Loading video...

Video Failed to Load

Go Home

Current sensitivity settings for Black Ops 6 #BlackOps6 6-6 Horizontal And Vertical 0.75ADS Speed 2 Deadzone Left | 3 Deadzone Right Aim Response Curve: Linear Left stick max threshold 80 | Right stick threshold max 99

216,539 views • 2 years ago •via X (Twitter)

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

When strangers become big sisters in seconds. GPT Image 2 + Seedance 2.0 on Renoise prompt Create a clean, professional Pixar-style 3D character sheet of a 6-year-old girl, highly detailed, vibrant colors, polished family-friendly animation style. Character Description: Adorable 6-year-old girl with soft dark wavy hair tied in a cute high ponytail with a small pink bow. Big sparkling brown eyes, round expressive face, rosy cheeks, small button nose, and a warm friendly smile. She has a healthy, energetic child body type suitable for a 6-year-old. Outfit: Bright yellow t-shirt, light pink shorts, white ankle socks, and colorful small sneakers (blue and pink accents). Character Sheet Layout: A single clean vertical character sheet with multiple views of the same girl arranged neatly: Top Left: Full-body front view, standing naturally with hands on hips, smiling confidently. Top Right: Full-body 3/4 angle view, showing depth and personality. Middle Left: Full-body side profile view (facing right). Middle Right: Full-body back view. Bottom Center: Large close-up of her face showing 4 different expressions in small circles — Happy smile, Surprised, Shy/embarrassed, and Excited/grinning. Bottom Right: Small extra details — close-up of her ponytail with bow, shoe details, and hand poses. Style & Quality: Beautiful 3D Pixar animation style, smooth rounded shapes, expressive eyes, soft realistic textures, vibrant yet soft lighting, clean white background with subtle light shadows, highly polished, professional character design sheet, perfect proportions, studio quality, sharp details, warm and wholesome feel. 16:9 aspect ratio, ultra-detailed, cinematic lighting. #RenoiseCanvas

Sharon Riley

157,561 views • 3 months ago

I improved the prompt 👇 { "archetype": "Artistic / Fashion / Conceptual", "duration": "15s", "prompt": { "concept": { "title": "Ink Smoke Art – Kinetic Title Sequence", "description": "Continuous 15s one-take black ink-smoke motion graphics. Five characters form from living smoke on pure white void, each performing a characteristic motion while smoke stays alive. Formation direction alternates every 3s. Characters dissolve smoothly through smoke into the next. Kinetic uppercase text emerges from smoke on the complementary side. Final invitation text at the end. Always fluid, never static.", "duration": "15s", "rhythm_structure": { "0-3s": "[image1] forms right-to-left + characteristic motion, text left", "3-6s": "Morph to [image3] left-to-right + characteristic motion, text right", "6-9s": "Morph to [image2] right-to-left + characteristic motion, text left", "9-12s": "Morph to [image4] left-to-right + characteristic motion, text right", "12-15s": "Morph to [image5] right-to-left + characteristic motion + final invitation text" } }, "camera_direction": { "shot_type": "Strict continuous one-take, locked or micro-drift", "forbidden": ["No cuts", "No teleportation", "No hidden transitions", "No freeze frames"], "camera_journey": "Centered medium-wide on pure white void. Locked or extremely slow drift. All energy from living smoke and character motion." }, "typography": { "allowed_words": [ "INK SMOKE ART", "MOTION GRAPHICS", "MIDJOURNEY + H3", "PROMPTS by TechHalla", "MAKE IT YOURS" ], "treatment": { "not_flat_overlay": true, "required_properties": [ "Formed from dense black smoke particles and tendrils", "Physical volumetric depth", "Smoke occlusion and interaction", "Subtle continuous warping", "Bold uppercase condensed sans-serif", "Kinetic emergence synchronized to morphs and directional flow" ] } }, "visual_style": { "overall": "Black ink-smoke art, ultra high-contrast monochrome, pure white void, volumetric living smoke with dense cores and wispy filaments", "inspired_by": [ "[image1]– exact silhouette, long hair, armor, smoke density", "[image2]– exact suit, gun, coat edges, frontal presence", "[image3]– exact spiky hair, martial pose, wristbands, full-body mass", "[image4]– exact cowl, cape flow, dramatic profile", "[image5]– exact straw hat, back view, coat tails, dynamic stance" ], "color_palette": ["pure black", "deep charcoal smoke", "pure white void"], "materials_and_texture": "Living ink smoke, variable density, continuous filament motion, soft volumetric edges, constant micro-turbulence" }, "motion_language": { "follows_music": false, "core_behavior": "Never static. Smoke always swirls. Characters form while performing characteristic motion. Morphs only through smoke densifying and reforming. Direction alternates every beat. Visible smoke motion in every frame." }, "storyboard": { "total_beats": 5, "beat_duration": "3 seconds each", "beats": [ { "id": "01", "time": "0.0–3.0", "description": "Pure white void. Black smoke enters from right, flows left, coalesces into [image1]. Smoke lives on hair, armor and cloak while figure performs slow head turn and shoulder roll, long hair and cloak billowing as if scanning the horizon. Text “INK SMOKE ART” forms left from arriving tendrils into bold uppercase interacting with smoke. End of beat: form smoothly dissolves into swirling smoke." }, { "id": "02", "time": "3.0–6.0", "description": "Smoke reverses, enters from left, flows right, reforms into [image3]. Smoke swirls on limbs and spiky hair while figure performs slight crouch into charged fighting stance, fists clenching, body vibrating with residual energy. Previous text dissolves; “MOTION GRAPHICS” emerges right from arriving smoke into bold uppercase. End of beat: form smoothly dissolves into smoke." }, { "id": "03", "time": "6.0–9.0", "description": "Smoke reverses, enters from right, flows left, reforms into [image32. Smoke lives on suit edges and coat while figure performs slow raise of gun-holding arm into low ready position, coat flaring, determined forward lean. Text “MIDJOURNEY + H3” forms left from rising particles into bold uppercase. End of beat: form smoothly dissolves into smoke." }, { "id": "04", "time": "9.0–12.0", "description": "Smoke reverses, enters from left, flows right, reforms into [image4]. Smoke billows on long cape while figure performs dramatic cape sweep and subtle crouch, head tilting under cowl as if listening. Text “PROMPTS by TechHalla” emerges right from trailing cape smoke into bold uppercase. End of beat: form smoothly dissolves into smoke." }, { "id": "05", "time": "12.0–15.0", "description": "Smoke reverses, enters from right, flows left, reforms into [image5]. Smoke rises and trails on coat tails and hat while figure performs confident stance shift, straw hat tilting, coat tails whipping backward, one arm slightly extending forward. Previous text dissolves; residual smoke briefly reforms titles, then “MAKE IT YOURS” emerges centered from final smoke into bold uppercase as smoke slowly dissipates into white void, never fully static until end frame." } ] } } } Check out the previous one along with the Midjourney prompt for the images!

TechHalla

182,622 views • 27 days ago

This happened last Monday at Phoenix Sky Harbor Airport, Terminal 4, 6:45 AM. Technical Sergeant Kevin Harris, 35, Air Force, was going through TSA screening when his former military dog, Riley — a seven-year-old German Shepherd - spotted him through the glass. Max and Kevin served together overseas from 2013 to 2015. When Max retired, Kevin was stationed abroad and couldn't take him right away, so Max entered the adoption system. Kevin searched for two years before finally locating him three weeks ago through a military dog rescue volunteer in Arizona. The plan was simple: volunteer Sandra would bring Max through security to meet Kevin on proper service dog credentials after he cleared TSA. But Max saw Kevin taking off his belt and shoes at the screening area - and everything changed. Security footage shows Max yanking the leash from Sandra's hands, sprinting full speed, and jumping a four-foot "Do Not Enter" barrier straight into the secure screening zone. He hit Kevin before Kevin even got his belt off. Both went down. TSA agents swarmed. Radios crackled. A supervisor reviewed the footage, checked Max's credentials, and questioned everyone involved. After fifteen minutes, he issued a formal warning — no charges. "I thought we were getting arrested," Sandra told us. "But the supervisor watched the footage and understood - it was a reunion, not a threat." Kevin laughed about it afterward: "I'm taking my belt off and Max comes flying over a TSA barrier in the middle of airport security. Worth every second of panic." The two flew home to Texas together that afternoon -twelve years after serving side by side, reunited by a barrier jump. Sometimes a dog's love doesn't wait for protocol. It just jumps the barrier and runs.

Gabriele Corno

148,558 views • 1 month ago

🔥 Late June 2026: The Great Selective Rotation is Accelerating $KAS $0.45–4.5 $HBAR $1–8 $FIL $35–150 $ICP $45–250 $AR $80–400 $STX $8–40 $QNT $400–2000 $RIVER $6–60+ (abstraction + stablecoin plays gaining steam) $AKT $18–80 $HNT $30–150 $PYTH $1.5–12 $WIF $7–35 $BONK $0.00007–0.0007 $FLOKI $0.0015–0.015 $BRETT $0.8–6 $PENDLE $9–45 $LDO $12–45 $GMX $80–300 $CRV $2–10 $DYDX $20–80 $MANTRA $6–30 $CFG $1.5–10 $GRT $1.3–8 $MINA $2.5–14 $KSM $100–400 $GLMR $1.4–7 $CFX $1.2–6 $AXS $16–70 $SAND $2–12 $VET $0.14–0.7 $ALGO $0.7–4 $TRX $0.65–3 $DOGE $1.3–7 $PIXEL $2–15 $ILV $400–2000 $BEAM $0.12–1.2 Not the chaotic 2021 flood — this is precision capital flowing into projects delivering real utility, on-chain activity, and infrastructure moats. BTC dominance holding firm \~58-59% but showing fatigue. Altseason Index in that measured "build quietly" zone. Smart money isn’t chasing noise; it’s stacking narratives with actual traction: DePIN compute demand, decentralized intelligence, high-performance trading infra, and BTC-aligned ecosystems. My Core Conviction Basket for this cycle (long-term targets, NFA, DYOR — position size responsibly): High-Momentum Plays Heating Up Right Now: $HYPE $60–200+ — Perp DEX king with insane volume, staking mechanics, and ecosystem flywheel $TAO $250–2500 — Decentralized AI subnets exploding with real compute demand and agent growth $RENDER $12–90 — GPU workloads going parabolic as AI infra demand surges This rotation rewards conviction in builders who ship, not hype cycles. Quality narratives + patient capital = asymmetric upside. What’s your strongest conviction bag heading into Q3? Top 3 plays or hidden gems? Drop them below — let’s crowdsource the alpha 👇 Steady rotation. Data over delusion. Builders win. #Altseason3 #DePIN #DeAI #RIVER River River4FUN 🐝

Đecentralized Člub ©

11,943 views • 3 months ago

What would you have done? Merge right and let it play out? Hold your ground? Exactly what a Preventable Crash Really Looks Like. You’re driving a semi. Three-lane highway. You're in the center lane. Left lane is ending. Right lane is completely empty. Convex mirror shows no one beside you on the right. Three cars are pacing you in the left lane… and they’re about to run out of road. So Why are you still in the center lane? You’re not boxed in. You’re not blind. And you’ve already seen the sign telling you the left lane ends. You could’ve merged right a half-mile ago and cruised on. Instead, you’re now stuck in the lane of most resistance. That car flying up on your left? It’s doing what 80% of cars do when the lane end, they punch it. They try to get ahead. Not smart. Not courteous. But absolutely predictable. And that’s the point. You’re the professional. They're not. You know how this goes. You should know exactly what to expect. Textbook behavior. So when that car forces a merge in front of your bumper with 20 feet left of asphalt, are they wrong? Yep. But when you don’t lift off the gas, don’t merge right, and don’t anticipate what’s clearly unfolding, that’s no longer just their problem. Now it’s yours. And it’s preventable. What happens next👇 ✅ You plow into the car. ✅ You get to sit roadside for 3 hours explaining it to law enforcement and doing paperwork. ✅ You spend another 3 months Data Q’ing it, defending it in court, or arguing it with claims adjusters. ✅ It’s on your CSA now. ✅ Your insurance premium goes up. ✅ The carrier eats the deductible. ✅ And you get labeled as someone who “could’ve avoided it but didn’t.” Being a truck driver isn’t just turning a wheel. It’s a chess match. It’s anticipating the next three moves. When you choose not to play defense, you’re the one who loses, even when you’re “not at fault.” Some stats to chew on👇 👉Lane change/merge crashes account for nearly 10% of all large truck crashes. 👉FMCSA's Large Truck Crash Causation Study consistently shows "decision error" and "recognition error" as top contributing factors in preventable crashes. 👉The average post-crash litigation process? 3–6 months minimum, and that’s before settlements, audits, or nuclear verdicts.

Rob Carpenter

16,777 views • 7 months ago

While working on a new video with solutions to the previous one, I found ChatGPT's new UI struggles even more with concurrent updates: entries lose state and stick around for too long (see video). If this was a LiveView app, we would be getting so much flak.😅 --- I believe part of the problem here is having separate mutate and fetch requests on every deletion. The first fetch is cancelled when the second one comes up, causing items to stick around for longer. Many said yesterday that you could do the mutation and fetch as a single request, but that leads to other problems, such zombie entries. For example, imagine you delete link1 and link2 within a brief period of time. There is no guarantee the deletion order in the database will match the order the client receives the response, so you may end up with this: 1. (client) request to delete link1 sent 2. (client) request to delete link2 sent 3. (server) deletes link1 and loads a new list (includes link2) 4. (server) deletes link2 and loads a new list (no link1 or link2) 5. (client) receives link2 response 6. (client) receives link1 response So if you choose to use the latest response (link1), you brought link2 back to life. If you say you will use the response from the last request, events 3-4 can be swapped, and now you bring link1 back to life. Another way to solve this is by basically not allowing concurrent requests at all but that can affect the user experience drastically in other ways. Next week I should publish a video explaining how LiveView tackles this. Stay tuned!

José Valim

23,050 views • 2 years ago

MLP in PyTorch by hand ✍️ ~ 7 steps walkthrough below Goal: fill in every blank in the PyTorch code to build a multi-layer perceptron. 1. Given Let us start with a code template on the left and the network it is supposed to build on the right. Every blank in the code can be worked out from the picture. 2. Linear layer We count: 3 features in, 4 features out. So the weight matrix is 4 by 3. There is an extra column for the biases, which means bias = T. 3. ReLU Let us apply the activation. ReLU crosses out the negatives, so -1 becomes 0. 4. Linear layer The input size is 4, because that is what the previous layer put out. The output size is 2. A 2 by 4 weight matrix, and this time no extra column, so bias = F. 5. ReLU We cross out the negatives again. 6. Linear layer Two features in, five out. A 5 by 2 weight matrix, with a bias column, so bias = T. 7. Sigmoid Let us finish. Sigmoid squashes the raw scores (3, 0, -2, 5, -5) into probabilities between 0 and 1. You have just implemented a three-layer deep neural network by hand. ✍️ == Story == Three years ago I gave this exercise to my students, to connect the code to the math. They found it odd. Every other AI course they were taking lived inside a Jupyter notebook, and here I was handing out paper. Three years later, my colleagues are the ones rushing to move their materials to paper. The exercise has not changed. Paper still asks the one thing a notebook lets you skip: do you actually understand what the code is doing? If you can tell me why the weight matrix is 4 by 3, and why bias is F on the second layer, you understand nn.Linear better than someone who has been copy-pasting it for a year. 💾 Save this post! #AIbyHand #PyTorch #DeepLearning

Tom Yeh

13,318 views • 2 months ago