code approaches for training models but times to the question if you're working on any problems you can always sprinkle in a smarter feature so you can make it more secure you can personalize it you can enhance it with my frog detection you can make it more ethical if it's healthier you can make it faster you can make it more accurate if it's shopping you can create better recommendations basically anything where you can get data behind the behavior of the users can be improved with AI so I guess it's all about changing the mindset for PMS taking a step back and just thinking about okay I have all this data that's just lying and sitting around what is it that they can do with it I've been meeting PMS that said oh we don't have any we're not collecting any data we're not any dashboards so even that is a huge first step towards AI and then just start thinking about it what you could do just hire and get a data science intern and just see what they they are going to do there's there's just so much people can do so say you want to start investing in some sort of model some sort of AI within your team you're saying maybe hire data scientists who can help you start to build something that you can start integrating is that your advice on the first step of once you start you want to start getting serious about building some sort of AI component there is something called the shiny object trap and I'm always telling people hey don't do AI for the sake of doing AI make sure there's a problem there make sure there is a pain point that needs to be solved in a Smart Way once you have identified what that problem is and what that's very very high level solution is then reach out and try to figure out how to actually implement it and there's a definition I like hearing that I usually say that the generalist PM helps their team and their company build and ship the right product but the aipm helps their team company solve the right problem so if you want to get into aipn figure out what the problem is that you will get a data scientist to create a more referral but there needs to be a problem there needs to be audience there needs to be a user and a pin code for it what are signs that AI may not be a good approach to solving a problem you said that you know and this happened on a lot of my teams oh we're gonna build a really cool model it's going to do something really smart in this case and it often ended up being very low Roi investment and took like six months to a year before I even knew what the hell it was what was happening do you have any thoughts on signs that maybe this isn't a place you should be putting a lot of time into AI versus like this is definitely an opportunity yes we should invest a lot of time into this don't do it for your MVP it makes zero sense you did not waste time of data scientists that can train models with using powerful machines that are going to take weeks to train this is because if you have an MVP and you just want to get buy-in for an ideal feature that may use AI in the future fake it create a little figma prototype and just show it some users and just pay what the AI is going to be doing so I have a lot of young early stage entrepreneurs who talk to me and they say oh how should we train this model to do this and that because we want to prove that there is a market no do not use Ayala you should use AI where you think you already have some data or data from an adjacent product that you feel you can leverage for your own product to create something that's meaningful the recommendation recognition that we talked about but not for an MVP please people this is this is my advice how much data do you think you need for Ai and ml to have a chance to contribute you have like a heuristic of if you have anything less than this it's not going to work at all this is a good question and it honestly depends I'm not trying to do if you're trying to classify if the photo is a category dog obviously even if you have like senior 20 labeled Footers that's going to work but if you want to create Voice recognizers or complicated NLP applications you're gonna need thousands of us yeah and and this is what's making this not be easy right AI systems are not easy to build there is a life cycle of a machine learning and project and after scoping you need to figure out oh God how much data do we need where do I find this data as well right how much data sometimes I've seen people synthesizing their own fake data just so that they can have something to train with and test their models but the exact amount is hard to be on the card especially from like I'm sure data scientists have a different opinion yeah my guess is most startups are going to have nowhere near enough data to build their old model and make it something really interesting so do you have a thought on when it makes sense to try to build your own model try to train your own gbt Type Thing versus use something that's already out there like say GPT or a journey or all those guys if you are a big tech company and you're offering a service that's is gonna do speech recognition or that it's gonna have like their own tragedy you want to use more data and more diverse they've got to train and retain train because if you don't then your quality is going to be the same as every other companies there are agencies that are selling data packages of data that already so you can get them and train your models but the question is if everyone takes that exact data set then the quality that every single company is producing is going to be the exact same so you do want to diversify they want to collect your own data and I guess a good question for my plan perspective when is the quality of your product good enough to launch and that is like a really interesting point because it's totally your responsibility as a PM to decide okay the recognition of whether this folder is a category dog is good enough for the users it's like 70 accurate 80 accurate where is the bar where do we launch and that's why I'm like the aipm role is so cool because you have problems like that the soul that no one else has kind of tackled before so it's all on you we've thrown out these words model and we talk about training models do you have a good succinct kind of explanation for what a model is for folks that haven't you know that aren't that Technical and then just the general idea of training a model like what is a simple way to think of here is what a model is so I have a three-year-old girl and I'm good to hear about life and everything so I was recently good to hear about the animals and you know you explain things to her once or twice like what the moment is or a rhino and so on but you will end up training your kids brain by repeating the same information again so you will say hey here's what the Rhino looks like here's what another phone looks like here's what the Marino looks like huge well they know the phone looks like and once you've done this enough times then your kid will see an animal on the street and they'll be able to rub a Max and say oh yeah that's like the Varina we were talking about this is exactly what a model is the model is like a kid's brain it has the ability to take an input which means it has the ability to take an email and say oh I recognize what this is that looks like a rhino but I'm 70 sure about this so it will output the probability as well of the certainty and you said image but it could be text for say chat GPT in the future I imagine video there's also voice like whisper that's an awesome explanation basically it's trying to recreate the human brain is uh is a nice way of thinking about it and then training a model can you talk about what that means the pros of training the model for example is providing a lot of images that are legal and say hey here's what God looks like here's what it all goes like and we're talking about thousands and thousands of data data sets around us and once you do this there's a process where the model is just processing this information and it's learning it's finding patterns through it and the patterns are not in the form of oh if this is gray then this means this no it just learns in the smart way how to identify specific things that we don't even understand and then it's able to Output the the probability of whether a photo is going to contain the color and Dot just conceptually what is the output of the training is it code that is auto-generated with these decision trees and weights and things like that is it a database of weight like just conceptually what is the output of a training that becomes a model well it's the simplest way to think about that so let's imagine speech speech is a great example for example I'm talking to a device which is like a home assistant and I say hey what is the weather like today this is going to take my foleys and audio and it's going to process it and the output is going to be a transcription so it's literally going to be text that corresponds to what I sent to it thinking about the stuff you've worked on at Google at meta anywhere else you've worked on side projects even what are some of the cooler applications of AI machine learning that you've worked on contributed to or even seen that you can talk about I imagine there's a lot of sensitive stuff too going on one thing I want to talk about is the team I used to work for for Google which was the the rvr team and they were working on an air glass and actually they they had a video on last year's Google I O they were able to have the Google Glass on someone that spoke one language and then this other person will stand in front of him that spoke a different language and the glass would take as an input that all the other came from that other person and they will transcribe it it would translate it and show it on the screen for that person in their language so we're talking about the ability for this devices to unlock the borders of communication and that is not science fiction this is what amazing and mind-blowing there's no science fiction anymore these things are real the technology is here it's just a matter of connecting the pieces to the puzzle in order to see them come into life so I think that one was the most one of the most impactful things I've ever seen I remember that demo it was pretty incredible okay so thinking a little more broadly do you think chat GPT or just say gbt4 or GPT 5 gpt6 do you think at some point this will replace product manager something I see on Twitter a lot of people are like oh my God product management did this thing made my product requirements document for me or you talked about how it makes your mission statement better you think there's a place where VMS aren't necessary anymore oh absolutely not as I said like it makes everything better if anything is gonna free out time for me to to do other things so there are less tedious for example I am running so many projects and they all need their period and appear these have all these areas that are common across of course all of them if I had a system that can actually write the tedious stuff for me so that I can focus on more strategic side of things that would be incredible it will make us smarter if anything you will unlock new areas of product management that we haven't realized that but are there are there areas do you think with your kind of vision of all PMS will be aipms are there areas that you think PM should invest more skill wise or areas they should less focus on and invest because say some machine learning model is going to do that for them I'd like to see people being less overwhelmed less intimidated less afraid to start learning how to code how to train a little model on their own this is because even if you know tragic or these local applications may be able to do this for us it gives you a different approach a different mindset a different if you want confidence to know how things work and here's a silly example I was learning how to play the piano when I was young and when my teacher came in I was like oh I want to learn how to play this cool song There were some songs that they're in like and she said no you need to start with a classical music and I just hated it all the time and I said why do I have to do this because she said if you learn the fundamentals and how you know where things started and the beginning of music It's Gonna help you along the way to create music on your own if you want to and she went right like I I just loved it so it's the same with coding I encourage people to just take an online course understand more get your hands dirty pair up with someone else that's in the same boat as you because this is going to give you the skill set to understand how that tool that's going to help you in your day-to-day was even created in the first place instead of blindfoldedly distrusted to do your job this episode is brought to you by Pando the always-on employee performance platform how much do you love the performance review process yeah it's time consuming subjective biased and there's rarely any transparency with the rapid shift of distributed work it's a struggle to create the structure and transparency that you want to help your employees have the highest impact and growth in their careers Pando is disrupting the old Paradigm of Performance Management including a continuous employee-centric approach so employees stay engaged see their progression in real time and know exactly when and how they can level up with pandu managers can leverage competency-based Frameworks to effectively coach and develop their teams and align on consistent growth standards resulting in higher quality feedback and higher performing teams visit pando.com Lenny for more info and get a special discount when you sign up and reference this podcast that's pando.com Lenny for someone that actually wants to do that and learn to code which I love that advice do you have any resources places that you point people to for learning to code getting started down that path it depends on what type of learner you are there are some people that like learn offline so just go Coursera there's so many courses there is an amazing one actually introduction to AI by Stanford whether they're going cars report let's take a look at that but I know that a lot of people don't like don't have the time to have the discipline to actually you know take time off or like after work after they put their kids to sleep to just do it so if you enjoyed learning with others if you enjoying being part of a team if you enjoy going through a journey together then I recommend these resources so there is something called Career fundry which is a fantastic online college School general assembly and then coding Dojo I I was actually giving talks about it is a god called Dojo about Python and all it takes is just a few weeks of your time and passion and just for you to roll up your sleeves and just realize that this is not intimidating and realize the benefits you can get from by learning how cool awesome thanks for sharing those we'll include links in the show notes going back to a PM trying to become better in AI if you think about a PM that's kind of early in their career and wants to become a very strong AI PM I know you have a whole course about this which we can talk about now or or later whatever is easier what should that PM be doing we talked a bit about learn to code maybe start playing with tools what else do you suggest PMS that want to become really strong aipms do now and invest in so I do have a course that's coming out on February 6th on Maven which is for current and aspiring product managers that want to build AI products but I also have offline recordings I have the same course and then I'll find bases on my website I'd be happy to talk to you prioritize me about this what I feel people should understand is what it takes to manage an AI products of course people are very familiar with the stages of product development in general but AI product development is different as I mentioned before sometimes you're actually managing the problem and not the product and you're trying to figure out if there is a problem that makes sense to be answered by a smart solution so it's kind of a very interesting and more complicated process than regular product management so number one figure out how it differs from General product management number two if you're already at the company that is actually having AR researchers and AI region scientists I encourage people to just reach out to them and Shadow them and spend an hour of their week just just talking to them and experiencing what they're doing this is going to open your mind this is going to give you so much context as to what it is and and the endless potential that you can identify there awesome and is there anything else you want to share from your course that you think might be interesting to folks so we talked about why it's awesome to be an aipm but I do want to collab that there are a few challenges that people need to be aware of number one and I kind of mentioned it before is the uncertainty you may have been working on all these incredible research and ideas in hypothesis but then when you actually train the model the results you may be getting may not be optimal may not be answering the questions or the hypothesis that you actually had in mind so that's number one you need to be able to encourage the team throughout this process because you're like the captain of the ship you need to be the one that's kind of cheerleading the team making sure everyone keeps going number two you are gonna have to be like you are gonna have to change the emotion in managing this from a leadership perspective can be tricky and it can be challenging number three we talked about data but getting good data is hard like you may need to be creative figure out ways for data collection that you never thought you'd do you may get on the street and ask for people to actually contribute data for my future drawing like you need to be able to and willing to do everything and the last thing is from a career trajectory usually product managers get ahead the more they launch but if you're in a research or if you're not going to learn to us often so you weave to make sure to clarify with the hiring managers early on hey what does progress how am I gonna get assessed in a research work which is different than what I've been doing so far so it's challenging but I always encourage people to flex different muscles and this is like the zero to one muscle the other thing is this is crucial when it comes to program this actually is a great segue to a question I definitely wanted to ask which is around getting buy-in for investment at a company for ML so there's sometimes like all this energy for like a zero to one let's just try something sometimes not but that maybe that's maybe there's a two-part question here do you have any advice on just getting buy-in for we want to try something with them out it's going to take us six months to figure out if it's worth the effort but we think there's something here and then sometimes there's like a lot of energy initially and then you get some win like your search rankings smarter and it's great but then maintaining that having like all these really expensive people working on just tweaking this model and continuing to make it smarter and a little more efficient often it's hard to continue to get buy-in for that sort of team do you have any advice on initial kind of buy-in let's try something here and then down the road just like keeping a team going trying to make this thing smarter and smarter people should know that there is an excellent source of inspiration and something that could kind of do risk things which is adjacent products maybe the company has already launched a product that has been successful those AI firsts and whenever I try to convince leadership about something that I want to do that's kind of a big bad I always use examples and like hey this it was crazy at the time here's how the work what I'm proposing is very similar to this crazy thing and then I propose a little contingency plan but hey that doesn't work out here is the rollback plan here's kind of the Maximum Impact it will have done in United Way which is not going to be too much and you kind of take it all on zero and it's interesting because the more you work on the specific company the more trust you get and if the culture is such then failing is going to be welcome so a lot of companies that welcome pink because you can just go ahead and do this sort of thing do you tell me if I'm wrong but I feel like most investments in ml are not successes and often not great uses of time I'm curious if that changes with more tooling and more kind of public models that people can plug into without having to build their own I wonder if it becomes like oh okay look we'll put in three weeks we'll get something really useful exactly and also the other thing and I wanted to add on the questions you asked me for about hey how do you actually updated about new Niche Tech we shouldn't underestimate Academia and the research blogs and there's a website called archive where you can see new papers that come up because this is where and like used to be there for a long time like there was a lot of information on this sort of thing but it's now recent where we see that research scientists and research orgs are kind of not as siled as the history so the more companies invest on Staffing this layer between production magazine and research academic research the more PMS you're gonna add there then the more you're gonna see this bridge kind of creating Goods products that are creating so sometimes you have amazing ideas by research scientists but you need the PM to take it and actually figure out ways to also monetize it right that's the other thing if you're a PM you need to come up with ways to actually be able to monetize and try gpp is now free for everyone but I don't know if you if you saw there was a there was a sign up Forum that was kind of coming around saying hey would you pay for this what would be the minimum yield people the Maxwell you think what would you like to see if you paid so having BMS Bridge the tap is crucial for companies to be able to take the pictures and actually come up with me in full use cases for users I think they actually started charging the other day I think it's like forty dollars forty two dollars a month to start using it as I think people have been talking about it on Twitter I don't know if that's live yet and then you talked about research papers when I think that I always think of Tyler Cohen he has this awesome blog marginal Revolution and he's really good at sharing insights from research papers that he's reading so that's another place for folks to check out he's just like he's a really smart dude he's really excited about Ai and GPT in general so he shares a lot of really interesting insights about it all so going a little bit to your course I have a couple questions about it one is just like can you just talk about like the broad framework of your course like how long is it what do you learn what are the workshops broadly and then I have a couple follow-up questions my course is three weeks long it's meant for people that they're either aspiring or crying PMS that they want to understand how to sprinkle in AI Solutions or they want to be a full-time AI games week one is more about introduction what the product development lifecycle is for regular products and how it differs for aipm specifically and then we talk about idea creation how long on Earth do you come up with ideas and I love what Steve Jobs said where she she used to say well users don't know what they want until you show it to them and that's exactly the mindset I want to invite to people and say hey people don't know how on Earth to use AI people would never have imagined a chance if you can be what it is and then we take that and we dive deep and we talk about how on Earth do you productionize something like this what are the different partners you're working with what is the research scientists and how on Earth do you collaborate and how do you partner with them how do you convince them of what you have in mind for their precious research to be converted into a product how on Earth do you convince them to trust you and and how do you influence them and then at the end we're talking about how you actually will be able to pave your path to afpm all the way from interviewing for this role from what good resume look like and doing some work interviews because Memorial practice the better it's going to be how many workshops are there through the course nine workshops nine workshops okay of the nine workshops which of them are you finding is the most exciting game changing for someone most interesting so throughout the duration of all these workshops people have homework and they actually take home an exercise where they need to create and develop their own AI product end-to-end and they can pair up with each other by the way there was this this two students paired up and actually where I would raise funding which is mind-blowing to me which is really that's awesome um but to continue the most exciting part is when everyone at the very end are actually presenting their work and they're actually asking questions and getting feedback and they're just really excited and proud for what they've created that's a good reminder of a lot of the learning that you do is just doing it not just kind of reading about it and following Twitter can you share any examples of stuff people built after the course someone was able to actually and I came to not create a loan model that was able to take as an input x-rays that they found online and was able to tell us what was wrong if something was wrong with that patient inmates just crazy to think that you can do that within three weeks obviously it was just by photos we were able to crawl online for x-rays but the concept is there that you can build something like that you can create it and to take it a bit further they wanted to create the lower recommender system and say hey we think this is what's wrong with you here are the steps into Polo obviously we're not trying to play doctors or to to pretend that you know we're Medical in any way but being able to see that actually functioning is just it's very that's amazing do they already know how to code the this team that built this thing they did not but part of the course is to teach people the basics that you are going to need from it PM rents and there are some no click tools as I mentioned that are gonna allow you to drive and drop and train these models and ebook photos in it and be able to can you mention those tools again because that is really interesting and it's just like a peek at your course but if someone wanted to start building something like this what what are some of these tools we could check out one of the tools I would like to recommend to people is actually autoimmel this is offered by Royal cloud and essentially it allows you to train high quality custom machine learning models with minimum effort you don't need to be able to understand cold or anything like that you need to have a lot of photos and images that you have already cool with it but it's not going to do the collection for you and a great application I had to see there's actually a YouTube video about this is there was this company that actually had a lot of winter Banks and what they did anyways in order to maintain these they would actually have people manually have huge ladders and go take a look and see if everything was okay so eventually they just got drones and they had these drones fly on all of these machines and take photos and everything and then they downloaded all these photos and they uploaded on automl they were able to see which ones to meet in maintenance and which did not and I think they reduced time from like three weeks of work to like a few hours of knowing which lead maintenance and just be able to send people there so it's this type of thing that you can do on your own by applying this sort of tools and that tool is called automl yes I don't know amazing we'll link to that in the show notes coming back to your course and maybe just a couple more questions can you just talk about what it takes to build a course like the course you built like how much time did it take you how much work did it take anything there you want to share they treated creating my course like a product it's just like what I did is I came up with some hypothesis as to who the audience was and as to what they were looking to get out of it and I started reaching out to people and I started saying hey first of all would you like to learn from me second of all what would you like to learn what are the specific questions that you will need answered because these are people that are working full-time with families right in order to take a break from all that you need to provide something to them that's meaningful and there were quite a few iterations in the beginning I was focusing the course more for software Engineers that wanted to become AI product managers but then they realized no there are a lot of PMS that want to become AI product manager so I I did a little online ship there so what it takes is make sure you find the Right audience make sure to figure out what that all viewers wants make sure to have the right duration one week I find it too short two weeks still a bit rushed three weeks is excellent because you give the opportunity to everyone to present and to get to know each other on like an offline Discord Community which is another important part and then the last thing you need to have a personal relationship with everyone so I've messaged everyone I've seen everyone's application I met with some people as well just to make sure to answer any questions and concerns because I wanted to make sure that people were comfortable distrusting and stranger like me and paying them for to provide that knowledge for their course so it was it took quite a few iterations but I was able to get there and I'm very very happy about it and I recorded it offline as well for people has anything had to change in this course maybe it's just as a last question things are moving so fast is there anything you've had to like rethink redo since you first built it I actually added bonus sections and one bonus section was Georgia bikini and how it was trained this is because I started this new cohort in December and on day one the question I got is what is this how did it start what is going on how did they train it so I added the beginning section for it and I point people to it amazing anything else that you'd like to share before we get to our very exciting lightning round it was someone that recommended I actually did a course and in the beginning I it was it was not in the beginning I laughed and I said wait people would want to learn from me really and of course they did and I'm teaching so many people so what I want to tell people is don't underestimate this try creating your own courses as well people may want to learn what you take for granted for them they need game changing it can be life-changing so building courses is an amazing thing and you know we're living in the whole collaboration Aaron so the course is content so go try this I find that teaching and at least crystallizing thoughts is one of the best ways to learn it yourself imagine you learned a lot about AI much more than even came into it with just putting it together into a course absolutely and I I got some unconfident questions that I had no idea how to tackle like people on day one were like how do I assess the trade-offs between these two different moments and I had to figure out how to answer these things and how to Incorporated them in my course so learning from the students learning from the course learning from explaining is just so by valuable so skills that they can get well with that we've reached our very very exciting lightning round I've got five questions for you I'm gonna go through them pretty quick whatever comes to mind share we'll see how it all goes sound good sounds good two or three books that you recommend most to other people inspired it taught me it's all about how to create pick products people love oh yeah Marty Kagan right yes that's the one you know right okay cool anything else or that's the one that's the one that comes to mind you look like a thing and I love you and I have it right here it's a great thing super super cool it's about how AI works and why it's making the world a weirder place it's actually a very fun and there's one more which is a book a workbook I recently launched with Atlanta car and it's about um it's a workbook for women in Tech trying to navigate working in Tech it's called Adventures of women in Tech workbook so that's another thing that I want to shamelessly that's a great choice to plug where I can folks find that is that on Amazon it's amazing what's a favorite other podcast that you like to listen to I like bosses podcast I don't know if you're aware of it boss is the CTO of Facebook he has a great podcast I have not heard it I do know of boz I will check that out I think I had a podcast he had some great writing over the years maybe that's way doesn't write anymore he has this podcast what is a favorite recent movie or TV show that you've loved oh my God the White Lotus people were talking about this thing I I ended up you know just trying it out and me and my husband we just binge watch the whole thing is just so different so mind-blowing get you excited about going to Hawaii again it's just it's really good have you seen the second season I've seen that and it's so much better than the first which is rare I agree awesome I love that show what is a favorite interview question you like to ask and bonus points if it's AI related I love to ask people how would you explain a database to a three-year-old and I know it's it's kind of an AI not very much Ai and but I love asking because people are kind of things that boxing wait what did you just ask me but it's so important to be able to explain things in a simple way and have the storytelling to convince a kid and really explain technical terms to non-technical people favorite AI based tool that you think people should check out I mean talk about tragically now my head is on tragedy this is what comes to mind um well the lens sound was pretty cool too right we all uploading our photos when we're able to see what they would look like as fantastic Heroes I have to say I tried being the nail version because it was so much cooler than the female version so that's what I recommend to people try the mail that's fun and there's actually a they actually have pets now that's what got me to download and pay for it he can take pictures of your pets and they look so fun that's like a killer feature right there good job linza and the app is lens uh right yeah once amazing merrily thank you so much for spending time with me sharing your wisdom two final questions where can folks find you online if they want to learn more and reach out and how can listeners be useful to you thank you so much uh people can find me on Instagram I also have a product tunnel on YouTube that you can check out I just started it I'm just getting used to the whole process I'm also kicking off a newsletter just any social reach out and you'll see all my links how do they find the YouTube channel how do they find a newsletter typing merlinica merrily thank you again for being here thank you so much Lainey it was a pleasure thank you so much for listening if you found this valuable you can subscribe to the show on Apple podcast Spotify or your favorite podcast app also please consider giving us a rating or leaving a review as that really helps other listeners find the podcast you can find all past episodes or learn more about the show at lennyspodcast.com see you in the next episode [Music]

Channel: Lenny's Podcast

Views: 25,481

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Id: qNPPoj1qUG0

Length: 48min 2sec (2882 seconds)

Published: Sun Feb 05 2023