This is the quintessential question that all the plans begin with: whether you want to hang out at the park with your friends or go spend the day at the museum; whether you want to eat Mexican or Thai tonight; or whether this summer you see yourself haggling in the Moroccan markets or swimming in the Jordanian dead sea. Our mood and emotions are ever changing, and we’ve all had those moments of indecision, trying to decipher the answers to the above questions. Luckily booqr is here to help!
Generative AI has already transformed the way we approach life. From productivity to creativity, there are tools empowering humans to try new things that were previously outside the limits of their abilities. Our company believes that AI can also help us maximize the pleasure in our lives.
Love the colour pink? booqr will take you to spend fall break Brugge.
Planning an outing can be so stressful that people often fall back to the same activities and the same places they have done and been to a million times before. Even when people want to try something new, they don’t have all the information to make the most informed choice. Maybe a particular hotel has excellent rating online, but is it good for you? The best hotels in the center of the most bustling cities may not appeal to a nature lover. To bridge this information gap, you can spend hours researching online, or alternatively, you can use booqr.
booqr is a new AI-powered platform that leverages your data to offer personalized and highly automated travel solutions. booqr plans not just general itinerary but the specifics too: maybe a boat trip to visit the lake palace in Jaipur followed by laal maas for dinner, or maybe a Lavaux wine tasting cycling tour along Lake Leman. Detailed travel plans like these, along with fully automated bookings, made possible through deep integrations and partnerships with industry leaders, is what make booqr special. Moreover, booqr uses GenAI to turn this up a notch by employing natural language processing (NLP) chatbot, which allows users to be as expressive or vague as they want to be. Tell booqr which movie you liked, or what colors are your favorite, and see oboqr analyze this information to understand what excites you, and create the perfect solutions for you.
Sit back and enjoy your journey!
booqr can go even further if you are truly unsure what you are in the mood for, by offering to book a completely surprise trip for you. “Mystery booqr” is for adventurers who like surprises, and is unmatched in the industry, as this mystery trip is truly customized to your needs. Without the usual hassle of endless forms or interviews, booqr sifts through your preferences and creates an unforgettable experience — with just the right balance of surprise and familiarity. Vacations are expensive endeavors, and that is why even though we humans like to be surprised by new things, our risk averseness prevents us from trying something that is completely new to us. This is why Mystery booqr is such a unique proposition, where risk is minimized for users while ensuring the “mystery” is kept alive.
The travel booking industry is seeing a gradual adoption of GenAI tools, but what they lack is the integration between multiple stages of the travel planning and booking process into one seamless experience. booqr’s comprehensive approach disrupts this pattern, and is bound to push the industry adoption of GenAI, and we are looking forward to leading the charge.
Authors: Laurens Meijer, Pravar Saran, Fabian Haak Wegmann, and Tjalling de Wit
Until a month ago, I had not used generative AI in any meaningful way in my life. Sure, I had played around with new apps like ChatGPT and Claude when they were released (I wanted to see how much fun talking to these notoriously lying, flirty, and joking AI chatbot could really be). I challenged Midjourney to make visual representations of my really dumb and nonsensical dreams as a fun exercise. And finally I was curious, as a music lover, about how good Google’s MusicLM was in creating a melody that was not only realistic, but also maybe beautiful (the output was quite pleasant to my surprise). But I refused to use any of these products in any meaningful way.
My big concerns were regarding their actual usefulness. Yes, whatever information these models provided was excellent in “passing” as correct (both factually and contextually), but we all knew that it was far from 100% accurate. Even Chat GPT’s latest reasoning model o1 has a “unique capacity to ‘scheme’ or ‘fake alignment.’” according to independent AI safety research firm Apollo Research. For me, using AI always felt like working with a lying sociopathic co-worker. Rather than living in the paranoia about where AI could be lying to me and going through its output with a fine toothed comb, it seemed easier to do the work myself. Similarly, or even more importantly to me, the fact that these models are trained on data not legally obtained by companies meant that their output is basically stolen.
As someone who has zero artistic bones in his body, I am in awe of what creatives in every field are able to bring to this world. Their work being used without their permission upset me as much as it would if someone were to steal my assignments (and my assignments are not even that good!). But a few things recently changed, that has finally started me on my journey to coming to terms with, and even starting to like, generative AI. Firstly, I wanted to start eating healthy.
The balance of my diet has never concerned me in any way, but my friends recently made a big fuss on my daily waffles and Nutella consumption (I still argue its not that unhealthy), and with a generally higher concern about health since the pandemic, I decided to make a change. But I still did not care enough about this issue to put in the work to understand what carbs are, how much is too little or too much protein, and what I need to do with calories. This is when my friend suggested I should just ask Gemini to develop my meal plan. The stakes being as low as they were, I gave it a try, it won me over. It was simple, it was easy, and it was unimportant! I am sure a nutritionist would have found problems with some of the things that were being suggested to me in my meal plan, and I don’t know if the recipe I made Gemini create of mussels with chicken stock, broccoli and Bolognese is an actual things humans anywhere in this world eat, or just Gemini going “Sure, put it all in in the pan, what could go wrong!”. It has had a practical impact in my life and has almost become part of my weekly routine.
It did taste really good!
The next big incident in my journey to AI adoption was my need to study RStudio. I have never learned coding, and it became quickly apparent to me that the traditional way of learning to code using books, articles or YouTube videos will take me too long. On an evening when I was too tired after class and not at all in the mood to watch another instructional video, I asked ChatGPT to help me code something. I get the code, input it in R, and it did not work. There is this error that kept popping up. This is where generative AI really surprised me. I asked ChatGPT why I was getting that error, and not only was it able to pinpoint whatthe exact mistake that I was making when loading the library in R, but also explain why it was a mistake in the first place! Moreover, when I asked how this code worked, ChatGPT broke down every-single-field-and-bracket in that code to explain to me what every element was meant to do, and how I could tinker with and alter those elements to play around with the output. It was the closest I have felt since high school when my teachers would take out time to sit down with me one-on-one and explain difficult concepts with which I was struggling. For a software to be able to imitate even a little bit of some of the best teachers I have had, is really an impressive feat.
However, the code it provided me with was still trained on data from coders who were not asked for their permission or compensated for their work, so the ethics of using this should still have been absolutely not ok, but I did not feel as bad about this. I wondered why I felt more comfortable using generative AI for coding, even though I would never use it to create art to publish under my name. Is it that I do not prescribe the same value to coding as I do to art? Or maybe, it is the fact that I know that my coding assignment does not really hold any real value in this world in the large scheme of things, and so I excuse using Gen AI in this instance. After all, I am not using the code to compete with actual coders. But here is the thing: I could. Instead of hiring an app developer in the future for my start-up idea, I could try to code it using generative AI, thus making obsolete the jobs of the coders whose output was used for training these models.
The code used in the training only exists because people spent their personal time and energy writing and publishing code online, whether to help their fellow colleagues, to show their skills, for practice, or whatever other reason. Their effort holds as much value as that of any artist involved in the field of painting, music, or literature.
This is where regulation has to come into play. I see the value of generative AI, both personally and professionally. I intend to “copy” my friend’s idea of creating a storybook for her niece’s first birthday using Midjourney, and I intend to continue learning coding using AI. But we have to solve the answer of how these tools are being developed: whether setting rules on compensations for using training data, or on how we can monetize the output of these tools, or some other solution that we all have to find together (with consensus of all the stakeholders), and not unilaterally by big corporations. I do see the value of these tools and am going to use them increasingly in the coming days, weeks and months. But we must make sure, that in the excitement of what is possible with these tools and their convenience, we do not ignore out responsibilities towards are fellow humans, their works, and their rights.
Good Artists Borrow, Great Artists Steal… and Apple Sics its Army of Lawyers on Your Patents.
19
September
2024
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How Apple uses its App Store platform to envelop and bully small developers.
Platform envelopment cases are often brushed aside as being part of normal business. After all, we cannot stop an existing platform, just by virtue of its size and “success”, to stop adding new features that their customers clearly desire. Taking the example of Apple, one of the most aggressive cases of a company using its closed ecosystem platform to ward off any competition, and you see the term “Sherlocking” come into play. The term originated when Apple added features of a third-party software called Watson into Apple’s Sherlock feature, and over the years have seen hundreds of more such instances occur.
Many try to argue that it is the normal progression that occurs with all technology, and features are meant to updated over the life of a company and product, and in an open competitive market, the person who develops the best product should win, rendering moot the need for any outside check. However, when it comes to huge platforms like Apple’s App Store (one of the best two-sided market platforms to ever exist), you must keep in mind this one essential fact: “Apple is not only a competitor, but it also sets the rules of the marketplace.” This is said by Rick VanMeter, the executive director of the advocacy group Coalition for App Fairness, which represents more than 80 popular apps, including Spotify, Match Group and Epic Games (Allyn, 2024). This makes the case of Apple so uniquely scary for small time developers, as: Apple has access to a huge chunk of your app usage data; Apple controls the rules and regulations which govern your app’s existence on their platform; Apple has no oversight on the decisions its make; and developers for the longest time had no way to dispute the decisions made by Apple.
A two-sided market platform, where user data is the main currency, means that Apple’s reign cannot be challenged by any competitor, no matter how meritorious (Condorelli and Padilla, 2020). Apple maintains this position by bundling, self-preferencing and leveraging its position as the owner of the platform itself. Defending against such envelopment attacks are very difficult. Patent applications and litigation are extremely costly endeavours for small developers. Moreover, even making sure all the paperwork is fully taken care of is not sufficient, when facing off against Apple’s lawyers. Apple’s playbook includes attacking multiple patents owned by companies that accuse Apple of violating those company’s patents. More egregiously, Apple even goes after the patents which are not even part of the dispute to begin with (Tilley, 2023)! Apple is getting a reputation in the industry for reaching out to smaller companies to show interest in their products, only to turn around and completely copy the products of those small developers, and sometimes even go ahead and poach the company’s top talents. Small developers had no recourse during these actions, and developers are sometimes very clearly told that the only way to exist is by following Apple’s rules, which it can change and apply in whatever inconsistent manner that conveniences them (Kastrenakes, 2020) (Statt, 2020). Developers share stories of how it is inevitable that their own success is not followed by an attempt to envelop their product, but what makes it worse is the way they cannot even speak up about how unfair this battle is, lest they make Apple furious (Gallagher, 2019).
Thus, it is extremely important for regulators, and antitrust laws, to focus on targeting big tech for the unfair advantages it has built by virtue of developing and running these huge platforms, as Apple is far from the only player who is engaging in their own unique flavour of anti-competitive behaviour.
Condorelli, D., and Padilla, J. (2020, May 21). Harnessing Platform Envelopment in the Digital World. Journal of Competition Law & Economics, 00(00), 1–45. doi: 10.1093/joclec/nhaa006
Gallagher, W. (2019, June 6) Developers talk about being ‘Sherlocked’ as Apple uses them ‘for market research’. Appleinsider.com, https://appleinsider.com/articles/19/06/06/developers-talk-about-being-sherlocked-as-apple-uses-them-for-market-research
