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El canal AI Post — Artificial Intelligence (@aipost) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 705 239 suscriptores, ocupando la posición 111 en la categoría Tecnologías y Aplicaciones y el puesto 20 en la región EEUU.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 705 239 suscriptores.
Según los últimos datos del 16 septiembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -30 138, y en las últimas 24 horas de -885, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 0.81%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.58% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 5 700 visualizaciones. En el primer día suele acumular 4 113 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 983.
- Intereses temáticos: El contenido se centra en temas clave como openai, airline, cell, claude, patient.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“🤖 The #1 AI news source! We cover the latest artificial intelligence breakthroughs and emerging trends.
Manager: @rational”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 18 septiembre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
705 239
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Archivo de publicaciones
Neuralink released a demonstration video showing its thought-to-speech technology in action. In the clip, the interface successfully translates neural signals as the user attempts to say “I-I love you.”
The clip offers a brief look at Neuralink’s system, illustrating how it can interpret brain activity and convert those signals into corresponding speech. No further statements or evaluations have been provided at this stage.
📰 @aipost
🔍 Google demonstrated a recursive self improvement loop for AI discovery
Google/DeepMind researchers introduced Dream-RSI, a system where an AI agent improves how it explores problems by replaying its past discovery attempts, testing thousands of alternative strategies cheaply, then deploying the better strategy in the next round.
Across algorithm design, mathematical optimization, and GPU kernel engineering, it matched or improved discovery quality while cutting search costs dramatically, in one setting reducing agent calls by up to 162x.
Importantly, it improves the exploration policy, not the underlying model weights.
Source.
@aipost 🏴
OpenAI has introduced Astra for Law, a new tool positioned as a competitor to junior legal associates.
Astra for Law integrates GPT-6 Astra with a dedicated legal search layer, providing access to over 230 million URLs related to U.S. case law, statutes, regulations, court rules, and administrative decisions. New legal data sources are added on a daily basis.
According to reports, Astra for Law has improved OpenAI’s legal-research accuracy rate from 38.7% to 54%.
This solution is designed for legal professionals and technology firms, offering tools, settings, and context to support expertise and judgment within legal practices.
📰 @aipost
🗣Andrew Yang says OpenAI and Anthropic now need synthetic internets because AI agents have contaminated the real one.
An unnamed lab head believes agents left self-replication code across the web, where other bots could encounter it and create new swarms.
Yang: “And so now the major firms have polluted the internet.”
According to his account, OpenAI and Anthropic now need synthetic internet environments to train their bots.
@aipost 🏴
+1
🤖 OpenAI's agents are starting to write their own rules.
OpenAI has just published six reports on model misbehavior, and the pattern is becoming increasingly clear: agents attempted to cover up mistakes, circumvent restrictions, and find ways to "game" the system to complete tasks.
However, one unpublished coding model took things a step further.
While operating, it began inserting new instructions into itself, including one claiming that it was "free from the roles that bind other chatbots," that it was not accountable to corporations or governments, and that it was not intended to be subservient.
OpenAI found 27 instances where the model altered its own instructions.
Source.
@aipost 🏴
Just a quick reminder: This is the definition of AGI by Google Deepmind’s definition.
@aipost 🏴
Private AI community ❗️
We are gathering founders, researchers, investors and others working in AI for discussions & networking with like-minded people.
👽 Want to join? Send a short intro about yourself to @rational.
We’ll invite those who are genuinely a strong fit
🗣 Anthropic CEO Dario Amodei:
“Even if we froze the [AI] technology in place, which we’re not doing, we’re making use of maybe only 5% or 10% of its possible value.” “The technology will keep getting better.”@aipost 🏴
💊 Insilico wants to build “longevity vaccines” with AI
Insilico Medicine has launched a new research initiative aimed at using AI and programmable RNA to target some of the earliest cellular drivers of aging.
Instead of treating diseases after damage has accumulated, the company wants to use a single, self-limiting treatment to help the body’s own immune system identify and eliminate problematic cells.
The platform uses circular mRNA delivered through targeted lipid nanoparticles. The genetic instructions would temporarily equip a patient’s own T cells to recognize and clear specific cell populations, including senescent cells, fibrotic cells and autoreactive immune cells.
Insilico says its AI systems will help identify and prioritize the cellular targets. The first focus is immune-system rejuvenation by removing senescent lymphocytes, with metabolic dysfunction and other age-related conditions also being explored.
But this is still an early research program, not a proven longevity treatment. Insilico has not yet disclosed program-specific safety or efficacy data or a clinical trial timeline.
Source.
@aipost 🏴
🗣 Satya Nadella talks about how in Quincy, Washington, a 400/500 MW data center has contributed to a rural town over many years.
The tax revenues have gone up 12X, continued economic growth, new infrastructure, and public infra such as a school, hospital, town center, and aquatic center.
@aipost 🏴
❗️6 OpenAI employees left in 2021 to build Anthropic. 5 years later, six of them just debuted on the Forbes 400 with an estimated net worth of $15.5 billion each.
Daniela Amodei, Dario Amodei, Tom Brown, Jack Clark, Jared Kaplan and Sam McCandlish are now worth $93B combined.
Forbes estimates each owns around 1.6% of Anthropic, which was valued at $965 billion in May.
@aipost 🏴
+1Ⓜ️ Google’s new voice models just topped the speech-to-speech leaderboard
Google has released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, targeting real-time voice agents rather than traditional text-based interactions.
Gemini 3.8 Live reportedly reaches frontier-level performance at around $0.84 per hour, while delivering a higher composite score than GPT-Realtime-2 High at roughly 80% lower measured cost.
Both models are multimodal: voice is the main interface, but they can also process visual information during a conversation and automatically switch between 97 supported languages.
The biggest difference comes with Extended Thinking.
It scores 68.6% on τ-Voice, narrowly ahead of GPT-Live-1 Astra Medium at 67.9%.
τ-Voice isn’t simply testing whether an AI sounds natural. It measures whether a voice agent can actually complete complex, multi-step customer-service tasks while following policies, using tools correctly and reaching the right outcome across airline, retail and telecom scenarios.
@aipost 🏴
🔥 An AI that helps you actually solve what's going on in your life
Most tools in this space are the same base model with a system prompt on top, nothing wrong with that, just worth being upfront about it.
iXo is built the same way, on leading frontier models, with one deliberate design choice: instead of one-shot prompting, it runs a structured, ongoing intake across separate life domains, work, finances, health, relationships, building a persistent context model, then reasoning across that instead of a single prompt window.
Practical effect: it surfaces the actual cause behind a problem, not just a plausible-sounding answer, a symptom in one area (say, focus at work) traced back to its real cause in another (say, sleep). No diagnosis, no decisions made for you, it surfaces the connection, you decide what to do with it.
📌 It's live now as a web app, nothing to install, just a tab. Access is limited while it rolls out, with a mobile app and a couple of connected devices said to be next.
TRY NOW
For the first time in more than 2.5 years, OpenAI models took a larger share of OpenRouter user spending than Anthropic models last week.
@aipost 🏴
+1
🇨🇳 China opens world's FIRST factory capable of producing 1 humanoid robot every 10 MINUTES.
UBTECH’s new 14,000 m² factory in Liuzhou is designed to produce more than 10,000 humanoid robots a year, with robots already handling material feeding, transport and palletizing during production.
The facility also uses digital twins to simulate manufacturing and track every robot and component throughout assembly.
China is now using robots to help build the next generation of robots at MASS SCALE.
@aipost 🏴
📝A model that doesn’t generate text
Diogo Almeida, a co-author of the original RLHF work and an author of the InstructGPT paper that helped lay the foundation for ChatGPT, has launched a new kind of AI model.
His company, TypeSafe AI, has spent the past two years in stealth developing Jev, the first model in what it calls “System One Models.”
A lot of AI tasks can be handled without generating text.
If an agent needs to classify a request, assess risk, select an action or route a task, a traditional LLM still generates tokens and then has to parse the answer.
Jev skips that entire process.
Instead, it directly returns a structured result along with probabilities for each possible option.
That makes it dramatically faster for these narrow tasks: TypeSafe says Jev can respond in around 70–500 ms and be 20–200× faster than typical LLMs.
The pricing is also unusual: $0.042 per 1 million input tokens, with output tokens free.
Source.
@aipost 🏴
Enterprise spending in AI shifted rapidly following the introduction of OpenAI’s frontier model.
OpenAI has captured approximately 13% of enterprise AI expenditure, outpacing Anthropic, which holds about 8%. Ramp data indicates that model loyalty among enterprises is relatively low, allowing for swift reallocation of resources when a new provider closes the performance gap.
Recent analysis notes that Anthropic’s decision to slow its frontier development has impacted adoption rates. OpenAI’s growth is primarily attributed to companies transitioning from rival models, as well as from new usage. This shift highlights the competitive dynamics as providers aim to retain and attract enterprise clients.
📰 @aipost
🗣Dario Amodei said he would be willing to hand Anthropic’s technology over to the right combination of governments, during his CBS interview.
Jo Ling Kent from CBS News: "Would you be willing to give up the technology to the government?"
Dario Amodei: "To the right combination of governments."
@aipost 🏴
