Man discovers unsupervised learning and confuses it with what "training on test" actually means.
MACHINE LEARNING
-
How AI Models Learn: Debunking Data Reproduction Myths
By
–
I’m tired of explaining how AI models learn. They don’t copy or reproduce data in the way you think they do.
-
Stanford Hiring Data Science Postdocs in Causal Inference
By
–
We're hiring data science postdocs! Work on interdisciplinary projects in causal inference, ML, econometrics, and more. Recent PhDs with coding expertise and cross-disciplinary experience are encouraged to apply: https://
datascience.stanford.edu/programs/data-
science-fellows
… -
Computer Vision: Much More Than Just Artificial Intelligence
By
–
Computer Vision isn’t “just AI.”
— Satya Mallick (@LearnOpenCV) 19 décembre 2025
It’s how machines interpret visual data—from cameras to X‑rays to telescopes—solving tasks like detection, recognition, OCR, and 3D reconstruction. #ComputerVision #AI #MachineLearning #DeepLearning #ImageProcessing pic.twitter.com/KhVODmTBBUComputer Vision isn't "just AI."
It's how machines interpret visual data—from cameras to X‑rays to telescopes—solving tasks like detection, recognition, OCR, and 3D reconstruction. #ComputerVision #AI #MachineLearning #DeepLearning #ImageProcessing -
Is Gemini 3 Pro the model behind this reasoning?
By
–
If reasoning – is it Gemini 3 Pro in this case?
-
Increasing Context Length and Model Capacity: Expensive Trade-offs
By
–
Either
a) you increase the context length and/or let the model crawl through stored data
b) you start of with a model that has large enough capacity and periodically update the weights
Both options are expensive, so I am not sure they actually want this right now. -
Mixture of Experts Models: Current Perspectives and Efficiency
By
–
Poll: How Are You Thinking About Mixture of Experts (MoE) Models Today? MoE architectures scale model intelligence by routing each request to a subset of specialized “experts,” improving efficiency. Which best matches your current perspective?
-
ODB-dLLM: Faster Parallelizable Diffusion-Based Language Models
By
–
Diffusion-based LLMs are fast and parallelizable, but bidirectional attention makes inference expensive due to repeated prefill and decoding. Enter ODB-dLLM, a dual-boundary framework with adaptive prefill length prediction and dLLM-specific jump-share speculative decoding.
-
9 AI Skills That Will Matter in 2026 Beyond ChatGPT
By
–
9 AI skills that will actually matter in 2026
(not just “use ChatGPT”) Prompt engineering RAG pipelines Agentic workflows Fine-tuning & distillation LLM evaluation & red-teaming Cost & latency optimization Tool calling + function calling Multimodal -
GPT 6 Is Coming to Crush Gemini3 Competition
By
–
GPT 6 is coming… And it's going to change everything Here's everything you need to know → https://
youtu.be/Kb61cQMlbGM The goal is clear: crush the competition, #Gemini3 in the lead!