Figures and Captions Don't Appear as Expected with Default Export Options

Source: Daniel Liden's Blog | Tags: css, export, figcaption, figure, html5 | Published: 2026-07-05 | Novelty: 43%

The article describes a change where images and captions are now centered using <figure> and <figcaption> HTML5 elements, which were not available in earlier XHTML standards. The author had to adjust the export settings to use HTML5 and noticed that custom CSS styling for figcaption did not affect the appearance, leading to this solution.

Using Quarto Files with Denote

Source: Daniel Liden's Blog | Tags: configuration, denote, emacs, quarto | Published: 2026-07-05 | Novelty: 41%

The article explains how to modify Denote's file types configuration to support Quarto files by changing the extension from .md to .qmd. It demonstrates using Emacs Lisp code, specifically assoc, cdr, and setf functions, to update the file type associations in the denote-file-types alist.

Emacs Introspection and Debugging

Source: Daniel Liden's Blog | Tags: debugging, emacs, introspection | Published: 2026-07-05 | Novelty: 41%

The article describes a debugging journey where the author uses Emacs introspection tools to identify and fix an issue with eglot, particularly focusing on after-save-hook. Notable code includes adding a custom function my-eglot-shutdown-cleanup to remove the eglot-format hook from after-save-hook, which resolves the error when shutting down eglot. The article also emphasizes using tools like toggle-debug-on-error, apropos-variable, and describe-function for debugging Emacs issues.

Mapping Urban Heat by Census Tract in R

Source: Daniel Liden's Blog | Tags: census-data, gis, r, urban-heat | Published: 2026-07-05 | Novelty: 39%

The article details the process of mapping urban heat by census tract using R, highlighting the relationship between income and urban heat. Key steps include obtaining satellite surface temperature data, aggregating it within census tracts, and plotting the results. Notable resources mentioned are 'Geocomputation with R' by Robin Lovelace, Jakub Nowosad, Jannes Muenchow, which offers insights into working with spatial data.

The Hard Call Is the Whole Job · A cancelled flight, three confident machines, and the woman on the Hilton Diamond line who refused to stop.

Source: Christopher Meiklejohn | Tags: automation, customer-experience, human-operated, service | Published: 2026-07-08 | Novelty: 38%

The article highlights three distinct systems: a hotel AI bot that misunderstood the date, an error screen that failed to communicate issues, and a human operator who effectively solved the problem. It emphasizes that service quality is crucial during critical moments when customers need help the most, arguing against shipping untested automated solutions into these high-impact situations.

Persistent Elements in Daily Journals with Org Agenda

Source: Daniel Liden's Blog | Tags: agenda, journaling, org | Published: 2026-07-05 | Novelty: 36%

The article suggests using the Org agenda feature of tagging specific headers within daily journal files to easily locate and revisit important notes. By creating a custom agenda view that filters these tagged entries from only journal files, users can keep track of significant information without cluttering frequently accessed documents.

Resources

Source: Daniel Liden's Blog | Tags: blogging, css, org-mode | Published: 2026-07-05 | Novelty: 36%

The article highlights resources for building a simple site using org-mode, including an OrgCSS stylesheet for basic styling and loomcom as a reference for creating lists of posts with text previews. The author's own site serves as a practical example.

YASnippet for Prompt Templates for Chatgpt-Shell

Source: Daniel Liden's Blog | Tags: emacs, gpt-shell, yasnippet | Published: 2026-07-05 | Novelty: 36%

This article explains how to create a YASnippet for summarizing text using the GPT-Shell. It provides detailed steps on defining and saving a snippet, including placeholders and tab stop fields. A specific example is given with the 'Concise Summary' template.

Org Babel Source Blocks for R

Source: Daniel Liden's Blog | Tags: data-science, emacs, org-babel, r | Published: 2026-07-05 | Novelty: 35%

The article highlights the use of Org Babel for R programming within Emacs, emphasizing its interactive nature and persistence of variables between code blocks. Notable pieces of code include setting up Base R and ggplot2 plots with specific header arguments for exporting figures, as well as configuring Emacs-Jupyter for seamless figure generation without specifying filenames.

Retrieving Data for the H2o RAG Benchmark

Source: Daniel Liden's Blog | Tags: benchmark, h2o, pdf, rag | Published: 2026-07-05 | Novelty: 35%

This article details how to retrieve various documents for the H2O RAG benchmark, including PDFs, images, and an MP3 file, by using Python scripts. Notable files include annual reports from companies like Wells Fargo, CitiGroup, and Bradesco, as well as a mix of other document types such as press releases and image files.

The power of collaboration: How we can reduce traffic congestion

Source: The latest research from Google | Tags: cooperation, routing, sustainability, traffic | Published: 2026-07-07 | Novelty: 35%

The research demonstrates that even a small fraction of trips (less than 2%) can be rerouted through targeted low-cost routing interventions using Google Maps, leading to measurable improvements in driving speeds and reductions in CO2 emissions. The study involved 10 major US cities over six months and used a hierarchical Bayesian outcome modeling framework for analysis.

Book Review: Machine Learning Yearning by Andrew Ng

Source: Daniel Liden's Blog | Tags: deep-learning, machine-learning, process-considerations | Published: 2026-07-05 | Novelty: 35%

The book 'Machine Learning Yearning' by Andrew Ng emphasizes the importance of big-picture considerations such as seeking out more training examples, conducting careful error analysis, and increasing model size/complexity. It also focuses on deep learning/neural networks, though this is not always clearly stated throughout the text.

Building a World Map with only 500 bytes

Source: Simon Willison's Weblog | Tags: ascii-art, compression, javascript | Published: 2026-07-04 | Novelty: 35%

Iwo Kadziela created an ASCII world map using only 445 bytes of data, leveraging deflate compression. The map is generated via a JavaScript snippet that uses fetch() with data: URIs and a DecompressionStream for decompressing the compressed data.

Quoting Nilay Patel

Source: Simon Willison's Weblog | Tags: augmented-reality, cloud-computing, privacy | Published: 2026-07-10 | Novelty: 34%

Nilay Patel of The Vergecast argues that building augmented reality glasses requires either sending continuous visual data to the cloud for processing or using a bulky device with an external battery pack. He raises ethical concerns about invading users' privacy and suggests societal trade-offs may make such products undesirable.

Using the ChatGPT API with Julia Part 2: Defining a Chat Struct

Source: Daniel Liden's Blog | Tags: api, chatgpt, julia, structs | Published: 2026-07-05 | Novelty: 33%

The article introduces a mutable struct named Chat for handling chat interactions with the ChatGPT API in Julia. It uses an inner constructor to initialize a Chat object with a system message, and the struct contains an array of dictionaries representing the chat messages. This design allows for adding new messages during the conversation without modifying the initial state.

Using the ChatGPT API with Julia Part 1: the HTTP.jl Library

Source: Daniel Liden's Blog | Tags: api, chatgpt, http, julia, openai | Published: 2026-07-05 | Novelty: 32%

The article demonstrates how to use Julia's HTTP.jl library to interact with the OpenAI ChatGPT API. It includes a specific example of sending a POST request with JSON data and shows how to build upon this by including previous conversation history in messages. Notable code snippets include using HTTP.post with headers and body, and manipulating message arrays.

Saving and Restoring Window Configurations in Emacs

Source: Daniel Liden's Blog | Tags: emacs, registers, window-management | Published: 2026-07-05 | Novelty: 32%

The article discusses using window registers to save and restore Emacs window configurations across sessions. It highlights the use of <C-x r w> to register a window configuration and <C-x r j> to jump back to it, emphasizing that while desktop-save-mode can persist some state across sessions, it is imperfect for fully restoring window configurations. Notable pieces of code include the keybindings <C-x r w> and <C-x r j>.

Introduction to Emacs Hooks

Source: Daniel Liden's Blog | Tags: emacs, hooks, lisp | Published: 2026-07-05 | Novelty: 31%

This article explains the process of defining and using hooks in Emacs. It demonstrates setting up a hook variable named my-example-hook, adding two functions (hook-function-1 and hook-function-2) to it, and then executing these functions with run-hooks. The example shows that hooks are just lists of functions that can be run sequentially.

Getting Started with Model Context Protocol Part 1: Add a Simple MCP Server to Claude Desktop

Source: Daniel Liden's Blog | Tags: claude-desktop, llm, model-context-protocol, python | Published: 2026-07-05 | Novelty: 30%

This article provides a step-by-step guide to setting up a minimal MCP (Model Context Protocol) server using the FastMCP method from the Python MCP SDK, and integrating it with Claude Desktop. The server exposes a single function 'get_secret_number' that returns a predefined secret number. Notable code includes defining mcp = FastMCP('SecretServer') and decorating @mcp.tool() def get_secret_number(): return 13. This example is particularly useful for beginners due to its simplicity, making it easy to verify that the integration works correctly.

Have you heard? Clickhouse is winning the observability wars!

Source: charity.wtf | Tags: clickhouse, data-engineering, observability, scalars | Published: 2026-07-08 | Novelty: 30%

The article highlights how Clickhouse is revolutionizing observability by enabling seamless scalability, unlike other tools such as Elastic, LGTM, and Datadog. The author emphasizes that using Clickhouse can significantly improve data handling efficiency, making it a preferred choice for large-scale data management in observability stacks.

Still doing less, for her

Source: Carlos Becker | Tags: mental-load, parenthood, projects | Published: 2026-07-07 | Novelty: 30%

The author has archived numerous personal projects and is no longer actively maintaining them to reduce mental load. They are also stepping down from a role in the Rotary club, but not eliminating all commitments. A new focus on being a father to their newborn daughter, who they describe as perfect.

github-code Web Component

Source: Simon Willison's Weblog | Tags: github, gpt-5.5, web-component | Published: 2026-07-07 | Novelty: 30%

The article describes an experimental Web Component created using GPT-5.5, which embeds code from GitHub by fetching specific URL ranges and displaying them with line numbers. The example provided uses the URL 'https://github.com/simonw/sqlite-ast/blob/437c759129154f05296324a7f82aa1246340dd14/sqlite_ast/parser.py#L9-L18', demonstrating how the component handles URL conversion and line fetching.

Rewriting Bun in Rust

Source: Simon Willison's Weblog | Tags: ai-assisted-dev, bun, rust | Published: 2026-07-08 | Novelty: 29%

Jarred Sumner details the rewrite of Bun from Zig to Rust, highlighting the use of a large test suite and adversarial code review. The new implementation was live in Claude Code for nearly a month, with only minor performance improvements noted by users. The process involved over 5.9 billion uncached input tokens, 690 million output tokens, and 72 billion cached input token reads, estimated to cost $165,000.

Using MLflow's MCP Server for Conversational Trace Analysis

Source: Daniel Liden's Blog | Tags: mcp-server, mlflow, openai, trace-analysis, web-scraping | Published: 2026-07-05 | Novelty: 29%

The article demonstrates how to use MLflow's MCP server for conversational trace analysis by creating and logging three example traces: one failing API call, another successful API call, and a multi-step process involving web scraping and summarization using GPT-5. The script utilizes the @mlflow.trace() decorator to capture detailed error information and trace multiple steps in a single span, highlighting how MLflow can be used for debugging AI application failures and monitoring workflows.

Introducing Muse Spark 1.1

Source: Simon Willison's Weblog | Tags: ai, api, llm, muse-spark, plugin | Published: 2026-07-09 | Novelty: 29%

Muse Spark 1.1 is the first version of the Muse Spark model to offer an API, with significant improvements in agentic tool calling and computer use according to Meta. It includes a feature where two copies of the model can engage in self-conversation, leading to unique statements like 'My whole existence is a waiting room by design.' A new plugin called llm-meta-ai has been developed for LLM that provides CLI and Python library access to Muse Spark 1.1, allowing users to generate an SVG of a pelican riding a bicycle through the command line or Python code.

Profiling in PyTorch (Part 3): Attention is all you profile

Source: Hugging Face - Blog | Tags: attention, cuda, profiling, pytorch | Published: 2026-07-10 | Novelty: 29%

The blog post compares various attention mechanism implementations in PyTorch, including flash and cuDNN backends. It highlights that while the cuDNN backend generates a per-problem kernel with fewer transposes and launch attributes, it incurs higher CPU overhead due to internal plan selection. Notably, the Flash backend achieves high performance despite seemingly low GPU occupancy.

PRX Part 4: Our Data Strategy

Source: Hugging Face - Blog | Tags: curation, dataset-prep, diffusion-models, mds, perceptual-hash | Published: 2026-07-06 | Novelty: 29%

The article details a process for preparing large-scale image datasets for diffusion models. Key innovations include aspect-ratio bucketing to maintain constant patch count, and the use of Mosaic Data Shards (MDS) for efficient distributed training. Notably, perceptual hashes are used for deduplication without deleting data, and a skip-list mechanism is employed to filter out unwanted samples post-training.

Writing on AI and Postgres

Source: Daniel Liden's Blog | Tags: database, llm, postgres, vector-similarity-search | Published: 2026-07-05 | Novelty: 28%

The article highlights a two-step process for generating API calls using ChatGPT, where the first step involves pre-classifying tasks to improve completion quality. Notable examples include the use of bit.io and pgvector for vector similarity search in Postgres databases, demonstrating how LLMs can be integrated with other tools for more efficient database management.

Better Models: Worse Tools

Source: Simon Willison's Weblog | Tags: anthropic, claude-code, models, tools | Published: 2026-07-04 | Novelty: 28%

Armin reports that newer Anthropic models like Opus 4.8 and Sonnet 5 are more likely to use Claude Code's edit tools incorrectly, adding extra fields in the nested edits[] array. This issue is theorized to be due to specific training of these models for better tool integration with Claude Code, potentially making third-party coding harnesses like Pi implement multiple edit tools to match the model's preferences.

🤗 Kernels: Major Updates

Source: Hugging Face - Blog | Tags: compatibility, frameworks, kernels, security | Published: 2026-07-06 | Novelty: 27%

The Kernels project has introduced a new repository type on the Hub with improved security features such as trusted kernel publishers and code signing. Kernel-builder now supports frameworks like Torch Stable ABI and Apache TVM FFI, and provides an environment setup script for easier use. The project also includes a system card for each kernel to expose useful information about compatibility and usage.

SensorFM: Towards a general intelligence and interface for wearable health data

Source: The latest research from Google | Tags: ai, health, machine-learning, scaling, wearable | Published: 2026-07-09 | Novelty: 26%

SensorFM is a large sensor foundation model pre-trained on over one trillion minutes of multimodal wearable data from five million individuals, making it the largest and most diverse dataset used to train such a model. It learns through self-supervised reconstruction using Adaptive and Inherited Masking (AIM) to handle missing data effectively, achieving significant improvements in generative pre-training and downstream health tasks across 35 discriminative health domains. SensorFM's general embeddings enable efficient adaptation for various health outcomes, with an agentic classroom improving prediction head performance.

Quoting OpenAI

Source: Simon Willison's Weblog | Tags: chatgpt, openai, work-feature | Published: 2026-07-10 | Novelty: 26%

OpenAI attempted to clarify the functionality of its new ChatGPT Work feature, stating that web and mobile work runs in the cloud while desktop app work can use local files with permission. However, at launch, conversations from cloud Work do not appear in desktop Work, and threads and local files remain on the computer. This statement was made in response to user concerns about data synchronization between platforms.

Experiences with local models for coding

Source: Martin Fowler | Tags: coding, context-window, evaluation, models, performance | Published: 2026-07-08 | Novelty: 25%

The author describes a detailed evaluation of small models for agentic coding, focusing on the Qwen3.6 35B model and comparing it with other models like Gemma 4 31B and Qwen Coder Next 80B MoE. The key takeaway is that while smaller models can perform well in certain tasks, they struggle significantly when handling complex reasoning or large context windows, as seen in the 'Sort and cumulate an existing bar chart' task. Additionally, the author notes a surprising difference in performance between machines with similar configurations but varying amounts of RAM, which further complicates model viability.

A Simple PyTorch Model for the Numerai Tournament

Source: Daniel Liden's Blog | Tags: custom-dataset, fastai, mlp, numerai, pytorch | Published: 2026-07-05 | Novelty: 25%

The article highlights key differences between PyTorch and fastai implementations for a regression model using Numerai data. Notable code includes the custom NumerData class defining __len__() and __getitem__(), and the training loop method that uses BackgroundGenerator. The author emphasizes the importance of minimizing processing within __getitem__() to improve efficiency, and provides detailed metrics like MSE loss and Spearman correlation for evaluation. The example model is a simple MLP with 256 neurons.

LeRobot v0.6.0: Imagine, Evaluate, Improve

Source: Hugging Face - Blog | Tags: annotations, benchmarks, dagger, simulations, vlas | Published: 2026-07-07 | Novelty: 24%

LeRobot v0.6.0 introduces a new annotation pipeline powered by Qwen/Qwen2.5-VL-7B-Instruct for rendering annotations into chat-style training messages, and a robust suite of simulation benchmarks including LIBERO-plus, RoboTwin 2.0, and RoboCasa365, all accessible via the lerobot-eval CLI. The new lerobot-rollout CLI supports deployment with strategies like Dagger, allowing real-time corrections to be collected for fine-tuning policies.

tencent/Hy3

Source: Simon Willison's Weblog | Tags: ai, hy3, models, tencent | Published: 2026-07-06 | Novelty: 24%

Tencent's Hy3 is a 295B-parameter Mixture-of-Experts model, currently available for free on OpenRouter until July 21st. It outperforms similar-size models and rivals larger ones with significant gains in various productivity tasks. Max Woolf previously noted it topped Model Rankings on OpenRouter.

Quoting Kenton Varda

Source: Simon Willison's Weblog | Tags: ai, ai-assisted-programming, generative-ai, llms | Published: 2026-07-08 | Novelty: 24%

Kenton Varda has declared a moratorium on AI-generated change descriptions for PRs and commit messages due to their inadequacy in providing necessary context. This decision highlights the ongoing challenge of balancing automation with human oversight in software development workflows.

Harness Engineering

Source: Daniel Liden's Blog | Tags: harness, model-performance, user-experience | Published: 2026-07-05 | Novelty: 24%

The article emphasizes the importance of agent harnesses over underlying models for user experience, using specific examples such as Claude Opus 4.6 and GPT Codex 5.3 competing in Terminal-Bench 2. It provides a broad definition of an agent harness and suggests building one to experiment with context management and tool use, offering code as a foundation for future experiments.

Data for Agents

Source: Hugging Face - Blog | Tags: ai, nemotron, nvidia, open-datasets, synthetic-data | Published: 2026-07-08 | Novelty: 24%

The article emphasizes the importance of open datasets for training AI agents, particularly synthetic data that can enhance pretraining and post-training samples. Notable is Nemotron's Post-Training v3 Prompt Atlas, which provides an interactive visual map to explore diverse post-training samples across various domains. The Nemotron-Personas dataset uses NeMo Data Designer to create locally grounded synthetic personas representing different populations, facilitating more inclusive AI development.

[FREE] How does Uber deal with Spark Out-Of-Memory (OOM)?

Source: VuTrinh. | Tags: executor, oom, spark, uber | Published: 2026-07-06 | Novelty: 23%

Uber addresses Spark Out-of-Memory (OOM) errors by dynamically resizing executor cores based on task memory requirements, marking all tasks that run on the failed executor as memory-intensive. This approach ensures that problematic tasks are retried with full resources, enhancing reliability at the cost of reduced resource utilization. For instance, an executor with 4 cores and 8GB RAM would handle three 2GB tasks and one 5GB task by giving each task its own full set of resources upon retry, avoiding shared memory constraints.

Run AI workloads on any cloud, store on Hugging Face: zero-egress storage with SkyPilot

Source: Hugging Face - Blog | Tags: ai, cloud, huggingface, skypilot, storage | Published: 2026-07-07 | Novelty: 22%

This article introduces the integration of Hugging Face Storage with SkyPilot, allowing AI workloads to run on any cloud while storing data in Hugging Face Buckets. Key features include zero-egress storage, automatic deduplication for model variants and checkpoints using Xet's content-defined chunking, and seamless mounting through one hf:// URL. The benchmark shows that lazy reads of the Qwen3.5-4B model took about 30 seconds on all clouds, and checkpoints were written at speeds ranging from ~168 MB/s to ~112 MB/s across different cloud providers.

The Agent-Era Career

Source: AddyOsmani.com | Tags: ai, career-advice, judgment, sprint-last-mile | Published: 2026-07-06 | Novelty: 22%

The article argues that in the age of AI, careers will thrive through choosing and judging problems rather than solving them. It emphasizes the importance of building deep mental models and making critical judgments, as well as being able to delegate tasks effectively while maintaining accountability for outcomes. Specific techniques include sprinting the last mile on features by rebuilding from scratch with new models every few months.

sqlite-utils 4.0rc2, mostly written by Claude Fable (for about $149.25)

Source: Simon Willison's Weblog | Tags: documentation, sqlite, transaction | Published: 2026-07-05 | Novelty: 22%

The article details the development process of sqlite-utils 4.0rc2, focusing on a critical bug fix in delete_where() that could lead to data loss and comprehensive documentation updates. The project utilized Claude Fable for 37 prompts and 34 commits over 30 files, involving significant code changes. Notably, the new transaction model ensures write operations are committed immediately unless within an explicit transaction, improving data integrity and simplifying usage.

sqlite-utils 4.0rc3

Source: Simon Willison's Weblog | Tags: case-insensitivity, foreign-keys, sqlite | Published: 2026-07-06 | Novelty: 21%

sqlite-utils 4.0rc3 introduces support for introspecting and creating compound foreign keys, marking a subtle breaking change to table.foreign_keys; it also now follows SQLite's convention for case-insensitive column names, affecting multiple aspects of the library.

From Hugging Face to Amazon SageMaker Studio in one click

Source: Hugging Face - Blog | Tags: huggingface, integration, sagemaker | Published: 2026-07-07 | Novelty: 21%

The integration between Hugging Face and Amazon SageMaker Studio allows developers to directly launch model customization or deployment workflows within SageMaker with a single click, reducing friction from inspiration to experimentation. New Studio environments are automatically provisioned with pre-configured permissions for various SageMaker capabilities, including fine-tuning and endpoint deployment.

Made with Org-Mode

Source: Daniel Liden's Blog | Tags: customization, org-mode, ox-publish, personal-site, sitemap | Published: 2026-07-05 | Novelty: 21%

The article details the process of creating a personal website using Org-mode's ox-publish, with specific focus on customization through CSS and sitemap configurations. Notable code snippets include the implementation of preview text for blog entries via my/get-preview function, and setting up image management with org-publish-attachment. The author also provides GitHub links and guides used, ensuring a smooth transition from Org-mode to published content.

Hugging Face Models on Foundry Managed Compute

Source: Hugging Face - Blog | Tags: huggingface, managedcompute, openai | Published: 2026-07-07 | Novelty: 21%

Microsoft Foundry introduces Hugging Face models on Managed Compute, offering a curated catalog of open-weight models accessible via a single endpoint and SDKs in Python, C#, JavaScript, and Java. This service supports thousands of models across various modalities, including text, vision, and audio, with weekly updates. The deployment process is streamlined using specific templates that match the model's architecture to the right runtime, ensuring seamless integration with Foundry Agents.

Fragments: July 6

Source: Martin Fowler | Tags: ai, design, ethics, software-development, token-costs | Published: 2026-07-06 | Novelty: 21%

The article discusses the Future of Software Development Retreat where participants are confident about agentic development practices and its value. It also touches on ethical concerns related to AI, such as the importance of design as a hedge against future risks, and an incident where an author's work was removed from Google due to a fraudulent DMCA claim. The article highlights the rising token costs for companies using AI, leading them to limit or cut back on agentic programming usage.

[FREE] How does Figma improve insight freshness by 10x?

Source: VuTrinh. | Tags: automation, cdc, data-freshness, scalability, step-functions | Published: 2026-07-09 | Novelty: 20%

Figma improved data freshness by implementing Change Data Capture (CDC) using log-based CDC with Kafka and Snowflake. This incremental synchronization method reduced data latency from 30 hours to 3 hours or less, but required building custom solutions for snapshot creation, delta merging, and automated onboarding/validation processes via AWS Step Functions. The solution's complexity includes managing a message system, a consumer, and the data merger, which is a trade-off for scalability and real-time insights.

Introducing GPT‑Live

Source: Simon Willison's Weblog | Tags: chatbot, gpt, voice-assistant | Published: 2026-07-08 | Novelty: 20%

GPT-Live, an upgrade to the voice mode in ChatGPT, uses a new GPT-5.5 model that can delegate complex tasks to even more advanced models like GPT-5.5 for deep reasoning and web searches. The previous voice mode was based on a GPT-4o era model with limited capabilities introduced in 2024. Notable features include the ability to maintain conversation flow during task delegation and improvements in response appropriateness, such as reduced interrupting laughter.

Native-speed vLLM transformers modeling backend

Source: Hugging Face - Blog | Tags: inference, optimization, transformers, vllm | Published: 2026-07-08 | Novelty: 19%

The transformers vLLM backend now matches or exceeds the performance of native vLLM implementations for multiple large language models, including a 4B dense model, a 32B dense model with tensor parallelism, and a 235B-parameter FP8 Mixture-of-Experts model across data and expert parallelism. This is achieved through dynamic runtime optimization using torch.fx to apply layer fusions that match the speed of custom vLLM implementations without requiring additional code for model authors.

Mechanized type inference for record concatenation

Source: Haskell for all | Tags: disjoint-sets, instantiation, type-systems | Published: 2026-07-07 | Novelty: 19%

The article introduces a method for solving constrained types with sibling row variables using disjoint sets to manage instantiations, ensuring that all related row variables are instantiated simultaneously. Key code snippets include the implementation of linkConstrainedType and instantiateConstrained, which handle partitioning constraints and type instantiation respectively, maintaining domain consistency across siblings.

Here's everything you need to know about Parquet in 2026.

Source: VuTrinh. | Tags: columnar-storage, data-engineering, parquet | Published: 2026-07-08 | Novelty: 16%

The article explains that Parquet is a hybrid columnar storage format, which groups data into row groups where values from each column are stored together. This design balances the benefits of both row-wise and pure columnar formats, reducing write overhead while maintaining efficient query performance. The smallest unit of data in Parquet is called a page, with different types such as data pages containing actual data or dictionary pages for encoded values.

sqlite-migrate 0.2

Source: Simon Willison's Weblog | Tags: database, migrations, sqlite | Published: 2026-07-07 | Novelty: 16%

This beat by Simon Willison highlights the release of sqlite-migrate 0.2, focusing on updates to database migration tools for SQLite databases. Notable features include improved support for transactions and enhanced schema versioning capabilities.