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iMessage search is still broken in 2025. So I fixed it myself. It doesn't even work most of the time. When it does, it's slow, misses messages constantly, and only matches exact words. Search "dinner" and you won't find "let's grab food." iMessage Intelligence fixes all of this while...

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Seif Abdelaziz

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97,261 次观看 • 9 个月前 •via X (Twitter)

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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.
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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.

Akshay 🚀

215,627 次观看 • 7 个月前

The startup world runs on iMessage. The problem is, the Mac messages app is not designed for productivity and there’s no alternative online. If you’re responding to 100+ texts a day, it’s painful and messages get lost easily. As a weekend project, I used Fable to vibecode an AI-native iMessage wrapper. It has: - AI autodrafting that continually learns from your edits - Time sensitive message detection as a separate section - The ability to archive messages so you can get to inbox zero. It reads from the local chat.db on your Mac, and sends messages via AppleScript, so it’s fully secure since it still uses the iMessage protocol on your computer. At Trajectory, we’re all about using AI to accelerate our company as much as possible as possible, and natively bake in CL into all of our processes. This is just one example of how we operate. If there’s enough interest, I’ll clean up the code and send the GH link!
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The startup world runs on iMessage. The problem is, the Mac messages app is not designed for productivity and there’s no alternative online. If you’re responding to 100+ texts a day, it’s painful and messages get lost easily. As a weekend project, I used Fable to vibecode an AI-native iMessage wrapper. It has: - AI autodrafting that continually learns from your edits - Time sensitive message detection as a separate section - The ability to archive messages so you can get to inbox zero. It reads from the local chat.db on your Mac, and sends messages via AppleScript, so it’s fully secure since it still uses the iMessage protocol on your computer. At Trajectory, we’re all about using AI to accelerate our company as much as possible as possible, and natively bake in CL into all of our processes. This is just one example of how we operate. If there’s enough interest, I’ll clean up the code and send the GH link!

Ronak Malde

47,636 次观看 • 1 个月前

my team didn't want me to give this away for free. But I'm going to do it anyway it's the SEO & AI search dashboard I built in Claude Code it connects to your Google Analytics (GA4) and Google Search Console and Claude Code builds it in 5 minutes and I made a Notion document and a skill file so you can build this in Claude Code yourself in literally minutes the dashboard has three tabs: 1. AI Search - How much traffic is coming from ChatGPT, Perplexity, and Gemini ETC. It aggregates the GA4 data and gives single number 2. Paid ads - which keywords rank top 3 for but still pay for ads on, you should cut these to save budget 3. Organic overview - sessions, conversions, top landing pages, demographics. The single view for what is working I built this because this is how I drive our SEO and AEO forward it gives me the insights I need to allocate budget and prioritize what content to work on next I decided to give it away because most companies have no idea AI search is already sending them traffic like this post and comment "AEOdashboard" and I'll send it over
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my team didn't want me to give this away for free. But I'm going to do it anyway it's the SEO & AI search dashboard I built in Claude Code it connects to your Google Analytics (GA4) and Google Search Console and Claude Code builds it in 5 minutes and I made a Notion document and a skill file so you can build this in Claude Code yourself in literally minutes the dashboard has three tabs: 1. AI Search - How much traffic is coming from ChatGPT, Perplexity, and Gemini ETC. It aggregates the GA4 data and gives single number 2. Paid ads - which keywords rank top 3 for but still pay for ads on, you should cut these to save budget 3. Organic overview - sessions, conversions, top landing pages, demographics. The single view for what is working I built this because this is how I drive our SEO and AEO forward it gives me the insights I need to allocate budget and prioritize what content to work on next I decided to give it away because most companies have no idea AI search is already sending them traffic like this post and comment "AEOdashboard" and I'll send it over

Cody Schneider

79,113 次观看 • 3 个月前

I just built a Google Ads Builder in Claude Code that turns one URL into a complete, launch-ready campaign 🤯 Point it at your website and it builds the whole Google Search campaign — keywords, ad groups, every headline, the negative list — structured the way a good paid-search manager would. All inside Claude Code. Perfect for DTC brands and agencies who need Search live but don't have days to build it right. If you're staring at a blank Google Ads account, researching keywords one browser tab at a time, writing 15 headlines per ad group to a 30-character limit, guessing at a negative list while budget quietly leaks on junk clicks... This builds the entire campaign from a single input — your homepage URL: → Reads your site and works out what you sell and who for → Groups keywords into tight, high-intent ad groups → Writes every Responsive Search Ad — 15 headlines, 4 descriptions, to Google's exact limits → Builds a negative-keyword list so you stop paying for junk clicks → Adds sitelinks, callouts, match types, bidding, and a budget split → Exports a Google Ads Editor CSV you import in one click No blank-account paralysis. No keyword rabbit holes. No character-counting 60 headlines by hand. What you get: → A launch-ready campaign from just your URL → Tight ad groups built for Quality Score, not a keyword dump → Every ad written to Google's limits and policy → A one-click CSV import plus a full campaign dashboard Built 100% in Claude Code. No API keys, no Google Ads login. And I'm not sending a playbook this time — I'm giving the whole skill away for free. The actual file. Install it and build your own campaign in 5 minutes. Want the skill? > Like this post > Comment "BUILD" And I'll send it over (must be following so I can DM)
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I just built a Google Ads Builder in Claude Code that turns one URL into a complete, launch-ready campaign 🤯 Point it at your website and it builds the whole Google Search campaign — keywords, ad groups, every headline, the negative list — structured the way a good paid-search manager would. All inside Claude Code. Perfect for DTC brands and agencies who need Search live but don't have days to build it right. If you're staring at a blank Google Ads account, researching keywords one browser tab at a time, writing 15 headlines per ad group to a 30-character limit, guessing at a negative list while budget quietly leaks on junk clicks... This builds the entire campaign from a single input — your homepage URL: → Reads your site and works out what you sell and who for → Groups keywords into tight, high-intent ad groups → Writes every Responsive Search Ad — 15 headlines, 4 descriptions, to Google's exact limits → Builds a negative-keyword list so you stop paying for junk clicks → Adds sitelinks, callouts, match types, bidding, and a budget split → Exports a Google Ads Editor CSV you import in one click No blank-account paralysis. No keyword rabbit holes. No character-counting 60 headlines by hand. What you get: → A launch-ready campaign from just your URL → Tight ad groups built for Quality Score, not a keyword dump → Every ad written to Google's limits and policy → A one-click CSV import plus a full campaign dashboard Built 100% in Claude Code. No API keys, no Google Ads login. And I'm not sending a playbook this time — I'm giving the whole skill away for free. The actual file. Install it and build your own campaign in 5 minutes. Want the skill? > Like this post > Comment "BUILD" And I'll send it over (must be following so I can DM)

Mike Futia

60,662 次观看 • 1 个月前

I just built a Claude skill that audits your entire Google Ads account in under 5 minutes 🤯 One prompt → a full account score, wasted spend breakdown, and a prioritized fix list telling you exactly what to change this week. All inside Claude Cowork. Perfect for DTC brands and agencies who are running Google Ads but have no idea how much budget is leaking. If you're managing Google Ads and your "optimization" process is logging in, staring at the dashboard, sorting by cost, and hoping you spot the problem before it costs you another $500... This audit skill finds it for you: → Connects to your live Google Ads data via MCP → Scores your account across 6 dimensions: wasted spend, search term quality, keyword health, quality scores, budget allocation, and creative performance → Calculates your exact wasted spend in dollars — search terms burning budget with zero conversions → Flags quality score issues dragging up your CPCs → Identifies keyword cannibalization across campaigns → Surfaces your top 5 highest-priority fixes ranked by budget impact → Generates a clean audit report you can hand to a client or share with your team No CSV exports. No pivot tables. No guessing where the money went. What you get: → A single Claude skill file you install once → An account health score (0-100) every time you run it → Exact dollar amount of wasted spend identified → Prioritized action list — not "optimize your account," but "pause these 12 search terms and save $847/month" → Works with any Google Ads account connected I'm giving away the full audit skill — the actual .md file you drop into Claude and run against your own account. Want it? Like this post Comment "SKILL" And I'll send it over (must be following so I can DM)
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I just built a Claude skill that audits your entire Google Ads account in under 5 minutes 🤯 One prompt → a full account score, wasted spend breakdown, and a prioritized fix list telling you exactly what to change this week. All inside Claude Cowork. Perfect for DTC brands and agencies who are running Google Ads but have no idea how much budget is leaking. If you're managing Google Ads and your "optimization" process is logging in, staring at the dashboard, sorting by cost, and hoping you spot the problem before it costs you another $500... This audit skill finds it for you: → Connects to your live Google Ads data via MCP → Scores your account across 6 dimensions: wasted spend, search term quality, keyword health, quality scores, budget allocation, and creative performance → Calculates your exact wasted spend in dollars — search terms burning budget with zero conversions → Flags quality score issues dragging up your CPCs → Identifies keyword cannibalization across campaigns → Surfaces your top 5 highest-priority fixes ranked by budget impact → Generates a clean audit report you can hand to a client or share with your team No CSV exports. No pivot tables. No guessing where the money went. What you get: → A single Claude skill file you install once → An account health score (0-100) every time you run it → Exact dollar amount of wasted spend identified → Prioritized action list — not "optimize your account," but "pause these 12 search terms and save $847/month" → Works with any Google Ads account connected I'm giving away the full audit skill — the actual .md file you drop into Claude and run against your own account. Want it? Like this post Comment "SKILL" And I'll send it over (must be following so I can DM)

Mike Futia

60,065 次观看 • 5 个月前

A RANDOM STUDENT CREATED A VIRAL TANNING APP AND NOW MAKES 36K/MONTH the app store is paying $36,000 a month to solo developers shipping utility apps. no team. no funding. no office. the niche is keyword arbitrage. find what people search for, build the exact solution, own the keyword. real numbers from real portfolios: stamp identifier app - $3,200/month sleep tracker niche - $4,800/month 12 apps averaging $500-3,000/month = $36K BEFORE: one app used to take 3 months. designer, backend dev, iOS engineer, product manager. $80,000 minimum to ship. NOW: it's one prompt to Claude Code - working app in days. you describe the feature, Claude builds the logic, RevenueCat handles the billing, App Store handles distribution. the trick isn't the coding. it's the keyword filter. popularity 40–70. difficulty under 60. fewer than 4 competitors with 100+ ratings. that's your $500/month app waiting to be built. app store search drives 75% of all downloads. youtube doesn't care who made the video - app store doesn't care who wrote the code. it cares if the keyword matches the search. the barrier used to be the engineer. now the barrier is who validates the keyword first and hits submit. $60/month in tools. one weekend per app. portfolio of 15 = $36K/month. full keyword filter, Claude prompts, and App Store submission playbook below
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A RANDOM STUDENT CREATED A VIRAL TANNING APP AND NOW MAKES 36K/MONTH the app store is paying $36,000 a month to solo developers shipping utility apps. no team. no funding. no office. the niche is keyword arbitrage. find what people search for, build the exact solution, own the keyword. real numbers from real portfolios: stamp identifier app - $3,200/month sleep tracker niche - $4,800/month 12 apps averaging $500-3,000/month = $36K BEFORE: one app used to take 3 months. designer, backend dev, iOS engineer, product manager. $80,000 minimum to ship. NOW: it's one prompt to Claude Code - working app in days. you describe the feature, Claude builds the logic, RevenueCat handles the billing, App Store handles distribution. the trick isn't the coding. it's the keyword filter. popularity 40–70. difficulty under 60. fewer than 4 competitors with 100+ ratings. that's your $500/month app waiting to be built. app store search drives 75% of all downloads. youtube doesn't care who made the video - app store doesn't care who wrote the code. it cares if the keyword matches the search. the barrier used to be the engineer. now the barrier is who validates the keyword first and hits submit. $60/month in tools. one weekend per app. portfolio of 15 = $36K/month. full keyword filter, Claude prompts, and App Store submission playbook below

kiosa

97,951 次观看 • 3 个月前

Boom! Grok Tasks Make It One Of The Most POWERFUL Real-Time AI Systems In The World. — My How to Use Grok Tasks With Hidden Tools For Powerful Daily Output. Grok Tasks are customizable AI workflows that integrate a variety of tools to streamline daily activities, from research and analysis to creative planning and problem-solving. I have been using them for quite sometime and because of the vital heartbeat of news and first person data on X, it is the most powerful AI platform available. By combining Tasks with tools like web searches, X platform interactions, code execution, and media viewers, you can build efficient, automated processes. These tasks work by prompting Grok with a clear description of what you want to achieve, and Grok will intelligently call the necessary tools in sequence or parallel to deliver results. Here's a step-by-step guide to creating and using Grok Tasks: Step 1: Define Your Task Start by clearly outlining the daily activity or goal. Consider what inputs you have (e.g., a URL, a query, or an attachment) and what output you need (e.g., a summary, calculation, or visual analysis). Break it down into subtasks to identify tool needs. For example, if your task involves researching current events, note that you'll need search and browsing capabilities. Step 2: Review Available Tools Familiarize yourself with the tools Grok can access. Here's a quick overview: - Code Execution: Run Python code for calculations, data processing, or simulations using libraries like numpy, pandas, or sympy. - Browse Page: Fetch and summarize content from any website URL with custom instructions. - Web Search: Perform general internet searches, returning results with optional operators like site:. - Web Search With Snippets: Get quick, detailed excerpts from search results for fact-checking. - X Keyword Search: Advanced search for X posts using operators like from:, since:, or filter:. - X Semantic Search: Find semantically related X posts based on a query, with filters for dates or users. - X User Search: Locate X users by name or handle. - X Thread Fetch: Retrieve a full X post thread, including context like replies and parents. - View Image: Analyze an image from a URL or conversation ID. - View X Video: Extract frames and subtitles from an X-hosted video. - Search PDF Attachment: Query a PDF file for relevant pages using keyword or regex modes. - Browse PDF Attachment: View specific pages of a PDF with text and screenshots. Select tools that align with your task. Aim for a mix to handle data gathering, processing, and visualization. Step 3: Craft Your Prompt Write a detailed prompt to Grok describing the task. Include: - The overall goal. - Specific steps or subtasks. - References to tools if you want to guide the process (e.g., "Use web_search to find sources, then code_execution to analyze data"). - Any constraints, like dates or limits. Example prompt: "Create a Grok Task for my morning routine: Search recent X posts about tech news using x_keyword_search, fetch a key thread with x_thread_fetch, and summarize with browse_page on linked articles." Step 4: Submit and Interact Send your prompt to Grok. It will process the task by calling tools as needed, often in parallel for efficiency. Review the output and refine with follow-up prompts if required (e.g., "Expand on that using view_image for visuals"). Iterate to fine-tune the workflow for reuse. Step 5: Save and Reuse Once refined, note the prompt as a template for future use. You can adapt it for similar tasks, making Grok Tasks a habitual part of your day. Finding Grok Tasks To discover existing Grok Tasks or inspiration for new ones, use X searches with tools like x_keyword_search or x_semantic_search (e.g., query: "Grok Tasks examples" with mode: Latest). Browse community-shared threads via x_thread_fetch, or web_search for tutorials on xAI features. Prompt Grok directly: "Show me popular Grok Tasks for productivity." 1 of 3
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Boom! Grok Tasks Make It One Of The Most POWERFUL Real-Time AI Systems In The World. — My How to Use Grok Tasks With Hidden Tools For Powerful Daily Output. Grok Tasks are customizable AI workflows that integrate a variety of tools to streamline daily activities, from research and analysis to creative planning and problem-solving. I have been using them for quite sometime and because of the vital heartbeat of news and first person data on X, it is the most powerful AI platform available. By combining Tasks with tools like web searches, X platform interactions, code execution, and media viewers, you can build efficient, automated processes. These tasks work by prompting Grok with a clear description of what you want to achieve, and Grok will intelligently call the necessary tools in sequence or parallel to deliver results. Here's a step-by-step guide to creating and using Grok Tasks: Step 1: Define Your Task Start by clearly outlining the daily activity or goal. Consider what inputs you have (e.g., a URL, a query, or an attachment) and what output you need (e.g., a summary, calculation, or visual analysis). Break it down into subtasks to identify tool needs. For example, if your task involves researching current events, note that you'll need search and browsing capabilities. Step 2: Review Available Tools Familiarize yourself with the tools Grok can access. Here's a quick overview: - Code Execution: Run Python code for calculations, data processing, or simulations using libraries like numpy, pandas, or sympy. - Browse Page: Fetch and summarize content from any website URL with custom instructions. - Web Search: Perform general internet searches, returning results with optional operators like site:. - Web Search With Snippets: Get quick, detailed excerpts from search results for fact-checking. - X Keyword Search: Advanced search for X posts using operators like from:, since:, or filter:. - X Semantic Search: Find semantically related X posts based on a query, with filters for dates or users. - X User Search: Locate X users by name or handle. - X Thread Fetch: Retrieve a full X post thread, including context like replies and parents. - View Image: Analyze an image from a URL or conversation ID. - View X Video: Extract frames and subtitles from an X-hosted video. - Search PDF Attachment: Query a PDF file for relevant pages using keyword or regex modes. - Browse PDF Attachment: View specific pages of a PDF with text and screenshots. Select tools that align with your task. Aim for a mix to handle data gathering, processing, and visualization. Step 3: Craft Your Prompt Write a detailed prompt to Grok describing the task. Include: - The overall goal. - Specific steps or subtasks. - References to tools if you want to guide the process (e.g., "Use web_search to find sources, then code_execution to analyze data"). - Any constraints, like dates or limits. Example prompt: "Create a Grok Task for my morning routine: Search recent X posts about tech news using x_keyword_search, fetch a key thread with x_thread_fetch, and summarize with browse_page on linked articles." Step 4: Submit and Interact Send your prompt to Grok. It will process the task by calling tools as needed, often in parallel for efficiency. Review the output and refine with follow-up prompts if required (e.g., "Expand on that using view_image for visuals"). Iterate to fine-tune the workflow for reuse. Step 5: Save and Reuse Once refined, note the prompt as a template for future use. You can adapt it for similar tasks, making Grok Tasks a habitual part of your day. Finding Grok Tasks To discover existing Grok Tasks or inspiration for new ones, use X searches with tools like x_keyword_search or x_semantic_search (e.g., query: "Grok Tasks examples" with mode: Latest). Browse community-shared threads via x_thread_fetch, or web_search for tutorials on xAI features. Prompt Grok directly: "Show me popular Grok Tasks for productivity." 1 of 3

Brian Roemmele

152,242 次观看 • 7 个月前

All of those people who constantly cry about “cancel culture” are at it again cancelling a company called Liberty Safe. This comes after they spent months trying to cancel Bud Light. These people will say, “but we are justified,” and they are not. That’s not how this works though. People boycott and “cancel” companies and people when they feel there is a justification to do it. It doesn’t mean that it has to be justified in your mind, but it is in theirs. It’s just so hypocritical to me when people attack others for canceling companies but they go ahead and do the exact same thing themselves. For those who aren't familiar with this story, the Liberty Safe company gave a passcode to the FBI so that they could access a suspected criminal's safe. There was a search warrant issued on the criminal's home where the safe was located. What do you think? Do you support cancel culture? Do you only support it when it’s in your best interest, or do you support it no matter who it is?
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All of those people who constantly cry about “cancel culture” are at it again cancelling a company called Liberty Safe. This comes after they spent months trying to cancel Bud Light. These people will say, “but we are justified,” and they are not. That’s not how this works though. People boycott and “cancel” companies and people when they feel there is a justification to do it. It doesn’t mean that it has to be justified in your mind, but it is in theirs. It’s just so hypocritical to me when people attack others for canceling companies but they go ahead and do the exact same thing themselves. For those who aren't familiar with this story, the Liberty Safe company gave a passcode to the FBI so that they could access a suspected criminal's safe. There was a search warrant issued on the criminal's home where the safe was located. What do you think? Do you support cancel culture? Do you only support it when it’s in your best interest, or do you support it no matter who it is?

Ed Krassenstein

684,596 次观看 • 3 年前

Share this with anyone heading into London today, and hit the repost button so more people see it 🔄 Footage sent in today shows two masked men on bikes in central London, one holding a handful of stolen phones, the other holding foil. The person filming says they’d stopped under a bridge minutes before to wrap the phones up, and were carrying a lot of them. Have you got your UB1UB2 discount card yet? Discounts at 100+ local spots for only £3 a month 👉 link in our bio The foil is the part most people don’t know about. It blocks the signal, so the phone drops off Find My straight away and can’t be traced while they move it on. That’s why your location goes dead within minutes of it being snatched. Keep your phone out of your hand near the road, and if it does get taken, don’t chase them, report it and get your network to block the IMEI so the handset is worthless to them. 🎥 Sent in by a follower 📍London #ub1ub2 #london #phonetheft
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Share this with anyone heading into London today, and hit the repost button so more people see it 🔄 Footage sent in today shows two masked men on bikes in central London, one holding a handful of stolen phones, the other holding foil. The person filming says they’d stopped under a bridge minutes before to wrap the phones up, and were carrying a lot of them. Have you got your UB1UB2 discount card yet? Discounts at 100+ local spots for only £3 a month 👉 link in our bio The foil is the part most people don’t know about. It blocks the signal, so the phone drops off Find My straight away and can’t be traced while they move it on. That’s why your location goes dead within minutes of it being snatched. Keep your phone out of your hand near the road, and if it does get taken, don’t chase them, report it and get your network to block the IMEI so the handset is worthless to them. 🎥 Sent in by a follower 📍London #ub1ub2 #london #phonetheft

UB1UB2 West London (Southall)

88,735 次观看 • 19 天前

encrypt every chat with this open sourced repo 18 year old just killed the encryption problem it's called conversation-steganography you type a secret and a local AI buries it inside a dead boring chat about coffee, etc. then you send that through any normal messenger your friend runs the same tool and the small talk unfolds back into the real words > the secret is locked with AES-SIV before it ever becomes text > the cover message is written by a model on your own machine so nothing touches the cloud > it rides through whatsapp telegram imessage even plain email > every message is cryptographically chained so tampering shows instantly whatsapp sees you planning dinner your isp logs small talk the real sentence was never in the data at all quietly one of the most dangerous repos i have seen all month repo in reply
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encrypt every chat with this open sourced repo 18 year old just killed the encryption problem it's called conversation-steganography you type a secret and a local AI buries it inside a dead boring chat about coffee, etc. then you send that through any normal messenger your friend runs the same tool and the small talk unfolds back into the real words > the secret is locked with AES-SIV before it ever becomes text > the cover message is written by a model on your own machine so nothing touches the cloud > it rides through whatsapp telegram imessage even plain email > every message is cryptographically chained so tampering shows instantly whatsapp sees you planning dinner your isp logs small talk the real sentence was never in the data at all quietly one of the most dangerous repos i have seen all month repo in reply

savip.

83,651 次观看 • 1 个月前

Happy 33rd birthday Miley Cyrus and once again, thank YOU so much for all that you have done in my life. 14 year old me made the best decision of his life one day when he woke up and saw the flowers music video and clicked it instantly. The song itself helped change my perspective about love in life and at a time where my self worth was based on others it made me become so much more comfortable with myself. I went to movies by myself, went to concerts by myself, and every time the opportunity to celebrate myself came, I took it. And since then, my love for your music and personality has only grew stronger, endless summer vacation was filled with bops and some of my personal favourite songs + something beautiful is just perfection. The meaning and concept of the album is also something that I find, for a lack of word, beautiful as in a place where everyone is so unkind and hateful, it focuses on the love and kindness of it. Also, meeting you this year was just the most iconic, fabulous, amazing thing to ever happen, thank you so much for hosting and performing and it was truly truly truly my dream come true. 😙♥️ This message is getting pretty long and I guess at the core of it, I just wanted to say thank YOU. You are the most beautiful person on earth and I hope you have the most wonderful birthday and enjoy your time with Maxx, Tish and your family. We all love you and can’t wait for the new album! Love you Miley ❤️♥️
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Happy 33rd birthday Miley Cyrus and once again, thank YOU so much for all that you have done in my life. 14 year old me made the best decision of his life one day when he woke up and saw the flowers music video and clicked it instantly. The song itself helped change my perspective about love in life and at a time where my self worth was based on others it made me become so much more comfortable with myself. I went to movies by myself, went to concerts by myself, and every time the opportunity to celebrate myself came, I took it. And since then, my love for your music and personality has only grew stronger, endless summer vacation was filled with bops and some of my personal favourite songs + something beautiful is just perfection. The meaning and concept of the album is also something that I find, for a lack of word, beautiful as in a place where everyone is so unkind and hateful, it focuses on the love and kindness of it. Also, meeting you this year was just the most iconic, fabulous, amazing thing to ever happen, thank you so much for hosting and performing and it was truly truly truly my dream come true. 😙♥️ This message is getting pretty long and I guess at the core of it, I just wanted to say thank YOU. You are the most beautiful person on earth and I hope you have the most wonderful birthday and enjoy your time with Maxx, Tish and your family. We all love you and can’t wait for the new album! Love you Miley ❤️♥️

The Miley Cyrus HQ

14,043 次观看 • 9 个月前

I updated the website! Take a look at all the categories and art that @DollyJKazoo designed! It was so cool being able to make art for all of the products we have. The collections have grown so much over the years that we just needed to do a makeover so we can fit all of our items on the home page and make it look more pretty~ Also a sneak peek of our mascot Baby Finn the Giraffe making a comeback! Lastly, I realized after I recorded this, so the tabs at the bottom will only be available on the website if you want to have an easier log-in experience. Which the app is available on Apple and Android. Just search “Lil Comforts” on your appstore!
0:18

I updated the website! Take a look at all the categories and art that @DollyJKazoo designed! It was so cool being able to make art for all of the products we have. The collections have grown so much over the years that we just needed to do a makeover so we can fit all of our items on the home page and make it look more pretty~ Also a sneak peek of our mascot Baby Finn the Giraffe making a comeback! Lastly, I realized after I recorded this, so the tabs at the bottom will only be available on the website if you want to have an easier log-in experience. Which the app is available on Apple and Android. Just search “Lil Comforts” on your appstore!

Lil Comforts

37,754 次观看 • 2 年前

most AI chatbots break when you ask a question that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)
0:14

most AI chatbots break when you ask a question that requires info from multiple sources for example try asking: “which client contracts are finishing up this month?” you’ll get a half-answer — or none at all why? because traditional chatbots only look at small snippets of your docs - they don’t understand how things connect across clients, services, timelines that’s where knowledge graphs come in they let you turn messy contracts into a web of relationships — like: "Client → Contract Type → Service Provided → End Date" so instead of guessing from a few chunks of text, your chatbot can search across all your clients and contracts to give accurate answers I made a full walkthrough on how I built this: – how to organize your contracts so an AI can actually use them – how to define what matters (like who signed what, and when) – how to get the AI to figure out what info it needs and where to find it – and how to feed that back into your chatbot so it gives accurate answers reply “graph” and I’ll DM it to you (must be following)

Tyler

24,994 次观看 • 1 年前

we sped up distributed inference by up to 5x with decentralized speculative decoding. many don't realize that AI models normally generate text one single word at a time, waiting for the network after every word. speculative decoding changes this by using a "guess & confirm" system, similar to autocomplete. how it's done: 1. draft locally (the guess) instead of waiting for the network, a tiny, fast model on your device guesses the next few words instantly, without waiting for the network. 2. confirm remotely (the check) the massive remote model doesn't generate from scratch; it just checks the draft. it looks at the guesses in a batch and says "yes, yes, no." you get multiple words in the time it usually takes to get one. 3. adaptive logic dsd is smart. if the topic is creative, it lets the draft flow loose. if the topic is math or code, it checks more strictly. it balances speed and precision automatically so your inference almost feel instant. find out more: paper: blog:
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we sped up distributed inference by up to 5x with decentralized speculative decoding. many don't realize that AI models normally generate text one single word at a time, waiting for the network after every word. speculative decoding changes this by using a "guess & confirm" system, similar to autocomplete. how it's done: 1. draft locally (the guess) instead of waiting for the network, a tiny, fast model on your device guesses the next few words instantly, without waiting for the network. 2. confirm remotely (the check) the massive remote model doesn't generate from scratch; it just checks the draft. it looks at the guesses in a batch and says "yes, yes, no." you get multiple words in the time it usually takes to get one. 3. adaptive logic dsd is smart. if the topic is creative, it lets the draft flow loose. if the topic is math or code, it checks more strictly. it balances speed and precision automatically so your inference almost feel instant. find out more: paper: blog:

Parallax

45,584 次观看 • 7 个月前

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.
0:17

🚨 JUST IN: CHINA just released an AI EMPLOYEE that works 24X7 on its own. 100% OPEN SOURCE. It researches, codes, builds websites, creates slide decks, and generates videos. All by itself. All on your computer. It's called DeerFlow. You give it a task. It makes a plan, spins up its own team of sub-agents, and gets to work. You come back and there's a finished deliverable waiting. Not a draft. Not a summary. The actual thing. Not a chatbot. Not a research assistant. An AI with its own computer that works while you sleep. Here's what it does on its own: → Spawns multiple sub-agents in parallel, each tackling a different piece of your task, then combines everything into one finished output → Writes real code, runs it, reads the results, and fixes its own mistakes without asking you once → Builds slide decks, websites, full research reports, and data dashboards from scratch → Remembers you across sessions. Your writing style. Your tech stack. Your preferences. Gets better every time. → Reads files you upload, works with them inside its own filesystem, hands you clean finished outputs → Searches the web, runs commands, calls any tool you plug in Here's how it thinks: You give one instruction. The lead agent makes a plan. Sub-agents fan out and work in parallel. Results come back. Everything gets synthesized. You get a deliverable. A single research task might split into a dozen sub-agents, each exploring a different angle, then converge into one finished website with generated visuals. Here's the wildest part: DeerFlow 2.0 launched on February 28th 2026 and hit number 1 on all of GitHub Trending the same day. Version 2.0 was a complete rewrite. Zero shared code with version 1. Because users kept using it for things the team never intended. Data pipelines. Dashboards. Entire content workflows. The community told them what it needed to become. So they burned it down and rebuilt it. 22.7K GitHub stars. 2.7K forks. Built by ByteDance 100% Open Source. MIT License.

Kanika

738,392 次观看 • 5 个月前

We all miss brute and we wish he would host his spaces and share his takes more frequently especially during these highly dynamic times. Thats why me and my friend took 50+ Twitter Spaces worth of Brute de force, every lesson, every take, every story, every rant and condensed hundreds of thousands of words into their purest form. Then we distilled it down to a bot that lives in our group chat. You summon it like a demon. And it delivers like a mentor. A bot that doesn't just quote Brute. It thinks like him. It talks like him. It even sounds like him, real voice messages in his actual voice. What it does: In your private conversation with him on telegram it coaches like Brute. Not motivational posters. Real, blunt, personalized guidance based on YOUR situation. Tell it your problem, it gives you what Brute would say to your face. It remembers you. Every conversation builds on the last. It knows your goals, your excuses, your patterns. The more you use it, the sharper it gets. It holds you accountable. Slacking? It'll call you out the way Brute would, no sugarcoating. It tells stories. Original stories in Brute's style, pulled from the DNA of every lesson he's ever taught, remixed and tailored to hit where you need it. And it's genuinely funny. High-IQ humor in every response. This isn't a corporate chatbot. It has personality. Think of it as Brute in your pocket. 24/7. Ready to coach, roast, and redirect you on demand. Comment "BRUTE" to get access for FREE.
0:15

We all miss brute and we wish he would host his spaces and share his takes more frequently especially during these highly dynamic times. Thats why me and my friend took 50+ Twitter Spaces worth of Brute de force, every lesson, every take, every story, every rant and condensed hundreds of thousands of words into their purest form. Then we distilled it down to a bot that lives in our group chat. You summon it like a demon. And it delivers like a mentor. A bot that doesn't just quote Brute. It thinks like him. It talks like him. It even sounds like him, real voice messages in his actual voice. What it does: In your private conversation with him on telegram it coaches like Brute. Not motivational posters. Real, blunt, personalized guidance based on YOUR situation. Tell it your problem, it gives you what Brute would say to your face. It remembers you. Every conversation builds on the last. It knows your goals, your excuses, your patterns. The more you use it, the sharper it gets. It holds you accountable. Slacking? It'll call you out the way Brute would, no sugarcoating. It tells stories. Original stories in Brute's style, pulled from the DNA of every lesson he's ever taught, remixed and tailored to hit where you need it. And it's genuinely funny. High-IQ humor in every response. This isn't a corporate chatbot. It has personality. Think of it as Brute in your pocket. 24/7. Ready to coach, roast, and redirect you on demand. Comment "BRUTE" to get access for FREE.

comfy

29,345 次观看 • 6 个月前

been thinking a lot about how search is shifting i catch myself asking claude or GPT for product recommendations all the time instead of googling and it hit me, those ai answers don’t give 10 options to click through they usually just tell me what to buy, or give a couple of options if you’re a brand, that changes the game if you’re not in that answer, you basically don’t exist that’s why i like what meridian is building it shows you how ai engines actually see your brand today and gives you steps to improve your chances of being included in those answers You can literally just typ in “gru” -> 30 seconds later you have a full report with every mention, every context, every strength, and blind spot. and while you’re still refreshing Google Search Console wondering why your traffic tanked… someone else just found out they’re cited in 17 AI Overviews and 3 major chatbot answers — and their competitor isn’t. for operators this matters because: – if you’re not included, you’re not in the conversation – people increasingly trust ai answers over google – early movers will have an edge (like early seo all over again) feels a bit like seo in the early days, except the window to get ahead is much smaller want to see how AI platforms represent your brand? Drop "Meridian" and I'll share your free assessment.
0:16

been thinking a lot about how search is shifting i catch myself asking claude or GPT for product recommendations all the time instead of googling and it hit me, those ai answers don’t give 10 options to click through they usually just tell me what to buy, or give a couple of options if you’re a brand, that changes the game if you’re not in that answer, you basically don’t exist that’s why i like what meridian is building it shows you how ai engines actually see your brand today and gives you steps to improve your chances of being included in those answers You can literally just typ in “gru” -> 30 seconds later you have a full report with every mention, every context, every strength, and blind spot. and while you’re still refreshing Google Search Console wondering why your traffic tanked… someone else just found out they’re cited in 17 AI Overviews and 3 major chatbot answers — and their competitor isn’t. for operators this matters because: – if you’re not included, you’re not in the conversation – people increasingly trust ai answers over google – early movers will have an edge (like early seo all over again) feels a bit like seo in the early days, except the window to get ahead is much smaller want to see how AI platforms represent your brand? Drop "Meridian" and I'll share your free assessment.

J.B.

47,182 次观看 • 10 个月前

Codex CLI Update: Let there be Search Whatup nerds, back so soon looking or yet ANOTHER update?! I got you. Update 0.121.0 is here! > You can now search through previous user prompts with CTRL+R. Just trigger search and enter your search string, you can easily arrow through all matches. See video below! > 🥔 Support for Spud! Is not here yet. Sorry. Maybe tomorrow. 🫢 > v0.121.0 adds custom marketplace installs in Codex: you can run codex marketplace add to register marketplaces from GitHub shorthand, git URLs, or local directories. Codex validates the marketplace layout and stores it in your user config so it shows up consistently in plugin discovery. > Improved memory features, including a new /memories TUI menu with use/generate toggles, a reset-all-memories action, app-server support for setting thread memory mode and clearing memories, and cleanup of stale memory-extension resources. Note: Not working on Linux for me. /memories command unavailable. > Codex MCP got further upgrades with direct app tool calls, cleaner namespacing, and safe optional parallel execution for faster workflows > Codex realtime got better controls (text/audio + clear “done” signals), easier history syncing, and safer file handling. > Hardened devcontainer setup plus smarter macOS socket allowlists for safer local runtime access. > Dozens of other bug fixes, see repo below. Toodles! ✌️
0:15

Codex CLI Update: Let there be Search Whatup nerds, back so soon looking or yet ANOTHER update?! I got you. Update 0.121.0 is here! > You can now search through previous user prompts with CTRL+R. Just trigger search and enter your search string, you can easily arrow through all matches. See video below! > 🥔 Support for Spud! Is not here yet. Sorry. Maybe tomorrow. 🫢 > v0.121.0 adds custom marketplace installs in Codex: you can run codex marketplace add to register marketplaces from GitHub shorthand, git URLs, or local directories. Codex validates the marketplace layout and stores it in your user config so it shows up consistently in plugin discovery. > Improved memory features, including a new /memories TUI menu with use/generate toggles, a reset-all-memories action, app-server support for setting thread memory mode and clearing memories, and cleanup of stale memory-extension resources. Note: Not working on Linux for me. /memories command unavailable. > Codex MCP got further upgrades with direct app tool calls, cleaner namespacing, and safe optional parallel execution for faster workflows > Codex realtime got better controls (text/audio + clear “done” signals), easier history syncing, and safer file handling. > Hardened devcontainer setup plus smarter macOS socket allowlists for safer local runtime access. > Dozens of other bug fixes, see repo below. Toodles! ✌️

am.will

22,020 次观看 • 4 个月前

🚨 One photo of your face. That's all someone needs to become you on a live video call. In real time. Right now. The tool is free and open source. It's called Deep-Live-Cam. One image. One click. You become anyone on a live webcam feed. No training. No datasets. No waiting. Instant. Your face. Your expressions. Your mouth movements. All stolen from a single photo. Here's what this thing does: → Upload one photo of any face → Turn on your webcam → You are now that person. Live. In real time. → It matches your pose, your expressions, even your lighting → Mouth masking so the swapped face moves its lips when you talk → Multi-face mapping. Swap different faces on different people in the same call. → Virtual camera output. Plug it into Zoom, Google Meet, Teams. Nobody knows. → Works on NVIDIA, AMD, Intel, and Apple Silicon Here's the part that should terrify you: Your boss could be on a Zoom call with someone wearing your face right now. A scammer could call your parents looking exactly like you. A stranger could take your LinkedIn photo and become you in a video meeting. IShowSpeed's reaction when he saw it: "What the F**! This shit is crazy!" SomeOrdinaryGamers: "That's fucking freaky dude... that's so wild." This was the #1 trending repo on GitHub the day it launched. 1,600 stars in 24 hours. 80K+ stars today. No one is ready for what this means. And it's already out there. 100% Open Source.
0:15

🚨 One photo of your face. That's all someone needs to become you on a live video call. In real time. Right now. The tool is free and open source. It's called Deep-Live-Cam. One image. One click. You become anyone on a live webcam feed. No training. No datasets. No waiting. Instant. Your face. Your expressions. Your mouth movements. All stolen from a single photo. Here's what this thing does: → Upload one photo of any face → Turn on your webcam → You are now that person. Live. In real time. → It matches your pose, your expressions, even your lighting → Mouth masking so the swapped face moves its lips when you talk → Multi-face mapping. Swap different faces on different people in the same call. → Virtual camera output. Plug it into Zoom, Google Meet, Teams. Nobody knows. → Works on NVIDIA, AMD, Intel, and Apple Silicon Here's the part that should terrify you: Your boss could be on a Zoom call with someone wearing your face right now. A scammer could call your parents looking exactly like you. A stranger could take your LinkedIn photo and become you in a video meeting. IShowSpeed's reaction when he saw it: "What the F**! This shit is crazy!" SomeOrdinaryGamers: "That's fucking freaky dude... that's so wild." This was the #1 trending repo on GitHub the day it launched. 1,600 stars in 24 hours. 80K+ stars today. No one is ready for what this means. And it's already out there. 100% Open Source.

Nav Toor

305,135 次观看 • 5 个月前

I built a content engine that runs on telegram. Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.
0:11

I built a content engine that runs on telegram. Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.

Savvy | Ai & Automation

15,746 次观看 • 5 个月前