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TL;DR Vibe coding is great for quick hacks. Lasting software still needs real engineers. Vibe coding, the trend of using AI to generate code by describing what you want in natural language, has been hailed as the future of programming. Coined by AI pioneer Andrej Karpathy in early 2025, the term refers to “fully giv[ing] […]
Vibe Coding is Shoot-and-Forget Coding Read More »
How do you get GPT-5-level reasoning on real long-context, tool-using workloads without paying the quadratic attention and GPU cost that usually makes those systems impractical? DeepSeek research introduces DeepSeek-V3.2 and DeepSeek-V3.2-Speciale. They are reasoning-first models built for agents and targets high quality reasoning, long context and agent workflows, with open weights and production APIs. The
The AI coding landscape just got a massive shake-up. If you’ve been relying on Claude 3.5 Sonnet or GPT-4o for your dev workflows, you know the pain: great performance often comes with a bill that makes your wallet weep, or latency that breaks your flow.This article provides a technical overview of MiniMax-M2, focusing on its
MiniMax-M2: Technical Deep Dive into Interleaved Thinking for Agentic Coding Workflows Read More »
In this tutorial, we build an advanced multi-page interactive dashboard using Panel. Through each component of implementation, we explore how to generate synthetic data, apply rich filters, visualize dynamic time-series trends, compare segments and regions, and even simulate live KPI updates. We design the system step by step so we can truly understand how each
How do you keep synthetic data fresh and diverse for modern AI models without turning a single orchestration pipeline into the bottleneck? Meta AI researchers introduce Matrix, a decentralized framework where both control and data flow are serialized into messages that move through distributed queues. As LLM training increasingly relies on synthetic conversations, tool traces
Why do current audio AI models often perform worse when they generate longer reasoning instead of grounding their decisions in the actual sound. StepFun research team releases Step-Audio-R1, a new audio LLM designed for test time compute scaling, address this failure mode by showing that the accuracy drop with chain of thought is not an
How can an AI system learn to pick the right model or tool for each step of a task instead of always relying on one large model for everything? NVIDIA researchers release ToolOrchestra, a novel method for training a small language model to act as the orchestrator- the ‘brain’ of a heterogeneous tool-use agent https://arxiv.org/pdf/2511.21689
How can an AI system prove complex olympiad level math problems in clear natural language while also checking that its own reasoning is actually correct? DeepSeek AI has released DeepSeekMath-V2, an open weights large language model that is optimized for natural language theorem proving with self verification. The model is built on DeepSeek-V3.2-Exp-Base, runs as
AI applications rarely deal with one clean table. They mix user profiles, chat logs, JSON metadata, embeddings, and sometimes spatial data. Most teams answer this with a patchwork of an OLTP database, a vector store, and a search engine. OceanBase released seekdb, an open source AI focused database (under the Apache 2.0 license). seekdb is
Amar Subramanya will replace John Giannandrea after firm has struggled to catch up with AI rollouts by competitorsApple’s head of artificial intelligence, John Giannandrea, is stepping down from the company. The move comes as the Silicon Valley giant has lagged behind its competitors in rolling out generative AI features, in particular its voice assistant Siri.
Siri-us setback: Apple’s AI chief steps down as company lags behind rivals Read More »
