algorithmswithpeter
@legitalgorithmswithpeter • 38,700 subscribers
Videos
🤯 If APIs already exist, why do we need MCP? The answer: APIs are built for developers. MCP helps AI agents discover and use tools automatically! 💻 API vs MCP: 🔹 API → Developers define how to interact with services. 🔹 MCP → AI agents discover available tools at runtime. 🔹 Tools → Actions AI can perform. 🔹 Resources → Data AI can access. 🔹 Prompts → Reusable instruction templates. 🚀 Think of MCP as USB-C for AI. One standard connecting AI apps to thousands of tools! ⚠️ MCP doesn’t replace APIs. It usually works on top of them. 💬 Have you built your own MCP server yet? YES or NO? #MCP #APIs #AIAgents #ArtificialIntelligence #TechExplained
algorithmswithpeter125,600 次观看 • 1 天前
🚀 Want to become an AI Engineer in 2026? Stop watching tutorials and start building! 🔥 5 REAL projects to add to your portfolio: 1️⃣ Production-Ready RAG System → Hybrid search, reranking & citations. 2️⃣ AI Agent + MCP Server → Build agents that use real tools and execute tasks. 3️⃣ Fine-Tune an LLM → Train open models using LoRA or QLoRA. 4️⃣ Self-Host an LLM → Deploy models with vLLM and measure performance. 5️⃣ AI Evaluation Pipeline → Monitor accuracy, latency, costs & security. 💡 Don’t just build demos. Deploy your projects, measure results and showcase them on GitHub! 💬 Which project are you building first: 1, 2, 3, 4 or 5? #AIEngineering #ArtificialIntelligence #LLM #MachineLearning #BuildInPublic
algorithmswithpeter28,500 次观看 • 2 天前
🤯 Your computer can’t calculate 0.1 + 0.2 correctly. And a similar rounding error once contributed to the deaths of 28 soldiers. Here’s why. 💻 Computers store numbers in binary, not decimal. Just like 1/3 becomes 0.3333… forever, numbers like 0.1 have repeating binary representations. IEEE 754 floating-point numbers have limited precision, so the computer stores the closest representable value instead. That’s why in languages like Python and JavaScript: 0.1 + 0.2 !== 0.3 😳 Usually harmless. But tiny errors can become dangerous when they accumulate over time. 🚨 In 1991, a Patriot missile system in Saudi Arabia suffered a timing error after running for around 100 hours. The accumulated drift contributed to its failure to track an incoming Scud missile. The missile struck a barracks, killing 28 soldiers. 🔥 How developers avoid these problems: ✅ Use integers for money, such as cents. ✅ Use exact decimal types when appropriate, like Java’s BigDecimal or Python’s Decimal. ✅ Compare floating-point numbers using a tolerance instead of exact equality. One tiny rounding error can teach a massive lesson about software engineering. 💬 Want to learn how banks handle precision in financial systems? Comment below! #Programming #FloatingPoint #SoftwareEngineering #ComputerScience #Coding
algorithmswithpeter215,200 次观看 • 23 天前
💻 ARM vs x86: Which processor architecture is winning in 2026? ⚡ ARM → Better battery life & power efficiency 🔥 x86 → Gaming, compatibility & legacy software 🍎 Apple Silicon, Snapdragon, AWS Graviton and NVIDIA Grace are pushing ARM forward, while Intel and AMD continue fighting for x86 dominance. 🚀 ARM is also making massive moves in data centers! 💬 Which team are you on: ARM or x86? #ARM #x86 #Processors #TechExplained #ComputerScience
algorithmswithpeter47,900 次观看 • 5 天前
Frontend, Backend, DevOps, Full Stack… what does everyone actually do? 👨💻 🖥️ Frontend builds what users see and interact with. ⚙️ Backend handles the logic behind the scenes—APIs, authentication, databases, validation, caching, and business logic. 🚀 DevOps helps get code from development to production reliably using CI/CD, containers, cloud infrastructure, monitoring, and automation. 🔄 Full Stack developers work across both frontend and backend. But building software takes more than just writing code. From Git and code reviews to Figma designs, automated testing, security tools, analytics, project management, and cloud infrastructure—an entire ecosystem works behind the scenes to turn an idea into a real product. Frontend builds what you see. Backend makes it work. DevOps keeps it running. Full Stack connects the pieces. #Frontend #Backend #DevOps #FullStack #SoftwareEngineering
algorithmswithpeter76,400 次观看 • 2 个月前
Docker sounds complicated until you understand Image vs Container 🐳 🧊 Image = a read-only snapshot containing your app + runtime + dependencies. 📦 Container = a running instance of that image. For a real Node.js app, the basic Docker workflow is: 1️⃣ Install Docker Desktop / Docker Engine 2️⃣ Create a Dockerfile 3️⃣ Choose a base image with FROM 4️⃣ Set the working directory with WORKDIR 5️⃣ Copy dependencies first for better layer caching 6️⃣ Install them with RUN npm install 7️⃣ Copy your source code 8️⃣ Document the port with EXPOSE 9️⃣ Start the app with CMD 🔟 Build → docker build 1️⃣1️⃣ Run → docker run And don’t forget .dockerignore to keep things like node_modules and environment files out of your image. Build once. Run anywhere. Same environment every time. 🚀 #Docker #DockerContainers #DevOps #NodeJS #Containerization
algorithmswithpeter59,200 次观看 • 2 个月前
If you’re trying to get into cybersecurity, save this one. I came across a GitHub repo called h4cker and it’s basically a massive collection of cybersecurity resources all in one place. Ethical hacking, penetration testing, Linux, networking, bug bounties, certification prep, labs, tools, courses, books — it’s all organized surprisingly well. What I liked most is that it works whether you’re just getting started or you’ve already been learning for a while. Instead of spending hours jumping between random websites, you can find a huge amount of useful material in one repo. Definitely one of the better cybersecurity resource collections I’ve seen on GitHub lately. #CyberSecurity #EthicalHacking #BugBounty #Linux #GitHub
algorithmswithpeter69,700 次观看 • 5 个月前
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