Updates and recent posts about GPT..

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@mashka shared a link, 1 week, 1 day ago

Paid Acquisition and Growth Marketing, xygeni

You don’t have a vulnerability problem. You have a prioritization problem.

Most teams today don’t struggle to find vulnerabilities; they struggle to decide what to fix first. With SAST, SCA, secrets, and CI/CD checks all generating signals, the real challenge is prioritization: what’s actually exploitable, what’s reachable, and what can be fixed without breaking things. Instead of relying only on severity, modern teams are shifting toward risk-based remediation, combining exploitability, context, and stability, while reducing noise across tools and automating safe fixes through PRs. If you’re dealing with alert fatigue or slow remediation cycles, this checklist is a practical starting point → https://go.xygeni.io/ai-driven-remediation-risk-prioritization-checklist

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@varbear shared a link, 1 week, 3 days ago

FAUN.dev()

A new chapter for the Nix language, courtesy of WebAssembly

Determinate Nix introduces experimental WebAssembly host calls. It lets Nix invoke Wasm modules, pass and return complex Nix values, and support Rust, C++, and Zig toolchains. It runs on Wasmtime/Cranelift and slashes runtime and memory: Fibonacci test 0.33s vs 79.33s, 30MB vs 4.5GB. Per-call instan.. read more

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@varbear shared a link, 1 week, 3 days ago

FAUN.dev()

Using Rust and Postgres for everything: patterns learned over the years

Rust and PostgreSQL are considered the best tools in the software world due to their performance and reliability. Rewriting a backend service from Go to Rust led to significant improvements in processing speed and memory usage. Using sqlx for database operations and leveraging PostgreSQL features li.. read more

GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.