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Answer any❓with a ⭕️ Launching January 31st on #Pixel8 and Pixel 8 Pro, Circle to Search is a new way to search anything without switching apps. Just draw a circle around an image, text, or video, and Google AI finds it, so you can round up answers fast:

Made by Google

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355,605 次观看 • 2 年前 •via X (Twitter)

科学技术 #Pixel8

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Circling back on this...Circle to Search is rolling out now to #Pixel7 and Pixel 7 Pro! 🎉 Just draw a circle with your finger around an image, text, or video to quickly find all the info you need.¹ Learn more about our latest #FeatureDrop²:

Circling back on this...Circle to Search is rolling out now to #Pixel7 and Pixel 7 Pro! 🎉 Just draw a circle with your finger around an image, text, or video to quickly find all the info you need.¹ Learn more about our latest #FeatureDrop²:

Made by Google

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When you move to a new city, and wonder where the safest neighborhood to live in is. Locate the government house/secretariat on your google map, draw a circle around it. Every residential area few centimeters away from that circle is your answer.

When you move to a new city, and wonder where the safest neighborhood to live in is. Locate the government house/secretariat on your google map, draw a circle around it. Every residential area few centimeters away from that circle is your answer.

your boy Armani 🫂

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This interface is a little "hidden" but you can access it easily. First, check that you have access to Google Search's AI functions. 1. Go to labs .google 2. Click on "Get started" in the Google Search category 3. Activate "SGE generative AI in Search" Next, write a prompt like I already showed you to draw an image in Google. Example: “draw a submarine in the sky” Once your images are generated, click on one then “Edit”.

This interface is a little "hidden" but you can access it easily. First, check that you have access to Google Search's AI functions. 1. Go to labs .google 2. Click on "Get started" in the Google Search category 3. Activate "SGE generative AI in Search" Next, write a prompt like I already showed you to draw an image in Google. Example: “draw a submarine in the sky” Once your images are generated, click on one then “Edit”.

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Awesome way to AI is here! Meet the latest Samsung Galaxy A17 5G, packed with core AI features like Gemini Live and Circle to Search. What you couldn’t earlier, Now you can with the new awesome!

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We’re testing SearchGPT, a temporary prototype of new AI search features that give you fast and timely answers with clear and relevant sources. We’re launching with a small group of users for feedback and plan to integrate the experience into ChatGPT.

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You can now generate public endpoints, UI snippets, and a MCP server with AI Search: making it easy to add search to your website or connect AI agents.

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Use video generation in Google Gemini App to turn words or photos into videos with sound🔊Type what you want to create to bring any idea to life in minutes.¹ And, if you buy #Pixel10 Pro or Pixel 10 Pro Fold, you get a year of Google AI Pro on us:² #MadeByGoogle

Use video generation in Google Gemini App to turn words or photos into videos with sound🔊Type what you want to create to bring any idea to life in minutes.¹ And, if you buy #Pixel10 Pro or Pixel 10 Pro Fold, you get a year of Google AI Pro on us:² #MadeByGoogle

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Whoa, you can now set headers for your app store connect page, and replace your screenshots on search results with a banner And both can be an image or video

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Woow Google has just rolled out the AI model Flash Thinking 2.0 This is the first reasoning model capable of accessing YouTube and it changes everything: - Search for a video on your topic - Ask Gemini to think about the video - You'll have a tailor-made result in 10 sec. And it's even connected to Google Search and Maps!

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The Google AI Professional Certificate is live on Coursera and it’s free! So excited to be teaching in this. With Gemini 3.1 Pro, I’ll show you how to vibe code apps + use AI to give you a massive edge at work. And you get 3 free months of Google AI Pro. See you in class! :)

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Big moment for Postgres! Search has always been Postgres' weak spot, and everyone just accepted it. If you needed a real relevance-ranked keyword search, the default answer was to spin up Elasticsearch or add Algolia and deal with the data sync headaches forever. The problem isn't that Postgres can't do text search. It can. But the built-in `ts_rank` function uses a basic term frequency algorithm that doesn't come close to what modern search engines deliver. So teams end up: - Running a separate Elasticsearch cluster just for search - Building sync pipelines that inevitably drift out of consistency - Paying for managed search services that charge per query - Accepting mediocre search relevance because "good enough" ships faster But this is actually a solvable problem. You can realistically bring industry-standard search ranking directly into Postgres, which eliminates the need for external infra entirely. This exact solution is now available with the newly open-sourced pg_textsearch by Tiger Data - Creators of TimescaleDB, a Postgres extension that brings true BM25 relevance ranking into the database. BM25 is the algorithm behind Elasticsearch, Lucene, and most modern search engines. Now it runs natively in Postgres. Here's what pg_textsearch enables: - True BM25 ranking with configurable parameters (the same algorithm powering production search systems) - Simple SQL syntax: `ORDER BY content 'search terms'` - Works with Postgres text search configurations for multiple languages - Pairs naturally with pgvector for hybrid keyword + semantic search That last point matters a lot for RAG apps. The video below shows this in action, and I worked with the team to put this together. You can now do hybrid retrieval (combining keyword matching with vector similarity) in a single database, without stitching together multiple systems. The syntax is clean enough that you can add relevance-ranked search to existing queries in minutes. pg_textsearch is fully open-source under the PostgreSQL license. You can find a link to their GitHub repo in the next tweet.

Big moment for Postgres! Search has always been Postgres' weak spot, and everyone just accepted it. If you needed a real relevance-ranked keyword search, the default answer was to spin up Elasticsearch or add Algolia and deal with the data sync headaches forever. The problem isn't that Postgres can't do text search. It can. But the built-in `ts_rank` function uses a basic term frequency algorithm that doesn't come close to what modern search engines deliver. So teams end up: - Running a separate Elasticsearch cluster just for search - Building sync pipelines that inevitably drift out of consistency - Paying for managed search services that charge per query - Accepting mediocre search relevance because "good enough" ships faster But this is actually a solvable problem. You can realistically bring industry-standard search ranking directly into Postgres, which eliminates the need for external infra entirely. This exact solution is now available with the newly open-sourced pg_textsearch by Tiger Data - Creators of TimescaleDB, a Postgres extension that brings true BM25 relevance ranking into the database. BM25 is the algorithm behind Elasticsearch, Lucene, and most modern search engines. Now it runs natively in Postgres. Here's what pg_textsearch enables: - True BM25 ranking with configurable parameters (the same algorithm powering production search systems) - Simple SQL syntax: `ORDER BY content 'search terms'` - Works with Postgres text search configurations for multiple languages - Pairs naturally with pgvector for hybrid keyword + semantic search That last point matters a lot for RAG apps. The video below shows this in action, and I worked with the team to put this together. You can now do hybrid retrieval (combining keyword matching with vector similarity) in a single database, without stitching together multiple systems. The syntax is clean enough that you can add relevance-ranked search to existing queries in minutes. pg_textsearch is fully open-source under the PostgreSQL license. You can find a link to their GitHub repo in the next tweet.

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215,344 次观看 • 6 个月前