{"id":22449,"date":"2024-11-02T09:44:18","date_gmt":"2024-11-02T01:44:18","guid":{"rendered":"https:\/\/www.1ai.net\/?p=22449"},"modified":"2024-11-02T09:44:18","modified_gmt":"2024-11-02T01:44:18","slug":"%e8%b0%b7%e6%ad%8c%e6%8e%a8%e5%87%ba%e6%96%b0%e4%bb%98%e8%b4%b9%e5%8a%9f%e8%83%bd%ef%bc%8c%e5%80%9f%e5%8a%a9%e6%90%9c%e7%b4%a2%e7%bb%93%e6%9e%9c%e5%af%b9%e6%8a%97ai%e5%b9%bb%e8%a7%89%e9%97%ae%e9%a2%98","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/22449.html","title":{"rendered":"Google Launches New Paid Feature to Fight AI Illusion Problem with Search Results"},"content":{"rendered":"<p><a href=\"https:\/\/www.1ai.net\/en\/tag\/%e8%b0%b7%e6%ad%8c\" title=\"[View articles tagged with [Google]]\" target=\"_blank\" >Google<\/a>The company issued a press release yesterday (October 31) announcing the launch of Grounding with Google Search functionality in its Google AI Studio and Gemini APIs, which supports users through the<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e8%b0%b7%e6%ad%8c%e6%90%9c%e7%b4%a2\" title=\"[Sees articles with tags]\" target=\"_blank\" >Google Search<\/a>Verify that the AI answers the content.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-22450\" title=\"fda0548dj00smavgp0048d000sg008lp\" src=\"https:\/\/www.1ai.net\/wp-content\/uploads\/2024\/11\/fda0548dj00smavgp0048d000sg008lp.jpg\" alt=\"fda0548dj00smavgp0048d000sg008lp\" width=\"1024\" height=\"309\" \/><\/p>\n<p>The Challenge of Mainstream Large Models<\/p>\n<p>Most Large Language Models (LLMs), including OpenAI, Anthropic, and Google, have 1 knowledge cutoff due to their training dataset, and thus perform very poorly in answering recent relevant events.<\/p>\n<p>New Features<\/p>\n<p>The Grounding with Google Search feature is designed to address the lack of response of large language models (LLMs) when dealing with the latest events. By combining this with real-time search, developers can obtain more accurate and time-sensitive information, improving the reliability and usefulness of AI applications.<\/p>\n<p>Quoting from Google's official press release blurb, the benefits of the feature are attached below:<\/p>\n<ul>\n<li><strong>Reduced hallucinations:<\/strong>The new feature ensures that AI apps deliver more accurate facts to users by providing reality-based information.<\/li>\n<li><strong>Get the latest information:<\/strong>Combined with Google search, the model is able to access information in real time, making it more relevant in multiple scenarios.<\/li>\n<li><strong>Enhance credibility:<\/strong>Enhances the transparency of AI applications by providing links to support, encouraging users to click through for more information.<\/li>\n<li><strong>Rich information content:<\/strong>Information extracted from Google searches can provide more detailed context for many queries.<\/li>\n<\/ul>\n<p>While the \"Integration with Google Search\" feature significantly improves the accuracy of information, it costs developers $35 per 1,000 basic queries.<\/p>","protected":false},"excerpt":{"rendered":"<p>Google Inc. issued a press release yesterday (October 31) announcing the launch of Grounding with Google Search functionality in its Google AI Studio and Gemini APIs to support users in verifying the content of AI responses via Google Search. Challenges for Mainstream Large Language Models Most Large Language Models (LLMs), including OpenAI, Anthropic, and Google, have a knowledge cutoff due to their training datasets, and therefore perform poorly when answering recent, relevant events. New Feature Description The Grounding with Google Search feature is designed to solve the problem of large<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[3042,281,1881],"collection":[],"class_list":["post-22449","post","type-post","status-publish","format-standard","hentry","category-news","tag-ai","tag-281","tag-1881"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/22449","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=22449"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/22449\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=22449"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=22449"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=22449"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=22449"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}