default mode network

A dialogue with Gary Weber on the default mode network, meditation and non-dual awakening, with discussion of psychedelics, thought and time. It is part of the Non-Dual Couch series.

A short cartoon explaining how language models like ChatGPT work, from autocomplete and conditional probabilities to neural networks, gradient descent and backpropagation. It shows how networks act as universal function approximators.

Van Jacobson's 2006 Google Tech Talk argues that networking should be rethought around named data rather than host-to-host conversations. He contrasts the circuit and datagram views of the internet and sketches content-centric networking as a replacement for the location-centric TCP/IP model.

Sentdex demonstrates GAN Theft Auto, a GameGAN-based neural network that recreates GTA V so the network itself is the playable environment. He shows the results and releases the code.

A standing whiteboard conversation at Lang.NEXT 2012 among Carl Hewitt, Erik Meijer and Clemens Szyperski about the actor model. Hewitt, who originated the model, explains its foundations.

A 2008 Google Tech Talk by the creator of Org-mode, introducing the Emacs subsystem for plain-text note-taking and project planning. It covers outlines, TODO states, tags, dates and priorities, and later shows using Org-mode as a spreadsheet.

Imphenzia's 83-minute tutorial covers the low poly modeling techniques he learned over five years of Blender use, with timestamps from navigation and extrusion onward. It uses Blender 2.83 with default keys.

A demo of writing technical documents in Emacs Org mode using org-babel, so that code blocks and generated content stay consistent when things change. The author shares the demo files and his dotfiles.

Tom Scott tells how John Reber's plan to dam San Francisco Bay was disproved by the Army Corps of Engineers' giant hydraulic Bay Model in Sausalito. The model showed the plan would have been dangerously wrong.

The first of a short series by Welch Labs on building a complete neural network in Python. It introduces the data and the architecture of a simple network before later parts cover forward propagation, gradient descent, and backpropagation.

Van Jacobson's 2006 Google Tech Talk argues for rethinking networking around named data rather than host-to-host connections. He gives the history and the unsolved problems of the current internet architecture.

The official tour video of Miniatur Wunderland in Hamburg, the world's largest model railway. It shows the 1,300 square meter layout with trains, aircraft, cars and ships moving around.

Harry Schwartz gives a roughly hour-long tour of Emacs Org mode as an outliner, task manager, markup language and agenda tool. He demonstrates how he uses it for documents, presentations and todo lists.

Rob Miles explains on Computerphile how language models generate plausible text and how transformers improved on recurrent networks, with a look at what comes next.

Andrej Karpathy builds a bigram character-level language model from scratch, introducing torch.Tensor and the framework of training, sampling and loss evaluation. It is the first step toward a GPT-style Transformer in his makemore series.

A two-hour NANOG tutorial by Richard Steenbergen aimed at network engineers, covering optical networking technologies. This is the updated 2017 edition of a recurring talk.

Harvard professor Arthur Brooks explains why boredom is useful rather than something to avoid. He describes how a wandering mind engages the brain's default mode network, which supports creativity and curiosity, and suggests it may protect against depression.

A spectrogram visualization of the sounds in a dial-up modem handshake, with an annotated image explaining each noise. It shows how the handshake's tones map to the negotiation steps.

A 2017 video arguing that banks and Blockstream steered Bitcoin toward the Lightning Network. It is partisan commentary from the Bitcoin Cash side of the scaling dispute.

Cloth Map documents Havana's SNET, a community-built private network that Cubans created because internet prices were high. It is used for gaming and sharing.

An Autoline After Hours episode with teardown expert Sandy Munro and a panel of auto journalists. It covers his Tesla Model 3 teardown, including the battery, drive modules, build quality and manufacturing automation.

Autoline's John McElroy visits Sandy Munro's shop, where a Tesla Model 3 is being prepared for a teardown benchmarking study. Munro, with deep design and manufacturing experience, points out issues he dislikes about the car's build.

Andrej Karpathy's first Neural Networks: Zero to Hero lecture, which builds micrograd, a tiny autograd engine, from scratch in Python. It explains backpropagation and neural network training step by step, assuming only basic Python and some high-school calculus.

Herb Sutter's CppCon 2015 plenary on writing safe, modern C++ by default using the C++ Core Guidelines. It includes a demo of lifetime-checking static analysis tooling.

Van Jacobson's 2006 Google Tech Talk on rethinking networking around named content instead of host-to-host conversations. He recounts packet-networking history and lays out the content-centric networking idea that later became NDN.

Geoffrey Hinton's 2025 Royal Institution Discourse on what AI has learned from biological intelligence and how it might surpass it. He explains neural networks and argues that human language use resembles what backpropagation-trained networks do.

An 8-minute explainer on the Lightning Network and how it relates to Segwit, Bitcoin and Litecoin. It covers how off-chain payment channels route payments to scale blockchain transactions.

Linus Tech Tips explains how Windows Modern Standby causes laptops to drain battery while asleep, arguing it makes Windows laptops hard to recommend compared to MacBooks.

A seven-minute Google I/O 2014 talk by Simon Newton on how developers can make use of Google's global network. It describes the network's footprint and some of the services running on it.

Rob Miles discusses GPT-3 on Computerphile, covering how scaling parameters kept improving results over GPT-2 and how the model nearly learned arithmetic without anyone knowing exactly how.

A short animation that pairs the sound of a dialup modem handshake with a graphic explaining what each phase of the sound means.

Google's Amin Vahdat gives the ONS 2015 keynote on Google's datacenter networking, including its custom hardware, software-defined networking and very high bisection bandwidth.

3Blue1Brown's first chapter on deep learning explains what neurons and layers are and the math underlying a basic neural network, using handwritten digit recognition with visual animations.

Scott Wlaschin's NDC talk on using statically typed functional programming, F# in particular, to model a business domain. Types are used to represent the domain precisely and to encode business rules so that illegal states cannot be built, with the compiler acting as an instant unit test.

John Kitchin shows how Emacs org-mode with Python lets researchers combine narrative, math, figures and executable code in one document. It exports to LaTeX, HTML and PDF, and he used it for papers and e-books.

Bungie's David Aldridge explains the networking programming behind Halo: Reach in a 2011 GDC session. It covers how gameplay stays in sync online, including forecasting and state reconciliation.

Casey Muratori's 2005 video introducing immediate-mode GUIs as an alternative to retained widget toolkits. He explains the motivation and shows minimal-state button logic.

Anders Hejlsberg whiteboards how compilers are taught versus how modern ones are actually built. He explains the shift to compilers as services with incremental, error-tolerant, IDE-oriented design, as in Roslyn and TypeScript.

Sasha Rush surveys linear RNNs and state space models as replacements for attention in transformer-style models, in a talk for MLSys. It covers the foundational preliminaries and predates Mamba.

Cliff Click walks through a small performance example on a modern out-of-order CPU. He covers pipelining, ILP, CISC vs RISC, multicore, and why cache misses and the memory subsystem dominate performance.