Signal Adds Optional Phone-Number-Free Sign-Up, Paid via Zero-Knowledge Credentials

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Signal has introduced an optional registration path that does not require a phone number, currently in its Android 8.28.0 beta released 16 September 2026. Accounts are identified by an Account ID and Account Key rather than any verified personal detail, and a one-time in-app purchase of about 3 USD in the US serves as the anti-spam measure. Zero-knowledge proofs, reused from Signal's donation badge system, are used so the payment cannot be linked to the new account. Google Play still records the purchase on the user's side, a limitation Signal acknowledges, and additional payment methods are planned. The feature is Android-only and unavailable on devices without Play Services for now.

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DeepSeek-Linked Paper Proposes Engram, a Lookup Memory Module for Transformers

A new paper from a DeepSeek-linked team argues that large language models waste computation by re-deriving static facts on every query, and proposes Engram, a module that retrieves stored knowledge through a direct lookup. Scaled to 27 billion parameters, the authors report that it outperforms a mixture-of-experts baseline with the same parameter and compute budget across the benchmarks they tested. The largest gains appear on reasoning and code tasks rather than pure knowledge tests. The authors frame the design as a budgeting problem, finding a U-shaped trade-off between neural computation and static memory, with an optimal mix in between. Their Engram-27B model reallocates parameters from expert modules into a 5.7 billion parameter memory, which they say frees the network's early layers and attention capacity for harder work.

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ProgrammingDEV Community ·

Guide: Running a 4B Qwen3 Chat Model Locally on Windows with a Small NVIDIA GPU

A DEV Community guide explains how to run the 4-billion-parameter Qwen3-4B chat model on a Windows PC with an NVIDIA RTX 30, 40, or 50 series GPU, using a prebuilt zip from the author's open-source Pingala-8 project. The only required install is a recent NVIDIA driver, since the package bundles the CUDA runtime files and avoids the full CUDA Toolkit and any compilation. Users extract the zip and run a batch script that downloads the roughly 1.24 GB model from Hugging Face on first launch, then starts a local llama.cpp server and opens a browser-based chat page at 127.0.0.1:8080. The author reports about 200 tokens per second on an RTX 5070 Ti Laptop GPU and notes that the setup requires roughly 5 GB of free disk space and an internet connection for the initial download.

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ProgrammingDEV Community ·

How to Use AI Tools for Studying Without Losing the Learning

AI tools can speed up studying and sharpen focus, but only if the learner stays in control of the process. Suggested practices include stating a specific learning goal, asking the tool to teach step by step and then explaining the material back in one's own words. Turning notes into practice questions and answering from memory before checking is recommended over rereading. Learners should also verify AI summaries against course notes or trusted sources, since details can be lost or oversimplified. Overall, the guidance is to use AI to support active, regular practice rather than to replace the thinking itself.

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ProgrammingDEV Community ·

Sloth Reads: An Open-Model Overnight Filter for Your Read-Later Pile

Sloth Reads is an open-source project by Souvik Biswas, built for a Hacktoberfest AI challenge, aimed at people who save far more articles than they ever read. Users save links as usual, and an open model reviews them overnight, delivering a one-minute morning brief with worth-reading, skim, or skip verdicts. A voice reader with word highlighting helps users consume the pieces chosen for them. A public audit of the launch post, live app, and README praises the product's clear positioning and emphasis on verdicts over summaries. The review also flags open questions for new visitors, such as whether they can try the app without signing in or connecting private accounts.

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