Posted by L'Espoir Royal February 24, 2024

Google Gemini

Google Gemini is a series of multimodal generative AI models developed by Google. It is the largest and most capable AI model built by Google to date, capable of accepting text and image in prompts and outputting text responses. Gemini models can perform a range of multimodal tasks, from transcribing speech to captioning images. Gemini 1.5 is the next-generation model that delivers dramatically enhanced performance, with a breakthrough in long-context understanding across modalities. It shows dramatic improvements across a number of dimensions and 1.5 Pro achieves comparable quality to 1.0 Ultra, Google's largest model to date. Developers and enterprise customers can access Gemini Pro via the Gemini API in Google AI Studio or Google Cloud Vertex AI. Gemini is available in English in more than 170 countries and territories, and Google plans to expand to different modalities and support new languages and locations in the near future.

Google Gemini comes in three versions: Gemini Nano, Gemini Pro, and Gemini Ultra.

- Gemini Nano: Optimized for mobile devices like the Pixel 8, excels in on-device tasks, offering powerful AI capabilities without relying on external servers.

- Gemini Pro: Positioned as the advanced variant, powers Google AI services and serves as the foundational support for Bard, the AI chatbot, operating in data centers for complex enterprise applications.

- Gemini Ultra: The most advanced model capable of highly complex tasks, suitable for data centers and enterprise applications, expected to outperform other models in standard tests.

Gemini models are multimodal, capable of understanding and working with text, images, audio, videos, and code. Developers and enterprise users can access Gemini Pro through the Gemini API in Google AI Studio or Google Cloud Vertex AI.

Visit official website here Gemini

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Gemini ♊

// node --version # Should be >= 18 // npm install @google/generative-ai const { GoogleGenerativeAI, HarmCategory, HarmBlockThreshold, } = require("@google/generative-ai"); const MODEL_NAME = "gemini-1.0-pro"; const API_KEY = "YOUR_API_KEY"; async function runChat() { const genAI = new GoogleGenerativeAI(API_KEY); const model = genAI.getGenerativeModel({ model: MODEL_NAME }); const generationConfig = { temperature: 0.9, topK: 1, topP: 1, maxOutputTokens: 2048, }; const safetySettings = [ { category: HarmCategory.HARM_CATEGORY_HARASSMENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_HATE_SPEECH, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, ]; const chat = model.startChat({ generationConfig, safetySettings, history: [ ], }); const result = await chat.sendMessage("YOUR_USER_INPUT"); const response = result.response; console.log(response.text()); } runChat();

Développer Service

{ "captchaResult": "CAPTCHA_NOT_NEEDED", "kind": "pagespeedonline#result", "id": "https://developers.google.com/", "loadingExperience": { "id": "https://developers.google.com/", "metrics": { "FIRST_CONTENTFUL_PAINT_MS": { "percentile": 3482, "distributions": [ { "min": 0, "max": 1000, "proportion": 0.37151728768042963 }, { "min": 1000, "max": 2500, "proportion": 0.4244153519077991 }, { "min": 2500, "proportion": 0.2040673604117713 } ], "category": "SLOW" }, "FIRST_INPUT_DELAY_MS": { "percentile": 36, "distributions": [ { "min": 0, "max": 50, "proportion": 0.960628961482204 }, { "min": 50, "max": 250, "proportion": 0.02888834714773281 }, { "min": 250, "proportion": 0.010482691370063388 } ], "category": "FAST" } }, "overall_category": "SLOW", "initial_url": "https://developers.google.com/" }, "originLoadingExperience": { "id": "https://developers.google.com", "metrics": { "FIRST_CONTENTFUL_PAINT_MS": { "percentile": 2761, "distributions": [ { "min": 0, "max": 1000, "proportion": 0.4236433226493666 }, { "min": 1000, "max": 2500, "proportion": 0.45045120795679117 }, { "min": 2500, "proportion": 0.1259054693938423 } ], "category": "SLOW" }, "FIRST_INPUT_DELAY_MS": { "percentile": 45, "distributions": [ { "min": 0, "max": 50, "proportion": 0.9537371485251699 }, { "min": 50, "max": 250, "proportion": 0.03044972719889055 }, { "min": 250, "proportion": 0.01581312427593959 } ], "category": "FAST" } }, "overall_category": "SLOW", "initial_url": "https://developers.google.com/" }, "lighthouseResult": { "requestedUrl": "https://developers.google.com/", "finalUrl": "https://developers.google.com/", "lighthouseVersion": "3.2.0", "userAgent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/72.0.3584.0 Safari/537.36", "fetchTime": "2018-11-01T03:03:58.394Z", "environment": { "networkUserAgent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3559.0 Safari/537.36", "hostUserAgent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) HeadlessChrome/72.0.3584.0 Safari/537.36", "benchmarkIndex": 590.0 }, "runWarnings": [], "configSettings": { "emulatedFormFactor": "desktop", "locale": "en-US", "onlyCategories": [ "performance" ] }, "audits": { "estimated-input-latency": { "id": "estimated-input-latency", "title": "Estimated Input Latency", "description": "The score above is an estimate of how long your app takes to respond to user input, in milliseconds, during the busiest 5s window of page load. If your latency is higher than 50 ms, users may perceive your app as laggy. [Learn more](https://developers.google.com/web/tools/lighthouse/audits/estimated-input-latency).", "score": 1.0, "scoreDisplayMode": "numeric", "displayValue": "30 ms" }, "uses-rel-preconnect": { "id": "uses-rel-preconnect", "title": "Preconnect to required origins", "description": "Consider adding preconnect or dns-prefetch resource hints to establish early connections to important third-party origins. [Learn more](https://developers.google.com/web/fundamentals/performance/resource-prioritization#preconnect).", "score": 1.0, "scoreDisplayMode": "numeric", "details": { "headings": [], "type": "opportunity", "items": [], "overallSavingsMs": 0.0 } }, ... }, "categories": { "performance": { "id": "performance", "title": "Performance", "score": 0.96, "auditRefs": [ { "id": "first-contentful-paint", "weight": 3.0, "group": "metrics" }, { "id": "first-meaningful-paint", "weight": 1.0, "group": "metrics" }, ... ] } }, "categoryGroups": { "a11y-element-names": { "title": "Elements Have Discernible Names", "description": "These are opportunities to improve the semantics of the controls in your application. This may enhance the experience for users of assistive technology, like a screen reader." }, "a11y-language": { "title": "Page Specifies Valid Language", "description": "These are opportunities to improve the interpretation of your content by users in different locales." }, ... }, "i18n": { "rendererFormattedStrings": { "varianceDisclaimer": "Values are estimated and may vary.", "opportunityResourceColumnLabel": "Opportunity", "opportunitySavingsColumnLabel": "Estimated Savings", "errorMissingAuditInfo": "Report error: no audit information", "errorLabel": "Error!", "warningHeader": "Warnings: ", "auditGroupExpandTooltip": "Show audits", "passedAuditsGroupTitle": "Passed audits", "notApplicableAuditsGroupTitle": "Not applicable", "manualAuditsGroupTitle": "Additional items to manually check", "toplevelWarningsMessage": "There were issues affecting this run of Lighthouse:", "scorescaleLabel": "Score scale:", "crcLongestDurationLabel": "Maximum critical path latency:", "crcInitialNavigation": "Initial Navigation", "lsPerformanceCategoryDescription": "[Lighthouse](https://developers.google.com/web/tools/lighthouse/) analysis of the current page on an emulated mobile network. Values are estimated and may vary.", "labDataTitle": "Lab Data" } } }, "analysisUTCTimestamp": "2018-11-01T03:03:58.394Z" }

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