Ümit Yılmaz @umitcoding

Jensen Huang: AI is going to make poorly defined work much more valuable. Because that’s all humans will do. AI will handle everything else. So what is poorly defined work, and how do you get good at it? Defined work means given these inputs, produce this output. Write code that does X. Summarize this document. Calculate this metric. The goal is specified. The constraints are known. The evaluation criteria exist before you start. Poorly defined work means should we even build this feature? What market should we enter next? Is this candidate going to work out? Which of these three strategic directions is least wrong? There’s no right answer you can verify. There’s only judgment. AI is going to get freakishly good at defined work. Give Claude a spec and it’ll execute. Give GPT a rubric and it’ll score. The skill of translating well-defined problems into solutions is getting automated at 10x speed every 18 months. But AI can’t tell you what problem to solve in the first place. It can generate 50 options. It can’t tell you which one matters. That requires something AI fundamentally lacks: skin in the game. Stakes. Consequences you actually have to live with. So how do you get good at poorly defined work? You make irreversible decisions faster than feels comfortable. The skill is pattern recognition built through reps. You can’t build judgment by thinking about decisions. You build it by making them and eating the outcomes. You get comfortable with “I don’t know yet” and commit anyway. Defined work has the comfort of eventual correctness. Poorly defined work means moving while uncertain. The people who thrive here tolerate that discomfort instead of seeking premature closure. You build taste through volume. Taste is internalized judgment from thousands of micro-decisions. The designer who can feel when something is off made 10,000 design choices before. The PM who senses a bad roadmap decision lived through 100 launches. You seek roles where you own outcomes, not tasks. Task ownership is defined work. Outcome ownership forces you into the undefined space constantly. You can’t own revenue without deciding which features matter. The uncomfortable truth: most people’s entire careers have been defined work dressed up as judgment. They executed someone else’s strategy. They optimized someone else’s metrics. They never had to decide which metrics mattered. That’s about to become visible. Fast.

Rohan Paul @rohanpaul_ai

5 months ago

Jensen Huang told a Cambridge Union "Intelligence is about to be a commodity" For a long time, school and hiring treated “smart” as scarce, because fast recall and clean problem solving were hard to scale beyond the best individuals. AI has flipped that. Jensen explained

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Introducing quickarXiv Papers are often written in convoluted language that is hard to understand. We're fixing that. Swap arxiv → quickarxiv on any paper URL to get an instant blog with figures, insights, and explanations. Now extracted with DeepSeek OCR 🚀

We built a @baseapp Mini App and deployed it live during the @0xBaseTurkiye event! 🔥 Big shoutout to @KarogluGoktug for the mentorship and support throughout the event. Amazing community and lots of onchain building. Base ecosystem is growing fast — proud to be part of it! 💙⚡

PewDiePie went from Minecraft let's plays to building 10xGPU rigs, training 120B LLMs, distributed vLLM inference, coding webapps, RAGs, speech recognition pipelines, linux sysadmin.. Millions of kids are watching him compile CUDA now. 110M+ subs. WHAT AN ABSOLUTE LEGEND!!

Image uploads aren't magical. You can build it yourself on the cloud. Here, Manish goes over how to build an image hosting service with Node.js + Express, object storage, & deploy it on Sevalla. freecodecamp.org/news/build-and…

🚀 Your Personal AI Travel Designer Is Here! 🍁 Stop wasting hours planning trips. Qwen Chat Travel Planner crafts complete, day-by-day itineraries tailored JUST for you — powered by Amap, Fliggy APIs and Search. ✅ Recommends perfect hotels & transport routes ✅ Builds detailed schedules ✅ Adapts to your interests, pace & budget Travel smarter, not harder. ✈️🗺️ Try it now：chat.qwen.ai/?inputFeature=…

🚀 Introducing Qwen3-Omni — the first natively end-to-end omni-modal AI unifying text, image, audio & video in one model — no modality trade-offs! 🏆 SOTA on 22/36 audio & AV benchmarks 🌍 119L text / 19L speech in / 10L speech out ⚡ 211ms latency | 🎧 30-min audio understanding 🎨 Fully customizable via system prompts 🔗 Built-in tool calling 🎤 Open-source Captioner model (low-hallucination!) 🌟 What’s Open-Sourced? We’ve open-sourced Qwen3-Omni-30B-A3B-Instruct, Qwen3-Omni-30B-A3B-Thinking, and Qwen3-Omni-30B-A3B-Captioner, to empower developers to explore a variety of applications from instruction-following to creative tasks. Try it now 👇 💬 Qwen Chat: chat.qwen.ai/?models=qwen3-… 💻 GitHub: github.com/QwenLM/Qwen3-O… 🤗 HF Models: huggingface.co/collections/Qw… 🤖 MS Models: modelscope.cn/collections/Qw… 🎬 Demo: huggingface.co/spaces/Qwen/Qw…

TSLA up $69 to ~$420 as foretold in the prophecy

I'm excited to announce that @BEBischof and @HamelHusain will also join us for our HORNET.dev event at @SHACK15sf. The no-bs panel could become interesting. luma.com/2augnidh

You don’t need a soulmate. You just need a Apple MacBook Pro (14.2 inch, M4, 16GB, 512GB, macOS Sequoia, Space Black)

Introducing: Nvidia Pro Mode! Basically GPT-5 Pro, but for the new Nvidia open source model :) Pro Mode chains together up to 50 instances of the new Nemotron 9B model, enabling it to produce a better answer than one instance alone could create! Open source, link here:

Claude can now create and edit files. Turn conversations into Excel spreadsheets, documents, PowerPoint slide decks, and PDFs directly.

Imagine if ChatGPT highlighted every word it wasn't sure about. We built a streaming hallucination detector that flags hallucinations in real-time.

İstanbul’un dijital dönüşümünde öncü rol üstlenen, ulaşım ve ulaşım dışı alanlarda güvenli, yenilikçi ve yaşamı kolaylaştıran finansal teknoloji çözümleri geliştiren BELBİM, Türkiye Yapay Zekâ İnisiyatifi destekçileri arasında yer alıyor. Türkiye’deki yapay zeka ekosistemine verdikleri katkılarından dolayı BELBİM’e teşekkür ederiz TRAI Kurumsal Üyelik & İş Birliği"nin detayları hakkında daha fazla bilgi için: buff.ly/h0HvzdC #TRAI #ai h#yapayzeka #artificialintelligence

3 trillions tokens finely distilled from more than a petabyte of PDF files We’ve just released FinePDF, the latest addition to the Fineweb datasets

Introducing ClockBench, a visual reasoning AI benchmark focused on telling the time with analog clocks: - Humans average 89.1% accuracy vs only 13.3% for top model out of 11 tested leading LLMs - Similar level of difficulty to @fchollet ARC-AGI-2 and seemingly harder for the models than @hendrycks Humanity's Last Exam - Inspired by original insight by @PMinervini , @aryopg and @rohit_saxena

You can now run 100B parameter models on your local CPU without GPUs. Microsoft finally open-sourced their 1-bit LLM inference framework called bitnet.cpp: > 6.17x faster inference > 82.2% less energy on CPUs > Supports Llama3, Falcon3, and BitNet models

Caching (Redis, Memcached) What is Caching? Caching is the process of storing frequently accessed data in a temporary storage (cache) so future requests can be served faster. Instead of querying the database every time, the system retrieves data from the cache, reducing response time and server load. Why Caching is Important → Improves application performance. → Reduces load on the database. → Enhances scalability and user experience. → Useful in real-time applications where speed is critical. Redis Redis (Remote Dictionary Server) is an open-source, in-memory data store often used as a cache, database, and message broker. → Stores data in key-value pairs. → Supports complex data structures like lists, sets, and hashes. → Provides persistence options (data can be saved to disk). → Commonly used in session storage, leaderboards, and pub/sub systems. Advantages of Redis → Very fast (in-memory). → Rich data types and features. → Persistence support (RDB, AOF). → Suitable for real-time analytics. Memcached Memcached is a high-performance, in-memory caching system designed for simplicity and speed. → Stores data in key-value pairs. → Focuses only on caching (no persistence, fewer data structures). → Commonly used for caching database queries, HTML fragments, or session data. Advantages of Memcached → Simple and lightweight. → Extremely fast read/write operations. → Scales horizontally across multiple servers. Redis vs Memcached → Redis: Feature-rich, supports persistence and advanced data types. → Memcached: Lightweight, purely focused on caching. → Redis: Best for applications needing caching + extra functionality. → Memcached: Best for simple caching with minimal overhead. Real-World Examples → Redis: Storing user sessions in large-scale apps like Twitter. → Memcached: Caching product details on e-commerce sites for faster page loads. Download The Backend Ebook ( it covers everything above and more) codewithdhanian.gumroad.com/l/juuzy

Docker components explained

My dream to have a team like this