Big Brother since 1984. @baubapmx (YC S21) co-founder. Optimist, building for many by amazing the one.

All over the place
Joined June 2010
Una de las preguntas que más me hacen es: ¿qué significa Baubap? Y siempre elijo contar toda la historia. En 2018, en una de esas pláticas pasionales que solo se pueden tener con un co-founder como @luisvcastilla, surgió la pregunta: ¿cómo se va a llamar nuestra empresa?
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Una obsesión compulsiva por el detalle es una característica invaluable para mí como founder de Baubap. Hay una frase que me funciona como mantra: “Perfection isn’t attainable, but if you chase it you may catch excellence”.
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Alzar el teléfono y hablar directamente con el cliente es la mejor técnica para identificar errores y conectar con las soluciones que necesita el producto y servicio. TODAS las respuestas las encontramos en los clientes.
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Cocinar es mi hobby. La primera vez que sentí el dolor/placer de trabajar dentro de una olla de presión y con todo mi esfuerzo y concentración fue cuando tuve la oportunidad de trabajar en un restaurante en Londres. Aquí la historia. linkedin.com/posts/roberto-s…
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Lo que me protegió de no sentir miedo cuando tomé la decisión de emprender, fue la ingenuidad de creer que estaría bien fácil. Un año y medio después de empezar y de haber invertido todo mi patrimonio en @Baubapmx, sí sentí miedo. Pero seguí y ya el resto es historia.
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Hasta en las series entretenidas y un poco violentas se pueden encontrar buenas reflexiones. ⁣ ⁣ En el camino de crear algo valioso hay muchos obstáculos reales y emocionales. Hay días buenos y malos. Si se fracasa, se puede volver a empezar y si persistes puedes crear algo extraordinario.⁣ ⁣ Les dejo este fragmento de 𝘉𝘭𝘶𝘦 𝘌𝘺𝘦 𝘚𝘢𝘮𝘶𝘳𝘢𝘪. 👇⁣ ⁣ 📹Clip tomado de Netflix.
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Emprender exige entregarnos completamente a ello. Aún cuando haya momentos de dolor y sacrificio. Al final, es justo eso lo que lo hace enriquecedor y entretenido.
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Tener 𝘈-𝑝𝘭𝘢𝘺𝘦𝘳𝘴 o gente súper talentosa en el equipo de trabajo es algo que atrae a más personas talentosas, y esto genera un círculo virtuoso de crecimiento para el negocio. El reto al principio, cuando no hay dinero ni resultados es convencerlos solo con tu visión.
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Primera pirámide: la correcta desde el punto de vista del desarrollo del negocio. 👇 Estrategia / \ Estructura del equipo de trabajo / \ Equipo de trabajo Segunda pirámide: la desviada cuando se construye la organización con base en las personas que trabajan en ella y no en las necesidades del negocio. 👇 Equipo de trabajo / \ Estructura del equipo de trabajo / \ Estrategia
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Un momento emocionalmente difícil es reconocer cuando las personas que funcionaban extraordinariamente al principio, no necesariamente son las que hoy necesita la empresa. Especialmente, cuando juntos logramos cosas chingonas.
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Roberto Salcedo retweeted
This is the difference between user experience and design
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Es inevitable generar un vínculo personal con tu equipo, y me parece incluso necesario para poder compartir el propósito de la empresa, elevar su compromiso con este y contigo como líder o compañero de trabajo, somos personas no herramientas.
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Para mí lo valioso del trabajo remoto es que atrae a personas con alta capacidad de autogestión y autodisciplina. Esto facilita aumentar la densidad de talento, ya que estas personas suelen ser más ambiciosas, creativas y motivadas por obtener resultados.
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Mientras más alto es el monto que un fondo va a invertir —arriesgar—, más amplio debe ser el historial del desempeño del negocio. Independiente de si la deuda se levanta para financiar un portafolio de crédito como es el caso de @Baubapmx o para financiar la propia operación del negocio.
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De vez en cuando es bueno dejarse llevar por el espíritu emprendedor contraintuitivo. Ese que va más allá de lo que la lógica de los conocedores y de las circunstancias dicen.
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Nuestra carrera para levantar deuda para lo que hacemos —que es prestar dinero—, fue como el dilema del huevo y la gallina.⁣ ⁣ PORQUE los fondos de deuda quieren 𝘵𝘳𝘢𝘤𝘬 𝘳𝘦𝘤𝘰𝘳𝘥. Y nosotros, precisamente, necesitábamos ese dinero para generar ese historial. Entonces, ¿qué va primero? 🤔
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If you actually want to regulate AI, first you need to have a clear, grounded, practical understanding of AI. Then you need to understand the limits of what legislation can and can't do. What legislation can't do is guarantee that something is always safe or we wouldn't have the Boeing MAX incident in one of the most heavily regulated industries on Earth. Those smart, savvy regulatory bodies would have swooped in and stopped the problem before it even happened like the pre-crime unit in Minority Report! On the flipside, heavily regulated industries are slow moving, bloated and have little to no competition. The same will happen to AI if people manage to ram through the kinds of overreaching and misguided bills we're seeing. Too many folks have a black mirror funhouse view of AI. The inevitable outcome of those views will be terrible legislation that crushes innovation and competition while solving exactly no problems. If you start from the wrong premise, everything you do after that it is inevitably wrong. Here's the key to understanding AI and how to regulate it with sound, sane, light touch regulation: - AI is not dangerous in the way Doomers think about it, i.e growing sentient, recursively self improving and treating us like the bugs in 3 Body Problem, aka "humans are bugs, must destroy." It does have some potential dangers in other ways that are barely talked about and those get lost in bombastic rhetoric. - AI is dangerous the way a kitchen knife is dangerous. 99% of the people will cut vegetables with it. 1% will stab someone. We should let most people cut vegetables and punish the 1% of people who stab someone. We do not take the kitchen knife off the market because it can be misused. Everything can be misused. - If you are building AI in a field where people could get physically hurt or killed, such as the medical field or self-driving cars, you should be held to a higher standard of safety. - The nuclear analogy to AI is specious. Nuclear weapons are designed to do one thing only, kill many people at once. AI has a huge range of capabilities and uses. This analogy is absurd. - Attempt to control AI will only lead to a global imbalance where some societies shoot themselves in the foot with overreaching and difficult to comply with regulation, while other countries see an opening and race ahead. This is how empires fall and new empires rise. We will never, ever come to a consensus on AI across the world. - The best regulations usually come after we see what problems happen in reality. As Mike Tyson said "everyone has a plan until you get punched in the face." We can foresee some challenges but mostly we can't see anything meaningful until something has contact with reality. We have a long history of safety bills that were very effective, such as in mining and worker safety, that came after we saw the patterns of problems and moved to address them. - The real dangers of AI are using it for mass surveillance and the military and there are 100% exceptions carved out in every law and proposed bill for military and surveillance use cases. This should shock no one. - Moral panics are delusional and they have a way of escalating and their inevitable outcome is bad/misguided/dangerous legislation or people getting hurt/killed (i.e, witches get burned (actually hung or drowned, for the nitpickers), real people go to jail like in the 80's Satanic panic where a couple went to jail for 28 years with no evidence of child abuse because "Satan made the evidence disappear" (for real). - Irrational fear is a terrible, terrible way to push for policies. Fear has a way of getting out of control and getting away from you. It sweeps out like a storm and it warps and changes as it goes, getting picked up and amplified by other unhinged people, who twist it into their own dark agenda and continue to escalate. What you get is just bad things at the end of that horrible cycle: again, people hurt or killed (and not by AI but by other people) and terrible policies. - Even worse, this irrational AI fear is already being picked up by far right and far left ideologues and being warped into whatever bizarre policy they want to push. The policies they get through with this kind of rhetoric, will have nothing to do with what the Doomers want, which is international cooperation and coordination. It will be used as lip service to justify bigger escalation with China, or sanctions, or anti-immigrant rhetoric. We've had a long history of absurd moral panics for everything from bicycles, to radio, to TV, to video games. They lead to nothing good. - "This time is different." It's not. - Apocalypse predictions have a 100% failure rate in the history of prediction. Predicting AI apocalypse is no different than predicting apocalypse because "God is mad at us and destroyed the crops." It has no validity or evidence to support it, expect in the mind of the people imagining it. Eventually someone may be right by sheer chance but nobody will be around to congratulate them. Much of the rhetoric around AI control and danger is drummed up by people with zero real, practical experience in AI, people who masquerade as researchers in the way the People's Democratic Republic of Korea is democratic and republic. These people are the useful idiots, aka the Baptists to the Bootleggers. - The Bootleggers are the big AI companies who are talking out of both sides of their mouth, claiming AI is dangerous (while they race to build bigger and better ones) and they're using the useful idiots to try to create monopolies and push for anti-business, anti-American licensing regimes to train and run big models that are in nobody's interest but their own. Their actions remind me of Pan Am in the 1950s trying to get a monopoly on international travel. See the new "protect OpenAI from competition bill in California (SB 1047) as the clearest possible example." - Open source/open weights are essential. If you oppose open source, you don't understand the history of the last 20 years of software development where open source is in 95% of software. Linux runs ever major cloud and super computer, your router, most phones, and control systems. It also runs botnets and enemy supercomputers. The benefits of having a common set of building blocks still far, far, far outweigh downsides. You can see more detailed arguments here: xitter.cf/Dan_Jeffries1/st… xitter.cf/Dan_Jeffries1/st… xitter.cf/Dan_Jeffries1/st… xitter.cf/Dan_Jeffries1/st… xitter.cf/Dan_Jeffries1/st… xitter.cf/Dan_Jeffries1/st…
Destroying Terrible Anti-AI Arguments: Day Six "ASI will kill us all" This one is similar to "my p(doom) is x%." It's a blind assertion. It has no validity outside the mind of the person saying it no matter how many times they repeat it. The reason is simple. We have no idea what ASI will be like and ascribing characteristics to it is an exercise in futility. Pausing AI to create solutions for a non-existent thing will be of zero value when (and if) ASI actually gets here. Here's a few illustrations to show you why: Imagine going back in time and asking da Vinci what are some of the characteristics of a modern aircraft in 2024, like the Boeing 787 Dreamliner? Ask him about how we can make it safer? Ask him about the general challenges of building such an aircraft and how we can improve the supply chain? Ask him about our safety protocols, like incentivizing pilots to report near accidents within two weeks and if they do that faithfully it can't be used against them in a court of law? Ask if that makes a big difference in airline safety and how? His answers on any of these questions will be utterly meaningless. That's because he can't conceive all the myriad economic developments (division of labor, specialization, free markets), supply chain developments (global interconnectedness, mega-boats, shipping containers), societal developments (modern democracy), and stacks of compounding technological development (lighter materials, engines, computers, electricity, wires, interchangeable parts, etc) which all weave together to make the modern airplane. These other inventions and technologies and cultural developments all influence, mitigate and create friction on the other technology. It does not exist on its own. Many folks will tell you that long term prediction is easy and they are dead wrong. Humans are absolutely terrible at this, even people who make a living doing it. We can sometimes predict near term trends pretty well but long term trends are beyond our event horizon. What almost inevitably happens is people project forward into the future all the characteristics of the present day and add one new invention. That is not how things develop in reality. Society, technologies, culture and people evolve in massive parallel at a level that is mindbogglingly complex. As we move forward in time we have a tremendous confluence of new inventions, political strategies, legal frameworks and more, all at the same time, all in parallel. It's everywhere, everything, all at once. A great example of this is the 1968 book, The Population Bomb, which predicted that we'd need to let 2 billion people starve because there just weren't enough resources to go around. Instead we got the Green Revolution and can sustain more folks than ever. In a classical example of terrible prediction error 101, Paul R Ehrlich, projected forward all the characteristics of the 1960's into the future and failed to predict any other possible societal, biological, or technological developments. Try explaining the Internet to an 18th century farmer. You can't do it. That's because it's built on the back of chain of inventions and societal developments like electricity, turbines, wires, information theory, the computer, browsers, digital computers, etc. If Da Vinci projects forward his flying machine to 2024, but imagines it with the characteristics of Renaissance Italy in 1500's, his predictions about life in 2024 are less than worthless. They have zero chance of being accurate. Even if he is more creative in his thinking, projecting forward hundreds of years is impossible for anyone because they have to come up with the distributed, collective inventions of the entire world of people working collectively over time, building on the back of the people who came before them. Even near term predictions are tricky. A great example comes from one of my favorite sci-fi books, Neuromancer, by William Gibson. Gibson came up with the idea of cyberspace before the Internet really came out of universities and the military, in the early 1980s. That's cool but how he saw it developing had nothing to do with how it actually developed. He saw all data as a kind of 3D construct because it was too difficult for any one person to perceive. Actually we can perceive data just fine and we can interpret it directly in databases and spreadsheets and documents. He also saw the Internet as something you go to, not something that is around you all the time on the laptop and phone and watch through wireless. In fact he failed to come up with wireless at all. One of the funniest moments in the book is hacker laying a fiber optic cable over five miles to connect to a modem to connect to cyberspace. Another hilarious moment is when a hacker calls up on landline phone (because he also failed to predict portable phones) to get the time, like people did in the 1960s. Despite all his prodigious prediction, he could not even conceive of the time being always available everywhere or the internet floating through the air. What we can do though is perceive patterns and abstractions of the past and the future. The pattern of the past is that we have always come up with a massive amount of parallel developments and inventions and mitigations for technology, all acting on, supporting and limiting each other. We are on solid ground when we predict in terms of patterns/abstractions. I don't know what those mitigations to ASI will be or what ASI will be like but I can predict that parallel inventions that act on AI will develop at the same time and as needed because that is how it worked 100% of the time in the past. There is no reason to imagine this is some kind of exception, no matter how many times X-riskers tell you "this time is different" (famous last words, used thousands of times in history to describe pretty much every technology that has ever existed and has been wrong precisely 100% of the time). We don't know what mitigations, parallel developments, societal/cultural developments and technologies will accompany ASI and how it will help keep it on the rails but we know they will come. Already we have people working on actual alignment solutions. We have RLHF and we have RLAIF, aka Reinforcement Learning with AI Feedback. Researchers are developing solutions. Others will follow. Regular engineers are now getting their hands on ML models and bringing their unique perspective to the problem as well. They see the problem differently than ML engineers and research scientists and bring a fresh perspective. As they work with open source models they're working on guardrails that come from their knowledge of traditional hand coded logic. Why? Because they want the AI to behave and give them consistently good results! They want it to do what they want so they can build apps. They don't want it to decide that it doesn't feel like clicking on the button to buy a ticket. We are incentivized to make these systems more reliable as a species because we want them to work. All these developments will inevitably lead to new solutions and ideas that are practical in the real world of AI, not the AI of fiction. While many "AI researchers" are writing philosophical treatise on why AI can never be our friend and warning about the end of the world like they're Jim Jones reincarnated, actual researchers are hard at work on the problem. Problems are solved in the real world through engineering, as they develop in time. We invent the seatbelt and the airbag and crumple zones for the car, after we realize that it can go too fast. We can't conceive of that problem before it happens. That may seem strange to you but you are looking at it after we have traveled faster than we could run, which was not the case for people before trains and cars existed. They never traveled faster than a horse could carry them. People before the train and the car had heated debates about what would happen to the human body if we went 10 miles an hour. Would we spontaneously explode? Would we die of a heart attack? Would we pass out? In short, their predictions were dead wrong. These all sound ridiculous now but that is because we know how it turned out after it happened in the real world. We have actual knowledge to build on. Once we get that, we build actual solutions. That's why calls to "pause AI" are deeply misguided. It is a basic misunderstanding or real world cause and effect. These folks do not understand that you don't invent solutions in a vacuum. We can't invent solutions to imaginary problems. We invent solutions by interacting with the problem in reality. Problem happens, you think about it, you work out a solution. Or rather, problem happens, lots of people work on it, trying many different solutions until we get one that works and then we deploy that solution. It's an iterative process that happens after or in parallel to the development of the original technology. The safety razor comes after the razor. Crumple zones come after the car. Don't worry. The engineers will take it from here and do what we always do when it comes to real world problems. We'll solve them.
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Soy de esas personas que toma notas en cualquier lado en donde pueda escribir 😁. PD: Esta foto fue cuando construíamos nuestro ingenuo plan 2020 (sin saber que vendría la pandemia). En estos días les comparto esa historia.
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La decisión de invertir o no en un fondo de deuda se basará en 𝑝𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦, 𝑝𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦, 𝑝𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦. A diferencia del 𝘦𝘲𝘶𝘪𝘵𝘺 (donde se vende la visión y los diferenciadores del negocio), en deuda, la decisión se va a centrar en el desempeño histórico de la empresa, 𝗻𝗼 𝗲𝗻 𝗹𝗮 𝗽𝗿𝗼𝗺𝗲𝘀𝗮 𝗱𝗲 𝗹𝗼 𝗾𝘂𝗲 𝘀𝗲 𝘃𝗮 𝗮 𝗹𝗼𝗴𝗿𝗮𝗿 𝗲𝗻 𝗲𝗹 𝗳𝘂𝘁𝘂𝗿𝗼. Las razones aquí. 👇 acortar.link/3DwFOe
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Cuando hablo con un fondo de inversión uno de mis objetivos es hacer muchas preguntas. Para mí no se trata de que solo el fondo haga due diligence de la empresa, sino que también tú como emprendedor conozcas con quien te vas a asociar.
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