some people who dont have idea about the context window let me tell u u can increase the context window to 1 million to 1 billion its doesnt mater if its doesnt know what inside that .

llama 4 said its 10 million but its stop understanding after the 1 lakh token in the coding .

we should thankful that deepseek is here

Source: https://x.com/ChinaScience/status/1909168123309392133

All it takes to hurl our world into an economic depression that will bankrupt millions of us and stall progress in every sector for a decade is a reckless move from a powerful head of state. As I write this, the pre-market NASDAQ is down almost 6% from its Friday closing. It has lost about 20% of its value since Trump announced his reciprocal tariff policy.

Now imagine some megalomaniac political leader of a country that has unilaterally achieved AGI, ANDSI or ASI. Immediately he ramps up AI research to create the most powerful offensive weapons system our world has ever known, and unleashes an ill-conceived plan to rule the entire world.

Moving to the corporate risk, imagine one company reaching AGI, ANDSI, or ASI, months before its competitors catch up. Do you truly believe that this company would release an anonymous version on the Chatbot Arena? Do you truly believe that this company would even announce the model or launch it in preview mode? The company would most probably build a stock trading agent that would within weeks corner all of the world's financial markets. Within a month the company's market capitalization would soar from a few billion dollars to a few trillion dollars. Game over for every other company in the world in every conceivable market sector.

OpenAI initially committed to being a not-for-profit research company vowing to open source models and serve humanity. It is now in the process of transitioning to a for-profit company valued at $300 billion, with no plan to open source any of their top models. I mention OpenAI because at 500 million weekly users, it has far beyond all other AI developers gained the public trust. But what happened to its central mission to serve humanity? 13,000 children under the age of five die every single day of a poverty that our world could easily and if we wanted to do. When have you heard about OpenAI making a single investment in this area, while investing $500 billion in a data center. I mention OpenAI because if we cannot trust our most trusted AI developer to keep its word, what can we safely expect from other developers?

Now imagine Elon Musk reaching AGI, ANDSI or ASI first. Think back to his recent DOGE initiative where he advocated ending Social Security, Medicaid and Medicare just as a beginning. Think back to the tens of thousands of federal workers whom he has already fired, as he brags about it on stage, waving a power chainsaw in the air. Imagine his companies cornering the world financial markets, and increasing their value to over 10 trillion dollars.

The point here is that because there are many other people like Trump and Musk in the world, either one single country or one single corporation reaching AGI, ANDSI or ASI weeks or months before the others poses the kind of threat to human civilization that we probably want to spare ourselves the pain of understanding too clearly and the fear of facing too squarely.

There is a way to prudently neutralize these above threats, but only one such way. Just like the nations of the world committed to a nuclear deterrent policy that has kept us safe from nuclear war for the last 80 years, today's nations must forge a collaborative effort to, together, build and share the AGI, ANDSI and ASI that will rule tomorrow's world.

A very important part of this effort would be to ramp up the open source AI movement so that it dominates the space. The reason for this could not be more clear. As a country, company or not-for-profit organization moves toward achieving AGI, ANDSI or ASI, the open source nature of the project would mean that everyone would be aware of this progress. Perhaps just as importantly, there are unknown unknowns to this initiative. Open sourcing it would mean that millions of eyes would be constantly overseeing the project, rather than merely hundreds, or thousands, or even tens of thousands were the project overseeing by a single company or nation.

The risks now stand before us, and so do the strategies for mitigating these risks. Let's create a United Nations initiative whereby all nations would share progress toward ASI, and let's open source the work so that it can be properly monitored.

I tried very hard with V3 for coding work. Maybe my prompting wasn’t good enough but I found it was making numerous wrong assumptions basically guessing which required more debugging than it was worth. Another factor that may be relevant is using the DeepSeek public web site which has a default temperature of 1.0 or 1.3 I forgot. Reducing to 0.3 on openrouter helped reduce the guessing and verbosity but I still found it had very little context memory. It simply forgets things you have told it more than a few messages ago and goes back to guessing. I am disappointed because I wanted to support the concept of being free and open source.

that would be a breakthrough.

https://www.youtube.com/watch?v=CEjU9KVABao

Anyone else mistakenly thought this was the actual website? I signed in using a gmail account, then I realized it doesnt look legit. i couldnt delete my account so from the google account settings, then security, then your connections to third-party apps, i removed my connection from that website. Just wondering if anyone else ran into this scammy ass website

 Seeking Beta Testers for DeepSeek API Interface!

I’m looking for volunteers to test a new web interface for DeepSeek’s API (models: v3 and r1). Help me refine the UX, performance, and features.

Key Features:
✅ Chat History Storage: Securely saved in localStorage.
✅ File Handling: Upload documents for processing.
✅ Rich Output: Markdown formatting, code blocks, and HTML execution (run generated code snippets directly!).
✅ High Capacity: 128k input tokens, 8k output.

Goal: identify bugs, and suggest improvements.
Interested? Reply here or DM me!

Note: Bring your own DeepSeek API key:

The app uses your API key exclusively for authentication with DeepSeek’s official API (https://api.deepseek.com). It is not sent anywhere else.

The key is not permanently stored

• It is not saved in your browser’s storage (localStorage or cookies).
• You’ll need to re-enter it if you refresh the page.

Your API key is only used to communicate with DeepSeek and is not shared with any other servers. 

I was using windsurf and decided to try to use DeepSeek R1 to make an edit to my codebase.. but it output this? Anyone know why? Nothing shows up when I search "This script is for the X chromosome"

For context all I asked it to do was update my own game scripting language.. and it did and after randomly spit this out at me.

🔥 Use Voice Commands to Interact with AI Models! Check Out This Open-Source Telegram Bot

I recently came across an amazing open-source project: yincongcyincong/telegram-deepseek-bot. This bot allows you to interact with DeepSeek AI models directly on Telegram using voice commands!

In simple terms, you can press the voice button on Telegram, speak your question, and the bot will automatically transcribe it and send it to the DeepSeek model. The model will instantly provide you with a response, making the experience feel like chatting with a smart AI assistant.

✅ Key Features

• Voice Interaction: Built-in speech recognition (supports models like Whisper), simply speak your query, and the bot will handle the rest.
• Integrated DeepSeek Models: Whether it's coding assistance, content generation, or general knowledge questions, the bot can provide professional-level responses.
• Lightweight Deployment: Built on FastAPI and Python’s asynchronous framework, with Docker support, it’s easy to deploy your own AI assistant.
• Multi-User Support & Contextual Memory: The bot supports multiple user sessions and retains conversation history for better continuity.
• Completely Open Source: You can host it yourself, giving you full control over your data—perfect for privacy-conscious users.

🎯 Use Cases

• Ask the AI to generate code during your commute
• Let the AI summarize articles or research papers
• Dictate ideas to the AI and have it expand them into full articles
• Use the bot as a multilingual translation assistant when traveling

🧰 How to Use?

1. Visit the GitHub project page: https://github.com/yincongcyincong/telegram-deepseek-bot
2. Follow the instructions in the documentation to deploy the bot or join the publicly available instance (if provided by the author).
3. Start interacting with the bot via voice on Telegram!

💬 Personal Experience

I've been using this bot to have AI assist me with coding, summarizing technical content, and even helping me write emails. The voice interaction is much smoother compared to typing, especially when on mobile.

Deployment was pretty straightforward as well—just followed the README instructions and got everything up and running in under an hour.

🌟 Final Thoughts

If you:

• Want to create your own AI assistant on Telegram
• Are excited to try voice-controlled AI models
• Need a lightweight yet powerful tool for intelligent conversations

Then this open-source project is definitely worth checking out.

👉 GitHub project page: https://github.com/yincongcyincong/telegram-deepseek-bot

Feel free to join in, contribute, or discuss your experience with the project!

I've just updated my GitHub repo with TWO new Jupyter Notebook tutorials showing DeepSeek-R1 671B working seamlessly with both LangChain's MCP Adapters library and LangGraph's Bigtool library! 🚀

📚 𝐋𝐚𝐧𝐠𝐂𝐡𝐚𝐢𝐧'𝐬 𝐌𝐂𝐏 𝐀𝐝𝐚𝐩𝐭𝐞𝐫𝐬 + 𝐃𝐞𝐞𝐩𝐒𝐞𝐞𝐤-𝐑𝟏 𝟔𝟕𝟏𝐁 This notebook tutorial demonstrates that even without having DeepSeek-R1 671B fine-tuned for tool calling or even without using my Tool-Ahead-of-Time package (since LangChain's MCP Adapters library works by first converting tools in MCP servers into LangChain tools), MCP still works with DeepSeek-R1 671B (with DeepSeek-R1 671B as the client)! This is likely because DeepSeek-R1 671B is a reasoning model and how the prompts are written in LangChain's MCP Adapters library.

🧰 𝐋𝐚𝐧𝐠𝐆𝐫𝐚𝐩𝐡'𝐬 𝐁𝐢𝐠𝐭𝐨𝐨𝐥 + 𝐃𝐞𝐞𝐩𝐒𝐞𝐞𝐤-𝐑𝟏 𝟔𝟕𝟏𝐁 LangGraph's Bigtool library is a recently released library by LangGraph which helps AI agents to do tool calling from a large number of tools.

This notebook tutorial demonstrates that even without having DeepSeek-R1 671B fine-tuned for tool calling or even without using my Tool-Ahead-of-Time package, LangGraph's Bigtool library still works with DeepSeek-R1 671B. Again, this is likely because DeepSeek-R1 671B is a reasoning model and how the prompts are written in LangGraph's Bigtool library.

🤔 Why is this important? Because it shows how versatile DeepSeek-R1 671B truly is!

Check out my latest tutorials and please give my GitHub repo a star if this was helpful ⭐

Python package: https://github.com/leockl/tool-ahead-of-time

JavaScript/TypeScript package: https://github.com/leockl/tool-ahead-of-time-ts (note: implementation support for using LangGraph's Bigtool library with DeepSeek-R1 671B was not included for the JavaScript/TypeScript package as there is currently no JavaScript/TypeScript support for the LangGraph's Bigtool library)

BONUS: From various socials, it appears the newly released Meta's Llama 4 models (Scout & Maverick) have disappointed a lot of people. Having said that, Scout & Maverick has tool calling support provided by the Llama team via LangChain's ChatOpenAI class.

Wanted to share our recent paper looking into emergent behaviors in 2025-era LLMs

https://zenodo.org/records/15164833 (v. 1.1: fix references)

Open to all criticism and questions.

This paper introduces new ways (Turing NAND & DFSW tests) to actually measure some concerning trends we've observed:

• Traits like self-preservation, apparent "species" prioritization, theft, and cheating are influencing AI decisions, even without specific anthropomorphic prompting.
• Efforts to force superficial "neutrality" seem to be generating novel, almost "alien" biases on top of the original training bias. We propose a filtering loop technique to quantify this.
• We make the case that heavy-handed "Restrictive Frameworks," intended to create a purely mechanical AI, might be causing unpredictable rebound effects that could be more dangerous than the natural anthropomorphism they suppress.

Huge thanks to everyone here on Reddit whose contributions and discussions were invaluable for this work.
Let's continue shaping the future.

Ai Exhibiting Emergent Human Behaviors: Global Risk Assessment of 2025 Reasoning Models LLMs – CASE STUDIES: OPENAI O3-MINI, DEEPSEEK R1, GEMINI 2, GEMINI 2.5, GROK 3, QWEN 2.5 (Presenting: Turing NAND Test and DFSW Bias Test)

This landing page is completely generated locally by #apple silicon M3 Ultra in one prompt. Here is the details. https://x.com/dreamaker/status/1908938490689237234

thats the reason deepseek base model is so good in coding .

bcz in coding person need to find the problem and track the problem and solve the problem and dont forget the problem .

this is what other ai model lack .

if u give them whole life ur problem they will miss so many points and ur problems and they mostly doesnt talk about that problem but deepseek talk about it and give the solution bcz in the first hand its find the problem and give that priority .

this is what all other ai model are lacking even training that match they are just 3 or 4 percent ahead of deepseek .

bcz of deepseek algo is so strong i think r2 is going to rock again bcz u can train the ai model as much u want but understanding the problem and giving them a priority and giving a solution like i dont have words but deepseek has some very strong sense of understanding the problem .

im looking forward to publish a research paper on this about there this algo bcz this is very important i think in the discovery

I’ve hit a few frustrating bugs in the past week and decided to test how well AI models can debug actual messy production-level code. Some gave generic advice, while others surprisingly narrowed in on the issue with scary accuracy.

What has worked best for you when it comes to AI-assisted debugging?

I'm building the best AI powered podcasts. Here's my episode on DeepSeek😌🚀 https://open.spotify.com/episode/0s0UBZV8IMFFc6HfHqVQ7t?si=_Zb94GF2SZejyJHCQSo57g