Wallapop

wallapop

Venture builders, organizations that create and scale startups from scratch, are wielding a growing influence in the Spanish startup ecosystem. Just a decade since the launch of the first Spanish venture builder, the number of similar vehicles in the country has . swelled to over 30 Unlike traditional venture capital firms or accelerators, which typically invest in and support already established startups, venture builders take a more active role in the development of new companies, coming up with business ideas in-house and using their own resources to bring them to the market. These entities have teams dedicated to identifying market opportunities, developing business models, and recruiting talent. Overall, their objective is to provide all the necessary resources and support to launch and grow the company. In return, they typically take a significant equity stake compared to other models. venture capital The era of the startup factories The of the Spanish startup ecosystem in recent years, as well as the nation’s tradition of innovation and entrepreneurship, has created fertile ground for venture builders. rapid growth These so-called “startup factories” have played a key role in creating and scaling some of Spain’s most successful startups, including Wallapop (which recently closed ) and Glovo. an €81M funding round Outside of Spain, venture builders have helped launch companies like Medium and Venmo. “Our goal is to build sustainable and scalable companies that take into account market trends and take advantage of the great opportunities offered by technology and innovation,” says Christian Rodríguez Fornós, CEO & Chairman at Mutter Ventures, a Spanish venture builder which has helped create startups such as Byhours, Northweek, Hawkers, and UrbanSecrets. The firm’s business model is based on attracting investment for the development of in-house projects. It distributes its own funding and resources according to the needs and development stage of each of its portfolio companies. According to Rodríguez Fornós, some of the biggest hurdles contributing to the failure of startups (inadequate teams, running out of capital, and incorrect market analysis) can be overcome with the support of venture builders, which provide all the necessary elements to help young companies thrive. “All our startups are led by professionals who are experts in the sector corresponding to each project,” Rodríguez Fornós points out. “In terms of structure, each one has a CEO and its own team that expands according to the stage of the company and taking into account the operational needs of the business.” The startup-as-a-service model With in-house experts dedicated to staying on top of market trends, emerging technologies, consumer habits, and regulatory changes, venture builders are well-positioned to identify lucrative opportunities, navigate evolving landscapes, and shape the future of industries. By leveraging their expertise and adaptability, they can proactively innovate and drive transformative change in the market. Corporate Lab, a Spanish venture builder backed by the VIKO Group whose portfolio companies include Okify and Equipzilla, works closely with large corporations looking to diversify their capital or business, offering them a “startup-as-a-service” model. “It is normal for corporations to expand their frontiers through startups. Some do so as venture clients: they contract a specific service or product from a startup. However, more and more companies are opting for other innovation models such as the creation of startups,” explains Brais Comesaña, Head of New Ventures at Corporate Lab. “Unlike the venture client, the result will be within its own business network and will become part of that group, instead of just hiring a service. This makes the process much more secure, as they benefit not only from the capital, but also from all the competitive advantages of having a large company as a parent company,” he adds. Corporate Lab helps companies explore new business models by following a two-step process. “First, we investigate an idea, possible competitors, potential users, and the market. From there, we get down to the nitty-gritty: we talk to all the parties that could potentially be part of what we are building, “ Comesaña says. “Additionally, the companies we work with benefit from being a part of the VIKO Group, which grants them access to specific resources and services that may be required in the future.” As the Spanish startup ecosystem continues to thrive, venture builders will remain a crucial alternative to traditional venture capital models, revolutionizing the way startups are created, nurtured, and scaled. By offering a blend of expertise, support, and risk reduction, they empower entrepreneurs and corporations alike to explore new horizons, foster innovation, and drive the growth of groundbreaking ventures. This article was originally published by Siobhan Parnell on . Novobrief

Redefining the Traditional Startup Model: Spain's Venture Builders Lead the Way

Redefiniendo el Modelo Tradicional de Startups: Los Venture Builders de España Lideran el Camino

Redéfinir le modèle de démarrage traditionnel : les créateurs d'entreprises espagnols ouvrent la voie

पारंपरिक स्टार्टअप मॉडल को फिर से परिभाषित करना: स्पेन के वेंचर बिल्डर्स ने रास्ता दिखाया

従来のスタートアップ モデルの再定義: スペインのベンチャー ビルダーが先導

Redefinindo o modelo tradicional de startup: os Venture Builders da Espanha lideram o caminho

Xác định lại mô hình khởi nghiệp truyền thống: Các nhà xây dựng mạo hiểm của Tây Ban Nha dẫn đường

重新定义传统创业模式：西班牙风险投资公司引领潮流

Unrealistic Valuations and Getting Back to Fundamentals It’s almost as if creating a company with a valuation of $1B+ is the single most important goal of entrepreneurs rather than creating a profitable and sustainable business. In the on-demand food/delivery space, there’s a ton of competition and a race to take the lead. Instead of achieving this goal through pure business growth fundamentals, popular thinking seems to dictate that the easier route is to just gain status and use the value of the company as the metric of market leader. (Granted, should be funding companies that have actual solid growth metrics or at the very least a leadership team that has absolutely zero doubt in their minds that they will win no matter what.) unicorn logical VCs The concept of enormous funding rounds and stretched valuations paving an easy road to success/growth may be changing. This is highlighted by recent failure of a new funding round at a supposed $1B valuation. DoorDash Perhaps racing to goals for investment should not be the primary objective. Perhaps companies should be focusing on core growth fundamentals such as the following strategies: Beating competition in quality vs. price. For example, a similar service like selects only top quality restaurants to feature in a local market. They don’t feature brands like Denny’s. The choose quality vs. quantity. Caviar Walking before running. Nailing operations. Gaining traction in the market, becoming the leader in the locale and moving onto another. Learning from and don’t disclose the capital raise amount or valuation. Wallapop’s leadership Focusing on getting good PR for outstanding service, an exceptional value proposition and building a fun and trustworthy brand, rather than the latest Techcrunch story on closing the Series B. The goal should not be to raise an obscene amount of capital which can lead to an artificial valuation. Note what happened with Gilt Groupe, as they once had a $1B valuation but we’re recently acquired by Hudson Bay (SAKS) for only $250M, less than the total amount of funding they took before being bought. Maybe it’s time for startups need to get back to small business fundamentals. (you know, those principles of “ ” that have been around for thousands of years…) buy for one, sell for two Just a thought…

Lessons From DoorDash’s Unicorn Quest

Have you ever seen a photo on Google Street View and thought ? Well, I have. So I started a project to get Street View photos at random and turning them into wallpapers. "Damn, this would make for a nice wallpaper" First problem is that Street View photos are cluttered with interface controls. I soon found out it's a problem that had been already tackled by another kind of people that need clean Street view pictures: journalists. Karl Hodge listed all the that should be hidden to get a clean picture. Andy Dickinson went one step further and created a Chrome to hide all those elements at once with a single click. elements extension Now, if I only wanted a couple of pictures from Street View, that extension would have sufficed. But I get tired of my wallpapers very quickly. My perfect day starts with a good wallpaper that I have never seen before. I needed a solution that could automatically generate many photos to save me from boredom. The good news for anyone who wants to automate Google Maps stuff is that there are APIs for that. They aren't free of charge, but Google gives free monthly credit to developers. That was more than enough for my small project. In my case, the perfect API to be the . It has a function to return a photo from a given location. The call is as simple as . Problem is that the maximum size allowed is 640x640. Not ideal for a wallpaper. seemed Street View Static API this After some research, I found another API called . It has a that allows web developers to include Street View panoramas on their sites. Google even provides a that was almost exactly what I was looking for. Maps JavaScript API Street View Service demo Street View Service is flexible enough to allow for the disabling of all interface controls, so no CSS hacking was needed. And as a very welcome bonus, it also permits removing the street names! Unfortunately, that API doesn't provide a way to get a picture from the panorama the same way the Static API. So the solution I made was to create a simple page with a clean panorama and take a screenshot. Here is the final version of the page's source. Clean Street View <!DOCTYPE html> < > html < > head < = > meta charset "utf-8" < > title </ > title < > style { : ;
        } , { : ; : ; : ;
        } /* Always set the map height explicitly to define the size of the div
    * element that contains the map. */ #map height 100% /* Optional: Makes the sample page fill the window. */ html body height 100% margin 0 padding 0 </ > style </ > head < > body < = > div id "map" </ > div < > script { urlParams = URLSearchParams( .location.search); latitude = (urlParams.get( )); longitude = (urlParams.get( )); panorama = google.maps.StreetViewPanorama( .getElementById( ), { : { : latitude, : longitude }, : , : , : , : , : , : , : });
        } ( ) function initPano // Note: constructed panorama objects have visible: true // set by default. const new window const parseFloat 'lat' const parseFloat 'lng' var new document 'map' position lat lng addressControl false linksControl false panControl false fullscreenControl false zoomControl false enableCloseButton false showRoadLabels false </ > script < = > script async defer src "https://maps.googleapis.com/maps/api/js?key=ADD_YOUR_KEY_HERE&callback=initPano" </ > script </ > body </ > html The page gets the query string parameters and and displays a full screen clean Street View panorama of the location. This page alone can be used as an alternative to the Clean Street View extension, with the advantage of having the street names removed, but the drawback of needing a Google API key (which, by the way, demands a credit card). lat lng At this point, I needed to somehow save that picture so I could use it later. And here is the part I apologize to all JavaScript developers out there. Although I could create the page (basically because almost all the code was in the Google's demo), I couldn't do the screenshot part. To be fair, I even tried. I resorted to Python. In Python, one way to render a page that runs some JavaScript is using . It's a library that allows for task automation on browsers. Originally created for web application testing, Selenium can be used for a variety of tasks, including , boring stuff automation and taking screenshots from pages :-) Selenium web scraping I won't get into the details of how Selenium work. But If you have never used it, it will open a browser and do whatever your code says. In my case, all I needed to do was to open my custom page with some values in the parameters in a fullscreen browser, take a screenshot and save the image file somewhere. Here is a sample code. time selenium webdriver lat = lng = options = webdriver.chrome.options.Options()
options.add_argument( ) options.add_argument( ) options.add_argument( )
driver = webdriver.Chrome( , options=options) driver.get(page_path)
time.sleep( ) driver.save_screenshot(str(lat) + + str(lng) + ) import from import # Fenway Park's coordinates 42.345573 -71.098326 # Webdriver setup "--log-level=3" # minimal logging "--headless" # hide browser's GUI "--window-size=1920,1080" "chromedriver.exe" # Get and save image 1 # wait for image to load "_" ".png" Only being able to save a screenshot of a specific location wasn't enough, though. I wanted photos from many random locations. This is another reason I quickly jumped to Python. I wouldn't be able to do that in JavaScript. Sorry again JS folks... Generating random coordinates that return valid Street View photos is harder than it seems. The API wouldn't help me with that, so I was left with the brute force approach. Fortunately, Google lets you check if a given pair of coordinates has a Street View photo free of charge through the . Street View Image Metadata API Still, picking random coordinates and checking if they are valid on Street View is quite literally picking drops in the ocean. To alleviate that, I restricted the search of coordinates to be only inside some polygons on Earth's land surface. And what polygons did I use? I drew two big polygons, one around the Americas and the other encompassing Africa, Asia, Europe and Oceania. It's still very much brute force because I'm not generating the points straight from the polygons, but checking if a totally random coordinate pair is inside one of the polygons. It turns out it can be done with the function, which implements a algorithm. And I thought this was a trivial mathematical problem... matplotlib.path.contains_point point-polygon Once a point is inside one of the polygons, I proceed to check if the point has a valid Street View panorama. Here is the final Python code: sys glob time csv requests matplotlib.path mplt_path selenium webdriver os path random uniform API_URL = API_KEY = WIDTH = HEIGHT = getattr(sys, , ):
    script_path = path.dirname(sys.executable) :
    script_path = path.dirname(path.abspath(__file__)) paths = [] poly_file glob.glob( ): open(poly_file, newline= ) f:
        data = list(csv.reader(f))
        paths.append(mplt_path.Path(data, closed= )) status = status != :
    onland = onland:
        lat, lng = uniform( , ), uniform( , ) p paths: p.contains_point((lat, lng)):
                onland = locstring = str(lat) + + str(lng)
    r = requests.get(API_URL + + API_KEY + + locstring)
    status = r.json()[ ] options = webdriver.chrome.options.Options()
options.add_argument( ) options.add_argument( + str(WIDTH) + + str(HEIGHT))
options.add_argument( )
driver = webdriver.Chrome( , options=options)
page_path = path.join(
    script_path, + str(lat) + + str(lng)
)
driver.get(page_path)
time.sleep( ) driver.save_screenshot( + str(lat) + + str(lng) + ) import import import import import import as from import from import from import # fmt: off "https://maps.googleapis.com/maps/api/streetview/metadata" # Not billed "ADD_YOUR_KEY_HERE" # get a key at https://developers.google.com/maps/documentation/streetview/get-api-key 1920 1080 # fmt: on if "frozen" False else # Setup on land polygons for in "polygons\*.csv" with "" as True # Get a valid Street View coordinate False while "OK" False # Pick a random point that is on land while not -180 180 -90 90 for in if True break # Check if random point has a Street View panorama "," "?key=" "&location=" "status" # Webdriver setup "--log-level=3" # minimal logging "--window-size=" "," "--headless" "chromedriver.exe" "clean_street_view.html?lat=" "&lng=" 1 # wait for image to load "images\\" "_" ".png" I must say that I'm very satisfied with the results! Most of the time, I get empty roads in the middle of rural areas. These bring me the feel of solitude I was looking for. No more dull wallpapers again. If want more implementation details, check out the repository. GitHub

Using Google Street View Photos as Wallpapers [A How-To Guide]

Over the years I have developed a certain way of thinking about my life and high-level goals, a general framework that I use to organize/optimize everything I care about in life in a comprehensive and flexible way. It really helped me to figure out what I want out of life, and to strategically pursue it. This is very personal stuff, and this post is my first attempt to describe it. Not everything will make sense to you, but I hope that you will find it interesting, and extract some general ideas that may help you come up with your own framework for organizing and pursuing life goals. I think about my life on four levels abstraction: Values and drives “Lanes” Projects (Goals) Habits Values and Drives are the highest-level desires I want to optimize for, the most abstract metrics I want to maximize: Values I want to be clever and creative. I want to learn things. I want to generate value with my mind and be good at it. I want to pursue the path to mastery at my craft. I want to do it as well and for as long as possible (without health/money/other problems getting in my way). are other, less abstract things I want to have in life and am trying to optimize for: Drives I want to have fun, engaging, and meaningful work. I want to be rich, healthy, safe, free. I want to be good at writing and comedy (just because I love them and want to max out my skills). I want to be good at teaching. I want to make impact. etc. Lanes are the general areas I focus on in order to pursue (maximize) my values and drives. I think of values/drives as a compass pointing me in the direction I want to walk towards, and lanes are the different paths I can take. Lanes What I want is to have the fewest number of lanes that are as effective at satisfying as many of my values/drives as possible. It’s a matter of balance, too many lanes would make me unfocused and distracted, and too few can’t cover everything I care about in life. I organize my lanes using app, it’s a constantly evolving document. I keep continuously tweaking and rearranging my lanes as I learn more about life, myself, and ways to approach my goals. It’s current version looks like this: draw.io is the most efficient way for me to maximize my creativity, have fun/engaging/meaningful work, generate value, make money, and impact the world. Startup Being good at is something I really want, and deeply enjoy for the sake of itself. It has to be a separate lane because no other lane can take care of this drive. comedy Learning all I can about is a way for me to satisfy my curiosity, and potentially contribute to the most meaningful, significant, impactful thing a human being can contribute to (in my opinion). Artificial Intelligence , like comedy, is something I value for the sake of itself. It satisfies my curiosity, drive for teaching, self expression, etc. Writing is everything related to taking care of my heatlh and general well being. Mainly, it includes staying on top of my clean diet, exercise, controlling my caffeine/nootropics addiction, improving my sleep. And also, keeping up with what I call “Info diet” — staying away from HN/Reddit and other social media, spending more time reading and less time refreshing social feeds. Lifestyle Projects are the goals I pursue in order to move further down the lanes. If values are the compass, and lanes are the available paths, then projects are like milestones I’m walking towards right now. As you can see in the picture above, they’re separated into the ones of the highest priority that I pursue actively(the ones in blue color), and the alternatives that I consider, but don’t actively work on(grayed-out ones). Projects Just like with lanes, I actively tweak and rearrange the projects. As I complete my goals, or find more optimal ones, I tweak them so that the most important goals are staying at the top, and the old ones are removed off the board. Since you won’t understand what each of the goals means based on the picture, I’ll describe the current active goals the best I can. Under , the goal number one is to complete the courses I’m currently going through so that I would have competent, complete understanding of React/Redux (which I use to build my startup). The goal number two is to develop features for my startup called . Webdev/Startup Nulis Under my goal is simply to get used to consistently posting the jokes I’m writing on twitter, every day. Comedy, For my first goal is to complete a about Deep Learning, and then go through the fast.ai , to gain a solid fundamental understanding of this field. AI, Machine Learning Mastery book Deep Learning course For , I want to keep writing my blog posts, and take well-written private notes about the things I’m learning about AI. writing For , my goal is to get through 1.5-months-long withdrawal from caffeine and nootropics(at most 4 packs of green tea per day, at most 2.5mg of noopept). My second goal is to stay on top of my info diet(avoiding HN and Reddit as much as possible, except for the times I’ve decided it’s okay). I’m pretty happy with my diet/exercise at the moment, so I’m keeping them the same. lifestyle Habits To continue with my metaphor (values are a compass, lanes are the available paths, projects are milestones), habits are like the engine — a set of things I do every day that take me at least one step further towards my goals, on every lane. I’ve developed an that helps me to track my habits, and currently they look like this: app Checkmarks represent the basic, minimal level of success, and thumbs-up icons represent more significant progress(read more about how it works ). here **Food**For a checkmark I need to keep up my clean diet, and drink less than 3 cups of coffee. For a thumbsup, I gotta limit caffeine consumption to no more than 4 packs of green tea. **Info diet**For a checkmark I need to avoid visiting HN/Reddit/YouTube subscriptions, and limit my news consumption to an RSS feed. For a thumbsup, I need to completely avoid internet and TV until the very end of the day. **Sport**For a checkmark I complete the most minimal basic exercises, for a thumbsup I go for a good long run around the lake. **AI**Checkmark — reading the books and watching video lectures, Thumbsup — writing actual code. **Webdev**Checkmark — watch Udemy videos, Thumbsup — implement features for my startups. Checkmark — write at least 4 jokes,Thumbsup — post good ones on twitter. Comedy Checkmark — write Quora answers, insightful HN comments, or well-written AI-notes,Thumbsup — write good articles for my blog. Writing Checkmark — listen to audiobooks,thumbsup — read actual books (I need to read some stuff not available on audible). Reading Conclusion I’m sure this framework will change and improve over time, and I will get better at using it. Meanwhile, it has really helped me to achieve clarity about the things I want out of life, and the paths I can take to get there. I was very hard to figure out and follow at first, but every time I look back over the past several months, I’m surprised at how much progress it has helped me to make. I have no idea if this made any sense to you guys, but I hope that at least someone will find it useful. This is my solution to finding a purpose and direction in life, and if you’re struggling with something like that, I hope this will help you out. If you’re have found this post useful/interesting, or perhaps have any feedback or questions — feel free to shoot me an email to . ray@startuplab.io

My new Home Screen Wallpaper (and a framework for approaching big-picture life goals)

Halloween. It’s spooky season, so let’s bludgeon a few old stack vendors to death — Appian, IBM, Salesforce, SAP, Pegasystems, IFS, Oracle, Software AG, TIBCO, UIPath…they’re The Walking Dead, and they know it. Back in 2010–2012 I wrote a fair bit about business process automation over on my old blog, BPM Redux, and something I was fascinated with was the concept of self-assembling or dynamic processes, created on the fly to handle a task using artificial intelligence without the need for drawing a process map or dicking around designing another set of screens. The problem I have with ‘business rules’ being an inherent part of some BPMS is that they start to constrain process decision making and flexibility, but having a set of AI routines that not only adapts on the fly (or JIT) but also learn and potentially create a brand new process instance out of evolving from previous instances… Fast forward to today and it might finally become a reality. I looked at what some of the larger stack and cloud vendors are doing today, and they all look so desperate — throwing Generative AI into their software stacks to appear relevant and forward-thinking. The trouble is, Gen-AI renders them pointless. Every. Single. One. Let’s take Pegasystems for example (disclosure: I used to work for them years ago). They have Generative AI as part of their software solutions now but it’s still rooted in the past, forcing enterprise users to not only continue using Pega but also to continually think about building workflows with it — it doesn’t matter that it’s “low-code” pseudo-development or that you can instantly draw new process steps using the magic of AI, you’re still stuck with using Pega. The same goes for all the rest — whether it be Salesforce, IFS, SAP; whether it’s ERP, CRM, RPA — what they all potentially understand and won’t tell customers is that you have all the data already, both structured and unstructured, and a Gen-AI layer is all you need on top. Think about the following example — a customer complaint. A customer emails in a complaint moaning about one of your products or services and expecting an action in response. Typically, the email will come from a contact form with all the required details to identify the customer or client, the product in question and what they expect done. If not, then it’s freeform unstructured data with a dollop of misery and anger. Normally, it falls into a defined process that an agent has been trained to perform, with clear steps already mapped out. If not, then it’s treated as an exception and passed to someone higher up the chain to make a decision on. All that takes time to create, and develop into someone’s expensive SaaS solution that looks like a dog’s dinner on the screen. Invariably, a few years later there will be a multi-million dollar “digital transformation” program sold by a consultancy deck to eke a few tweaks and savings out of this godforsaken process to justify the cost. But what if all this didn’t need to be done anymore? What if training a Large Language Model on your existing processes, rules, customer data, product or service information was all you needed to do? Going down this train of thought leads to a very different outcome. The LLM reads and understands the content of the email, pulling out key information like customer details, the product or service mentioned, and the specific issue being raised. In the case of a telephone conversation then we’ve already seen some Gen-AI solutions transcribe in real-time an interaction and then offer up advice, a response, or an answer to a question. So, already there is no need for parsing of data to another system to fill out a screen for an agent to look at. Based on this information, the LLM figures out the priority of the complaint, sees if the issue is common or recurring, and decides if any specific business rules or past actions apply. In some cases there may well be sentiment analysis done on the language of the complaint to determine just how important this is, how urgent or how annoyed the customer is. Things can get funky from here. Based on the type of complaint, the LLM creates a workflow to resolve the issue on the fly. This could involve updating customer data, processing a refund, or sending the complaint to a specialised team but it’s all done without a front end system we’ve all grown accustomed to loathe. With JIT (Just In Time) capabilities, the LLM can generate code on the spot to do necessary backend tasks. For example, if a refund is needed, the LLM creates the code to process it and updates the backend customer database with the details. Since the LLM has been trained on business rules, it makes sure all actions follow company policies — checking if the customer is eligible for a refund before processing it for example. The results of each complaint handling process are used to train the LLM further. If a complaint is resolved successfully, the LLM learns from the actions taken, improving future responses and workflows. Over time, the LLM can find recurring issues, improve existing workflows, and even suggest changes to business rules or policies based on patterns in customer complaints. The point here is that (a) you don’t need to define what the business process is any more than you do with task definition, nobody cares about static processes anymore when you can dynamically generate and execute them, (b) the LLM generates code and minimal screen UI to complete the task and have the agent involved but after that’s done the code and the UI is deleted, it’s an artefact that is no longer required because it was created to handle an interaction that is personal to that customer, and (c) humans are still in the loop, the efficiency gains are not in reducing headcount but removing the expensive excuse of paying for ancient software and unnecessary transformation programs based on old methods that are always initiated by some incoming c-suite with a relationship with a favourite vendor. It’s not as simplistic and current Gen-AI solutions aren’t geared up for this (yet) but this should be enough to start to question why you need a huge ERP implementation, or why an expensive CRM is required at all if you can just have a conversation with the customer data directly. Remember Master Data Management? Enterprises spent millions and years on making sure all their backend databases were fit for purpose, clean, deduped, they’re in potentially good shape and structured enough for a single Gen-AI layer on top and nothing else. Imagine not having to worry about integrating one behemoth frankenstack vendor to another, having to sync data sources, transform the data, orchestrate processes between them…it’s a pretty tantalising prospect and one that none of the aforementioned vendors really want you to know about. Major vendors offering Gen-AI wallpaper on top of the cracked and creaking software they push are slowly dying, the benefits they offer will eventually run dry when stacked up against using artificial intelligence as the alternative on its own. In a way Altman was right, it’s a new type of operating system, in this case it’s a business operating system and one that doesn’t need the bloatware. I’ve maybe sat on these ideas for too long now, I might go and start building again. I mean, depending on who you read the global workflow automation market size was valued at $16.41 billion in 2021 and is projected to reach $34.4 billion by 2030, growing at a CAGR of 9.71%. Not small numbers. Who’s with me? Halloween. It’s spooky season, so let’s bludgeon a few old stack vendors to death — Appian, IBM, Salesforce, SAP, Pegasystems, IFS, Oracle, Software AG, TIBCO, UIPath …they’re The Walking Dead, and they know it. Appian, IBM, Salesforce, SAP, Pegasystems, IFS, Oracle, Software AG, TIBCO, UIPath The Walking Dead, Back in 2010–2012 I wrote a fair bit about business process automation over on my old blog, BPM Redux , and something I was fascinated with was the concept of self-assembling or dynamic processes , created on the fly to handle a task using artificial intelligence without the need for drawing a process map or dicking around designing another set of screens. BPM Redux BPM Redux self-assembling or dynamic processes The problem I have with ‘business rules’ being an inherent part of some BPMS is that they start to constrain process decision making and flexibility, but having a set of AI routines that not only adapts on the fly (or JIT) but also learn and potentially create a brand new process instance out of evolving from previous instances… The problem I have with ‘business rules’ being an inherent part of some BPMS is that they start to constrain process decision making and flexibility, but having a set of AI routines that not only adapts on the fly (or JIT) but also learn and potentially create a brand new process instance out of evolving from previous instances… The problem I have with ‘business rules’ being an inherent part of some BPMS is that they start to constrain process decision making and flexibility, but having a set of AI routines that not only adapts on the fly (or JIT) but also learn and potentially create a brand new process instance out of evolving from previous instances… Fast forward to today and it might finally become a reality. Fast forward to today and it might finally become a reality. I looked at what some of the larger stack and cloud vendors are doing today, and they all look so desperate — throwing Generative AI into their software stacks to appear relevant and forward-thinking. The trouble is, Gen-AI renders them pointless. Every. Single. One. Every. Single. One. Let’s take Pegasystems for example (disclosure: I used to work for them years ago). They have Generative AI as part of their software solutions now but it’s still rooted in the past, forcing enterprise users to not only continue using Pega but also to continually think about building workflows with it — it doesn’t matter that it’s “low-code” pseudo-development or that you can instantly draw new process steps using the magic of AI, you’re still stuck with using Pega. Pegasystems Pegasystems The same goes for all the rest — whether it be Salesforce, IFS, SAP; whether it’s ERP, CRM, RPA — what they all potentially understand and won’t tell customers is that you have all the data already, both structured and unstructured, and a Gen-AI layer is all you need on top. you have all the data already, both structured and unstructured, and a Gen-AI layer is all you need on top. Think about the following example — a customer complaint. A customer emails in a complaint moaning about one of your products or services and expecting an action in response. Typically, the email will come from a contact form with all the required details to identify the customer or client, the product in question and what they expect done. If not, then it’s freeform unstructured data with a dollop of misery and anger. Normally, it falls into a defined process that an agent has been trained to perform, with clear steps already mapped out. If not, then it’s treated as an exception and passed to someone higher up the chain to make a decision on. All that takes time to create, and develop into someone’s expensive SaaS solution that looks like a dog’s dinner on the screen. Invariably, a few years later there will be a multi-million dollar “digital transformation” program sold by a consultancy deck to eke a few tweaks and savings out of this godforsaken process to justify the cost. But what if all this didn’t need to be done anymore? But what if all this didn’t need to be done anymore? What if training a Large Language Model on your existing processes, rules, customer data, product or service information was all you needed to do? Going down this train of thought leads to a very different outcome. The LLM reads and understands the content of the email, pulling out key information like customer details, the product or service mentioned, and the specific issue being raised. In the case of a telephone conversation then we’ve already seen some Gen-AI solutions transcribe in real-time an interaction and then offer up advice, a response, or an answer to a question. So, already there is no need for parsing of data to another system to fill out a screen for an agent to look at. Based on this information, the LLM figures out the priority of the complaint, sees if the issue is common or recurring, and decides if any specific business rules or past actions apply. In some cases there may well be sentiment analysis done on the language of the complaint to determine just how important this is, how urgent or how annoyed the customer is. Things can get funky from here. Things can get funky from here. Based on the type of complaint, the LLM creates a workflow to resolve the issue on the fly. This could involve updating customer data, processing a refund, or sending the complaint to a specialised team but it’s all done without a front end system we’ve all grown accustomed to loathe. With JIT (Just In Time) capabilities, the LLM can generate code on the spot to do necessary backend tasks. For example, if a refund is needed, the LLM creates the code to process it and updates the backend customer database with the details. Since the LLM has been trained on business rules, it makes sure all actions follow company policies — checking if the customer is eligible for a refund before processing it for example. The results of each complaint handling process are used to train the LLM further. If a complaint is resolved successfully, the LLM learns from the actions taken, improving future responses and workflows. Over time, the LLM can find recurring issues, improve existing workflows, and even suggest changes to business rules or policies based on patterns in customer complaints. The point here is that (a) you don’t need to define what the business process is any more than you do with task definition, nobody cares about static processes anymore when you can dynamically generate and execute them, (b) the LLM generates code and minimal screen UI to complete the task and have the agent involved but after that’s done the code and the UI is deleted, it’s an artefact that is no longer required because it was created to handle an interaction that is personal to that customer, and (c) humans are still in the loop, the efficiency gains are not in reducing headcount but removing the expensive excuse of paying for ancient software and unnecessary transformation programs based on old methods that are always initiated by some incoming c-suite with a relationship with a favourite vendor. (a) you don’t need to define what the business process is any more than you do with task definition, nobody cares about static processes anymore when you can dynamically generate and execute them, (b) the LLM generates code and minimal screen UI to complete the task and have the agent involved but after that’s done the code and the UI is deleted, it’s an artefact that is no longer required because it was created to handle an interaction that is personal to that customer, and (c) humans are still in the loop, the efficiency gains are not in reducing headcount but removing the expensive excuse of paying for ancient software and unnecessary transformation programs based on old methods It’s not as simplistic and current Gen-AI solutions aren’t geared up for this ( yet ) but this should be enough to start to question why you need a huge ERP implementation, or why an expensive CRM is required at all if you can just have a conversation with the customer data directly. yet Remember Master Data Management? Enterprises spent millions and years on making sure all their backend databases were fit for purpose, clean, deduped, they’re in potentially good shape and structured enough for a single Gen-AI layer on top and nothing else. Imagine not having to worry about integrating one behemoth frankenstack vendor to another, having to sync data sources, transform the data, orchestrate processes between them…it’s a pretty tantalising prospect and one that none of the aforementioned vendors really want you to know about. Imagine not having to worry about integrating one behemoth frankenstack vendor to another, having to sync data sources, transform the data, orchestrate processes between them…it’s a pretty tantalising prospect and one that none of the aforementioned vendors really want you to know about. Major vendors offering Gen-AI wallpaper on top of the cracked and creaking software they push are slowly dying, the benefits they offer will eventually run dry when stacked up against using artificial intelligence as the alternative on its own. In a way Altman was right, it’s a new type of operating system, in this case it’s a business operating system and one that doesn’t need the bloatware. In a way Altman was right, it’s a new type of operating system, in this case it’s a business operating system and one that doesn’t need the bloatware. I’ve maybe sat on these ideas for too long now, I might go and start building again. I mean, depending on who you read the global workflow automation market size was valued at $16.41 billion in 2021 and is projected to reach $34.4 billion by 2030, growing at a CAGR of 9.71%. Not small numbers. Who’s with me? Who’s with me?

Generative AI Will Kill Old Stack Vendors. Let It.

Why We Can’t Put Down Our Phones: The Psychological Barriers to Reducing Screen Time

"Art is not a thing; it is a doing." - Paul Klee Today, the world of NFTs, which is a huge kingdom of its own, has taken the art arena by storm. Believe it or not, these digital assets that represent unique ownership of digital items have indeed skyrocketed in popularity as well as great value. Of course, although many different factors contribute to the cost/price of an NFT, certain key factors significantly influence its cost to a greater extent. In this blog post, I will give you a smooth ride into the top 5 factors that determine the price of NFT art so that you can decide whether you have enough in your pocket to invest in the same. Obviously, who would want a hole in their pocket? HEHE….. Let’s jump right into it!!! Number 1 The Reputation Of The Artist and the Following Ummm! Maybe you are an artist with a minimal number of followers. So in that case would you be able to sell your NFT? While you can, the hard truth is that the chances are way too low. One of the critical factors affecting an NFT’s price is the artist’s reputation and the number of followers. Very established artists with a proven reputation and track record with a loyal fan base are more likely to gather higher prices for their digital creations. It is their name recognition and creative, artistic expertise that lend credibility and desirability to their NFTs. Nevertheless, the size and engagement of an artist’s social media platform and following can also significantly influence the value of their NFT work. **Let’s see an example: Just imagine that you are trying to sell an NFT of a pixelated cat. The artist is a very, very renowned master of fine art, who is known for their intricate oil paintings. Although the cat might seem too cute, it is very unlikely that it will fetch a high price. The mismatch between the artist’s reputation and the NFT’s content would be literally like trying to sell a Ferrari to a person who only knows how to drive a bicycle. True right? Number 2 Being Rare and Unique The most important elements that drive up the price of NFTs are its rarity and uniqueness. Limited edition or one-of-a-kind pieces are highly sought after by collectors, who are really willing to pay a premium for exclusive, rare digital assets. Various factors such as the number of copies available, the incorporation of specific varied features, or the artist’s creative techniques can contribute to the perceived rarity and uniqueness of an NFT. Think about it…. Someone comes to you, and they tell you that they had a one-of-a-kind NFT of a digital potato... Would you even buy it? Probably not! I would definitely not! But…but…but what if they told you it was the last potato on Earth and the only way to save humanity from starvation was to buy it? That’s the catch! Now you might be more inclined to pay a hefty price for it! True right?\ Number #3 Utility and Functionality Believe me! NFTs can offer more than just digital art; they can indeed also provide utility and functionality. For example, some NFTs come with rare exclusive access to physical products, experiences, or virtual communities. These additional benefits can for sure enormously increase the perceived value of an NFT and attract buyers who are seeking both aesthetic and practical value. Imagine this… You have bought an NFT of a digital painting. But instead of just looking at it on your screen, you can also use it as a wallpaper for your virtual reality headset. Niceee right? Now you have a unique and immersive experience that you can share with your friends. Number #4 The Evolving Market Trends and Hype Let me tell you! Market trends and hype can play an important role in determining the price of NFTs. Of course, when a particular artist, collection, art, or genre gains popularity, it can create a frenzy and huge demand, driving the prices high. However, it’s important to be cautious of speculative bubbles and ensure that you’re investing in NFTs based on intrinsic value rather than short-term hype. It's better to be a MASTER than to be a FOOL. Think about it… Do you remember Beanie Babies? They were all around the rage for a while, and people were paying enormous prices for them. But then all of a sudden the hype died down and they were worth almost nothing. The same can happen with NFTs if the market becomes saturated or people lose interest in it. Number #5 Blockchain Technology and Platform Fact is a fact. The underlying blockchain technology and platform used to create and trade NFTs can also largely impact their price. Consider Ethereum! Ethereum, being one of the most popular blockchains for NFTs, has a well-established ecosystem and a large community of developers and collectors. Nevertheless, other blockchains with varied features or lower transaction fees may also emerge as viable options for NFT creators and buyers. Take this example… What if you are trying to buy an NFT on a novel blockchain that no one has even heard of? It might be really cheaper, but there’s also a significant risk that the platform could collapse or be hacked. SCRAYYYY!! It’s like buying a car from a shady used car salesman-you might get a really great deal, but you're also taking a risk. So now having read all this, the question is: DO YOU HAVE ENOUGH IN YOUR POCKET TO JOIN THE NFT ART MARKET? The cost of NFTs can vary widely, from a few dollars to millions to crores. While it’s tempting to jump on the bandwagon and invest in the latest trending NFTs, it’s essential to conduct thorough research and consider your financial goals. If you are really passionate about art and believe in the potential of NFTs, then it might be worth exploring this exciting market. However, always approach investments with great caution and be prepared to face potential risks. Remember, the value of an NFT art is subjective and can indeed fluctuate over time. The best strategy is to invest in pieces that you genuinely appreciate and love and believe will hold their value in the long term. By understanding the key factors that influence NFT prices and conducting due diligence, you can make informed decisions and potentially reap huge rewards from this ever-growing innovative market. So now the question is DO YOU HAVE ENOUGH MONEY IN YOUR POCKET TO INVEST IN LATEST TRENDING NFTs? Let me know your thoughts in the comments! "Art is not a thing; it is a doing." - Paul Klee "Art is not a thing; it is a doing." - Paul Klee Today, the world of NFTs, which is a huge kingdom of its own, has taken the art arena by storm. Believe it or not, these digital assets that represent unique ownership of digital items have indeed skyrocketed in popularity as well as great value. Of course, although many different factors contribute to the cost/price of an NFT, certain key factors significantly influence its cost to a greater extent. In this blog post, I will give you a smooth ride into the top 5 factors that determine the price of NFT art so that you can decide whether you have enough in your pocket to invest in the same. Obviously, who would want a hole in their pocket? HEHE….. Let’s jump right into it!!! Number 1 The Reputation Of The Artist and the Following Ummm! Maybe you are an artist with a minimal number of followers. So in that case would you be able to sell your NFT? While you can, the hard truth is that the chances are way too low. One of the critical factors affecting an NFT’s price is the artist’s reputation and the number of followers. Very established artists with a proven reputation and track record with a loyal fan base are more likely to gather higher prices for their digital creations. It is their name recognition and creative, artistic expertise that lend credibility and desirability to their NFTs. Nevertheless, the size and engagement of an artist’s social media platform and following can also significantly influence the value of their NFT work. **Let’s see an example: Just imagine that you are trying to sell an NFT of a pixelated cat. The artist is a very, very renowned master of fine art, who is known for their intricate oil paintings. Although the cat might seem too cute, it is very unlikely that it will fetch a high price. The mismatch between the artist’s reputation and the NFT’s content would be literally like trying to sell a Ferrari to a person who only knows how to drive a bicycle. True right? Number 2 Number 2 Being Rare and Unique Being Rare and Unique The most important elements that drive up the price of NFTs are its rarity and uniqueness. Limited edition or one-of-a-kind pieces are highly sought after by collectors, who are really willing to pay a premium for exclusive, rare digital assets. Various factors such as the number of copies available, the incorporation of specific varied features, or the artist’s creative techniques can contribute to the perceived rarity and uniqueness of an NFT. Think about it…. Think about it…. Someone comes to you, and they tell you that they had a one-of-a-kind NFT of a digital potato... Would you even buy it? Probably not! I would definitely not! But…but…but what if they told you it was the last potato on Earth and the only way to save humanity from starvation was to buy it? That’s the catch! Now you might be more inclined to pay a hefty price for it! True right?\ Number #3 Number #3 Utility and Functionality Utility and Functionality Believe me! NFTs can offer more than just digital art; they can indeed also provide utility and functionality. For example, some NFTs come with rare exclusive access to physical products, experiences, or virtual communities. These additional benefits can for sure enormously increase the perceived value of an NFT and attract buyers who are seeking both aesthetic and practical value. Imagine this… Imagine this… You have bought an NFT of a digital painting. But instead of just looking at it on your screen, you can also use it as a wallpaper for your virtual reality headset. Niceee right? Now you have a unique and immersive experience that you can share with your friends. Number #4 Number #4 The Evolving Market Trends and Hype The Evolving Market Trends and Hype Let me tell you! Market trends and hype can play an important role in determining the price of NFTs. Of course, when a particular artist, collection, art, or genre gains popularity, it can create a frenzy and huge demand, driving the prices high. However, it’s important to be cautious of speculative bubbles and ensure that you’re investing in NFTs based on intrinsic value rather than short-term hype. It's better to be a MASTER than to be a FOOL. Think about it… Think about it… Do you remember Beanie Babies ? They were all around the rage for a while, and people were paying enormous prices for them. But then all of a sudden the hype died down and they were worth almost nothing. The same can happen with NFTs if the market becomes saturated or people lose interest in it. Beanie Babies Beanie Babies Number #5 Number #5 Blockchain Technology and Platform Blockchain Technology and Platform Fact is a fact. The underlying blockchain technology and platform used to create and trade NFTs can also largely impact their price. Consider Ethereum! Ethereum , being one of the most popular blockchains for NFTs, has a well-established ecosystem and a large community of developers and collectors. Nevertheless, other blockchains with varied features or lower transaction fees may also emerge as viable options for NFT creators and buyers. Ethereum Ethereum Take this example… Take this example… What if you are trying to buy an NFT on a novel blockchain that no one has even heard of? It might be really cheaper, but there’s also a significant risk that the platform could collapse or be hacked. SCRAYYYY!! It’s like buying a car from a shady used car salesman-you might get a really great deal, but you're also taking a risk. So now having read all this, the question is: DO YOU HAVE ENOUGH IN YOUR POCKET TO JOIN THE NFT ART MARKET? DO YOU HAVE ENOUGH IN YOUR POCKET TO JOIN THE NFT ART MARKET? DO YOU HAVE ENOUGH IN YOUR POCKET TO JOIN THE NFT ART MARKET? The cost of NFTs can vary widely, from a few dollars to millions to crores. While it’s tempting to jump on the bandwagon and invest in the latest trending NFTs, it’s essential to conduct thorough research and consider your financial goals. If you are really passionate about art and believe in the potential of NFTs, then it might be worth exploring this exciting market. However, always approach investments with great caution and be prepared to face potential risks. Remember, the value of an NFT art is subjective and can indeed fluctuate over time. The best strategy is to invest in pieces that you genuinely appreciate and love and believe will hold their value in the long term. By understanding the key factors that influence NFT prices and conducting due diligence, you can make informed decisions and potentially reap huge rewards from this ever-growing innovative market. So now the question is So now the question is DO YOU HAVE ENOUGH MONEY IN YOUR POCKET TO INVEST IN LATEST TRENDING NFTs? Let me know your thoughts in the comments! Let me know your thoughts in the comments!

Top 5 Factors That Affect the Cost of NFT Art - Do You Have Enough In Your Pocket?

Desktop customization is a fun activity that many of you have likely tried at least once. There are various customization options, such as changing the boot screen logo, the start menu icon, or transforming the entire Windows interface to resemble macOS. Today, we are about to discuss one such customization, which is setting a different background wallpaper for each desktop (or monitor) in Windows 11 and 10 for aesthetics, productivity, creativity, or any other reason. Setting Different Backgrounds for Each Desktop on Windows 11, 10 In Windows, there is no limit on the number of desktops you can create from Task View (though more desktops will consume more system resources), allowing you to create as many desktops as you want and set different wallpapers for each. To customize which wallpaper appears on each desktop, 1. Press Win+Tab to open Task View. All your existing desktops will be listed below, with a "+" option to create more. 2. Right-click on the respective desktop (in my case, "Desktop 2") whose background wallpaper you want to change, and then select "Choose background" from the context menu. 3. It will redirect you to the "Personalize your background" section for that desktop, where you can choose a wallpaper from the recent images or select a new one from the file explorer. 4. Once the new background wallpaper for the desktop is set, you can confirm the changes by visiting the desktop. 5. To verify that each desktop has its own separate background wallpaper, you can take another peek into the Task View using Win+Tab shortcut. That's it! You've successfully set a different background wallpaper for each desktop on Windows 11 and 10. Bonus Tip! You can directly change the desktop background wallpaper from your current desktop by navigating to "Settings" -> "Personalization" -> "Background" and then right-clicking on any image to open a context menu with the "Set for desktop" option, allowing you to change the background wallpaper of your preferred desktop. Wrap Up That’s how you can change the background wallpaper for each desktop on Windows 11 and 10. You can further change all of your existing desktops background wallpaper by following this method. Desktop customization is a fun activity that many of you have likely tried at least once. There are various customization options, such as changing the boot screen logo, the start menu icon, or transforming the entire Windows interface to resemble macOS. Today, we are about to discuss one such customization, which is setting a different background wallpaper for each desktop (or monitor) in Windows 11 and 10 for aesthetics, productivity, creativity, or any other reason. Setting Different Backgrounds for Each Desktop on Windows 11, 10 In Windows, there is no limit on the number of desktops you can create from Task View (though more desktops will consume more system resources), allowing you to create as many desktops as you want and set different wallpapers for each. To customize which wallpaper appears on each desktop, 1. Press Win+Tab to open Task View. Win+Tab All your existing desktops will be listed below, with a "+" option to create more. All your existing desktops will be listed below, with a "+" option to create more. 2. Right-click on the respective desktop (in my case, " Desktop 2 ") whose background wallpaper you want to change, and then select " Choose background " from the context menu. Desktop 2 Choose background 3. It will redirect you to the " Personalize your background " section for that desktop, where you can choose a wallpaper from the recent images or select a new one from the file explorer. Personalize your background 4. Once the new background wallpaper for the desktop is set, you can confirm the changes by visiting the desktop. 5. To verify that each desktop has its own separate background wallpaper, you can take another peek into the Task View using Win+Tab shortcut. Win+Tab That's it! You've successfully set a different background wallpaper for each desktop on Windows 11 and 10. Bonus Tip! You can directly change the desktop background wallpaper from your current desktop by navigating to " Settings " -> " Personalization " -> " Background " and then right-clicking on any image to open a context menu with the " Set for desktop " option, allowing you to change the background wallpaper of your preferred desktop. Settings Personalization Background Set for desktop Wrap Up That’s how you can change the background wallpaper for each desktop on Windows 11 and 10. You can further change all of your existing desktops background wallpaper by following this method.

Setting Different Backgrounds for Each Desktop on Windows 11 and 10

Now that you are stoked and enthusiastic about ZeptoN 🤩 knowing what the do-while ZeptoN is [Gilrea 2024], the time is now to get started with ZeptoN with what you need for the how. This is simplicity, as there are two things you need to get started: Java environment - ZeptoN is written in Java, and transcompiles to Java bytecode that runs on a Java Virtual Machine (JVM). Hence, you need the Java Development Kit to trancompile or transpile and run your ZeptoN code.


ZeptoN - ZeptoN is transpiled, thus, you need the ZeptoN transcompiler ZepT, or Zeptor, the ZEPton code editor. Both tools, the transpiler or code editor, are needed to write, transpile, run, debug, and rewrite ZeptoN source code ad infinitum. The three intended platforms for getting started with ZeptoN are: Linux, MacOS, and Windows. Other platforms are a big unknown, and thus, not covered or explained, so caveat emptor and quod, quod, fiat. Part 1: What You Need...Some Java The first thing you need to get started is some Java, the Java Developer's Kit (JDK). At the time of writing this, Java has reached Java 22 or JDK version 22. You can find out more about Java history elsewhere, but each version of Java is a release starting with JDK 1 back in the mid-1990s, until now at JDK 22, or Java 22. What you need is a favorite OpenJavaDevelopmentKit, the JDK that is described with "OpenJDK (OpenJavaDevelopmentKit) is a free and open-source implementation of the Java Platform..." [Wikip 2024] The JDK is free and open-source, so it only requires you to download and install it to your computer platform. Important Caveat about Getting Java An important caveat is to install the JDK, not the Java Runtime Environment (JRE). The JRE is the JVM that runs bytecode but does not include some libraries and packages required to transcompile ZeptoN into bytecode for the JVM. Thus, download the JDK (or more specifically, the OpenJDK) and NOT the JRE. The OpenJDK you download will include the libraries and packages, along with a JRE. Which OpenJDK is Which? Which OpenJDK is Which? There are many vendors that are providers of an OpenJDK. An Internet search can find them. The important requirement is that the OpenJDK be version 11 or greater. Java is awesome in that later JDKs are backward compatible with the previous version. Thus, choose an OpenJDK release 11 or greater, for example, I have used OpenJDK release 17. Many vendors have multiple versions of an OpenJDK that you can download for your platform. The author personally uses Zulu OpenJDK 17 for MacOS to use with ZeptoN. You can download it here... https://www.azul.com/downloads/?package=jdk#zulu (but caveat emptor!) yet, you can use your favorite, chosen OpenJDK. Once you download your favorite, choose OpenJDK 11 or greater, and install it on your system platform. The author’s platform is a MacBook Pro 80x86 16” laptop. Verify You've Got OpenJDK If all goes well for the installation of the OpenJDK, all you need now to do is to verify that the installation is successful. This is simple enough to do. Simply open a console or terminal on your platform, and then type the following: javac --version This is invoking or running the Java compiler "javac" and passing the parameter for the version of the Java compiler. The Java Compiler javac tool responds with the version of the release of the Java compiler: javac 11.0.23 This confirms Java runs thus it’s available, and the version checks the version of the OpenJDK installed, and it must be greater than or equal to release 11. The release version is 17.0.11 so greater than the requirement minimum of 11. If you have made it this far, congratulations! You now have the OpenJDK installed and running on your system. 🥳 You are halfway there to having ZeptoN up and running on your system. Part 2: ZeptoN to It for Doing It With the Java environment and runtime installed and running, the second requirement is to install either the ZeptoN transcompiler or Zeptor the ZeptoN code editor. Zeptor also contains the ZeptoN ZepT transcompiler built into the code editor. Since further articles will be discussing, explaining, and illustrating ZeptoN source code, the focus is on downloading, installing, and running Zeptor. Zeptor to it! 😜 Gimme Zeptor Or Else...No Zept To It! Gimme Zeptor Or Else…No Zept To It! First, we must download Zeptor in order to install Zeptor on our system. 🤪 Zeptor is free and open-source and available on GitHub in a repository for download. Download Zeptor as the file "Zeptor.jdk11.jar" in the directory "assets" from the GitHub repository at the link: https://github.com/wgilreath/Zeptor. Once Zeptor is downloaded, create a Zeptor home directory where the Zeptor app will live on your computer system. Next, copy Zeptor to the home directory as "Zeptor.jar" to keep the file name simple but accurate. Check that Zeptor has the correct operating system permissions to be read, executed, and run on your computer system--this depends on the platform and operating system. Part 3: Verifying Ready to Start with ZeptoN Now that Zeptor has been downloaded and installed in a home directory, we need to verify that Zeptor will run without any problems. Open a console or terminal window, and then run Zeptor with the command: java -jar Zeptor.jar Zeptor should start running as a visual application, with the start screen a blank background, and the version, release, copyright, and license dialog in the center of the computer screen. This verifies that Zeptor runs, but on-file verification is needed--that Zeptor can transpile ZeptoN source code, and then run the transpiled code as JVM bytecode. Your First ZeptoN Program In the Zeptor "File" menu, click the menu item "New" to create a simple ZeptoN program that prints "Hello, World!!!" (check literal) to the console screen. Zeptor automatically or auto-magically creates the ubiquitous “Hello, World!!!” program in ZeptoN. After creating the simple ZeptoN program automatically, save it. Now, in the "Build" menu, click the menu item "Make," and then wait. After a second or two, a compiler dialog will appear with an indication of success of compiling the ZeptoN source code into Java bytecode. Other information is given, such as the OpenJDK release and version, and the total time. The important thing is that the transcompilation process is successful. ZeptoN Start to It Finally, execute or run the simple ZeptoN program. In the "Build" menu, click the menu item "Start," which will run the ZeptoN program in the Zeptor console. Once the ZeptoN program runs, press a key to close, and exit the Zeptor console. Now, Zeptor is installed, executes, and works -- the verification and validation are complete. Blimey! Congratulations, Felicitations, and Whoopee! Congratulations and celebrations are in order! 🥳 You have a working ZeptoN development system with the Java environment, runtime, and the Zeptor code editor. Huzzah! Now that we have a working ZeptoN code editor and runtime on your system, we can learn by doing how to code with ZeptoN in continuing articles in the future. How to do it? ZeptoN to it! 😎 References [Azul 2024] Azul Systems, Inc. "Download Azul JDKs," https://www.azul.com/downloads/?package=jdk#zulu, Accessed May 26, 2024. [Gilre 2024] Gilreath, William F. “What the Do-While is ZeptoN?” May 14, 2024. https://hackernoon.com/what-the-do-while-is-zepton


[Gilre 2024] Gilreath, William F. "Zeptor: The ZeptoN Code Editor," https://github.com/wgilreath/Zeptor, Accessed May 26, 2024. [Ku 2017] Ku, Kevin. “Data Codes through Eyeglasses,” September 5, 2017, https://www.pexels.com/photo/data-codes-through-eyeglasses-577585/, Accessed April 8, 2020.


[Kniaz 2024] Kniaz, Artem. “Woman hands cheers with two glasses of champagne holidays festive atmosphere concept wallpaper with illumination lights background," https://www.istockphoto.com/photo/woman-hands-cheers-with-two-glasses-of-champagne-holidays-festive-atmosphere-concept-gm1193770436-339688919, December 17, 2019, Downloaded December 31, 2022.


[Wikip 2024] Wikipedia Editors, "OpenJDK" https://en.wikipedia.org/wiki/OpenJDK, Accessed May 19, 2024. Now that you are stoked and enthusiastic about ZeptoN 🤩 knowing what the do-while ZeptoN is [Gilrea 2024] , the time is now to get started with ZeptoN with what you need for the how. This is simplicity, as there are two things you need to get started: [Gilrea 2024] Java environment - ZeptoN is written in Java, and transcompiles to Java bytecode that runs on a Java Virtual Machine (JVM). Hence, you need the Java Development Kit to trancompile or transpile and run your ZeptoN code. ZeptoN - ZeptoN is transpiled, thus, you need the ZeptoN transcompiler ZepT, or Zeptor, the ZEPton code editor. Both tools, the transpiler or code editor, are needed to write, transpile, run, debug, and rewrite ZeptoN source code ad infinitum. Java environment - ZeptoN is written in Java, and transcompiles to Java bytecode that runs on a Java Virtual Machine (JVM). Hence, you need the Java Development Kit to trancompile or transpile and run your ZeptoN code. Java environment - ZeptoN is written in Java, and transcompiles to Java bytecode that runs on a Java Virtual Machine (JVM). Hence, you need the Java Development Kit to trancompile or transpile and run your ZeptoN code. ZeptoN - ZeptoN is transpiled, thus, you need the ZeptoN transcompiler ZepT, or Zeptor, the ZEPton code editor. Both tools, the transpiler or code editor, are needed to write, transpile, run, debug, and rewrite ZeptoN source code ad infinitum. ZeptoN - ZeptoN is transpiled, thus, you need the ZeptoN transcompiler ZepT, or Zeptor, the ZEPton code editor. Both tools, the transpiler or code editor, are needed to write, transpile, run, debug, and rewrite ZeptoN source code ad infinitum. The three intended platforms for getting started with ZeptoN are: Linux, MacOS, and Windows. Other platforms are a big unknown, and thus, not covered or explained, so caveat emptor and quod, quod, fiat. Part 1: What You Need...Some Java The first thing you need to get started is some Java, the Java Developer's Kit (JDK). At the time of writing this, Java has reached Java 22 or JDK version 22. You can find out more about Java history elsewhere, but each version of Java is a release starting with JDK 1 back in the mid-1990s, until now at JDK 22, or Java 22. What you need is a favorite Open Java Development Kit, the JDK that is described with "OpenJDK (Open Java Development Kit) is a free and open-source implementation of the Java Platform ..." [Wikip 2024] The JDK is free and open-source, so it only requires you to download and install it to your computer platform. Java Kit, the JDK that is described with "OpenJDK (Open Development free and open-source Java Platform Important Caveat about Getting Java An important caveat is to install the JDK, not the Java Runtime Environment (JRE). The JRE is the JVM that runs bytecode but does not include some libraries and packages required to transcompile ZeptoN into bytecode for the JVM. Thus, download the JDK (or more specifically, the OpenJDK) and NOT the JRE. The OpenJDK you download will include the libraries and packages, along with a JRE. not NOT NOT NOT Which OpenJDK is Which? Which OpenJDK is Which? There are many vendors that are providers of an OpenJDK. An Internet search can find them. The important requirement is that the OpenJDK be version 11 or greater. Java is awesome in that later JDKs are backward compatible with the previous version. Thus, choose an OpenJDK release 11 or greater, for example, I have used OpenJDK release 17. Many vendors have multiple versions of an OpenJDK that you can download for your platform. The author personally uses Zulu OpenJDK 17 for MacOS to use with ZeptoN. You can download it here... https://www.azul.com/downloads/?package=jdk#zulu (but caveat emptor!) yet, you can use your favorite, chosen OpenJDK. https://www.azul.com/downloads/?package=jdk#zulu Once you download your favorite, choose OpenJDK 11 or greater, and install it on your system platform. The author’s platform is a MacBook Pro 80x86 16” laptop. Verify You've Got OpenJDK If all goes well for the installation of the OpenJDK, all you need now to do is to verify that the installation is successful. This is simple enough to do. Simply open a console or terminal on your platform, and then type the following: javac --version javac --version javac --version javac --version This is invoking or running the Java compiler "javac" and passing the parameter for the version of the Java compiler. The Java Compiler javac tool responds with the version of the release of the Java compiler: javac 11.0.23 javac 11.0.23 This confirms Java runs thus it’s available, and the version checks the version of the OpenJDK installed, and it must be greater than or equal to release 11. The release version is 17.0.11 so greater than the requirement minimum of 11. If you have made it this far, congratulations! You now have the OpenJDK installed and running on your system. 🥳 You are halfway there to having ZeptoN up and running on your system. Part 2: ZeptoN to It for Doing It With the Java environment and runtime installed and running, the second requirement is to install either the ZeptoN transcompiler or Zeptor the ZeptoN code editor. Zeptor also contains the ZeptoN ZepT transcompiler built into the code editor. Since further articles will be discussing, explaining, and illustrating ZeptoN source code, the focus is on downloading, installing, and running Zeptor. Zeptor to it! 😜 Gimme Zeptor Or Else...No Zept To It! Gimme Zeptor Or Else…No Zept To It! First, we must download Zeptor in order to install Zeptor on our system. 🤪 Zeptor is free and open-source and available on GitHub in a repository for download. Download Zeptor as the file " Zeptor.jdk11.jar " in the directory "assets" from the GitHub repository at the link: https://github.com/wgilreath/Zeptor . Zeptor.jdk11.jar https://github.com/wgilreath/Zeptor Once Zeptor is downloaded, create a Zeptor home directory where the Zeptor app will live on your computer system. Next, copy Zeptor to the home directory as "Zeptor.jar" to keep the file name simple but accurate. Check that Zeptor has the correct operating system permissions to be read, executed, and run on your computer system--this depends on the platform and operating system. Part 3: Verifying Ready to Start with ZeptoN Now that Zeptor has been downloaded and installed in a home directory, we need to verify that Zeptor will run without any problems. Open a console or terminal window, and then run Zeptor with the command: java -jar Zeptor.jar java -jar Zeptor.jar java -jar Zeptor.jar Zeptor should start running as a visual application, with the start screen a blank background, and the version, release, copyright, and license dialog in the center of the computer screen. This verifies that Zeptor runs, but on-file verification is needed--that Zeptor can transpile ZeptoN source code, and then run the transpiled code as JVM bytecode. Your First ZeptoN Program In the Zeptor "File" menu, click the menu item "New" to create a simple ZeptoN program that prints "Hello, World!!!" (check literal) to the console screen. Zeptor automatically or auto-magically creates the ubiquitous “Hello, World!!!” program in ZeptoN. After creating the simple ZeptoN program automatically, save it. Now, in the "Build" menu, click the menu item "Make," and then wait. After a second or two, a compiler dialog will appear with an indication of success of compiling the ZeptoN source code into Java bytecode. Other information is given, such as the OpenJDK release and version, and the total time. The important thing is that the transcompilation process is successful. ZeptoN Start to It Finally, execute or run the simple ZeptoN program. In the "Build" menu, click the menu item "Start," which will run the ZeptoN program in the Zeptor console. Once the ZeptoN program runs, press a key to close, and exit the Zeptor console. Now, Zeptor is installed, executes, and works -- the verification and validation are complete. Blimey! Congratulations, Felicitations, and Whoopee! Congratulations and celebrations are in order! 🥳 You have a working ZeptoN development system with the Java environment, runtime, and the Zeptor code editor. Huzzah! Now that we have a working ZeptoN code editor and runtime on your system, we can learn by doing how to code with ZeptoN in continuing articles in the future. How to do it? ZeptoN to it! 😎 References [Azul 2024] Azul Systems, Inc. "Download Azul JDKs," https://www.azul.com/downloads/?package=jdk#zulu, Accessed May 26, 2024. [Azul 2024] Azul Systems, Inc. "Download Azul JDKs," https://www.azul.com/downloads/?package=jdk#zulu , Accessed May 26, 2024. https://www.azul.com/downloads/?package=jdk#zulu [Gilre 2024] Gilreath, William F. “What the Do-While is ZeptoN?” May 14, 2024. https://hackernoon.com/what-the-do-while-is-zepton [Gilre 2024] Gilreath, William F. "Zeptor: The ZeptoN Code Editor," https://github.com/wgilreath/Zeptor, Accessed May 26, 2024. [Gilre 2024] Gilreath, William F. “What the Do-While is ZeptoN?” May 14, 2024. https://hackernoon.com/what-the-do-while-is-zepton [Gilre 2024] Gilreath, William F. “What the Do-While is ZeptoN?” May 14, 2024. https://hackernoon.com/what-the-do-while-is-zepton https://hackernoon.com/what-the-do-while-is-zepton [Gilre 2024] Gilreath, William F. "Zeptor: The ZeptoN Code Editor," https://github.com/wgilreath/Zeptor, Accessed May 26, 2024. [Gilre 2024] Gilreath, William F. "Zeptor: The ZeptoN Code Editor," https://github.com/wgilreath/Zeptor , Accessed May 26, 2024. https://github.com/wgilreath/Zeptor [Ku 2017] Ku, Kevin. “Data Codes through Eyeglasses,” September 5, 2017, https://www.pexels.com/photo/data-codes-through-eyeglasses-577585/, Accessed April 8, 2020. [Kniaz 2024] Kniaz, Artem. “Woman hands cheers with two glasses of champagne holidays festive atmosphere concept wallpaper with illumination lights background," https://www.istockphoto.com/photo/woman-hands-cheers-with-two-glasses-of-champagne-holidays-festive-atmosphere-concept-gm1193770436-339688919, December 17, 2019, Downloaded December 31, 2022. [Wikip 2024] Wikipedia Editors, "OpenJDK" https://en.wikipedia.org/wiki/OpenJDK, Accessed May 19, 2024. [Ku 2017] Ku, Kevin. “Data Codes through Eyeglasses,” September 5, 2017, https://www.pexels.com/photo/data-codes-through-eyeglasses-577585/, Accessed April 8, 2020. [Ku 2017] Ku, Kevin. “Data Codes through Eyeglasses,” September 5, 2017, https://www.pexels.com/photo/data-codes-through-eyeglasses-577585/ , Accessed April 8, 2020. https://www.pexels.com/photo/data-codes-through-eyeglasses-577585/ [Kniaz 2024] Kniaz, Artem. “Woman hands cheers with two glasses of champagne holidays festive atmosphere concept wallpaper with illumination lights background," https://www.istockphoto.com/photo/woman-hands-cheers-with-two-glasses-of-champagne-holidays-festive-atmosphere-concept-gm1193770436-339688919, December 17, 2019, Downloaded December 31, 2022. [Kniaz 2024] Kniaz, Artem. “Woman hands cheers with two glasses of champagne holidays festive atmosphere concept wallpaper with illumination lights background," https://www.istockphoto.com/photo/woman-hands-cheers-with-two-glasses-of-champagne-holidays-festive-atmosphere-concept-gm1193770436-339688919 , December 17, 2019, Downloaded December 31, 2022. https://www.istockphoto.com/photo/woman-hands-cheers-with-two-glasses-of-champagne-holidays-festive-atmosphere-concept-gm1193770436-339688919 [Wikip 2024] Wikipedia Editors, "OpenJDK" https://en.wikipedia.org/wiki/OpenJDK, Accessed May 19, 2024. [Wikip 2024] Wikipedia Editors, "OpenJDK" https://en.wikipedia.org/wiki/OpenJDK , Accessed May 19, 2024. https://en.wikipedia.org/wiki/OpenJDK

What the Do-While Is ZeptoN? Part II: Getting Started... What You Need

Example code generated by Microsoft Copilot. iPhone mockup by on Freepik. Background by on Pexels.com zlatko_plamenov FWStudio The development of the Internet is a story of democratization. Computing power and information progressively become easier to access over time. Now, in the middle of generative AI’s hype cycle, visions of a farther future of the Internet are becoming clearer. In fact, the acceleration of AI technology makes me wonder just how far away we really are from revolution. That revolution will overturn everything we know about apps, software, and programming. The “real-time Internet” may be on the horizon, and it’s wise that business leaders understand its implications now before it’s upon us. An Internet Programmed in Real-Time Generative AI has the capability to create not just blog posts, poetry, and images. With the right training sets, it can write entire pieces of software. As seen with tools like , it can work easily with 3D environments for augmented reality projects. Spline Argo Design’s Lead Creative Technologist Jared Ficklin predicts that the future of software and interfaces will become increasingly personalized and produced in real-time by AI. In an episode of Ficklin goes into great detail about his vision of a world computed by generative AI in real-time. He describes it as a natural progression of the evolution of the Internet and of computing itself. He also shares insight into the new ways we will interact with computers in the future. Freethink’s Hard Reset, The Past and Future of Interfaces Ficklin is fascinated by interfaces and how they democratize technology to the masses. Early computing was performed by punch cards, where programmers had to deeply understand how machines functioned. However, punch cards evolved into syntax and programming languages, and then to desktop environments. Now, anyone in the world can use a computer thanks to interfaces like Windows and MacOS. As of now, creating augmented reality experiences is too complicated without the help of talented software developers. Similar to how Unix terminals and desktop environments made computing more accessible, generative AI may make augmented reality development, or rather, experiences more accessible than ever before. “Quantum-like” Websites One example Ficklin points to in the present day that relates to his ideas is “quantum-like” websites. These are web pages or sites that look completely different based on who is viewing them. Amazon is a great example. Every time you visit Amazon’s website, it looks different. This is especially true from person to person. Thanks to personalized shopping results, Amazon can programmatically suggest content to you based on your interests and history. Just like how these websites are unique and personalized to their users, Ficklin imagines that the next step will be completely unique software for each person, all generated by AI on demand. Creating New Experiences From Scratch: Realtime AR Ficklin’s ‘real-time Internet’ is a radical concept that rewrites the rules of how software is developed. For augmented reality, this could mean that AR experiences could be written on demand by on-board or cloud-based generative AI. “We’re going to have a new [multimodal] vocabulary…launch that, put it there, close that.” Ficklin explains in a Freethink interview. “…using gesture…voice, and certain control surfaces all together.” In a nutshell, a future augmented reality experience using this ‘real-time’ approach might look something like this: With a wearable mobile computer like an AR headset, dictate: “Show me what it would look like if the wallpaper in this room was blue.” The generative AI model uses natural language processing and understanding to interpret the user’s prompt and begins writing an AR program from scratch, using the headset’s sensors as environmental data. The AI creates the app using room-scanning training data and specially tailors the new app to identify the walls of the room. The program is ready for launch and shows the user what the room would look like with blue wallpaper. Once the user is finished with the experience, the generated software is deleted. Ficklin’s interview with Freethink fascinated me. I was curious just how close we are to the future he describes. So, I decided to dig deeper. Reality Check With an AI Expert Now, let’s be honest. I’m not an AI expert. While I was coming up with this piece, I realized the best thing I could probably do was ask someone who knew what they were doing about their opinion. I’ve done a lot of writing on behalf of MoibDev in the past, so I couldn’t think of anyone better to ask than their AI experts. I asked MobiDev AI Team Leader for her opinion. Liubov Zatolokina She’s been helping MobiDev’s clients around the world succeed for over four years, so I was really excited to get her opinion on the Real-Time Internet. Is the Real-Time Internet Even Possible? “In my opinion, we already partially have this experience,” Liubov explains. “we can already create simple prompts like images, music, movies, poetry, and social media posts, and even basic programming code and prototypes. It won’t always look like a ready-to-use product, but it’s an excellent place to start. Very quickly we’ve seen an exponential increase in the quality of not only images, text, and software code, but also video creation." Based on her analysis, it sounds to me like Ficklin’s future is possible if AI technology continues to advance at its current pace, but when? In a very short period of time, we’ve seen an exponential increase in the quaity of not only images, text, and software code, but also video creation. How Far Are We From That Future? “It’s hard to say exactly when the next step will be, but we’re already seeing amazing products from leading companies every month,” Liubov continues. “There are hundreds of AI-related articles and news from open-source projects every day. This only accelerates and fuels our curiosity. I expect we’ll see more improvements to the quality of generation and data processing this year, but it probably won’t lead to AGI or the ‘Real-Time Internet’. Each innovation is iterative, and with some patience the future will be mind-blowing.” It’s hard to say exactly when the next step will be, but we’re already seeing amazing products from leading companies every month How Would That Future Disrupt the Status Quo of Software Development? “Every cutting-edge technology disrupts someone’s status quo,” Liubov asserts, “and software developers are no exception. We are now seeing an increase in the amount of automation in development. Code writing assistants and testing tools lead to faster development, less red tape, and more time spent on idea generation. I expect the iterative advances of AI to result in a ‘snowball effect’ in software development and technology sectors.” Every cutting-edge technology disrupts someone’s status quo, and software developers are no exception. So, Do On-Demand AI-Generated Applications Pose a Threat to the Jobs of Programmers and Software Developers? I’m particularly interested in whether , and how Ficklin’s Real-Time Internet may impact programmers. “One way or another, progress affects each of us,” Liubov explains. AI may start to replace existing jobs “But I can’t call on-demand AI generation a threat to software developers. This is the same change for humanity as the invention of the wheel. Some professions may disappear, but many new ones will appear in their place.” This is the same change for humanity as the invention of the wheel. Some professions may disappear, but a large number of new ones will appear in their place. If More and More Applications Are Built Automatically With AI, How Will That Affect the Pool of Available Training Data? “Soon, I think we’ll see further growth and development in the data storage industry, especially with regards to processing and labeling. The incredible speed of generative AI contributes to the fact that there’s more and more unlabeled, automatically generated data in the network.” Liubov says. "Although the content might be high quality, it’s not real-world data. Real-world examples in those datasets is crucial for proper and high-quality training of models. Re-use of that data leads to ‘model collapse’, a decrease in input data diversity, leading to a decrease in model quality.” The phenomenon Liubov describes is also called Model Autophagy Disorder (MAD). Image source. Re-use of [AI-generated content in datasets] leads to ‘model collapse’, a decrease in input data diversity, leading to a decrease in model quality. What Do You Believe Are the Primary Obstacles to Achieving On-Demand AI-Generated Apps, Such as AR Experiences? What Would It Take to Overcome Those Obstacles? “The main obstacle is the intersection of available computational power and how much power the AI models need,” Liubov says. “So far, AI tasks are best suited for use by powerful cloud computing and parallel processing systems. However, the AI engineering community has already seen that scalability isn’t the cure-all in terms of the challenges AI faces. New data processing algorithms combined with new advanced hardware, both focused on energy and computational efficiency, could make things a lot easier.” Based on Liubov’s analysis, I suspect that this may be why businesses are starting to pay closer attention to ‘on-device’ generative AI solutions. and other companies have discussed on-device AI a number of times this year, and some companies like are already releasing products with these features. Qualcomm Samsung New data processing algorithms combined with new advanced hardware, both focused on energy and computational efficiency, could make things a lot easier. The Future of the Real-Time Internet Jared Ficklin’s visions of the next generation of computing may not be here just yet. It remains to be seen just how far off the horizon AI-generated apps on demand are, but there’s no denying that we’re seeing exponential growth in artificial intelligence. Each advancement iterates on the last, and there’s no sign of stopping. I still personally have a lot of questions, like how do we ensure that AI-generated apps are secure? How will AI safety play a role in Ficklin’s envisioned future? There’s a lot we don’t know, but there’s also a lot to be excited about. No matter what happens, AI is going to change the world, and we have to prepare for that future. Thank you Liubov Zatolokina for your insights on this story! Also, thank you for reading! What do you think about the Real-Time Internet? How far do you think we are from that future? Let me know in the comments.

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