You don't need to learn about machine learning in depth to become an AI engineer.
I know this goes against a lot of advice online, even some of my own. But ML engineers and AI engineers are two different roles now. An ML engineer works inside the model. Training pipelines, loss
AI
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Distinguishing between ML Engineers and AI Engineers
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The Hidden Human Labor Behind AI Model Training
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La IA no es magia, hay que entrenarla, y a las grandes tecnológicas les sale barato… porque gran parte de ese entrenamiento ocurre lejos de donde se presentan las demos espectaculares.
— Juan Merodio (@juanmerodio) 18 mai 2026
Detrás de cada respuesta “inteligente” hay muchísimo trabajo humano invisible y mal pagado pic.twitter.com/IqpIPihu1SLa IA no es magia, hay que entrenarla, y a las grandes tecnológicas les sale barato… porque gran parte de ese entrenamiento ocurre lejos de donde se presentan las demos espectaculares. Detrás de cada respuesta “inteligente” hay muchísimo trabajo humano invisible y mal pagado
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AI’s Third Superpower: From Answers to Actions to Advocacy
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The Third Superpower Of #AI: From Answers To Actions To Advocacy
by Doug Marinaro @Forbes Learn more: https://
bit.ly/3PJtV2i #ArtificialIntelligence #MachineLearning #ML #DL -
Discussion on OpenAI’s current and future model iterations
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I love GPT-5.5. It's a workhorse and exactly the model I was hoping for. But the fact that rumors say version 5.6 is already in the starting blocks makes me even more excited! OpenAI is on fire.
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Corporate AI Investment ROI and Its Impact on Workforce Hiring
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43% of CEOs plan to cut junior roles in the next two years, up from 17% last year. However, at the same time, only 27% say their AI investments have met expectations – down from 38%. Yet. The small group of companies that ARE seeing real AI ROI are actually more likely to hire
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GPT Image 2 sees 50% usage growth and 1.5bn weekly images
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GPT Image 2: two weeks after launching the model, usage is up 50% and 1.5bn images generated every week in ChatGPT only.
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Levangie Labs Introduces Cognitive Architecture to Enhance LLM Capabilities
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Levangie Labs. Cognitive Architecture that greatly improves any LLM it sits on top of. Only used by big companies right now. I've seen people test it out against the others and it is way better.
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Standardizing Skills for Portable AI Coding Agent Workflows
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If you're building AI workflows for yourself or clients, the practical takeaway is simple: Write your Skills in the SKILL .md format. You're not locked to one vendor. Your thinking systems become portable across every major coding agent. One Skill, 30+ compatible tools. That's
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Comparative analysis of AI agent capabilities in Claude and Perplexity
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Here's what "Skills" actually means on each platform: Claude: Full code execution in a sandbox. Works across Claude. ai, Claude Code, the API, and the Agent SDK. Ships scripts. Persists across sessions. The deepest implementation. Perplexity: Same SKILL. md format running
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Industry-wide adoption of the SKILL.md format for AI agents
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Within months, the adoption list grew: → Perplexity adopted the format for Computer Skills (March 2026)
→ OpenAI adopted it for Codex CLI
→ Cursor adopted it
→ Windsurf adopted it
→ GitHub Copilot adopted it 30+ agents now support the same SKILL. md format. Anthropic