167 related articles

OpenAI's GPT-5.6 launches with Sawa, Terra, and Luna sub-models the same day as Musk's Grok 4.5, while Anthropic, Meta, and NVIDIA make their moves. A packed week of flagship AI launches.

A longtime user calls Gemini 3.1 Pro "a masterclass in empathetic conversing" — concise, context-aware, and intent-driven. We break down why empathy is becoming AI's new competitive frontier.

GPT 5.6 updates Codex with Sol/Terra/Luna model tiers, Ultra thinking mode, 350K context, and stronger autonomous loops. Full hands-on review of all core upgrades.

A Reddit user ran EQ tests on ChatGPT 5.5 and 5.6, covering meeting emotion ranking, chess-behavior judgment, and facial attractiveness. Version 5.6 shows clear gains in multimodal emotional understanding, but social common sense remains a core weakness.

Torn between Géron, Chollet, and Raschka? This article breaks down 4 classic ML books for self-learners aiming at finetuning and small language models (SLM), helping you find the best advanced path.

A Reddit post sparks debate: what happens when a user asks AI to "push guardrails to the limit"? An in-depth look at AI safety guardrails, jailbreaks, and content balance.

Ditch inefficient noise prediction and train character LoRAs by directly optimizing face similarity. Using the DRaFT differentiable reward method, training completes in 10-12 minutes on an RTX 4090, far outperforming traditional SFT. Includes open-source code.

In-depth analysis of AI Agent core principles: why LLMs need Agent technology, the evolution from Prompt to RAG to Agent, Agent Tuning methods, and enterprise cost evaluation to help you build enterprise-grade agent applications.

Gemini 3.5 Pro's latest delay sparks community debate. This article dives deep into the technical causes, safety review pressures, and expectation-management challenges behind frequent LLM delays.

OpenAI releases the GPT-5.6 series (Sol/Terra/Luna), with flagship Sol directly handling smaller model Luna's post-training—marking recursive AI self-improvement in practice. A deep dive into performance, cost, ChatGPT Work, and computer use design leaps.
Local Coding Agents in Practice: A Com…
An in-depth look at local coding agents—core concepts, advantages, and real challenges. Compare against Claude Code and learn to build a zero-subscription, private AI coding workflow with open-weight models.

The full GPT-5.6 model lineup is live. How can domestic developers access it at low cost via API relay stations? This article explains the principles, registration, token setup, client integration, and key risks.

OpenAI launches GPT-5.6 with three models — Sol, Terra, and Luna — plus ChatGPT Work, a new desktop app, and Hosted Sites. Codex now autonomously trains models.

An AI research engineer with 3 years of experience sent 50 applications to FAANG with zero replies. This article breaks down the hidden barriers of top-tech AI roles, the truth about LinkedIn ghost jobs, and the MLE vs. Research Engineer divide.

OpenAI releases GPT-5.6 and integrates Codex directly into ChatGPT, letting developers invoke code generation and debugging within conversations. A deep dive into the product logic and ecosystem impact.

OpenAI confirms GPT-5.6 as the preferred model for Microsoft Copilot 365, responding to "breakup rumors." A deep dive into the strategy, multi-model trends, and AI productivity commercialization.

OpenAI launches Build Week, a global developer event centered on Codex AI coding tool, featuring live sessions and community events to help developers ship ideas fast.

OpenAI launches the GPT-5.6 model family with cybersecurity as its biggest highlight. A deep analysis of GPT-5.6's differentiation, double-edged-sword effect, and enterprise strategy.

Tencent Hunyuan HY3 official version is open-sourced under Apache 2.0, priced as low as 1 yuan per million input tokens, with major gains in agents, reasoning, coding, and long context. On the same day, Meituan open-sourced its trillion-parameter LongCat 2.0.

Deep dive into DeepSeek-V4: 1.6T-parameter MoE, CSA+HCA hybrid attention, MHC & MUON optimizer. Inference FLOPs drop to 27% of V3.2, redefining open-source LLM SOTA.