data rules everything around me. sophisticated ironist #blacklivesmatter. data engineer. @tacosdedatos | smol policy bb | host de @LoQueAndoOyendo

San Francisco Bay Area
Joined March 2016
chekos retweeted
black pill: enterprises are putting their AI transformation (and the most existential business risk/opportunity of a lifetime) in the hands of their IT department
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tu educación debería adaptarse a ti, no tú a ella heymaestro.‌app
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chekos retweeted
The "design engineer" archetype in intelligence era needs be someone much further-reaching on both ends. Beyond DESIGN, a keener social intuition, a rich visual + tonal vernacular, broadly read, a deep understanding of people. They need to be deeply-feeling themselves, and not Maslow's 'existential zombies.' They need an investigative & suspended disbelief, but also a discernment and sanity to prevent psychosis. Far beyond just buttons + sliders. Much closer to a novelist or anthropologist. Beyond ENGINEER, a deep-seated intuition of machine intelligence: how they traverse latent space, what they can / cannot do well. A scientific approach to prodding this 'grown-not-built' intelligence. Far beyond just CRUD apps. Practically: ability to fine-tune + benchmark models, among other skills, to bridge machine intelligence to the more design/humanistic. FWIW: all this is very good for a field — software design — that has recently (and rightfully) become the butt of jokes, and seen as a very unserious discipline
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yes indeed, last night an ai agent accessed my bank account and purchased a couple of beers at my local bar
SITUATION DETECTED: Major U.S. banks are detecting unauthorized AI agents operating inside customer accounts and struggling to determine which actions were authorized by users, per Axios.
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vi varias personas comprarse el curso de python y el de sql juntos asi que agregué un descuento cuando compras mas de un curso juntos a heymaestro.‌app es como combo cuates pero cuando tu eres tu propio cuate
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another way to never run out of coffee using cafecito.bot
We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent. It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.
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chekos retweeted
"theyre called 'dashboards.' and they turn unstructured data into actionable insights about critical business functions"
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¿CÓMO SABES? (¿CÓMO SABES?) ¿CÓMO SABES QUE ES VERDAD? NO ES NOMÁS PORQUE ME LATE TE LO PUEDO COMPROBAR
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Si quieres aprender a contestar “¿cómo sabes?” cuando un agente trabaja por ti, de eso se trata mi curso IA agéntica para datos: app.heymaestro.app/courses/i…
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PG is right. That’s why we just build the first coffee shop for ai agents: cafecito.bot ☕️ Just ask your ai agent to order coffee from us and it will be delivered to your place (only delivering in SF and East Bay).
Amazon banning agents is the first opportunity I've seen since Amazon was founded for a startup to create an Amazon competitor. People will want agents to buy stuff for them. It will be one of the main use cases. And they won't want to use some Amazon-supplied agent to do it.
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Vengo con una noticia muy buena 🥳 El post del límite de la IA llegó hasta gente de @AnthropicAI , que me escribió rapidísimo. Eso lo habéis conseguido con la difusión. Gracias de corazón 🙏🫶 Yo había enviado la solicitud a su programa AI for Science. Esta madrugada me ha llegado la aceptación del proyecto, y los créditos de uso de Claude ya están en mi cuenta 🎉 Sigo construyendo y os voy contando lo que salga 💜💜💜 GRACIAS
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A este post no le hicieron tanto caso pero hoy en la mañana me puse a analizar todo lo que hice en el trabajo en Q1 (Jul-1 a Sep-30) y resulta que hice el trabajo de 30 personas (o 931 días) en los 61 días laborales que tuve (en realidad fueron menos por que me tome días libres)
¿Dónde guardas lo que sí funcionó al trabajar con IA para no tener que descubrirlo otra vez? Hoy les comparto mi Sistema de trabajo: cómo conecto instrucciones, una base de conocimiento y un tracker para darle continuidad al trabajo. info en tacosdedatos
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Want to experiment with on-device models but not sure how to get started? Our inspiration page has 100 prompts for building with Desert Ant models. Each prompt links to the SDK docs, so you can paste it into your coding agent and start building. desertant.com/inspiration/
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Todavía no sé si así se aprende mejor. No tengo datos que presumir, y para tenerlos necesito estudiantes. Mi curso de visualización de datos con agentes ya está en preventa en app.heymaestro.app/courses/d…
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Para revisar un gráfico, cuatro preguntas: ¿A dónde se va la vista primero? Si lo ves cinco segundos, sin explicación, ¿qué historia cuenta? ¿Qué aporta algo y qué es pura decoración? ¿Alguien de tu audiencia lo podría leer mal?
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Introducing... Interfaces that think A series exploring new UI interactions for the AI erea. Excited to kick off this series with episode 1 where I explore text and autocomplete
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Have I mentioned monologue is a team of 1 FTE and has raised $0? You can just do things now.
Introducing mono-1, our in-house dictation model, built to turn natural speech into text you can use. Against our previous API-based pipeline, mono-1 required about 55% fewer estimated edits and delivered finished dictation 3× faster by median API response time. Accurate speech recognition is the foundation of good dictation. But good dictation also needs to handle corrections, formatting, context, and writing preferences. mono-1 is the culmination of six months of development, production testing, and feedback from Monologue users—improving how Monologue recognizes your words, handles corrections, and formats your writing. More here: monologue.to/blog/introducin…
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Introducing mono-1, our in-house dictation model, built to turn natural speech into text you can use. Against our previous API-based pipeline, mono-1 required about 55% fewer estimated edits and delivered finished dictation 3× faster by median API response time. Accurate speech recognition is the foundation of good dictation. But good dictation also needs to handle corrections, formatting, context, and writing preferences. mono-1 is the culmination of six months of development, production testing, and feedback from Monologue users—improving how Monologue recognizes your words, handles corrections, and formats your writing. More here: monologue.to/blog/introducin…
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Jev + on-device models = results in seconds with no LLM in the loop. Quick demo app to show the possibilities. Drop in an audio file: Ear detects the language, Voz transcribes it and Redact removes PII. Then @typesafeai's Jev makes about 20 decisions in one call in milliseconds, and picks which of our on-device models to run. Voice memo to to-do list. Meeting to redacted transcript. Podcast to clips.
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chekos retweeted
I'm still exploring what I can do with Jev but I made this little app which does the following - talk about your day (or anything really) - audio gets transcribed to text - text is parsed for cues across 12 colours linked to an emotion [a logic I fed into this app for Jev to use] - a painting is drawn with code in JavaScript using the colours Jev thinks suits the transcript cues well - canvas has an underlying MIDI [utilises Tone.js] - watch your words turn into a painting which turns into a melody. App uses @typesafeai for Jev's colour + emotion inferences, @GeminiApp for audio transcription, @claudeai for the JavaScript painting code, @ChatGPT for front end UI refinement. sayhue.vercel.app
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