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Fresh from the notebook

Linux 26 Sep 2026 4 min read

Batch Resize Images with Bash and ImageMagick Without Overwriting Originals

A resize command is straightforward. Keeping a batch recoverable takes more care. Writing results over the source images can leave a collection only partly processed if a conversion fails. Flattening every result into one folder also creates collisions: events/photo.jpg and products/photo.jpg would have the same destination name. A separate output tree avoids both problems. The script below accepts a source directory, a destination directory, and a maximum edge length. It processes JPEG, PNG, and WebP files recursively, retains their relative paths and formats, and leaves the originals alone.

Linux Bash

Linux 26 Sep 2026 5 min read

Batch Convert JPEG and PNG to WebP with Bash and cwebp

Two files named photo.jpg and photo.png in the same directory would both become photo.webp. A batch converter that notices the collision only after it starts encoding may leave one image unconverted or replace an earlier result. It is better to check the entire input list first. The Bash script here uses cwebp for encoding and keeps a separate output tree. Its default auto mode encodes JPEG with lossy WebP and PNG with lossless WebP. The source images stay in place; existing destination files are skipped.

Linux Bash

Cybersecurity 24 Sep 2026 6 min read

TLS Delegated Credentials Limit Certificate Key Exposure

Large TLS deployments often need signing capability on many serving machines. Copying the certificate private key to every endpoint expands the set of systems whose compromise can expose a long-lived credential. Keeping that key in one tightly controlled location reduces exposure, but remote signing for every handshake can add an operational dependency to the serving path. Delegated Credentials for TLS, standardized in RFC 9345, provide a narrower option for TLS 1.3. A certificate holder can use its certificate private key to authorize another public key for a limited period. The endpoint receives the corresponding delegated private key and can authenticate TLS handshakes without holding the certificate private key itself.

Cybersecurity TLS

Artificial Intelligence 24 Sep 2026 5 min read

Temperature Scaling Recalibrates Classifier Confidence Without Changing Class Order

A classifier can rank the correct class above every alternative yet attach probabilities that are systematically too concentrated or too diffuse. Temperature scaling addresses that mismatch after training by applying one scalar to the logits before softmax. It changes reported confidence without changing the underlying classifier parameters. The mechanism is narrow. It does not repair incorrect class rankings, add information to the representation, or make every individual probability accurate. Its target is the relationship between confidence and observed outcomes on data representative of deployment.

Artificial Intelligence Calibration

Artificial Intelligence 24 Sep 2026 6 min read

Tanh Logit Soft Capping Bounds Extreme Scores Before Softmax

A softmax can accept logits of any finite magnitude, but large score gaps make its output increasingly concentrated. Tanh logit soft capping inserts a bounded nonlinear transform before softmax so that no transformed logit exceeds a configured magnitude. For a positive cap c, a common form is: softcap(z; c) = c * tanh(z / c) The operation does not clip at a hard threshold. It behaves almost linearly near zero and gradually compresses larger magnitudes as they approach -c or c.

Artificial Intelligence Transformers

Artificial Intelligence 24 Sep 2026 5 min read

SwiGLU Gates Transformer Feed-Forward Channels with a Second Projection

SwiGLU splits a transformer feed-forward input into two projected paths, applies SiLU to one path, then multiplies the two results element by element. The second projection is not an auxiliary statistic: its values directly gate the activated path before the output projection. For hidden state x, a common structural form is: g = SiLU(x W_gate) u = x W_up h = g * u y = h W_down Bias terms, projection orientation, intermediate width, and parameter names vary across architectures. The defining boundary is the element-wise product between a nonlinear projected branch and another projected branch.

Artificial Intelligence Transformers

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