Eros Caamaño | 🇩🇴

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Eros Caamaño | 🇩🇴

Eros Caamaño | 🇩🇴

@ecaamano

Co-Founder and Broker/Owner Plusval Inmobiliaria. @plusvalrd 809-860-2269 🖖🚀🍻☺️

Santo Domingo, Dominican Repub Katılım Mayıs 2007
2.2K Takip Edilen963 Takipçiler
Tommy Christie
Tommy Christie@tommyswriting·
You can't drive here. You can't walk here. Playa Frontón only lets you in by boat. La tierra del dios. Samaná 🇩🇴 (all photos by me with my Fujifilm XT-5)
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Tony Dunn
Tony Dunn@tony873004·
Artemis II is scheduled to launch on Wednesday evening.
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Eros Caamaño | 🇩🇴
Amazing advice. This is exactly how I’ve been thinking lately and acting on it every day. I’m even teaching my kids (8 & 11) Python to build their foundation before diving them into AI and full-on vibe coding. As you said, The future belongs to those who adapt. New follower here 🤝
Xiaoyin Qu@quxiaoyin

I have kids. I work in AI every day. And honestly? I have no idea what their careers will look like in 15 years. But I know what will carry them through. First, and this might sound unromantic: make money and save it for them. We can debate educational philosophy all day, but the world is changing so fast that financial security might be the most practical gift we can give. Buy some gold bars. Seriously. Second, nurture their imagination. AI rewards people with initiative and wild ideas. The kid who daydreams, who asks weird questions, who wants to try ten things at once? That kid will thrive. AI can execute. AI can be disciplined. What AI can't do is dream up something nobody's thought of before. Third, build resilience. There are no more iron rice bowls (guaranteed lifetime jobs). Any stable, predictable job is exactly the kind of job AI will learn to replace. Our kids will likely switch directions many times in their lives. Learn something new, get replaced, pivot, repeat. It's more like being a hunter than a farmer. Schools don't teach this. Schools teach you to follow a linear path: high school, college, grad school, stable job. That linear path is becoming the most dangerous one. Last, invest in their ability to connect with other humans. Not networking. Not schmoozing. Real emotional connection. Building trust, offering support, making people feel seen. As AI handles more of the rational, analytical work, the human ability to genuinely relate to other humans becomes more rare and more valuable. I don't have all the answers. But I know that imagination, resilience, and genuine human warmth aren't going out of style anytime soon. #AI #Parenting #Education #FutureOfWork

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Tommy Christie
Tommy Christie@tommyswriting·
Hot Take: The Samaná Peninsula in the Dominican Republic is one of the most beautiful places on Earth. S-Tier. It doesn't get the respect that Bali, the Amalfi Coast, or the Greek Isles do. But it sure as hell deserves it. Epic waterfalls. Pristine white-sand beaches. Endless groves of coconut-bearing palm trees. Humpback Whales breaching the surf. Pure paradise. A lot of Westerners cast aside the DR into the dustbin of touristic hell bc of the all-inclusivity, gringofied hordes of Punta Cana. Samaná is the real deal.
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El CondeNado
El CondeNado@elconde_nad0·
Si ves un perro, estás usando el hemisferio izquierdo, y si ves un avión, el hemisferio derecho. ¿Qué ves? 🤔
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Ryan Leachman
Ryan Leachman@RG_Leachman·
@lpignate @eterevsky I drill oil and gas wells. I think I would know what’s best for teaching children how to play piano compared to a performance piano major
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Ryan Leachman
Ryan Leachman@RG_Leachman·
I asked Claude to build my daughter an app that plugs into our piano, can read live key strokes, can show her sheet notes and key view and ends with a Guitar Hero style game. All while giving progressively harder songs. Today she’s using It and crushing It.
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Zara Zhang
Zara Zhang@zarazhangrui·
Almost every AI power user I know is MORE stressed and busier after using AI, not less What people thought AI would do: 10x productivity so that we can finish work earlier & relax more What it’s actually doing: 10x productivity so that we end up with 20x more things to do cos of the sheer possibilities
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Chanel Mateo Rosa
Chanel Mateo Rosa@chanelsocial·
Casi de cumpleaños esta pregunta y mi repuesta . Seguimos igual @AnaSimo
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Wise
Wise@trikcode·
No Claude, the project will not take me 2-3 months. We will finish it today.
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Jorge Gómez
Jorge Gómez@pelotazo·
Respiraba aire cinco veces al día. No dormía. Esperaba. Contó hasta el infinito… dos veces. Hablaba en braille. Lo mordió una cobra y murió la cobra. La oscuridad le tenía miedo. Mataba dos piedras con un pájaro. Aplaudía con una mano. Hacía fuego con hielo. QEPD Chuck Norris
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Hayddé Domínguez, MS
Hayddé Domínguez, MS@Haydde22·
Gasolina carísima. ¿Adivina quién ya anda en carro eléctrico, y no lo soltará nunca? Sí, yo misma.
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Eros Caamaño | 🇩🇴
Eros Caamaño | 🇩🇴@ecaamano·
Lección histórica aquí sobre njestro uso de AI para todo 🫠 Tiempos muy distintos serán
The Husky@Mr_Husky1

May 16, 1963. Gordon Cooper was orbiting Earth alone inside a capsule barely big enough to turn around in, moving at 17,500 miles per hour. He had been up there for over a day. Then the warnings started. First a faulty sensor screaming that the ship was falling — it wasn't. He switched it off. Then something far worse: a short circuit knocked out the entire automated guidance system. The one that kept the capsule steady. The one that was supposed to bring him home. Without it, reentry was nearly impossible. Too shallow an angle and the capsule would bounce off the atmosphere back into space. Too steep and it would incinerate. The margin for error was razor thin — and every computer that was supposed to hit that margin was dead. Down on the ground, NASA engineers watched the telemetry in silence. They could see everything going wrong. They could fix nothing. Cooper didn't panic. He uncapped a grease pencil and drew lines directly on the inside of his window to track the horizon. He looked up at the stars he had spent months memorizing and used their positions to orient the ship by eye. Then he set his wristwatch. Because when you have no computers left, you become the computer. At exactly the right moment — calculated in his head, confirmed by the stars outside — he fired the retrorockets. The capsule shook. The sky turned to fire. For several minutes, no one on Earth could reach him as plasma swallowed the ship whole. Then the parachutes opened. Faith 7 hit the water just four miles from the recovery ship — the single most accurate splashdown in the entire Mercury program. The man with a wristwatch and a few pencil marks on a window had outperformed every automated system NASA had. We talk a lot about technology saving us. And it often does. But Cooper's story is a quiet reminder that behind every machine, there still has to be a human being who can look out the window, think clearly under pressure, and decide what to do next. The final backup was never the software. It was him.

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JDG
JDG@financialjohnny·
@JoshLilj1 Vine a tuiter a reír, no a llorar.
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Dios
Dios@diostuitero·
Me acaban de presentar a Chuck Norris. Le he dicho, "Hola, soy Dios". Y me ha contestado: "Eras".
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Creepy.org
Creepy.org@creepydotorg·
Very few will know what this is…
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Hadas Gold
Hadas Gold@Hadas_Gold·
Hello from Nvidia's GTC where it's crazy to think of what's happened to OpenClaw creator @steipete ... launched OpenClaw in November, now having its whole own section at Jensen Huang's keynote.
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Josh Kale
Josh Kale@JoshKale·
Andrej Karpathy just dropped a project scoring every job in America on how likely an AI will replace it from 0-10 > Scraped all 342 occupations from the Bureau of Labor > Fed each one to an LLM with a detailed scoring rubric > Built an interactive treemap where rectangle size = number of jobs and color = how exposed that job is to AI The key signal in his scoring: if the work product is fundamentally digital and the job can be done entirely from a home office, exposure is inherently high. The scale: 0-1: Roofers, janitors 4-5: Nurses, retail, physicians 8-9: Software devs, paralegals, data analysts 10: Medical transcriptionists Average across all 342 occupations: 5.3/10. The entire pipeline is open source. BLS scraping, LLM scoring, the visualization. All of it. Much respect for the sensei this is scary and awesome
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Eros Caamaño | 🇩🇴
Eros Caamaño | 🇩🇴@ecaamano·
Radiology might actually be one of the worst examples you could pick here. It’s one of the most digitized, data-rich, pattern-recognition-heavy medical fields , which is exactly why AI progress there has been so fast. Deep learning systems have already shown radiologist-level or better performance in tasks like breast cancer detection (Nature study): nature.com/articles/s4158…⁠ The future i assume will be likely hybrid human + AI workflows. But higher diagnostic throughput per doctor can usually means fewer doctors needed over time. PS: Treat this as an uneducated reply 'cause im not a doctor! The efficiency gradient @karpathy was pointing to is not that remote = replaced, but that fully digital cognitive work sits closer to the automation frontier.
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Hemang Singh
Hemang Singh@InsaniDarinda·
The methodology is interesting but the scoring feels arbitrary. Why is "can be done from home" the primary signal? Remote-capable work ≠ AI-replaceable work. A radiologist can work from home, but interpreting nuanced imaging still requires human judgment. This oversimplifies job complexity into a single dimension.
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