--- title: "A Brief Discussion on 2025 AI Trends" description: "A discussion on AI evolution trends for 2025, covering the MCP Protocol, AI Agents, open-source large models, and the impact of the NVIDIA DGX Spark personal AI supercomputer on the work of software engineers." canonical_url: "https://blog.markkulab.net/en/post/talk-about-ai-trend" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2025-06-10 01:00:35 +0800" category: "AI" tags: ["ai", "agent", "mcp", "llm", "nvidia", "open source"] language: "en" license: "CC BY 4.0" license_url: "https://creativecommons.org/licenses/by/4.0/" attribution: "when reusing or quoting, credit the author and link back to the original" --- # A Brief Discussion on 2025 AI Trends ## A Look at the Evolution of AI When we talk about the development of AI, we have to discuss its evolution. Deep Learning 1.0 > Large Language Models 2.0 > Embodied Intelligence 3.0 ![AI evolution](https://blog.markkulab.net/content/markku/posts/talk-about-ai-trend/images/ai-evolution-1.png) We are now in the third stage, and as developers, we should keep a close eye on the evolution of AI 3.0 technology, especially in the following two major directions: ## What to Keep an Eye On While I was away studying at a language school, the development of AI didn't stop for a moment. The following two technologies have rapidly gained prominence during this time and are worth a deep dive: ### **MCP (Model Context Protocol)** MCP is an open standard protocol proposed by Anthropic. It aims to provide a unified interface for Large Language Models (LLMs), enabling them to connect and interact with various external systems and tools. It's like the USB-C port for AI applications: a secure, standardized way for AI models to access external data and tools, further expanding their capabilities and application scenarios. For example: * Performing code reviews based on a company's coding standards * Checking documents or contracts against company documentation guidelines ### **AI Agent** An AI Agent is an intelligent system that combines Large Language Models with the ability to operate tools. It doesn't just respond to user input; it can understand tasks, plan steps, execute them autonomously, and even has memory and learning capabilities. I believe that in the future, AI Agents will gradually begin to observe their environment and become goal-oriented AIs with the ability to act, proactively completing tasks rather than just passively responding. ![AI agent](https://blog.markkulab.net/content/markku/posts/talk-about-ai-trend/images/ai-agent.png) ## [My Starting Point: Playing with Open-Source Large Models on a 4070 Super](https://blog.markkulab.net/category/ai/) In 2024, I got my hands on an **NVIDIA 4070 Super** graphics card and started trying to run open-source large language models at home. Although this card is considered a mid-to-high-end consumer card, it's limited by its VRAM, meaning it can only run smaller, "stripped-down" models like the **7B (7 billion parameter)** ones. For instance: * A 7B model can generally handle text generation. * A 13B model is barely usable for writing code. While this kind of graphics card is serviceable for running open-source models locally and offline, it's still a long way from being suitable for real commercial use or model training. The application of these consumer-grade cards is limited to small-scale scenarios, such as development testing, personal learning, and so on. ## Noteworthy Open-Source Frameworks and Models ### Agent Frameworks * LangChain Agents * N8N * CrewAI ### Open-Source Models * [Cosyvoice (Speech Synthesis Model)](https://www.youtube.com/watch?v=2cM1k0FjK0o) * [Llama 3-TAIDE-LX-8B-Chat-Alpha1](https://taide.tw/index/newsList/newsDetail/4b114181951853cb0195268c8ee544ed) ## The Turning Point: The Arrival of the Personal AI Supercomputer VRAM has always been an issue. That's why many people in mainland China are modding their graphics cards to increase memory. I think GPU companies are well aware that increasing VRAM on consumer cards could hurt sales of their high-end products. By creating a separate personal AI computer product line, they avoid their own products competing with each other. And so, on March 22, 2025, NVIDIA announced a revolutionary product at its GTC conference: the personal AI supercomputer, **[DGX Spark](https://www.nvidia.com/zh-tw/products/workstations/dgx-spark/)**. This device is equipped with the **GB10 superchip**, co-developed by NVIDIA and MediaTek. It boasts **128GB of memory** and is only about the size of an iPhone in length and width. Its eye-catching champagne gold finish is quite appealing. It's priced at approximately **NT$130,000** and is already available for pre-order. The launch of this machine is expected to **break through the VRAM bottleneck of traditional consumer or workstation graphics cards**. It can directly support large models, **paving the way for the accelerated development of AI Agents**. The DGX Spark is somewhat similar to Apple's "[Unified Memory Architecture](https://www.youtube.com/watch?v=iCJN28MsPh0&t=466s)," which allows for efficient memory sharing between different computing units. Although Apple's machines can also run larger models, the number of tokens they can generate in a response is still relatively low, limiting their practical flexibility. ## The Future of Software Engineering: From Writing Code to Training AI Agents When every company can deploy large language models in their own environment—not just for inference, but also for fine-tuning and training—the definition of a software engineer's job will change. In the past, software engineers primarily "maintained systems." In the future, their role will shift to "designing and managing AI agents," deeply integrating AI into various industries and completely transforming workflows and services. AI agents, with large language models at their core, combine functionalities like task planning, tool operation, and memory systems. Currently, most AI agents are reactive, but in the future, they are likely to become more proactive, capable of autonomously handling problems, making decisions, and taking action. --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/post/talk-about-ai-trend) License: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — when reusing or quoting, credit the author and link back to the original ### About the author **[Mark Ku](https://blog.markkulab.net/en/author/mark-ku)** — Software Solution Provider - 10+ years senior software engineer, now an AI Builder - Focused on large-platform architecture — North-American e-commerce, AI SaaS subscription billing - Combining AI Agents and automation to build evolvable product foundations ### Free tools built by the author All of these are free to use: - [Free PDF Sign Tool](https://blog.markkulab.net/en/tools/pdf-sign): Online PDF sign tool — draw, type, or upload a signature, then drag, resize, and download. Everything runs in your browser; nothing is uploaded. - [VS Code Refactory](https://blog.markkulab.net/en/tools/refactory): Refactory is a VS Code refactoring extension: 34 actions plus a 37-rule code-smell inspection layer with a Code Health dashboard, across 18 languages, backed by 534 tests. It learns your repo's conventions: where interfaces live, where DI is registered, whether 'use client' belongs. It ranks files by git churn × complexity so you know what to fix first, and hands any smell to the Claude Code already on your machine. Free to use, and your source never leaves your computer. - [DB-Kit Database Manager](https://blog.markkulab.net/en/tools/db-kit): DB-Kit is a lightweight, cross-platform database manager built with Tauri + Rust + React. Manage MySQL, MariaDB, PostgreSQL, SQL Server, Oracle, SQLite, MongoDB, Redis, Kafka, Elasticsearch and RabbitMQ from one consistent interface: passwords encrypted in the OS keychain, SSH tunnels, full CRUD, a visual query builder, stacked multi-statement result sets, cross-connection data transfer and compare/sync, Excel / CSV import & export, visualized execution plans, ER diagrams, scheduled backups, SQL stress testing with p50–p99 latency percentiles, a 15-rule SQL review engine, Kafka message browsing with monitoring & alerts, a bilingual UI (Traditional Chinese / English), a built-in AI assistant (natural-language SQL, AI review and tuning advice) and the dbk CLI. Free and open source (MIT), with installers for Windows, macOS and Linux. - [VS Code Super Mermaid](https://blog.markkulab.net/en/tools/super-mermaid): Super Mermaid is a VS Code extension for beautiful Mermaid diagrams out of the box: auto-colored live preview, mouse pan & zoom, high-res PNG / SVG export, 21 templates and multiple themes. Free and open source (MIT). - [React Super Mermaid](https://blog.markkulab.net/en/tools/react-super-mermaid): react-super-mermaid is an open-source React component library: render beautiful Mermaid diagrams with a single , with built-in colorful / sketch themes, pan & zoom, in-diagram search, and high-res SVG / PNG export. Lightweight, SSR-safe, fully typed. 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No sign-up, nothing uploaded to a server, and mermaid.live share links work as-is. - [React Intl Phone Number](https://blog.markkulab.net/en/tools/react-intl-phone-number): react-intl-phone-number is an open-source React component: framework-agnostic and antd-free, with E.164 in/out, a searchable flag / country-code dropdown, configurable validation levels (strict / mobile-strict / loose), themeable CSS, and i18n — phone logic powered by google-libphonenumber. Lightweight and fully typed. Free and open source (MIT). - [Uptime Kuma Cluster](https://blog.markkulab.net/en/tools/uptime-kuma-cluster): Turn single-node Uptime Kuma into a highly available cluster: OpenResty + Lua smart load balancing, shared MariaDB state, health checks and automatic failover, plus cluster-management REST APIs. One Docker Compose command to start. 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