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ICLR 2024, Part 2 of 4: Adversarial Examples, Transformer Workspace, and Long Context Part 2 follows tiny image perturbations, tokens that provide working space, selective training data, and cheaper context extension—ending with the distinction between a larger window and the ability to use it. Writeup · Date unavailable	Writeup	—	—
ICLR 2024, Part 2 of 5: Compute, Context, and Benchmarks for Working Agents Part 2 moves from the experiments academia can afford to run into SWE-Bench, contamination detection, and GAIA’s tests of everyday assistance. Writeup · Date unavailable	Writeup	—	—
ICLR 2024, Part 3 of 4: What Should a Model Remember? Part 3 of 4 moves from the limits of longer context to synthetic-data selection, adaptive KV caches and distributed training, then follows Sasha Rush’s tutorial on recurrent models for language and diffusion. Writeup · Date unavailable	Writeup	—	—
ICLR 2024, Part 4 of 5: Verifiers, Safety Systems, and Agents Part 4 follows stepwise reasoning feedback into deployment safety, browser automation, and multi-agent software development, then closes with the reversal curse: why learning a fact in one direction may not teach its reverse. Writeup · Date unavailable	Writeup	—	—
Inference Efficiency Starts with the Application From image search to conversational characters, useful AI depends on matching hardware, model size and training data to the task—and meeting its response-time budget. Writeup · Date unavailable	Writeup	—	—
Inference Engineering, Part 2 of 2: Parallelism, Video, and Learning Loops Part 2 of 2 follows inference engineering from distributing a model across GPUs to keeping video coherent, training for efficient serving, and preserving knowledge across requests. Writeup · Date unavailable	Writeup	—	—
Inference Engineering: From a 200,000-Token Request to the GPU — Part 1 of 2 Part 1 follows a long request through caching, speculative decoding and production serving, then examines quantization fidelity, meaningful speed comparisons and the constraints of local inference. Writeup · Date unavailable	Writeup	—	—
Inside Brex’s AI Engineering: Platforms, Specialists, and Agent Networks How Brex combines a small AI team with shared infrastructure—and handles the harder work of evaluation, institutional knowledge, and code ownership. Writeup · Date unavailable	Writeup	—	—
Inside Gemini Deep Research: Planning, Evidence, and the Five-Minute Agent How Gemini turns a question into an adaptive investigation—and the model, interface, evaluation, and execution choices that make it useful. Writeup · Date unavailable	Writeup	—	—
Inside Poolside’s Model Factory Streaming data, reproducible experiments and persistent agents serve a common goal: shorten the path from a research idea to a trustworthy model improvement. Writeup · Date unavailable	Writeup	—	—
Instructor: Typed Outputs, Explicit Workflows, and the Direction of Agency Jason Liu’s April 2024 conversation on turning model outputs into usable data, keeping libraries focused, and learning from experiments. Writeup · Date unavailable	Writeup	—	—
Jailbreaking AGI: From Prompt Templates to Full-Stack Security Intuitive prompt exploration, contested evaluations, open research, and the risks of agents that see only part of a task. Writeup · Date unavailable	Writeup	—	—