# Сопутствующие статьи по теме Research

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Research", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

From Understanding Skill to Learning How to Build Crypto Research Skill

This article explores the evolution and application of Agent Skill, a modular framework introduced by Anthropic in late 2025, which has become a foundational design pattern in the AI Agent ecosystem. Initially a tool to improve Claude's performance on specific tasks, it evolved into an open standard due to high developer adoption. Agent Skill functions like a "dynamic instruction manual" that AI can reference to perform tasks consistently without repetitive user prompting. It is built using a `skill.md` file containing metadata (name and description) and detailed instructions. The system operates through an on-demand loading workflow: the AI first scans lightweight skill metadata, matches the user's intent, then loads only the relevant skill's full instructions, optimizing token usage. Two advanced mechanisms enhance its functionality: - **Reference**: Conditionally loads external documents (e.g., a finance handbook) only when triggered by specific keywords, avoiding unnecessary context consumption. - **Script**: Executes external code (e.g., a Python script) without reading its content, enabling actions like file uploads with zero token cost. The article contrasts Agent Skill with Model Context Protocol (MCP), noting that MCP connects AI to data sources, while Skill defines how to process that data. For advanced use cases like crypto research, combining both is recommended: MCP fetches real-time data (e.g., blockchain info, news APIs), while Skill structures the analysis and output format. A practical example demonstrates building a crypto research agent using an `opennews-mcp` server. The Skill automates workflows like due diligence on new tokens (pulling Twitter data, news sentiment, KOL tracking) and real-time event monitoring (e.g., ZK-proof breakthroughs) to generate structured reports or trading alerts. This combination creates a powerful, automated research system tailored for Web3 analytics.

marsbit03/10 10:41

From Understanding Skill to Learning How to Build Crypto Research Skill

marsbit03/10 10:41

In a World of Dramatic Change, How Should Humanities Workers Better Use AI?

In a rapidly changing landscape, humanities professionals are increasingly turning to AI not as a magic solution, but as a practical tool integrated into their research, writing workflows. This guide outlines key principles for effectively using AI, moving beyond simple "prompts" to a systematic, controllable methodology. The approach is built on three core tenets: processes must be traceable, verifiable, and supervised; the user must remain in control; and the final output must be something the creator is willing to sign their name to. Key principles include: * **Treat AI as a workbench, not a wish-granter:** Clearly define tasks, audiences, and standards instead of making vague requests. * **You are the responsible agent:** Provide clear context, constraints, and executable steps. Dissatisfaction often stems from unclear instructions, not AI failure. * **Compare multiple models:** Different AIs have different strengths (writing, reasoning, coding); use them like a team. * **Manage expectations:** Assume AI has the knowledge level of a top undergraduate; provide examples and standards for specialized tasks. * **Break tasks into steps:** A white-box process of small, reliable steps is better than a single, error-prone black-box request. * **Industrialize first, then automate:** Define and structure your workflow into reproducible steps before assigning sub-tasks to AI. * **Anticipate AI's laziness:** Remove format barriers (e.g., clean text from PDFs/websites) to focus its effort on comprehension. * **Prioritize compression over expansion:** It's more reliable to condense large amounts of provided material than to ask AI to generate content from little context. * **Iterate on the pipeline, not the output:** Aim for a system that consistently produces good-enough drafts (e.g., 75/100) rather than manually perfecting each result. * **Generate quantity to find quality:** Request multiple versions (e.g., 5 summaries, 50 headlines) to combat mediocrity and discover excellent samples. * **Act as a head chef:** Provide clear feedback for revisions instead of rewriting the output yourself. The ultimate quality of work depends on **materials × taste**. AI enhances interaction with materials, but genuine research, unique sources, and cultivated judgment remain irreplaceable. The goal is to replace anxiety with practical skill by engineering tasks, making processes transparent, and integrating AI as a verb within a credible,署名-worthy creative process.

marsbit03/05 05:20

In a World of Dramatic Change, How Should Humanities Workers Better Use AI?

marsbit03/05 05:20

Sentient Foundation Officially Established: Committed to Promoting Open Source AGI to Ensure It Benefits All Humanity

Sentient Foundation has officially launched on February 10 as a nonprofit organization dedicated to ensuring that artificial general intelligence (AGI) remains open-source, decentralized, and aligned with human interests. It aims to prevent AGI from being monopolized by a few corporations and instead advocates for a future where this transformative technology benefits all of humanity. The foundation emphasizes that current powerful models like ChatGPT and Gemini are controlled by private entities, risking the concentration of power. It highlights the success of open-source alternatives like DeepSeek and Qwen, which demonstrate that open AI can compete with and even surpass closed models. Sentient Foundation will act as a neutral guardian of the open AGI ecosystem, focusing on key areas such as value alignment and safety, global research collaboration, developer support, inclusive governance, and public advocacy. It draws inspiration from historic open-source successes like Linux, Apache, and Android. Working alongside Sentient Labs, which leads technical research on AI frameworks and models, the foundation ensures that innovations serve the broader goal of open and aligned AGI. It invites researchers, developers, institutions, and policymakers to join its global efforts in promoting transparent, equitable, and beneficial AGI development.

marsbit02/20 01:41

Sentient Foundation Officially Established: Committed to Promoting Open Source AGI to Ensure It Benefits All Humanity

marsbit02/20 01:41

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