For coding it is, but not for typical LLM outputs. DeepSeek is tied with GPT-5 on LM Arena and it was released in August.
CODE
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Open-source AI on Mac Studios: Cheaper, faster, and free alternative to ChatGPT
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Small companies could run DeepSeek-V3.2 on one of these souped-up Mac Studios instead of paying for dozens and dozens of ChatGPT licenses for employees. Open-source models are only about 6 months behind the proprietary models. And they’re free. Forever.
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Databricks IDE: Data Pipeline Authoring and Testing Tool
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The IDE for Data Engineering is everything you need to author and test data pipelines, directly inside the Databricks Workspace.
— Databricks (@databricks) 20 décembre 2025
The IDE is designed to improve productivity and debugging with features like dependency graphs, built-in data previews and execution insights.
Now… pic.twitter.com/VeW4MUkTlpThe IDE for Data Engineering is everything you need to author and test data pipelines, directly inside the Databricks Workspace. The IDE is designed to improve productivity and debugging with features like dependency graphs, built-in data previews and execution insights. Now
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8 RAG Architectures Every AI Engineer Must Know
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8 RAG architectures all AI Engineers should know:
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Building RAG Applications on AWS: Ingestion and Querying Stages
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Building a RAG app on AWS is simpler than you might think.
— Akshay 🚀 (@akshay_pachaar) 20 décembre 2025
Let me explain how you can achieve this using services you already know:
At its core, RAG follows a two-stage pattern: ingestion and querying.
Here's how you can implement each stage on AWS:
1️⃣ Ingestion: Turning raw… pic.twitter.com/UOTBpoUcpeBuilding a RAG app on AWS is simpler than you might think. Let me explain how you can achieve this using services you already know: At its core, RAG follows a two-stage pattern: ingestion and querying. Here's how you can implement each stage on AWS: Ingestion: Turning raw
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AI 2025 Breakthroughs: RL, Reasoning Models, and Future Paradigms
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Things move very very fast in AI. 2025 was a year of RL with verifiable rewards(RLVR), LLM ghosts/jagged intelligence, Cursor-like LLM apps, claude code/codex, vibe-coding, NanoBanana showing early glimpse of LLM promptable graphical interfaces(PGI, i just coined this lol), LLM reasoning models crushing olympiad competitions (maths, physics, code). Most altering releases tend to come early in a year, jan-feb, and then scaling-up and small fixes begin. Eagerly looking forward to new paradigm shifts. What will next NanoBanana look like, just bigger or new capabilities no one thought before? There are several stages of training now, RL(VR) being the most recent. What will be the RL successor? And continual learning, will it be fixed in 2026, or this is a problem we will live with for long? There are also world models, agents that actually work reliably in the wild for hours. Andrej Karpathy (@karpathy) x.com/i/article/200211463822… — https://nitter.net/karpathy/status/2002118205729562949#m
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Mini-SGLang: Simplified LLM Serving in 5000 Lines of Code
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vLLM has 100k+ lines of code. Mini-SGLang does the same core job under 5000 lines of code. this repo is designed to simplify modern LLM serving systems, offering a capable inference engine and a clear reference code for researchers and developers. 100% open-source.
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GPT-5.2 Codex excels on real-world codebases
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gpt-5.2 codex works great on big, real-world codebases
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Claude Web Features Converge with Claude Code Integration
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Haven't used Claude Web in a while… and I just saw that it has compacting now. It looks like Claude Code features are now converging onto Claude Web
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React2Shell: The Log4j Moment for Frontend Development
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#React2Shell is the #Log4j moment for front end development | InfoWorld https://
share.google/RzDD9PZ86zAotJ
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… #development #CyberSec #CyberAttack #OpenSource #100DaysOfCyberSecurity