Google just launched Simplify in its iOS app, powered by Gemini models designed for minimally-lossy text simplification. Unlike basic summarization that cuts content, the system preserves nuance and original details while making dense language readable. In trials, it improved reading comprehension accuracy on complex medical texts by 15%.
Google just added native compatibility for Gemini models directly inside the OpenAI Library and REST API. Developers can now switch to Gemini using Chat Completions and Embeddings endpoints without rewriting code—simply point the base URL to Google and plug in a Gemini API key.
Google and Sourcegraph just shared test results from plugging Gemini 1.5 Flash's 1M-token context into the Cody coding assistant. The massive context dropped hallucination rates from 18.97% down to 10.48% on complex codebase tasks, while custom caching trimmed initial response latency from 40 seconds to roughly 5.
Google just graduated Gemini 1.5 Flash-8B from experimental status to general availability. The ultra-lightweight model nearly matches the standard 1.5 Flash on key benchmarks while offering Google's lowest price per token yet and doubled rate limits of up to 4,000 requests per minute.
Google just rolled out updated versions of its Gemini 1.5 Pro and Flash models, boosting math reasoning by around 20% and cutting unnecessary refusals. The company also slashed 1.5 Pro input token costs by 64% and output tokens by 52%, while ramping up API rate limits. Why it matters: Developers can now run faster and sharper frontier models at substantially lower operating costs.
Google just rolled out three experimental models: an ultra-compact Gemini 1.5 Flash-8B, a significantly upgraded Flash, and a stronger Pro model that levels up coding and complex prompt reasoning. Both maintain 1M token context windows and are available to test for free in Google AI Studio and the Gemini API.
Google just slashed Gemini 1.5 Flash pricing, cutting input costs by 78% to $0.075 per million tokens and output by 71% starting August 12. The update also rolls out text tuning to all developers via AI Studio and the Gemini API, alongside native multimodal understanding for image-heavy PDFs.
Google just upgraded the free version of Gemini to its speedier 1.5 Flash model, bringing noticeable latency drops, stronger reasoning, and a 4x context boost to 32K tokens. Responses now include clickable source chips to tackle hallucinations, with file uploads and chart visualization rolling out soon. Why it matters: Google is making its fastest frontier capabilities accessible to everyone without a paywall.
Google just opened up Gemini 1.5 Pro's 2-million-token context window to all developers, removing the waitlist. Both 1.5 Pro and Flash now also feature built-in Python code execution in an offline sandbox to tackle math and data reasoning, alongside Gemma 2 landing in Google AI Studio. Why it matters: developers can now feed entire codebases into Gemini while letting the model verify its own math by running code.
