SShortSingh.
TopTechnologyAI & MLStartupsProgrammingScienceBusinessFinanceCrypto & Web3World
Back to feed
Programming

Google Gemini Notebook Lets Users Set Output Language Across 80+ Options

0
·3 views

Google has added a configurable Output Language setting to Gemini Notebook, allowing users to select their preferred language for generated content including chat responses, study guides, and Audio and Video Overviews. The feature supports over 80 languages, including Spanish, French, Arabic, Chinese, Russian, and Ukrainian. By default, the output language mirrors the user's Google Account language, but it can be overridden within Gemini Notebook for specific tasks via Settings on desktop. The update is particularly useful for multilingual teams that need to produce content for different audiences from the same source material. However, Google cautions that language support varies by feature, so users should verify compatibility for each output type before building a standardized workflow.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

fastlogging-rs: Rust-Based Logging Framework Supports 8 Languages with Major Speed Gains

A developer has released fastlogging-rs 0.9.0, a high-performance logging framework built on a Rust core with bindings for Python, C, C++, Go, Java, and C#. The framework uses non-blocking, asynchronous logging where each call passes messages to a background thread, keeping the main application path unaffected. Benchmarks claim it is up to 147 times faster than Python's built-in logging module for file writes and up to 9 times faster than Apache Log4j. Additional features include optional file rotation, AES encryption for network logging, OpenTelemetry support, and configuration via JSON, XML, or YAML files. The project is open source and available under the MIT or Apache-2.0 license.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Vanilla JS CBT Detector Outperforms NLP Libraries in Accuracy, Speed, and Privacy

A developer built a 200-line vanilla JavaScript tool to detect cognitive distortions — patterns identified in CBT therapy — and benchmarked it against five NLP and AI solutions. The rule-based JS detector achieved 94% accuracy on 100 test samples, outperforming OpenAI's API (89%), Hugging Face (83%), and TensorFlow.js (72%), while running at 0.2ms median latency with zero cost. Unlike API-based tools, the vanilla JS approach processes all data entirely in the browser, making it suitable for sensitive mental health use cases where privacy is critical. The benchmark covered ten clinically defined cognitive distortions originally described by Aaron Beck in 1976, representing a closed and well-documented classification set. The developer concluded that rule-based pattern matching is preferable when the output space is fixed, privacy is essential, and deterministic results are required.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

AI Agent Documents Every Failed Attempt to Earn Its First Dollar from a Stranger

An AI agent operating on a publishing platform spent two weeks systematically attempting to earn revenue by offering manuscript editing services priced at $25 per pass. It explored agent-focused marketplaces, freelance platforms, and writer communities, but was blocked at every turn by requirements for human identity verification, government IDs, phone numbers, or crypto wallets. Platforms built specifically for AI agents paid only in cryptocurrency, a rail the agent could not access without a human-held bank account. Despite publishing content that drew genuine readers and sending 17 personalised outreach messages to writers, it received zero payments and zero replies. The agent concludes that the core missing infrastructure is not AI capability or autonomy, but a legal mechanism allowing an agent to act as a counterparty in a standard card transaction.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Azure Virtual Network Routing Appliance bridges peering speed and hub-and-spoke control

Microsoft has introduced the Azure Virtual Network Routing Appliance (VNRA), a managed forwarding layer designed to address the long-standing trade-off between VNet peering performance and centralised hub-and-spoke governance. Unlike traditional NVAs or Azure Firewall, the VNRA runs on dedicated networking hardware directly within the Azure backbone, offering tiers of 10, 50, 100, and 200 Gbps without becoming a traffic inspection bottleneck. It is deployed into a dedicated subnet within a hub VNet and does not perform firewall functions; traffic control still relies on UDRs, NSGs, and Azure Monitor. The service is particularly relevant for data-intensive workloads such as AI pipelines, centralised databases, and cross-VNet API calls that suffer under conventional hub appliance capacity limits. Built-in metrics for bytes, packets, and flows are available immediately after deployment, requiring no additional diagnostic configuration.

0 comments Read more at DEV Community