Tech Lead at @mango 👕 Sharing real-world tech and AI stuff Founder of sidebmusic.app · yizihanzi.app · ichiji.app
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I don’t trust AI companies much, but I trust Zuckerberg even less
Muse, your personal agent, now has voice and real-time video. You can have long conversations and Muse will work in the background and get things done for you as you're talking. We're also bringing Muse to glasses so you can talk hands-free throughout the day.
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Y como con el Kit Digital, se vienen empresas aprovechandose de ser Agente Digitalizador, para cobrar autenticas burradas por hacer una API que llame a ChatGPT en una tarde.
Hoy presentamos el Plan IA360 para un despliegue responsable de la Inteligencia Artificial.
Un plan con acciones concretas a desarrollar en los proximos 12 meses para que España aproveche las oportunidades que la IA ofrece a nuestra economía.
Poniendo en el centro la seguridad ciudadana, la confianza y la protección de los más vulnerables, empezando por los menores.
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What are you planning to build this weekend?
Are you going to try Jev, or keep working on your current projects?
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AI is going through a small revolution right now with the arrival of Jev, a new type of model created by TypeSafe AI, founded by Diogo Almeida, a former OpenAI employee.
🔸 And the interesting part?
Jev is NOT an LLM.
🔸 So what makes it different?
Jev is not designed to generate text. It is designed to make structured, probabilistic decisions inside software.
A simple way to think about it:
An LLM is someone you ask to think and answer.
Jev is someone you give several options to and ask to decide.
Example: customer support.
Imagine a user says:
“You charged me twice this month and I want my money back.”
With an LLM:
Message
↓
Generate an explanation about the issue
↓
Interpret / parse the answer
↓
Route it to Billing
With Jev:
Message
↓
Which department?
Billing → 97%
Support → 2%
Sales → 1%
↓
Billing
No generated explanation is needed.
Just a structured decision.
🔸 So why is this interesting?
⚡ Much faster
Jev does not generate a response token by token like an LLM. It returns a structured decision directly.
For example, videogames.
Instead of asking an LLM:
“What should the character do?”
You define the possible actions:
← → ↑ ↓ A B
And the model decides which one to execute.
💸 Much cheaper for decisions at scale
If your system needs to make millions of small decisions, calling GPT or Claude for every single one can become expensive.
TypeSafe currently advertises pricing of around $42 per billion input tokens.
🎯 Constrained outputs by construction
This is probably one of the most interesting parts.
Instead of hoping the model returns exactly the JSON, action or value your software expects, the possible outputs are defined beforehand.
The model chooses from the allowed options.
That can mean:
→ more predictable outputs
→ easier integrations
→ less parsing
→ fewer invalid responses
→ smaller hallucination surface
→ more deterministic behaviour
🔸 Does Jev replace LLMs?
No. They solve different problems.
Models like Jev become interesting when you need to classify, route, choose, rank or trigger actions.
Have you had a chance to try it yet? What use cases can you think of??
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Seba Lopez 💻 retweeted
I'm 31.
Software engineer at Mango and a solo founder in my free time.
I love building things, music, traveling, and studying Japanese.
From Andalucía, Spain 🇪🇸
Looking to connect with more founders, builders, indie hackers, and software engineers 💻
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Mi tio el que no sabe ni usar el Word cuando descubre ChatGPT
Si vuestro trabajo depende de teclear frente a un ordenador, estáis jodidos. Pasado mañana sobráis.
Hace un par de semanas empecé a probar en serio las nuevas inteligencias artificiales en mi teléfono y me di cuenta de que hemos abierto una puerta a otra dimensión.
Esto es revolucionario y la gente no es consciente de la velocidad a la que avanza.
Los agentes de IA van a sustituir a miles de personas en los próximos 4 años.
El que hace atención al cliente está sentenciado.
El que coge teléfonos en un call center, también.
No creo que las empresas hagan una escabechina despidiendo a todo el mundo mañana.
Lo que va a pasar será mucho más silencioso:
• Congelar las nuevas contrataciones.
• Mantener a los perfiles senior apoyados por una IA.
• Dejar de contratar perfiles junior porque ya no tienen sentido.
Hoy, con un buen senior y un par de herramientas sacas el trabajo de todo un departamento.
Esta revolución no avisa y se llevará por delante a los menos preparados.
Mis hijos me preguntan a menudo hacia dónde tirar con su futuro y mi consejo siempre es el mismo:
Haced lo que os guste, pero que dependa de vuestras manos.
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The other day, a developer friend disagreed with me when I said AI already codes better than 99% of developers
What do you think?
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Looking to connect with people building in:
🍽️ SaaS
🚀 Tech
🧠 AI
📱 Product Development
🔥 apps
💻 Devs
Time to promote. Drop what you working on 👇
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It’s crazy how years of reputation can be destroyed in just two years by poor leadership and bad decisions.
Numbers matter, but reputation is one of the most valuable assets a company has.
As confirmed earlier through our official channels, in mid-June of this year, we unexpectedly received notice from PlayStation Studios that they would cancel the PHYSINT project. PHYSINT is an important project both to me personally and to KOJIMA PRODUCTIONS. Determined to keep the project alive, we have spent the last three months searching tirelessly for a new partner. In the course of seeking advice and pursuing negotiations with people across many fields, we found in XBOX a partner with whom we share a common vision for the future, and we have decided to team up with them once again. Please rest assured that development of PHYSINT, our genre-defining action-espionage title, is ongoing and will continue moving forward.
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What’s up with gaining 120k+ followers from just 7 posts?
I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.
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This is the biggest AI news of the year so far
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
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