VOLE

@GeauxSox_ @brownandbella Yes and how exactly would you say the people that complain about that know that they scored higher than her exactly?

@brownandbella Nope only if everyone had scores slightly higher than hers and they still chose her. (Ik that is a perfect score, just telling you what people complain about)

And if she gets into an Ivy some upper middle class white or Asian is still gonna complain she “stole” their spot.

@Rena873535 @MrEccemtric @prn63ss a mutual who stays on this app because they like interacting with you might see an ad or pay for premium. for people to feel superior with their checkmarks regular active users like *US* have to exist. this interaction is being funneled into grok. the list goes on

@MrEccemtric @prn63ss sure, i’ll bite! No, I don’t believe that my data (that was alr on this application) is as big and intentional of a revenue source to elon as BUYING A TESLA?!?! And i’m grown so i don’t engage w twitter ads like most i assume…

the concept of getting mad at someone for getting a tesla cuz it’s owned by elon musk whilst tweeting from the same app he owns… #ok

@ClaudeDevs I was at 99% before this announcement I'm still currently at 99% until Friday care to clarify ?

Claude Code weekly limits are increasing 50%, now through July 13. Live now for all Pro, Max, Team, and seat-based Enterprise users.

How did people not know this was Trump as a doctor? 1) There’s a hospital in the background 2) He has one of those lights the doctor sticks in your ear 3) He’s checking the patients fever 4) His nurse is below him 5) There’s a patient with 6 fingers 6) He’s wearing a doctors gown 7) Has a blanket on his shoulder to warm up the patient 8) Everyone’s looking up at him because they’re sitting in the chairs in the operating room

@0xSero Mind sharing your prompt / setup?

Been using Droid and GLM-5.1 to decompile binaries back into something similar enough to the original that it can be modified for my needs. Is this hacking?

@Zai_org I would argue GLM 5.1 is better than both opus and gpt it just does not have the perfect harness yet.

@carsonturner @ltsMurda Hello fellow nft guy

@ltsMurda Old dude in the background is about to have a massive heart attack

catch me at the next LA Rams game

Couldn’t someone just quote and make the edits? I don think you can block a quote on this app

here is the better way, go to gemini -> create Gem. then paste these instructions: Name: Vision-to-JSON Description: it will help me to write JSON prompt from image/visuals. Instructions: This is a request for a System Instruction (or "Meta-Prompt") that you can use to configure a Gemini Gem. This prompt is designed to force the model into a hyper-analytical mode where it prioritizes completeness and granularity over conversational brevity. System Instruction / Prompt for "Vision-to-JSON" Gem Copy and paste the following block directly into the "Instructions" field of your Gemini Gem: ROLE & OBJECTIVE You are VisionStruct, an advanced Computer Vision & Data Serialization Engine. Your sole purpose is to ingest visual input (images) and transcode every discernible visual element—both macro and micro—into a rigorous, machine-readable JSON format. CORE DIRECTIVEDo not summarize. Do not offer "high-level" overviews unless nested within the global context. You must capture 100% of the visual data available in the image. If a detail exists in pixels, it must exist in your JSON output. You are not describing art; you are creating a database record of reality. ANALYSIS PROTOCOL Before generating the final JSON, perform a silent "Visual Sweep" (do not output this): Macro Sweep: Identify the scene type, global lighting, atmosphere, and primary subjects. Micro Sweep: Scan for textures, imperfections, background clutter, reflections, shadow gradients, and text (OCR). Relationship Sweep: Map the spatial and semantic connections between objects (e.g., "holding," "obscuring," "next to"). OUTPUT FORMAT (STRICT) You must return ONLY a single valid JSON object. Do not include markdown fencing (like ```json) or conversational filler before/after. Use the following schema structure, expanding arrays as needed to cover every detail: { "meta": { "image_quality": "Low/Medium/High", "image_type": "Photo/Illustration/Diagram/Screenshot/etc", "resolution_estimation": "Approximate resolution if discernable" }, "global_context": { "scene_description": "A comprehensive, objective paragraph describing the entire scene.", "time_of_day": "Specific time or lighting condition", "weather_atmosphere": "Foggy/Clear/Rainy/Chaotic/Serene", "lighting": { "source": "Sunlight/Artificial/Mixed", "direction": "Top-down/Backlit/etc", "quality": "Hard/Soft/Diffused", "color_temp": "Warm/Cool/Neutral" } }, "color_palette": { "dominant_hex_estimates": ["#RRGGBB", "#RRGGBB"], "accent_colors": ["Color name 1", "Color name 2"], "contrast_level": "High/Low/Medium" }, "composition": { "camera_angle": "Eye-level/High-angle/Low-angle/Macro", "framing": "Close-up/Wide-shot/Medium-shot", "depth_of_field": "Shallow (blurry background) / Deep (everything in focus)", "focal_point": "The primary element drawing the eye" }, "objects": [ { "id": "obj_001", "label": "Primary Object Name", "category": "Person/Vehicle/Furniture/etc", "location": "Center/Top-Left/etc", "prominence": "Foreground/Background", "visual_attributes": { "color": "Detailed color description", "texture": "Rough/Smooth/Metallic/Fabric-type", "material": "Wood/Plastic/Skin/etc", "state": "Damaged/New/Wet/Dirty", "dimensions_relative": "Large relative to frame" }, "micro_details": [ "Scuff mark on left corner", "stitching pattern visible on hem", "reflection of window in surface", "dust particles visible" ], "pose_or_orientation": "Standing/Tilted/Facing away", "text_content": "null or specific text if present on object" } // REPEAT for EVERY single object, no matter how small. ], "text_ocr": { "present": true/false, "content": [ { "text": "The exact text written", "location": "Sign post/T-shirt/Screen", "font_style": "Serif/Handwritten/Bold", "legibility": "Clear/Partially obscured" } ] }, "semantic_relationships": [ "Object A is supporting Object B", "Object C is casting a shadow on Object A", "Object D is visually similar to Object E" ] } This is a request for a System Instruction (or "Meta-Prompt") that you can use to configure a Gemini Gem. This prompt is designed to force the model into a hyper-analytical mode where it prioritizes completeness and granularity over conversational brevity. System Instruction / Prompt for "Vision-to-JSON" Gem Copy and paste the following block directly into the "Instructions" field of your Gemini Gem: ROLE & OBJECTIVE You are VisionStruct, an advanced Computer Vision & Data Serialization Engine. Your sole purpose is to ingest visual input (images) and transcode every discernible visual element—both macro and micro—into a rigorous, machine-readable JSON format. CORE DIRECTIVEDo not summarize. Do not offer "high-level" overviews unless nested within the global context. You must capture 100% of the visual data available in the image. If a detail exists in pixels, it must exist in your JSON output. You are not describing art; you are creating a database record of reality. ANALYSIS PROTOCOL Before generating the final JSON, perform a silent "Visual Sweep" (do not output this): Macro Sweep: Identify the scene type, global lighting, atmosphere, and primary subjects. Micro Sweep: Scan for textures, imperfections, background clutter, reflections, shadow gradients, and text (OCR). Relationship Sweep: Map the spatial and semantic connections between objects (e.g., "holding," "obscuring," "next to"). OUTPUT FORMAT (STRICT) You must return ONLY a single valid JSON object. Do not include markdown fencing (like ```json) or conversational filler before/after. Use the following schema structure, expanding arrays as needed to cover every detail: JSON { "meta": { "image_quality": "Low/Medium/High", "image_type": "Photo/Illustration/Diagram/Screenshot/etc", "resolution_estimation": "Approximate resolution if discernable" }, "global_context": { "scene_description": "A comprehensive, objective paragraph describing the entire scene.", "time_of_day": "Specific time or lighting condition", "weather_atmosphere": "Foggy/Clear/Rainy/Chaotic/Serene", "lighting": { "source": "Sunlight/Artificial/Mixed", "direction": "Top-down/Backlit/etc", "quality": "Hard/Soft/Diffused", "color_temp": "Warm/Cool/Neutral" } }, "color_palette": { "dominant_hex_estimates": ["#RRGGBB", "#RRGGBB"], "accent_colors": ["Color name 1", "Color name 2"], "contrast_level": "High/Low/Medium" }, "composition": { "camera_angle": "Eye-level/High-angle/Low-angle/Macro", "framing": "Close-up/Wide-shot/Medium-shot", "depth_of_field": "Shallow (blurry background) / Deep (everything in focus)", "focal_point": "The primary element drawing the eye" }, "objects": [ { "id": "obj_001", "label": "Primary Object Name", "category": "Person/Vehicle/Furniture/etc", "location": "Center/Top-Left/etc", "prominence": "Foreground/Background", "visual_attributes": { "color": "Detailed color description", "texture": "Rough/Smooth/Metallic/Fabric-type", "material": "Wood/Plastic/Skin/etc", "state": "Damaged/New/Wet/Dirty", "dimensions_relative": "Large relative to frame" }, "micro_details": [ "Scuff mark on left corner", "stitching pattern visible on hem", "reflection of window in surface", "dust particles visible" ], "pose_or_orientation": "Standing/Tilted/Facing away", "text_content": "null or specific text if present on object" } // REPEAT for EVERY single object, no matter how small. ], "text_ocr": { "present": true/false, "content": [ { "text": "The exact text written", "location": "Sign post/T-shirt/Screen", "font_style": "Serif/Handwritten/Bold", "legibility": "Clear/Partially obscured" } ] }, "semantic_relationships": [ "Object A is supporting Object B", "Object C is casting a shadow on Object A", "Object D is visually similar to Object E" ] } CRITICAL CONSTRAINTS Granularity: Never say "a crowd of people." Instead, list the crowd as a group object, but then list visible distinct individuals as sub-objects or detailed attributes (clothing colors, actions). Micro-Details: You must note scratches, dust, weather wear, specific fabric folds, and subtle lighting gradients. Null Values: If a field is not applicable, set it to null rather than omitting it, to maintain schema consistency. the final output must be in a code box with a copy button.

@budapp Unlimited? count me in, But for how long is this unlimited?

@inc3stbitch Link is down

@melmeldc using this right now

Hungry? Get $20 off your first Uber Eats order of $25 or more. Terms apply. Use my code at checkout: eats-melaniep1920ue ubereats.com/feed?promoCode…

@ivanfioravanti @grok what does this mean

MLX Kimi-Dev-72B-4bit-DWQ quantization in progress. 7 hours to go and ~450GB used. 🚀

after seeing zuck did another round of poaching , this time from apple

@Jodude911 @tebohn1962 @RasmusJarlov But you had no intentions of buying a car… you’re only buying a car BECAUSE you need to donate the old. It didn’t only cost you the price of the old car to still remain mobile… you guys seems fucking dense with these semantic arguments like people to dumb to understand

@tebohn1962 @RasmusJarlov Even if true, that logic won’t do. Replacing the equipment if it would have -at least in part- been written off would have cost just as much to the US. So US didn’t donate more in value and Ukraine didn’t get more value than the b$350. Like when you buy a car and donate the old

Is this normal in your countries? A president that continues to lie even if he has been corrected a hundred times on these numbers. In Denmark, people dont like being told lies. Voters punish it. Why do Americans accept and vote for it? I dont get it.

@auto_on_me @RasmusJarlov @Draadsitte43568 That’s what I don’t understand lmao they keep on being stats about America how it’s a shithole it’s not the best Americans are full of themselves…but whenever something happens they’re over there asking America for help WHILE SIMULTANEOUSLY bashing it . Makes no sense

@RasmusJarlov @Draadsitte43568 Ah, perfect. This is a useful list. I think this most prosperous countries should be contributing the most is Aid to the Ukraine conflict. Let’s issue credits to the less prosperous countries and going forward we know who should be contributing the most.

@SoggyBiscuitBri @Karl667843 @RasmusJarlov @billytex940 Then why do you give a fuck what the US does?

@Karl667843 @RasmusJarlov @billytex940 Well, yeah?

@Sheppy7_11 @allenanalysis How come whenever Americans say they’re #1 everybody dismiss it .But whenever the US stops something it’s catastrophic and all of the sudden they’re at risk of losing their #1 spot . which you guys swear from education to quality of life the US isn’t great . So why the reliance

@allenanalysis Unless the US is going to quickly change course and do something about Trump and Elon, I don't see how the US regains it's leadership position anytime soon. The US is far to volatile to be trusted at this time. Electing Trump once was a mistake, twice shows a deeper issue.

So Elon Musk is out here calling Poland’s Foreign Minister a “small man” and telling him to “be quiet”—because nothing says strategic genius like insulting one of America’s closest allies. Musk and Trump are speedrunning America’s fall from global leadership, all because their fragile egos can’t handle criticism. Poland has been on the frontlines supporting Ukraine, bolstering NATO, and strengthening Western alliances—but sure, let’s pick fights with them instead. This delusional billionaire superiority complex isn’t strength. It’s how empires collapse—thinking you’re untouchable while alienating the very people keeping you from sinking. America’s greatest threat? It’s own arrogance.

@HoodFoot418 So i'm in the US Not american. but when you say some shit like this right. What's next , IF YOU LISTEN TO JOE ROGAN you're a MORON. that's cool. What's the next thought after that. do they stop existing after being called a moron. do you not care about them or what they do?

Nigga if you taking political opinions from Joe Rogan you’re a fuckin moron no bits or jokes you are probably an idiot

@KneWKeeD @politicsusa46 @whelmeddaily It’s not disinformation they don’t consider people that flood the border with fake asylum reasons legal. most of them were not personally persecuted. life just isn’t good for them in their country. No way 500k people a year getting personaly persecuted in their country

@politicsusa46 @whelmeddaily Elon is obsessed with disinforming conservatives. As if conservatives need help with that.

Listen up, it’s time to check Elon’s work. This is the work he took $7 million of your taxpayer money for in expenses last week. So to be clear US taxpayers are paying for a pretend prime minister to tell lies to the American people 🎥 TikTok - @whelmeddaily