Hello from TASTEDEV,
We would like to introduce TASTEREMOTE, a remote desktop project that lets you view and control a remote computer through a web browser. Install the host app on the PC you want to access, then connect from a browser without installing a separate viewer app. You can use the TASTEDEV-operated server or run your own server.
TASTEREMOTE is under active development as we continue to improve its features and stability. Depending on your setup, you may encounter bugs or features that are not yet fully polished. Please review the supported operating systems and known limitations before getting started.
If you run into a problem or have feedback, please leave a comment or question on the product page. Including your operating system, TASTEREMOTE version, and the steps that led to the issue will help us investigate and improve the project.
Product and downloads: https://tastedev.net/products/remote
Documentation: https://tastedev.net/docs/remote
For setup instructions and development updates, follow the development log through the Learn more link below.
There is still work to do, and your feedback will help us improve TASTEREMOTE step by step. Thank you for your interest, for trying the project, and for sharing your experience with us.
The TASTEDEV Team
On November 2 at 21:02:19 KST, GitHub Trending daily showed vercel-labs/agent-desktop with 7,864 total stars and 2,243 stars today. The Vercel Labs README describes a CLI and C library that inspect and operate desktop apps through OS accessibility-tree element references. Developers can examine the observe–act–verify loop for agents. This is a daily observation, not an AI vendor’s official plugin, skill or new-version announcement. Reliability and safety were not independently tested; no installations, usage ranking or growth were inferred.
On November 2, OpenAI introduced LifeVal to assess practical AI performance on everyday tasks. It describes tasks drawn from time-use studies and a representative survey of 3,995 people, covering care, education, shopping and administration, with browser, computer and connector workflows. Developers can consider evaluating completed actions beyond chat responses. Example scores are vendor-reported results, not independent validation or general success rates. This is not a new model, API or dataset-distribution announcement. Only the source date was verified; no time was inferred.
On November 2, OpenAI raised the critical base-reward ceiling for core products including ChatGPT, Codex and API Platform to $30,000. Exceptional critical findings may qualify for up to $100,000, or about $172,000 with eligible bonuses; these are not universal payouts. New ranges apply to unpaid reports, with differences for awards in the preceding 30 days when revised base and loyalty criteria yield more. Researchers can review scope and eligibility. Vulnerability and payout scenarios are illustrative.
On November 2, OpenAI described Pando, its Rust-based backend serving an internal monorepo. It preserves per-ref ordering and causal dependencies rather than a single repository-wide snapshot, and reuses packfiles for concurrent pushes and fetches while retaining Git client and protocol compatibility. Developers can examine consistency boundaries and cache-reuse tradeoffs. This is a company-reported internal architecture case, not an independent performance benchmark or public SDK launch.
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