Gerard (@grdmorera) profile picture

Building NUA, your AI sports personal agent. Trail runner. Go player. 2e

Joined October 2014
Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)Photo by Gerard (@grdmorera)
ANTONIO ACEDO - MAQUINISTA del AVE 02080 siniestrado en URDA. Este hombre dio su vida a sabiendas para salvar a quienes tenía bajo su responsabilidad. Se mantuvo en su puesto accionando el freno para reducir al máximo la velocidad del tren que conducía hacia su inexorable muerte mientras la veía venir ante sus ojos por unas circunstancias en las que le pusieron sus responsables. Desgraciamente España está forjada de esta manera, con una élite cobarde, irresponsable y ruin y un pueblo honorable, abnegado y entregado. Antonio Acedo forma parte ya de ese linaje de héroes Españoles y debemos recordar siempre que en el momento de la verdad su mano no tembló para cumplir con su deber para con los demás, exactamente todo lo contrario que nuestra clase dirigente.
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We've just launched the NUA app on iOS and Android. NUA is a personal sports agent for cyclists: training, nutrition, routes and more. Born on WhatsApp on purpose: good coaching takes trust. So we didn't build an app with a chat inside it. We built a chat with an interface.
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Your calendar or a session appears in the conversation when you need it. Moving a session to another day? Drag it. Point at a spot on the chart, ask "why so hard here?", and NUA knows what you mean.
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NUA remembers you, so you can pick up the conversation on WhatsApp, Telegram, web, iOS or Android without starting over. Cards in the app, text on WhatsApp. Tomorrow it could be earbuds or glasses. This is the first version.
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Gerard retweeted
Había que hacerlo.
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A legend is born
Sé diferenciar la buena publicidad cuando la veo
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Había que hacerlo.
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Me escribe un maquinista. Imagino que a esto es a lo que se refieren cuando hablan de “error humano”.
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We launched @agent__swarm at Dev Hunt today, come help use give some noise! AI software factories, Rick!! → devhunt.org/tool/agent-swarm…
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Cuando no tienes que rendir cuentas por los resultados, es fácil perder de vista el propósito de tu trabajo y convertir el propio ejercicio de hacerlo en un fin en sí mismo.
Wow, over 1,000 mathematicians have now joined the Association for Human Mathematics (AHM), committing to: > NOT publish AI generated math papers > NOT work with frontier labs > 654 of them went even further to NOT even use AI in their research, at all
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No estic a favor del vandalisme i el saqueig però ara sabeu què van sentir els romans al 410 dC.
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Every new Claude model feels like magic. Then my expectations catch up. Is this hedonic adaptation?
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Me sigue volando la cabeza que tengamos algo así al alcance de nuestras manos.
Claude Opus 5.5’s Oboe Concerto in C minor. 60% of respondents identified it as being human-written -- higher than pieces by Handel (58%) and Vivaldi (43%).
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AI will commoditize software while creating a golden age of consumer products.
Software is dead It's now the era of personal software and everyone just builds what they need whenever they need it I think
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The question is whether this will be a golden age for consumer startups, or just for consumers.
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Here's Opus 5.5 with a visual reading of Karpathy's latest tweet. Watch on 2x speed. (one prompt btw)
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
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Gerard retweeted
Bestial lo de Barcelona Fotos propias mirando a la bestia desde la Barceloneta a las 12:15h @MeteoredES @meteocat
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Cuando descubres que los partidos cambian de posicionamiento eligiendo problemas, víctimas y culpables para que les votes y les necesites, te das cuenta de que actúan con una lógica empresarial inmoral.
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Gerard retweeted
AI isn’t going away. Barring unprecedented global government coordination, it isn’t even slowing down. The only real decision is whether to centralize power, or disperse it. Do you fear the technology? Or a small number of people controlling the technology?
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Gerard retweeted
Dario is right
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training. You can read the full post here: darioamodei.com/post/we-must…
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