Formerly Known as Captain Speaking

Mi nueva pantalla también tiene indicadores de niveles, velocidad, tiempo y distancia; mirando por la ventana; horas de aburrimiento y minutos de terror.

[Formerly Known as Captain Speaking @Proyect7010]

https://t.co/WIVtVOvx7e //

[Formerly Known as Captain Speaking @Proyect7010]

Cardióloga que me enseñaste a hacer RDL con técnica "como si cerrará la puerta del carro, gracias por todo y si a todo (tu sabes quién eres)

[Elena Chávez @luzelenachavez8]

Apenas ayer @Claudiashein le daba palmaditas en el hombro a @MarinadelPilar sin saber que ésta ya tenía todo un plan para traicionar a Andrés Manuel López Obrador, a ella y al movimiento morenista que la hizo gobernadora de Baja California. ¿Qué información dará para que la consideren en EU como informante?

Salvar su “pellejo” es lo que le importa a esta señora que ya siente como el gobierno de @realDonaldTrump se le acerca cada vez más para que sea juzgada por narcotráfico y lavado de dinero, entre otros delitos en una corte gringa.

Sabe que por más que Sheinbaum la cubra con su manto de falsa feminista, no le alcanzará para que no pague sus fechorías que le han costado a los bajacalifornianos tanto sufrimiento.

Este audio es revelador: traiciona a sus benefactores.

Deja al descubierto que en menos de seis años se hizo de tanto dinero que con facilidad puede pagar a unos de los abogados más caros: Michael Nadler, quien se encargará de negociar con los gringos su buena voluntad para delatar a sus jefes y a Mario Delgado que la ayudó a ganar la elección interna para ser gobernadora de un estado donde, además de narco, hay trata de personas, venta de niños, prostitución, desapariciones forzadas, homicidios y una corrupción insultante con la que pagará los honorarios de Nadler.

[Formerly Known as Captain Speaking @Proyect7010]

Que cagadero tienen en la salida a Tepic, pensé que era un accidentado con mil muertos y todo, solo un camión en la cuneta

[Zenith_Ai @Alam_coder]

🚨 Anthropic just dropped a 31-page prompting guide.

I distilled it into 9 practical prompt tips you can learn in under 60 seconds:

1️⃣ Name the output, not the task.

❌ "Review this" ✅ "Create a risk assessment table"

Be specific about what you want delivered.

2️⃣ Define the length upfront.

• Set word counts • Specify bullet counts • Add: "No filler. No recap. No preamble."

Constraints improve outputs.

3️⃣ Replace negatives with positives.

❌ "Don't be verbose" ✅ "Be concise and direct"

Tell AI what to do, not what to avoid.

4️⃣ Start with action verbs.

Skip: "Can you help me..."

Use: • Write • Draft • Analyze • Summarize

Clear instructions get faster results.

5️⃣ Trigger deeper reasoning.

End prompts with:

"Think before answering."

Better thinking often leads to better outputs.

6️⃣ Push beyond default quality.

Add:

"Go beyond the basics." "Polish this like a client-ready deliverable."

Raise the standard.

7️⃣ Teach AI your voice.

Provide 2–3 writing samples and say:

"Match the style of these examples."

Consistency compounds.

8️⃣ Control tool usage.

For research: "Use search and cite sources."

For speed: "Answer from training data only."

Be intentional.

9️⃣ State the goal first.

Start with:

Goal: [desired outcome]

Then define the audience and task.

A clear goal turns a prompt into a plan.

🔖 Save this for your next AI session. ♻️ Repost to help others write better prompts.
@Alamcoder

[Chesny @chesny]

Vale la pena guardar esta clase de Stanford.

1 hora y 44 minutos dedicados por completo a entender los modelos de lenguaje grandes desde cero.

No es el típico video corto de "Entiende ChatGPT en 10 minutos".

Es una clase real de CS229 que profundiza en la lógica subyacente.

Hoy en día, mucha gente usa la IA de forma intensiva, pero realmente no tiene ni idea de cómo funcionan estos modelos.

Cómo se generan los tokens.

Por qué el modelo predice la siguiente palabra.

Cuál es la diferencia entre entrenamiento e inferencia.

Por qué el contexto afecta el resultado.

Por qué la misma pregunta, planteada de forma diferente, puede arrojar resultados totalmente distintos.

No necesitas aprender todo esto hasta el punto de construir modelos tú mismo.

Pero si quieres usar la IA a largo plazo para escribir código, crear productos, generar contenido o hacer automatizaciones, al menos necesitas saber a grandes rasgos cómo funciona.

De lo contrario, es muy probable que termines viendo la IA como una herramienta mística.

Cuando funciona bien, piensas que es magia.

Cuando falla estrepitosamente, no tienes ni idea de dónde está el problema.

Este tipo de clase gratuita y pública vale mucho más la pena que pasar el tiempo viendo un montón de consejos fragmentados.

[Chesny @chesny]

https://t.co/GLxSdsSSX1

[Bober_smart @Bober_smart]

A 19-year-old student from China, Zhang Wei, developed an AI radar and sold it to Hong Kong for $550,000

He created it using Claude, spending just $20 and a month on development

He walked into the Hong Kong administration office with a flash drive and asked for just 5 minutes of their time. 30 minutes later, he walked out with a check for $550,000

The code, connected to a camera, detects speed in real time. If the speed exceeds the limit, Claude takes a video clip and identifies the owner by the car's license plate. The video and the fine are then automatically sent to the owner's email address

Unlike a conventional radar that only takes a photo and doesn't always work, this AI radar eliminates disputes because it captures video and makes the process fully autonomous by sending out the fines on its own

The article includes the ready-to-use configurations.

[Formerly Known as Captain Speaking @Proyect7010]

@GinieSigonney Es un barril volado, pero está mal hecho, cada barril pierde energía y va quedando más atrás. Ni un paletero los hace tan mal

[Formerly Known as Captain Speaking @Proyect7010]

Perra gente NAQUETES de mierda que no usa audífonos en el gym. No, pendejete, no! No nos interesa el partido!

[Formerly Known as Captain Speaking @Proyect7010]

Es imposible despreciar los suficiente a esta clase de negros.

[Derrick Evans @DerrickEvans4WV]

She says they are going around the airport in style.

She thinks this is cool.

Get your lazy butt up and walk across the airport like everyone else.

[Formerly Known as Captain Speaking @Proyect7010]

@NelsonMogaka_ Cardio

[Formerly Known as Captain Speaking @Proyect7010]

A estos simios son a los que estar domesticando cada que alguna tripulación llega con gripa y los pendejos no saben que no se puede volar así. Se los pides por escrito y se pandean. Pendejos y culeros

[Dr del pueblo guano del bienestar. @BaurodMF]

EzdeKe me duele Vien mucho no puedo Hir a traVajar azi

*Procede a indicarle una DEXAMETASONA Y UN C LISINA IM

[Formerly Known as Captain Speaking @Proyect7010]

Nomás no sueltan los 30000. Compran hasta con la cubeta

[Formerly Known as Captain Speaking @Proyect7010]

@EddyWarman Bueno, antes tener AMEX era un simbolo de status, hoy cualquier pelagatos tiene una y una consecuencia es eso; a un lado está la sala Beyond Banamex

[Formerly Known as Captain Speaking @Proyect7010]

Sigo sin entender, si se mueve 5 ticks, pierdo 1000usd, pero si fuera para ganar yo, 3000000ticks= 15usd

[Formerly Known as Captain Speaking @Proyect7010]

@JCFights Negras gringas, europeas comunes

[Formerly Known as Captain Speaking @Proyect7010]

@phavlovah Por lo general citaría a Kafka y Kundera, pero por el solo hecho de joder y presumir: Nikki Montana

[Millie Marconi @MillieMarconnni]

A self-taught Irish schoolteacher wrote a book in 1854 that almost nobody read for 80 years, until a 21-year-old MIT student picked it up and realized it could be used to design every computer in human history.

His name was George Boole. The book is called An Investigation of the Laws of Thought.

Boole was born in 1815 in Lincoln, England. His family was poor. He left school at 16 to support them. He taught himself Latin, Greek, French, German, and Italian.

Then he taught himself mathematics. By 19 he had opened his own school. By 24 he was publishing original papers in the Cambridge Mathematical Journal, competing with men who had spent decades inside the best universities in Britain.

He never had a degree. He never had a mentor. In 1849, Queen's College in Cork hired him as a professor anyway.

In 1854, he published his masterwork. What he built inside it was something nobody had attempted before at this scale. He turned logic into algebra.

Before Boole, logic was philosophy. You argued in sentences. You reasoned in paragraphs. It was powerful and completely impossible to automate, because there was no formal system underneath it, just language.

Boole stripped it down to arithmetic. He showed that every act of human reasoning could be reduced to operations on two values. True or false. One or zero. AND, OR, NOT. If both conditions are true, the result is true. If neither is, the result is false. Every judgment a human mind makes, every decision, every deduction, could be written as an equation following those rules.

Logicians read it. They found it interesting. Engineers building machines had never heard of it.

For 83 years, the book sat there.

Then in 1937, a 21-year-old MIT master's student named Claude Shannon was working on a thesis about electrical relay circuits. Switches that could be open or closed. Current that either flowed or didn't.

He read Boole and understood something nobody had connected before.

An open switch is a zero. A closed switch is a one. A circuit with two switches in series only carries current when both are closed. That is AND. A circuit with two switches in parallel carries current when either is closed. That is OR. Shannon proved that every possible logical relationship Boole had described could be physically built using wire and switches.

That single insight is the foundation of every computer ever made.

After Shannon, chip designers stopped thinking about electricity and started thinking about logic. Every transistor on every processor running right now is implementing a Boolean operation. Every if-statement in every codebase is Boolean logic. Every database query using AND or OR. Every neural network threshold that fires or doesn't fire. All of it is running the algebra of a self-taught schoolteacher from Lincoln who died 160 years ago.

The strangest part is what happened to Boole at the end.

He was walking to class in November 1864 when he got caught in a rainstorm. He lectured for hours in wet clothes. He went home sick. His wife, Mary, believed in homeopathic medicine and thought the cure should mirror the cause. She wrapped him in wet sheets and poured cold water over him repeatedly.

He died a few days later. He was 49.

He never saw a transistor. He never saw a circuit. He never saw a single physical machine run a single one of his rules.

His book is in the public domain. Free to download. Most engineers use the word Boolean dozens of times a week. Almost none of them know who they are saying.

The man whose logic runs inside every phone, every server, and every AI model on Earth died soaking wet in a small Irish town, 83 years before anyone figured out what he had actually built.

[Python Programming @PythonPr]

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