Palabra de Pomero

Ninguna biografía, solo yo... 😏

[Palabra de Pomero @bodoke1969]

@Punkecit0 Y si puedes dar el playlist ? 🤔

[Palabra de Pomero @bodoke1969]

@BanorteEscucha De nuevo, marque para que me dieran una explicación y solo dijeron que el banco se reserva el derecho de disminuir o aumentar el limite de crédito. Me da gusto que no reciban comisiones por el manejo de tarjeta de crédito, estoy viendo cambiarme de banco.

[Palabra de Pomero @bodoke1969]

@ErrorGramatica C 😌

[Palabra de Pomero @bodoke1969]

@UnPocoTende Así hasta yo, lo ayudó la cuerda 🤣

[Palabra de Pomero @bodoke1969]

@onlyskypace The 1 of course 🙋‍♂️

[Palabra de Pomero @bodoke1969]

@ErrorGramatica C 🙋‍♂️

[Palabra de Pomero @bodoke1969]

@ErrorGramatica 90 😌. Solo me faltó hacerme un tatuaje, y tengo ganas de hacerme uno, próximamente 🙋‍♂️

[Palabra de Pomero @bodoke1969]

@renabaddie_ 49 😌

[Palabra de Pomero @bodoke1969]

@SteveStuWill

[Nav Toor @heynavtoor]

🚨BREAKING: OpenAI published a paper proving that ChatGPT will always make things up.

Not sometimes. Not until the next update. Always. They proved it with math.

Even with perfect training data and unlimited computing power, AI models will still confidently tell you things that are completely false. This isn't a bug they're working on. It's baked into how these systems work at a fundamental level.

And their own numbers are brutal. OpenAI's o1 reasoning model hallucinates 16% of the time. Their newer o3 model? 33%. Their newest o4-mini? 48%. Nearly half of what their most recent model tells you could be fabricated. The "smarter" models are actually getting worse at telling the truth.

Here's why it can't be fixed. Language models work by predicting the next word based on probability. When they hit something uncertain, they don't pause. They don't flag it. They guess. And they guess with complete confidence, because that's exactly what they were trained to do.

The researchers looked at the 10 biggest AI benchmarks used to measure how good these models are. 9 out of 10 give the same score for saying "I don't know" as for giving a completely wrong answer: zero points. The entire testing system literally punishes honesty and rewards guessing.

So the AI learned the optimal strategy: always guess. Never admit uncertainty. Sound confident even when you're making it up.

OpenAI's proposed fix? Have ChatGPT say "I don't know" when it's unsure. Their own math shows this would mean roughly 30% of your questions get no answer. Imagine asking ChatGPT something three times out of ten and getting "I'm not confident enough to respond." Users would leave overnight. So the fix exists, but it would kill the product.

This isn't just OpenAI's problem. DeepMind and Tsinghua University independently reached the same conclusion. Three of the world's top AI labs, working separately, all agree: this is permanent.

Every time ChatGPT gives you an answer, ask yourself: is this real, or is it just a confident guess?

[Palabra de Pomero @bodoke1969]

@SolPavicich A bailar se ha dicho... 🥳🥳🥳

[Palabra de Pomero @bodoke1969]

@IGN Quiero horizon 3, no la película 😡

[Palabra de Pomero @bodoke1969]

@lola_rabbitx Leer 🙋‍♂️

[Palabra de Pomero @bodoke1969]

@sysxplore Mandrake 🙋‍♂️

[Palabra de Pomero @bodoke1969]

@laurita_cuerva 🙋‍♂️

[Palabra de Pomero @bodoke1969]

@OreoDeFresas Rusa 😏🙋‍♂️

[Palabra de Pomero @bodoke1969]

@eltarotde_agos 🙏🙏🙏

[Palabra de Pomero @bodoke1969]

@Taiytotsuki1 Más vale saber algo de todo, que todo de algo. 😏

[Palabra de Pomero @bodoke1969]

@livingdevops Living devops. Thanks 🙏