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What are autonomous AI agents? How they work & perform
Agents11 mins read

What are autonomous AI agents? How they work & perform

Autonomous AI agents can plan, act, adapt, and carry multistep workflows toward completion with less human direction. Learn how autonomous agents work, how they differ from standard AI agents, where businesses are using them, and how to evaluate their benefits, risks, and real-world performance.

Latest Expert resources

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Career Exploration11 mins read

New jobs emerging due to AI in 2026

From AI trainers and evaluators to governance and leadership positions, companies across industries like healthcare, finance, consulting, and technology are looking for professionals to support AI systems and workflows in 2026.

Career Exploration11 mins read

14 best entry-level AI jobs: A beginner’s guide

Explore some of the best entry-level AI jobs for beginners in 2026, including remote and freelance opportunities in AI training, prompt engineering, etc. Learn what skills employers look for, average pay ranges from job sites, and how to get started in the growing AI job market.

AI Training Concepts8 mins read

DPO vs. RLHF: Comparison and when to use each

What are the differences between DPO vs. RLHF, including how each alignment method works, their costs, performance trade-offs, and when to use each one for LLM training?

AI Training Concepts9 mins read

What is DPO in AI? Everything you need to know

Learn about direct preference optimization (DPO), how it works, how it compares with RLHF, and when to use it for efficient LLM alignment and fine-tuning.

AI Training Concepts8 mins read

SFT vs. RLHF: Compare LLM training approaches

Compare SFT vs. RLHF to understand how each LLM training method works, when to use supervised fine-tuning or preference optimization, and how newer approaches like DPO, GRPO, and RFT are reshaping AI alignment.

AI Training Concepts10 mins read

What is RLAIF in AI alignment, and how does it work?

Learn what RLAIF (Reinforcement Learning from AI Feedback) is, how it works, how it compares with RLHF, its benefits and limitations, and when AI feedback makes sense in LLM alignment.

Latest APEX resources

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Evaluation Concepts11 mins read

How to test AI models for performance, trust, & fit

Learn how to test AI models for performance, reliability, cost, and workflow fit using practical testing methods, meaningful metrics, real-world benchmarks, and a repeatable evaluation process.

Models4 mins read

Best AI Models Right Now: 2026 Leaders & Rankings

Most AI rankings rely on trivia, but real work requires more. Our guide leverages Mercor's APEX productivity benchmarks, graded by domain experts in law, finance, and engineering, to rank AI models by their ability to handle autonomous agent tasks and complex software engineering issues.

Future of work10 mins read

Will AI replace doctors? What do the benchmarks say?

Could AI replace doctors? See what real-world benchmarks reveal about current model performance, medical specialties most exposed to change, and the clinical work that still requires human judgment.

Industry10 mins read

AI in medicine: Use cases, benchmarks, & reality

AI in medicine supports imaging, documentation, clinical decisions, and drug discovery, but its capabilities remain uneven. See what real-world benchmarks reveal about its benefits, risks, and limits.

Future of work9 mins read

AI impact on jobs: What the benchmark data shows

AI is changing professional work by accelerating structured, digital tasks rather than replacing entire roles. See what benchmark data reveals about job exposure, human expertise, and the future of work.

Benchmarks7 mins read

LMSYS Chatbot Arena vs. Mercor’s APEX benchmarks

LMSYS Chatbot Arena ranks AI models through blind human preference voting, while Mercor’s APEX benchmarks measure performance on expert-graded professional tasks. Compare how each system works, what its scores reveal, its limitations, and when organizations should use both to evaluate models for deployment.