Transformers
Learn to implement transformer components and mini-GPT models from the ground up using Tinygrad. This technical deep dive covers attention mechanisms, layer normalization, and neural network fundamentals to understand how modern AI systems work.
voice cloning
New research uses latent space mixing to generate diverse synthetic voices, addressing underrepresented accents in automatic speech recognition training. The technique improves ASR equity without real voice data from marginalized communities.
deepfake detection
New research introduces semi-supervised learning approach to detect AI-generated images beyond simple real-vs-fake classification, addressing the challenge of identifying images from unknown generative models.
LLM Security
Researchers demonstrate scalable methods for automating multi-turn jailbreak attacks against large language models, revealing critical vulnerabilities in current AI safety measures and guardrails.
prompt engineering
Master advanced prompt engineering techniques used by AI engineers. Learn structured approaches, few-shot learning, chain-of-thought reasoning, and system prompt optimization to maximize LLM performance across technical applications.
agentic AI
Exploring how decision memory architectures enable AI systems to build cognitive reasoning capabilities through persistent memory structures, iterative reflection, and structured decision-making frameworks.
deepfakes
Sumsub reports sophisticated fraud including deepfake attacks increased 180% globally in 2024, with UK deepfake incidents doubling. Identity verification systems face escalating synthetic media threats as fraudsters deploy AI-generated content.
synthetic media
New research introduces hierarchical framework for detecting contamination in synthetic training data for foundation models, addressing limitations of surface-level similarity metrics through multi-level analysis of data quality and authenticity.
AI Agents
New research introduces a cognitive architecture that bridges symbolic control and neural reasoning in LLM agents, offering a structured framework for more reliable and interpretable AI systems with explicit planning and execution phases.
machine learning
Tensors are the fundamental data structures powering modern AI systems. This technical deep dive explains how these mathematical objects enable neural networks to process images, video, and audio for generation and manipulation.
PyTorch
Deep dive into PyTorch neural network development, from manual gradient computation to leveraging nn.Module and optim for efficient training. Technical tutorial covering implementation fundamentals for modern deep learning.
agentic AI
Microsoft releases Fara-7B, a 7-billion parameter agentic AI model designed for computer control tasks. The model demonstrates competitive performance against larger systems while maintaining efficiency for autonomous GUI interaction.