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 Microsoft CEO Satya Nadella has declared that Microsoft will become a completely new company, effective immediately.
The article <a href="https://the-decoder.com/microsoft-ceo-satya-nadella-promises-a-completely-new-microsoft/">Microsoft CEO Satya Nadella promises a completely new Microsoft</a> appeared first on <a href="https://the-decoder.com">THE DECODER</a>.

أعلن الرئيس التنفيذي لشركة مايكروسوفت، ساتيا ناديلا، أن الشركة ستخضع لتحول كبير، لتصبح كيانًا جديدًا تمامًا اعتبارًا من الآن. تمثل هذه التصريح لحظة حاسمة في تطور مايكروسوفت حيث تهدف إلى إعادة تعريف نموذج أعمالها وعملياتها.

El CEO de Microsoft, Satya Nadella, ha anunciado que la compañía se transformará significativamente, convirtiéndose en una entidad completamente nueva de inmediato. Esta declaración marca un momento crucial en la evolución de Microsoft mientras busca redefinir su modelo de negocio y operaciones.

Le PDG de Microsoft, Satya Nadella, a annoncé que l'entreprise subira une transformation significative, devenant une entité complètement nouvelle dès maintenant. Cette déclaration marque un moment clé dans l'évolution de Microsoft alors qu'elle vise à redéfinir son modèle commercial et ses opérations.

Microsoft CEO Satya Nadella has announced that the company will undergo a significant transformation, becoming a completely new entity effective immediately. This declaration marks a pivotal moment in Microsoft's evolution as it aims to redefine its business model and operations.

Microsoft CEO Satya Nadella promises a completely new Microsoft

حقق Google Gemini 3 إنجازًا كبيرًا من خلال تجاوز جميع معايير الذكاء الاصطناعي الحالية، بما في ذلك الأكثر تحديًا. يبرز هذا الإنجاز التقدم الذي حققته فريق الذكاء الاصطناعي في Google ويضع Gemini 3 كمتنافس رائد في مجال الذكاء الاصطناعي. يتم الاحتفال بهذا النجاح داخل مجتمع التكنولوجيا، مما يعكس التطور المستمر لتقنيات الذكاء الاصطناعي وقدراتها.

Google Gemini 3 ha logrado un hito significativo al superar todos los benchmarks de IA existentes, incluidos los más desafiantes. Este logro resalta los avances realizados por el equipo de IA de Google y posiciona a Gemini 3 como un competidor líder en el panorama de la inteligencia artificial. El éxito es celebrado dentro de la comunidad tecnológica, reflejando la evolución continua de las tecnologías de IA y sus capacidades.

Google Gemini 3 a atteint un jalon significatif en surpassant tous les benchmarks d'IA existants, y compris les plus difficiles. Cet accomplissement met en évidence les avancées réalisées par l'équipe d'IA de Google et positionne Gemini 3 comme un concurrent de premier plan dans le paysage de l'intelligence artificielle. Le succès est célébré au sein de la communauté technologique, reflétant l'évolution continue des technologies d'IA et de leurs capacités.

Google Gemini 3 has achieved a significant milestone by surpassing all existing AI benchmarks, including the most challenging ones. This accomplishment highlights the advancements made by Google's AI team and positions Gemini 3 as a leading contender in the artificial intelligence landscape. The success is celebrated within the tech community, reflecting the ongoing evolution of AI technologies and their capabilities.

Google Gemini 3 Just Killed Every AI Benchmark, Including the Hardest of All

Two weeks ago I read a line about tool use with Claude that stuck in my head. Paraphrased:

<blockquote>
Direct tool calls don’t really scale. 
Have the model write code that uses tools, and execute that code instead.
</blockquote>

At the same time, I was knee-deep in wiring a JavaScript execution environment into Contenox, my self-hosted runtime for deterministic, chat-native AI workflows.

So of course the thought was:

<blockquote>
What if I just let the model write the JavaScript and run it inside the runtime? 😅
</blockquote>

This post is about what happened when I tried exactly that.




<h2>
 
 
 What is Contenox?
</h2>

Very short version:

<blockquote>
Contenox is a self-hostable runtime for sovereign GenAI applications. 
It models AI behavior as explicit state machines, not opaque prompt chains.
</blockquote>

Some key properties:

Runtime, not a library, Explicit state machines, Chat-native interface, Vendor-agnostic &amp; self-hosted, written in go with lots of passion and zero tolerance for shortcuts




<h2>
 
 
 The experiment: ask it to fetch and summarize a TODO
</h2>

Once the JS execution hook was in place (a Goja VM with some globals exposed), I wired up a new state machine: 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>mux_input → moderate → generate_js → run_js → eval_js_result → (repair_js?) → answer
</code></pre>

</div>



Then I opened the Contenox chat UI and typed:

<blockquote>
Me: “Hey Contenox, fetch the TODO item from jsonplaceholder and summarize it.”
</blockquote>

The first attempt didn’t go as planned.

Instead of a neat summary, I got:

<blockquote>
Contenox: 
“I'm sorry, but it seems there was a problem fetching the TODO item from the provided URL due to an Internal Server Error (status code: 500). Unfortunately, I couldn't retrieve any data at this time. My apologies for the inconvenience!”
</blockquote>

I checked manually – Cloudflare was having a moment, JSONPlaceholder was behind it, and the request really was failing. Okay, fair. Long coffee break.

A bit later, I went back to the same chat and typed:

<blockquote>
Me: “okay let's try again now.”
</blockquote>

This time the reply was:

<blockquote>
Contenox: 
<code>Task titled "delectus aut autem" is incomplete. Nothing to summarize here.</code>
</blockquote>

Wait. It worked? Just like that?




<h2>
 
 
 Under the hood: LLM → JavaScript → tools → LLM
</h2>

Looking at the execution trace made it clear what happened.

<h3>
 
 
 1. Input is normalized and moderated
</h3>

The workflow starts with:

<ol>
<li><code>mux_input</code></li>
</ol>

<ul>
<li>
Parses the incoming chat history into a normalized <code>messages</code> array.

<ol>
<li><code>moderate</code></li>
</ol>
</li>
<li>Uses a small model to classify the input as safe/unsafe.</li>
<li>Output: <code>0</code> → safe → continue.</li>
</ul>

So far this is standard workflow stuff.

<h3>
 
 
 2. <code>generate_js</code>: the LLM writes JavaScript
</h3>

Next, the <code>generate_js</code> task runs with a system instruction like:

<ul>
<li>“You are an expert JavaScript agent for the Contenox runtime…”</li>
<li>“You must output JSON: { "code": "" }”</li>
<li>“You can use httpFetch, executeTask, executeTaskChain, …”</li>
<li>“Script must be synchronous, no async/await, and must return a JSON-serializable object.”</li>
</ul>

Given the chat history, the model produced something like this (simplified): 


<div class="highlight js-code-highlight">
<pre class="highlight json"><code>{
 "code": "var result;
var answer;
var meta = { steps: [] };

var todoUrl = \"https://jsonplaceholder.typicode.com/todos/1\";

// Step 1: Fetch the TODO item
meta.steps.push(\"Fetching TODO item from \" + todoUrl);
var fetchResponse = httpFetch(todoUrl);

if (!fetchResponse.ok) {
 answer = \"I couldn't access that item right now because there was some trouble with getting it. Please check the URL or try again later.\";
 meta.error = {
 message: \"HTTP fetch failed\",
 url: todoUrl,
 status: fetchResponse.status,
 statusText: fetchResponse.statusText,
 body: fetchResponse.body,
 error: fetchResponse.error
 };
 result = { answer: answer, meta: meta };
} else {
 var todoItem;
 try {
 todoItem = JSON.parse(fetchResponse.body);
 meta.raw = todoItem;
 } catch (e) {
 answer = \"I fetched the item, but I couldn't understand its format. It doesn't seem to be valid JSON.\";
 meta.error = {
 message: \"JSON parse error\",
 rawBody: fetchResponse.body,
 parseError: e.toString()
 };
 result = { answer: answer, meta: meta };
 }

 if (todoItem) {
 // Step 2: Summarize the TODO item using an LLM
 meta.steps.push(\"Summarizing TODO item with LLM\");
 var prompt = \"Summarize the following TODO item in a concise sentence: \" + JSON.stringify(todoItem);
 var summarizeTask = executeTask(prompt, \"gpt-4o-mini\", \"openai\");

 if (!summarizeTask.success) {
 answer = \"While I managed to fetch your TODO details, the summary tool had a hiccup and couldn't provide me with a concise sentence right now. We seem to be experiencing some temporary issues.\";
 meta.error = {
 message: \"LLM task execution failed\",
 task_id: summarizeTask.task_id,
 error: summarizeTask.error
 };
 result = { answer: answer, meta: meta };
 } else {
 answer = summarizeTask.response;
 meta.llmResponse = summarizeTask.response;
 result = { answer: answer, meta: meta };
 }
 }
}

result;"
}
</code></pre>

</div>



A few important details here:

<ul>
<li>
It encodes error handling:

<ul>
<li>If HTTP fails → user-friendly <code>answer</code>, raw error in <code>meta.error</code>.</li>
<li>If JSON parse fails → similar pattern.</li>
<li>If the inner LLM call fails → fallback message.</li>
</ul>


</li>

<li>It delegates the actual summarization to another model via <code>executeTask</code>.</li>

<li>It returns a structured <code>result</code> with both <code>answer</code> and <code>meta</code>.</li>

</ul>

This is not the model “calling tools” directly. It’s the model writing a program that calls tools.

<h3>
 
 
 3. <code>run_js</code>: execute the code in a sandbox
</h3>

The next task is <code>run_js</code>, which is just a Contenox <code>hook</code> that calls the JS sandbox: 


<div class="highlight js-code-highlight">
<pre class="highlight json"><code>{
 "name": "js_sandbox",
 "tool_name": "execute_js",
 "args": {
 "code": "{{.generate_js.code}}"
 }
}
</code></pre>

</div>



Inside the trace you can see:

<ul>
<li>An <code>httpFetch</code> log for the JSONPlaceholder URL.</li>
<li>A response with <code>status: 200 OK</code> when things finally worked.</li>
<li>
An <code>executeTask</code> log with the summarization prompt:

<ul>
<li><code>Summarize the following TODO item in a concise sentence: {"userId":1,"id":1,"title":"delectus aut autem","completed":false}</code></li>
</ul>


</li>

</ul>

The sandbox result looked roughly like: 


<div class="highlight js-code-highlight">
<pre class="highlight json"><code>{
 "ok": true,
 "result": {
 "answer": "Task titled \"delectus aut autem\" is incomplete.",
 "meta": {
 "llmResponse": "Task titled \"delectus aut autem\" is incomplete.",
 "raw": {
 "userId": 1,
 "id": 1,
 "title": "delectus aut autem",
 "completed": false
 },
 "steps": [
 "Fetching TODO item from https://jsonplaceholder.typicode.com/todos/1",
 "Summarizing TODO item with LLM"
 ]
 }
 },
 "logs": [ ... ],
 "code": "var result; ..."
}
</code></pre>

</div>



<h3>
 
 
 4. <code>eval_js_result</code>: success or retry?
</h3>

Now comes the evaluator:

<ul>
<li>It receives a description of the JS sandbox output.</li>
<li>
The system prompt is very strict:

<ul>
<li>If <code>ok</code> is true and there is a non-empty <code>result.answer</code> → respond with <code>success</code>.</li>
<li>Otherwise → respond with <code>retry</code>.</li>
</ul>


</li>

</ul>

On the successful run, it answered: 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>success
</code></pre>

</div>



So the workflow does not go into <code>repair_js</code> or <code>run_js_retry</code>. Happy path.

<h3>
 
 
 5. <code>answer</code>: extract the final user message
</h3>

The final task, <code>answer</code>, is intentionally boring:

<ul>
<li>System prompt: “You are a purely extractive post-processor. Do NOT invent content. Just surface the best existing <code>answer</code> field.”
</li>
<li>
It gets:

<ul>
<li>First run (<code>run_js</code> result).</li>
<li>Second run (<code>run_js_retry</code>), if any.</li>
</ul>


</li>

<li>

Selection rule:

<ul>
<li>Take the last non-empty <code>answer</code> you see.</li>
<li>Output it verbatim.</li>
</ul>


</li>

</ul>

In our case it found: 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>Task titled "delectus aut autem" is incomplete.
</code></pre>

</div>



And that’s exactly what Contenox replied in chat.




<h2>
 
 
 Why this is interesting (to me, at least)
</h2>

What I originally set out to build:

<blockquote>
A runtime for deterministic, observable GenAI workflows. 
Tasks, transitions, hooks – all explicit and replayable.
</blockquote>

What I accidentally stumbled into:

<blockquote>
A multi-model, self-orchestrating agent pattern, 
where LLMs write code that uses tools, and the runtime executes and evaluates that code.
</blockquote>

The pattern looks like this:

<ol>
<li>
Planner LLM (<code>generate_js</code>)</li>
</ol>

<ul>
<li>Reads user intent + history.</li>
<li>Emits JavaScript that calls <code>httpFetch</code>, <code>executeTask</code>, <code>executeTaskChain</code>, hooks, etc.</li>
</ul>

<ol>
<li>
Execution environment (<code>run_js</code> in Goja)</li>
</ol>

<ul>
<li>Deterministic execution of that JS.</li>
<li>Full logs of every HTTP call, every inner LLM call, every step.</li>
</ul>

<ol>
<li>
Controller LLM (<code>eval_js_result</code>)</li>
</ol>

<ul>
<li>Looks at the sandbox result.</li>
<li>Decides: is this good enough? Retry? Repair?</li>
</ul>

<ol>
<li>
Repair LLM (<code>repair_js</code>, if needed)</li>
</ol>

<ul>
<li>Gets the previous code + error output.</li>
<li>Writes a fixed version of the JS.</li>
</ul>

<ol>
<li>
Answer LLM (<code>answer</code>)</li>
</ol>

<ul>
<li>Doesn’t “reason” at all.</li>
<li>Just extracts the final <code>answer</code> text safely.</li>
</ul>

All of that is expressed as an explicit state machine in Contenox.

No hidden loops, no undocumented retries, no magic glue code inside some SDK. It’s all visible in the workflow graph and trace.




To me, that’s the exciting part:

<blockquote>
You don’t have to choose between “boring deterministic workflows” and “fancy agents”. 
You can build the agent on top of deterministic workflows. 
And everything stays **self-hosted, inspectable, and auditable if you want.
</blockquote>

يتناول المقال تجربة تم فيها السماح لنموذج ذكاء اصطناعي بكتابة كود جافا سكريبت داخل بيئة مستقلة تُدعى كونتينوكس. يتأمل الكاتب في مفهوم يتعلق باستخدام الأدوات في الذكاء الاصطناعي، مقترحًا أن النماذج يجب أن تولد كودًا لاستخدام الأدوات بدلاً من إجراء مكالمات مباشرة. تم اختبار هذا النهج من خلال تنفيذ كود جافا سكريبت الذي تم إنشاؤه داخل بيئة كونتينوكس، بهدف تحسين كفاءة سير العمل في الذكاء الاصطناعي.

El artículo discute un experimento en el que se permitió a un modelo de IA escribir código JavaScript dentro de un entorno autónomo llamado Contenox. El autor reflexiona sobre un concepto relacionado con el uso de herramientas en IA, sugiriendo que los modelos deberían generar código para utilizar herramientas en lugar de realizar llamadas directas. Este enfoque se probó ejecutando el JavaScript generado dentro del entorno Contenox, con el objetivo de mejorar la eficiencia de los flujos de trabajo de IA.

L'article traite d'une expérience où un modèle d'IA a été autorisé à écrire du code JavaScript au sein d'un environnement autonome appelé Contenox. L'auteur réfléchit à un concept concernant l'utilisation des outils en IA, suggérant que les modèles devraient générer du code pour utiliser des outils plutôt que d'effectuer des appels directs. Cette approche a été testée en exécutant le JavaScript généré dans l'environnement Contenox, visant à améliorer l'efficacité des flux de travail en IA.

The article discusses an experiment where an AI model was allowed to write JavaScript code within a self-hosted runtime called Contenox. The author reflects on a concept regarding tool usage in AI, suggesting that models should generate code to utilize tools instead of direct calls. This approach was tested by executing the generated JavaScript within the Contenox environment, aiming to enhance the efficiency of AI workflows.

I Let an LLM Write JavaScript Inside My AI Runtime. Here’s What Happened

Caterpillar Inc. was always an unlikely winner in the artificial intelligence craze. It makes the bulk of its money selling the equipment like yellow earth movers that has made it a stalwart of American industry.

تظهر شركة كاتربيلر كجهة غير متوقعة في قطاع الذكاء الاصطناعي، حيث تُعرف أساسًا بتصنيع الآلات الثقيلة مثل آلات الحفر. تاريخيًا، كانت الشركة تركز على المعدات الصناعية التقليدية، مما يجعلها أقل توافقًا مع الاتجاهات التكنولوجية المدفوعة بالذكاء الاصطناعي التي اجتذبت العديد من القطاعات الأخرى. على الرغم من الاهتمام المتزايد بالذكاء الاصطناعي، لا يزال النشاط الرئيسي لشركة كاتربيلر متجذرًا في الآلات المادية، مما قد يحد من جاذبيتها في مشهد تكنولوجي سريع التطور.

Caterpillar Inc. se ha presentado como un jugador improbable en el sector de la inteligencia artificial, siendo principalmente conocida por la fabricación de maquinaria pesada como las excavadoras. La compañía ha estado históricamente enfocada en equipos industriales tradicionales, lo que la hace menos alineada con las tendencias tecnológicas impulsadas por la IA que han cautivado a muchos otros sectores. A pesar del creciente interés en la IA, el negocio principal de Caterpillar sigue anclado en la maquinaria física, lo que podría limitar su atractivo en un paisaje tecnológico en rápida evolu…

Caterpillar Inc. se présente comme un acteur improbable dans le secteur de l'intelligence artificielle, étant principalement connu pour sa fabrication de machines lourdes telles que les pelles mécaniques. L'entreprise s'est historiquement concentrée sur l'équipement industriel traditionnel, ce qui la rend moins alignée avec les tendances technologiques axées sur l'IA qui ont captivé de nombreux autres secteurs. Malgré l'intérêt croissant pour l'IA, le cœur de métier de Caterpillar reste ancré dans la machinerie physique, ce qui pourrait limiter son attrait dans un paysage technologique en évol…

Caterpillar Inc. has emerged as an unlikely player in the artificial intelligence sector, primarily known for its manufacturing of heavy machinery such as earth movers. The company has historically focused on traditional industrial equipment, making it less aligned with the AI-driven technology trends that have captivated many other sectors. Despite the growing interest in AI, Caterpillar's core business remains rooted in physical machinery, which may limit its appeal in the rapidly evolving tech landscape.

Caterpillar’s Lone Bear Says Machinery Maker Is No AI Darling

<a href="https://www.techspot.com/news/110306-microsoft-explains-how-windows-11-become-agentic-os.html" target="_blank"><img src="https://www.techspot.com/images2/news/ts3_thumbs/2025/11/2025-11-18-ts3_thumbs-d01.jpg" width="800" height="560" style="padding: 15px 0" title="Microsoft explains how Windows 11 will become an agentic OS whether you like it or not" /></a> Windows president Pavan Davuluri recently described the future of Windows as an agentic operating system, where AI bots and large language models handle the user's commands on files and computing tasks. Critics mostly greeted the idea with scorn, cursing, and frustration over the "bug-ridden slop pile" the OS currently is.... <a href="https://www.techspot.com/news/110306-microsoft-explains-how-windows-11-become-agentic-os.html">Read Entire Article</a>

وصف رئيس شركة مايكروسوفت، بavan دافولوري، خطط ويندوز 11 للتطور إلى ما يسميه 'نظام تشغيل وكيل'. ستتضمن هذه التحويلة دمج روبوتات الذكاء الاصطناعي ونماذج اللغة الكبيرة لإدارة أوامر المستخدم ومهام الحوسبة. ومع ذلك، تم استقبال هذا الإعلان بسخرية وانتقادات من المستخدمين الذين يشعرون بالإحباط من الحالة الحالية لنظام التشغيل، الذي يصفونه بأنه مليء بالأخطاء.

El presidente de Microsoft, Pavan Davuluri, ha descrito los planes para que Windows 11 evolucione hacia lo que él llama un 'sistema operativo agente'. Esta transformación implicará la integración de bots de IA y modelos de lenguaje para gestionar los comandos y tareas informáticas del usuario. Sin embargo, el anuncio ha sido recibido con escepticismo y críticas por parte de los usuarios, que están frustrados con el estado actual del sistema operativo, que describen como plagado de errores.

Le président de Microsoft, Pavan Davuluri, a décrit les projets de Windows 11 pour évoluer vers ce qu'il appelle un 'système d'exploitation agentique'. Cette transformation impliquera l'intégration de bots IA et de modèles de langage pour gérer les commandes des utilisateurs et les tâches informatiques. Cependant, cette annonce a été accueillie avec scepticisme et critiques de la part des utilisateurs frustrés par l'état actuel du système d'exploitation, qu'ils décrivent comme rempli de bogues.

Microsoft's president, Pavan Davuluri, has outlined plans for Windows 11 to evolve into what he describes as an 'agentic operating system.' This transformation will involve the integration of AI bots and large language models to manage user commands and computing tasks. However, the announcement has been met with skepticism and criticism from users who are frustrated with the current state of the operating system, which they describe as plagued by bugs.

Microsoft explains how Windows 11 will become an agentic OS whether you like it or not

Although Black Friday is still two weeks away, you can find great Nintendo Switch and Switch 2 deals now. I've collected the best from Walmart, Best Buy, and more.

مع اقتراب يوم الجمعة السوداء بعد أسبوعين، تتوفر بالفعل عروض مبكرة على أجهزة نينتندو سويتش وسويتش 2. تقدم متاجر كبيرة مثل وول مارت وبيست باي أكثر من 20 عرضًا، مما يوفر للمستهلكين فرصة لتوفير المال على منتجات الألعاب الشهيرة قبل موسم التسوق للعطلات.

A medida que se acerca el Black Friday en dos semanas, ya están disponibles ofertas anticipadas en las consolas Nintendo Switch y Switch 2. Grandes minoristas como Walmart y Best Buy están ofreciendo más de 20 ventas, brindando a los consumidores la oportunidad de ahorrar en productos de videojuegos populares antes de la locura de compras navideñas.

À l'approche de Black Friday dans deux semaines, des offres anticipées sur les consoles Nintendo Switch et Switch 2 sont déjà disponibles. Des détaillants majeurs comme Walmart et Best Buy proposent plus de 20 ventes, offrant aux consommateurs l'occasion d'économiser sur des produits de jeu populaires avant la ruée des achats de vacances.

As Black Friday approaches in two weeks, early deals on Nintendo Switch and Switch 2 consoles are already available. Major retailers like Walmart and Best Buy are offering over 20 sales, providing consumers with an opportunity to save on popular gaming products ahead of the holiday shopping rush.

Best early Black Friday Nintendo Switch deals 2025: 20+ sales out early

<A HREF="https://substack.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.MstA6dhKs3CLxJgLSEpyVK_D4Oz9SmcjeXKNnqEDzIg?"><IMG VSPACE="4" HSPACE="4" BORDER="0" ALIGN="RIGHT" SRC="http://www.techmeme.com/251118/i47.jpg"></A>
<A HREF="http://www.techmeme.com/251118/p47#a251118p47" TITLE="Techmeme permalink"><IMG WIDTH=11 HEIGHT=12 SRC="http://www.techmeme.com/img/pml.png" STYLE="border:none;padding:0;margin:0;"></A> Alex Heath / <A HREF="https://sources.news/">Sources</A>: 
<A HREF="https://substack.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.MstA6dhKs3CLxJgLSEpyVK_D4Oz9SmcjeXKNnqEDzIg?">Q&amp;A with Demis Hassabis on Gemini 3, spending most of his research time on world models, fitting the entire Google Search index into Gemini, AI bubble, and more</A>&nbsp; &mdash;&nbsp; Demis Hassabis was noticeably relaxed when he joined our virtual call from London.&nbsp; &mdash;&nbsp; It was the day before the release of Gemini 3 &hellip;

ناقش ديميس هاسابيس، المؤسس المشارك لشركة ديب مايند، تقدم نموذج جيميني 3، أحدث نموذج للذكاء الاصطناعي من جوجل، مشددًا على قدراته في نمذجة العالم ودمج كامل فهرس بحث جوجل في النظام. تناول المخاوف بشأن فقاعة الذكاء الاصطناعي وأبرز إمكانيات النموذج في تحسين تفاعلات المستخدمين وتوفير معلومات أكثر دقة. تعكس أفكار هاسابيس التزامًا بدفع حدود تكنولوجيا الذكاء الاصطناعي ودمجها في التطبيقات اليومية.

Demis Hassabis, cofundador de DeepMind, discutió los avances de Gemini 3, el último modelo de IA de Google, enfatizando sus capacidades en modelos del mundo y la integración de todo el índice de búsqueda de Google en el sistema. Abordó las preocupaciones sobre la burbuja de la IA y destacó el potencial del modelo para mejorar las interacciones con los usuarios y proporcionar información más precisa. Las ideas de Hassabis reflejan un compromiso por llevar la tecnología de IA a nuevos límites y su integración en aplicaciones cotidianas.

Demis Hassabis, co-fondateur de DeepMind, a discuté des avancées de Gemini 3, le dernier modèle d'IA de Google, en mettant l'accent sur ses capacités en modélisation du monde et l'intégration de l'ensemble de l'index de recherche de Google dans le système. Il a abordé les préoccupations concernant la bulle de l'IA et a souligné le potentiel du modèle à améliorer les interactions avec les utilisateurs et à fournir des informations plus précises. Les réflexions de Hassabis reflètent un engagement à repousser les limites de la technologie IA et son intégration dans les applications quotidiennes.

Demis Hassabis, co-founder of DeepMind, discussed the advancements of Gemini 3, Google's latest AI model, emphasizing its capabilities in world modeling and fitting the entire Google Search index into the system. He addressed concerns about the AI bubble and highlighted the model's potential to enhance user interactions and provide more accurate information. Hassabis's insights reflect a commitment to pushing the boundaries of AI technology and its integration into everyday applications.

Q&A with Demis Hassabis on Gemini 3, spending most of his research time on world models, fitting the entire Google Search index into Gemini, AI bubble, and more (Alex Heath/Sources)

<h1>
 
 
 Sector HQ Weekly Digest - November 17, 2025
</h1>

Who's shipping vs who's just talking? Here's this week's AI industry intelligence.

<h2>
 
 
 🏆 Top 10 Companies
</h2>

<ol>
<li>
OpenAI - Score: 442385.7 | 343 events this week</li>
<li>
Anthropic - Score: 266113.1 | 51 events this week</li>
<li>
Amazon - Score: 135242.8 | 22 events this week</li>
<li>
Nvidia - Score: 128360.7 | 161 events this week</li>
<li>
Google - Score: 111135.8 | 125 events this week</li>
<li>
Microsoft - Score: 95559.7 | 99 events this week</li>
<li>
Meta - Score: 78015.6 | 61 events this week</li>
<li>
Apple - Score: 64936.3 | 94 events this week</li>
<li>
Tesla - Score: 41242.1 | 12 events this week</li>
<li>
AMD - Score: 40235.9 | 43 events this week</li>
</ol>

<h2>
 
 
 📈 Biggest Movers
</h2>

<ul>
<li>↑ Sony jumped 277 positions to #58</li>
<li>↑ Stability AI jumped 183 positions to #78</li>
<li>↑ Bytedance jumped 143 positions to #68</li>
<li>↑ Scale AI jumped 122 positions to #66</li>
<li>↑ Palantir jumped 107 positions to #17</li>
</ul>

<h2>
 
 
 🚨 Hype Gap Alerts
</h2>

No high hype alerts this week

<h2>
 
 
 📊 Key Insights
</h2>

<ul>
<li>Total companies tracked: 100</li>
<li>Total events this week: 1317</li>
<li>Average activity per company: 13.2 events</li>
</ul>

<h2>
 
 
 💡 What This Means
</h2>

The AI industry continues to evolve rapidly. Companies that ship consistently rise in our rankings, while those focused on hype alone get flagged by our Hype Gap detector.

Methodology: Our leaderboard tracks real product releases, funding events, partnerships, and market traction - not just PR and social media buzz.




Want real-time updates? Check out the live leaderboard at <a href="https://sectorhq.co" rel="noopener noreferrer">sectorhq.co</a>

Track specific companies and get instant alerts when they move in the rankings.

<h2>
 
 
 Tags
</h2>

<h1>
 
 
 AI #ArtificialIntelligence #MachineLearning #TechIndustry #Startups #AILeaderboard
</h1>

تسليط الضوء على أحدث التطورات في صناعة الذكاء الاصطناعي في نشرة قطاع HQ الأسبوعية بتاريخ 17 نوفمبر 2025، مع التركيز على أداء الشركات الرائدة. تتصدر OpenAI القائمة برصيد 442385.7 و343 حدثًا، تليها Anthropic وAmazon. كما يشير التقرير إلى تحركات كبيرة، حيث قفزت Sony 277 مركزًا في الترتيب، مما يعكس الطبيعة الديناميكية للقطاع.

El Digest semanal de Sector HQ del 17 de noviembre de 2025 destaca los últimos desarrollos en la industria de la IA, centrándose en el rendimiento de las principales empresas. OpenAI lidera con una puntuación de 442385.7 y 343 eventos, seguido de Anthropic y Amazon. El informe también señala movimientos significativos, con Sony saltando 277 posiciones en el ranking, reflejando la naturaleza dinámica del sector de la IA.

Le Digest hebdomadaire du Secteur HQ du 17 novembre 2025 met en lumière les derniers développements de l'industrie de l'IA, en se concentrant sur la performance des principales entreprises. OpenAI est en tête avec un score de 442385,7 et 343 événements, suivi d'Anthropic et d'Amazon. Le rapport note également des mouvements significatifs, Sony ayant grimpé de 277 positions dans le classement, reflétant la nature dynamique du secteur de l'IA.

The Sector HQ Weekly Digest for November 17, 2025, highlights the latest developments in the AI industry, focusing on the performance of top companies. OpenAI leads with a score of 442385.7 and 343 events, followed by Anthropic and Amazon. The report also notes significant movements, with Sony jumping 277 positions in the rankings, reflecting the dynamic nature of the AI sector.

Sector HQ Weekly Digest - November 17, 2025

<img width="1536" height="1024" src="https://the-decoder.com/wp-content/uploads/2025/11/openai_microsoft_partner.png" class="attachment-full size-full wp-post-image" alt="" style="height: auto; margin-bottom: 10px;" decoding="async" />
 According to Techcrunch and blogger Ed Zitron, new internal documents outline how much money is moving between OpenAI and Microsoft. The documents suggest that the cost of simply running OpenAI's models is enormous. Based on these figures, a profitable OpenAI still seems far off.
The article <a href="https://the-decoder.com/leaked-finances-hint-that-openais-inference-may-be-swallowing-its-revenue/">Leaked finances hint that OpenAI&#039;s inference may be swallowing its revenue</a> appeared first on <a href="https://the-decoder.com">THE DECODER</a>.

تكشف الوثائق الداخلية الأخيرة عن تفاصيل مالية مهمة حول عمليات OpenAI، مما يشير إلى أن التكاليف المرتبطة بتشغيل نماذجها كبيرة. تشير التقارير من Techcrunch والمدون إد زيتورن إلى أن ربحية OpenAI لا تزال بعيدة المنال، حيث قد يكون العبء المالي قد أرهق قدراتها على توليد الإيرادات.

Documentos internos recientes revelan detalles financieros significativos sobre las operaciones de OpenAI, indicando que los costos asociados con la ejecución de sus modelos son sustanciales. Informes de Techcrunch y del bloguero Ed Zitron sugieren que la rentabilidad de OpenAI sigue siendo esquiva, ya que la carga financiera podría estar abrumando sus capacidades de generación de ingresos.

Des documents internes récents révèlent des détails financiers significatifs sur les opérations d'OpenAI, indiquant que les coûts associés à l'exécution de ses modèles sont considérables. Les rapports de Techcrunch et du blogueur Ed Zitron suggèrent que la rentabilité d'OpenAI reste insaisissable, car le fardeau financier pourrait submerger ses capacités de génération de revenus.

Recent internal documents reveal significant financial details about OpenAI's operations, indicating that the costs associated with running its models are substantial. Reports from Techcrunch and blogger Ed Zitron suggest that OpenAI's profitability remains elusive, as the financial burden may be overwhelming its revenue generation capabilities.

Leaked finances hint that OpenAI's inference may be swallowing its revenue

<img width="2096" height="1182" src="https://the-decoder.com/wp-content/uploads/2025/11/gemini-3_model-blog_header-dark.webp" class="attachment-full size-full wp-post-image" alt="" style="height: auto; margin-bottom: 10px;" decoding="async" fetchpriority="high" />
 Gemini 3 Pro debuts with major gains in logic, multimodality, and speed, along with a new agent platform that hints at where Google wants AI to go next.
The article <a href="https://the-decoder.com/analysts-say-google-now-leads-the-ai-performance-race-with-gemini-3-pro/">Analysts say Google now leads the AI performance race with Gemini 3 Pro</a> appeared first on <a href="https://the-decoder.com">THE DECODER</a>.

أعلن المحللون أن جوجل أصبحت الآن رائدة في أداء الذكاء الاصطناعي مع إطلاق نموذج Gemini 3 Pro. يتميز هذا النموذج بتحسينات كبيرة في المنطق والتعددية والسرعة، بالإضافة إلى منصة جديدة تشير إلى الاتجاه المستقبلي لجوجل في تكنولوجيا الذكاء الاصطناعي.

Los analistas han declarado a Google como líder en rendimiento de IA con la introducción de Gemini 3 Pro. Este nuevo modelo muestra avances significativos en lógica, multimodalidad y velocidad, junto con una nueva plataforma de agentes que indica la dirección futura de Google en la tecnología de IA.

Des analystes ont déclaré que Google est désormais le leader en performance d'IA avec le lancement de Gemini 3 Pro. Ce nouveau modèle présente des avancées significatives en logique, multimodalité et rapidité, ainsi qu'une nouvelle plateforme d'agent qui indique la direction future de Google en matière de technologie IA.

Analysts have declared Google as the leader in AI performance with the introduction of Gemini 3 Pro. This new model showcases significant advancements in logic, multimodality, and speed, alongside a new agent platform that indicates Google's future direction in AI technology.

Analysts say Google now leads the AI performance race with Gemini 3 Pro

<img width="960" height="540" src="https://the-decoder.com/wp-content/uploads/2025/11/Anthropic-Nivida-Microsoft-Logos-2025.png" class="attachment-full size-full wp-post-image" alt="Logos of Anthropic, Microsoft and Nvidia next to each other on a white background" style="height: auto; margin-bottom: 10px;" decoding="async" />
 Microsoft, Nvidia, and Anthropic have unveiled a set of new strategic partnerships valued at 45 billion dollars.
The article <a href="https://the-decoder.com/microsoft-nvidia-and-anthropic-close-45-billion-dollar-deal/">Microsoft, Nvidia and Anthropic close 45 billion dollar deal</a> appeared first on <a href="https://the-decoder.com">THE DECODER</a>.

أعلنت مايكروسوفت وإنفيديا وأنتروبيك عن شراكة استراتيجية كبيرة بقيمة 45 مليار دولار. تهدف هذه الشراكة إلى تعزيز تطوير ونشر تقنيات الذكاء الاصطناعي المتقدمة، مما يضع الشركات في طليعة صناعة الذكاء الاصطناعي. يعكس هذا الاتفاق اتجاهًا متزايدًا من الشركات التكنولوجية الكبرى للاستثمار بكثافة في قدرات الذكاء الاصطناعي لدفع الابتكار والحفاظ على المزايا التنافسية.

Microsoft, Nvidia y Anthropic han anunciado una asociación estratégica significativa valorada en 45 mil millones de dólares. Esta colaboración tiene como objetivo mejorar el desarrollo y la implementación de tecnologías avanzadas de inteligencia artificial, posicionando a las empresas a la vanguardia de la industria de la IA. El acuerdo refleja una tendencia creciente de las grandes empresas tecnológicas a invertir fuertemente en capacidades de IA para impulsar la innovación y mantener ventajas competitivas.

Microsoft, Nvidia et Anthropic ont annoncé un partenariat stratégique majeur d'une valeur de 45 milliards de dollars. Cette collaboration vise à améliorer le développement et le déploiement de technologies avancées en intelligence artificielle, plaçant les entreprises à l'avant-garde de l'industrie de l'IA. Cet accord reflète une tendance croissante des grandes entreprises technologiques à investir massivement dans les capacités d'IA pour stimuler l'innovation et maintenir des avantages concurrentiels.

Microsoft, Nvidia, and Anthropic have announced a significant strategic partnership valued at $45 billion. This collaboration aims to enhance the development and deployment of advanced artificial intelligence technologies, positioning the companies at the forefront of the AI industry. The deal reflects a growing trend of major tech firms investing heavily in AI capabilities to drive innovation and maintain competitive advantages.

Microsoft, Nvidia and Anthropic close 45 billion dollar deal

<img width="1527" height="946" src="https://the-decoder.com/wp-content/uploads/2025/09/thinking_machines_ca_illustration.png" class="attachment-full size-full wp-post-image" alt="" style="height: auto; margin-bottom: 10px;" decoding="async" fetchpriority="high" />
 Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, is looking to raise up to five billion dollars in new funding, according to The Information.
The article <a href="https://the-decoder.com/thinking-machines-lab-reportedly-seeks-up-to-5-billion-dollars-in-new-funding/">Thinking Machines Lab reportedly seeks up to 5 billion dollars in new funding</a> appeared first on <a href="https://the-decoder.com">THE DECODER</a>.

تسعى مختبرات التفكير الآلي، التي أسستها ميرا موراتى، المديرة التقنية السابقة لشركة OpenAI، لجمع ما يصل إلى خمسة مليارات دولار من التمويل الجديد. وقد تم الكشف عن هذه المعلومات من قبل The Information، مما يسلط الضوء على الأهداف المالية الطموحة للشركة بينما تهدف إلى توسيع عملياتها وتأثيرها في قطاع الذكاء الاصطناعي.

Thinking Machines Lab, fundado por la ex-CTO de OpenAI, Mira Murati, está buscando recaudar hasta cinco mil millones de dólares en nueva financiación. Esta información fue revelada por The Information, destacando los ambiciosos objetivos financieros de la empresa mientras busca expandir sus operaciones e influencia en el sector de la inteligencia artificial.

Thinking Machines Lab, fondé par l'ancienne CTO d'OpenAI, Mira Murati, cherche à lever jusqu'à cinq milliards de dollars de nouveaux financements. Cette information a été révélée par The Information, mettant en lumière les objectifs financiers ambitieux de l'entreprise alors qu'elle vise à étendre ses opérations et son influence dans le secteur de l'intelligence artificielle.

Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, is reportedly seeking to raise up to five billion dollars in new funding. This information was disclosed by The Information, highlighting the company's ambitious financial goals as it aims to expand its operations and influence in the artificial intelligence sector.

Microsoft CEO Satya Nadella promises a completely new Microsoft

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