🤖 AI Isn’t a Job Killer: It’s a Job Shifter

🪦AI Isn’t a Job Killer: It’s a Job Shifter

🕹️AI Agent Teaches Itself To Play Minecraft

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Since OpenAI released ChatGPT in November 2022, the number of new companies with “AI” in their name has more than tripled. The Budget Lab at Yale found that despite this rapid adoption, AI has yet to cause widespread job losses across the U.S. workforce.

Instead, the U.S. workforce remains “a story of continuity over change.” In other words, AI hasn’t disrupted employment levels any more than previous waves of technological advancements.

While unemployment levels for 20- to 24-year-olds have jumped from 8.2% in April 2025 to 9.3% by August 2025, it’s “a cyclical trend that’s not purely tech-driven.”

Macro Research Analyst at Goldman Sachs, Sarah Dong, explained: “Predictions of technology reducing the need for human labor have a long history but a poor track record.”

Approximately 60% of U.S. workers today are employed in job roles that didn’t even exist in 1940, implying that more than 85% of all employment growth over the last 80 years has been driven by new technologies.

Most economists expect AI to follow the same historical pattern as previous technological advancements, only causing a period of temporary job loss, where the U.S. Unemployment Rate (UR) briefly increases by just 0.5 percentage points (%pt).

That’s great news, right? While surviving three years without an AI-driven job apocalypse is reassuring, the technology continues to evolve rapidly. Anthropic CEO Dario Amodei warned that AI could wipe out half of all entry-level white-collar job roles within the next five years.

In Minecraft, you explore a virtual three-dimensional (3D) world containing a variety of terrains, including forests, deserts, swamps, and mountains. You gather resources like oak logs, sandstone, and diamond ore to create items like chests, fences, and swords.

“DreamerV4” wasn’t given any step-by-step guidance by humans. Instead, it was trained offline by watching recorded gameplay and analyzing actions to understand cause-and-effect relationships.

For instance, “DreamerV4” observed that chopping down oak trees located in forests yielded oak logs. This observation established an essential relationship between an action and the consequence of that action.

It relies on Model-Based Reinforcement Learning (MBRL), which mimics the trial-and-error process humans use to learn, where actions that lead to desired outcomes are reinforced. This process guides the AI Agent toward better decision-making as it gains more experience.

“You must really understand what’s in front of you; you can’t just memorize a specific strategy,” said Google DeepMind Research Scientist Danijar Hafner. “It forces the AI Agent to self-improve over time.”

Context: I want to handle conflict better by responding calmly, clearly, and constructively,

Clarity: but I often get defensive, avoid confrontation, or struggle to express myself effectively.

Guidance: Can you provide me with actionable tips to navigate conflict more effectively when I’m dealing with {Insert Specific Person} about {Insert Specific Topic}?

AudioShake raised a $14M Series A for AI-powered audio separation technology.

RunBuggy landed a $37M Series B to help you ship any vehicle, anywhere.

Simple closed a $35M Series B for AI-based weight loss coaching.

Samsung (San Jose, CA): CPU Design Engineer Intern, Summer 2026

Replit (Foster City, CA): Software Engineer, AI Agents, Entry-Level

Meta (New York, NY): GenAI Research Scientist, Language, Mid-Level

Anthropic (Washington, DC): External Affairs, U.S. Federal, Senior-Level