116 related articles
Structured Information Extraction with…
Using Qwen 2.5 7B quantized locally to extract 60+ fields from insurance/financial contracts? Learn why it struggles and how task splitting, RAG, GBNF, and smarter chunking can fix it.

Is $200/month for AI Agents worth it? We break down credit consumption mechanics, tool tradeoffs, and ROI calculations for ChatGPT Pro, Claude Max, and more.

An ML engineer trained SmoLLM, a 109M-parameter LLaMA-style model from scratch for under $50. Full breakdown of architecture, training pitfalls, instruction tuning, and real-world performance.

Perplexity Max users find monthly credits slashed from 40,000 to 10,000 with no notice. We break down why, how Agent features drain credits, and what paid users should do.

A comprehensive guide to preparing for the National Mathematical Modeling Contest: covering the essence of modeling, judging rules, topic selection, AI usage guidelines, and a four-day schedule to boost your chances of winning.

The New York Times and other publishers accuse OpenAI of withholding key tools and datasets in the ChatGPT copyright lawsuit, filing a sanctions motion. A deep analysis of the Discovery dispute, AI training data copyright dilemmas, and implications for AI industry compliance.

Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.
Mesh LLM: A Practical Exploration of B…
Mesh LLM leverages the Rust P2P framework iroh to integrate compute from scattered nodes, exploring a viable path for decentralized LLM inference. This article analyzes its architecture, challenges, and prospects.

An in-depth breakdown of the fully automated AI writing workflow popular in web novel circles: from data-driven topic selection, book deconstruction and imitation, AI-trace removal, to one-click distribution and monetization. Efficiency tool or content bubble?

Perplexity's Comet browser faces user criticism over lagging model versions, stalled updates, and stability issues. A deep analysis of AI browser challenges.

Generative AI tools have flooded social media with AI-generated content, hitting LinkedIn hardest due to its professional nature. A deep dive into the causes, ecosystem impact, and solutions.

Alibaba bans Claude Code over security risks, sparking tech community debate. An in-depth analysis of data leakage risks with cloud AI coding tools and the rise of local AI deployment.
Embracing AI in the Classroom: A Teach…
One teacher chose not to ban AI but to co-create a classroom contract with students. This article examines the logic, contract design, and educational philosophy behind this teaching experiment.

Local LLM tool Ollama closes a $65M Series B, bringing total funding to $88M. With 9M developers and 85% of Fortune 500 having deployed internally, this deep dive explores why enterprises embrace local LLMs: compliance, Agent cost savings, and open-source ecosystem.

Why can a mini PC with unified memory run a 70B model while an RTX 4090 can't? A deep dive into the VRAM wall and unified memory architecture for smarter local AI hardware choices.

How did Ollama grow from a niche open-source project into developers' default choice for running local LLMs? This article breaks down its rise across product design, technical strategy, and ecosystem building.

A collection of 28 fully reproducible enterprise-grade AI Agent projects covering code debugging, financial analysis, customer service, and multi-agent collaboration—deployable even for beginners.

Players widely distrust Steam's AI disclosure labels, suspecting developers hide AI usage. We examine the three root causes and how the games industry can rebuild trust.

Google Search Console's new "platform properties" feature lets creators track which Google search terms drive traffic to Instagram, YouTube, and other social accounts — no standalone website required.

An Agent developer's three-round interview reveals why general-purpose Agents are a dead end for startups. The path forward: vertical Agents, domain context, and iteration speed as a moat.