Crater Lake from the ISS last night. Just past the solar arrays. Even from 250 miles up, you can't miss it — that deep blue caldera, Wizard Island tucked in the corner. But look east of the lake and you'll see the other story: smoke from wildfires stretching across Oregon. Before I was an astronaut, I served as a flight surgeon with the 173rd Fighter Wing at Kingsley Field in Klamath Falls, just down the road from this lake. I spent a lot of good years in that corner of Oregon, and it's hard to watch it burn from up here. Thinking of everyone impacted by the fires — the families who've lost homes, and the thousands of firefighters and aircrews working around the clock down there. From this altitude you see how big the smoke is. You also see how many people are fighting it.

After nearly 14 years online, Dalaran-WoW has announced that its servers will shut down today, marking the end of one of the longest-running Wrath of the Lich King private servers. Since launching in 2012, Dalaran-WoW built a loyal community and became known for its unique progression system and dedication to the Wrath of the Lich King experience. The team thanked the community and wrote: “The realm falls silent now. But it was never the servers that made this place magic. It was you.” “Every raid, every battleground, every late-night conversation and unexpected friendship became part of something bigger than we ever imagined.”

Seedance 2.5 Emotional Acting Test | Expression Shift + Micro-Emotion 🎬 Made this 8s emotional close-up with Seedance 2.5. No explosions. No complex camera moves. Just one face carrying the whole scene. Prompt👇 Close-up of an emotional monologue. The woman in @image_1 sits at a wooden dining table in the dimly lit, warm wooden kitchen of @image_2—wooden cabinets, deeply blurred bowls, plates, and storage shelves behind her, night outside the window. There are no visible light sources in the frame—no chandeliers, lamps, lighting equipment, or fixtures—only the light itself and how it falls on her face are visible; all light sources are outside the frame. The entire film is shot in a single, continuous long take, without any editing, transitions, or camera changes—the same uninterrupted camera from beginning to end. She remains silent throughout, not uttering a single word—the entire emotion is conveyed solely through facial expressions and eye contact. All emotions shift rapidly, quickly transitioning from one to the next, each stage brief—the performance swiftly glides through each emotional phase in a tight rhythm. Camera: The camera position is fixed in place, but it presents the texture of handheld shooting—vivid handheld tremors, slight shaking and vibrations, the lens drifting almost imperceptibly left and right, breathing with the scene. The camera consistently focuses on her face, a close-up, keeping her centered and within the frame—only the subtle hand-held movement around her creates tension. This trembling, intimate feel builds tension, amplifying the emotional outburst. The light moves in circles around her, an invisible beam smoothly circling her along its trajectory, the illumination shifting with each stage: Stage 1 (Fast) – Suppressing bitterness. Her gaze is lowered, tears welling, her lower lip trembling, her chin furrowed, her breathing labored, her lips pressed tightly together. Lighting: Directly facing her, illuminating her entire face evenly and softly from the front, warm spots of light falling on her face, the surrounding background fading into warm darkness. Stage 2 (Fast) – Tears. Tears stream down her cheeks, she abruptly looks up, blinking to force the tears back, quickly wiping her eyes with the back of her hand, her eyes bright and red. Lighting: Shifts to her right side—now only the right half of her face is illuminated, the left half sinking into shadow, a soft, flowing shadow spreading across her face. Stage 3 (Fast) – A burst of laughter. A silent, hysterical laugh bursts forth through her tears, a mixture of sobs and laughter, her head shaking, her expression shifting from pain to relief. The lighting: continues to move behind her—her entire face sinks into shadow, the light coming from behind, the harsh backlight outlining her head with bright edges, illuminating her ears, cheekbones, and wispy strands of hair, leaving her face mostly dark, almost a silhouette with luminous edges. Fourth Stage (Climax)—Breakdown and Relief. She slams her hand on the table—the instant she strikes, the light suddenly blazes, illuminating her entire body. The lighting during the table slam: a strong, direct beam of light shines directly on her, bright, even light flooding in from all sides, clearly overexposed, shadows disappear, her face completely exposed and submerged in light. She then leans back in her chair, arms crossed, exhales a short breath, her eyes resolute, relieved. Fifth Stage (Ending)—The light shifts to candlelight. Lighting: Everything goes dark, leaving only the warm, flickering candlelight from off-screen sources (the candles themselves and any other light fixtures are not in the frame)—the warm, dancing light moves and flickers across faces, casting deep, soft shadows, with points of light dancing in the eyes. The lighting changes rapidly, but always smoothly—not abrupt cuts, nor flashes (except for the sudden, intense flash when the table is slammed), but rather the light source moves smoothly in circles, allowing the eye time to clearly see and understand each type of light before it transitions to the next; the intensity increases layer by layer with each stage. All of this happens without a single cut or splicing, within the same continuous long take: only the lighting changes, the camera remains vibrant and continuous. Close-up shots, anamorphic widescreen lenses, oval bokeh, shallow depth of field, no lens flare, no horizontal flare, no lens flare. Slight film grain, cinematic color grading. 8K. Audio: No music, no dialogue, only sound effects—intermittent breathing, sobbing, sniffling, a silent, nervous laugh with a breathy sound, the sound of slamming a table, the creaking of a chair, and slight crackling sounds. Try Seedance 2.5 on Ima Studio 👉 #Seedance25# #AIVideo# #AIActing# #CinematicAI# #Filmmaking#

Grok Imagine text-to-video prompt: SCENE CONTEXT One continuous locked-off wide shot inside a cluttered high-rise gaming apartment at night. A fully clothed adult man sits at his desk facing the monitor, absorbed in a computer game. An adult anime woman (age 22 or older) carrying a metal frying pan sneaks up behind him from frame-left, swings the pan hard and fast into the back of his head with a single whip-crack strike that knocks him out cold instantly, his head dropping hard onto the desk with a small bounce. She delivers a short Japanese line, then runs off frame-right while giggling. LOCATION MAP Foreground: edge of the desk and chair legs. Midground: the seated man at the gaming desk with dual monitors, keyboard, mouse, RGB lighting, and scattered energy-drink cans. Background: cluttered apartment wall with posters, shelves of figures, city-window view at night. The anime woman enters from frame-left rear, moves behind the man's chair, then exits frame-right. Warm practical room lamps mixed with cool blue monitor glow and red PC accent lights. FIRST FRAME / BLOCKING Wide shot already framed and locked. The man is seated center-right, torso facing the monitors, head slightly forward. The anime woman is partially visible at the far left edge of frame, body oriented toward the man, frying pan held low in both hands at waist height. Spatial relationship readable immediately: she is behind and slightly to his left, outside his peripheral vision. FORMAT MODE One continuous shot, the camera does not cut on its own. The frame stays identical from first second to last. OPTICS 47° neutral wide FOV, eye-level height matching the man's seated eye line, deep focus so both the desk and the space behind the chair remain sharp. No drift for the full duration. CAMERA Locked tripod, completely stationary, frame fixed for the entire 15 seconds. The operator stays hands-off after the first frame. ACTION 0.0s–3.5s — The man clicks the mouse and taps the keyboard with natural, focused movements, leaning slightly toward the monitor. The anime woman advances on light tiptoe steps from frame-left at about 3 km/h, body low, frying pan close to her torso, eyes fixed on the back of his head. 3.5s–6.0s — She reaches the position directly behind his chair and coils into a short compact wind-up: pan raised above her right shoulder, both hands gripping the handle, weight loaded onto her rear foot, hips turned slightly away like a batter ready to swing. 6.0s–6.5s — She uncoils and swings hard and fast: hips rotate first, shoulders whip through, the pan accelerates through a tight horizontal arc and reaches roughly 30 km/h at the moment the flat of the pan meets the exact center of the back of his head. The full swing takes 0.4 seconds from launch to contact, a single clean whip of motion. 6.5s–7.5s — Knocked out cold, lights out on impact. On the exact contact frame his eyes shut and every muscle releases at once. His head drops hard and fast, driven forward by the strike, and his forehead smacks the desk surface with a solid thud, bounces up once about five centimeters, and lands again, coming to rest cheek-down on the desk. His torso folds forward behind the falling head, arms flopping off the keyboard and mouse and settling limp on the desk. He is out cold and remains completely motionless from this point through the end of the shot, head down, dead to the world. 7.5s–10.5s — She lowers the pan to her side, stands upright behind the slumped man, and speaks her line with clear lip sync while looking down at his knocked-out body, chest rising with a satisfied breath. 10.5s–15.0s — She turns sharply to her right, takes three quick running steps toward frame-right at about 10 km/h, and exits the frame still holding the frying pan, body leaning forward into the run, shoulders bouncing with a giggle. PERFORMANCE Man: fully absorbed in the game until impact, natural micro-adjustments of hands and slight forward lean. From the contact frame onward he is unconscious dead weight: face slack, jaw loose, eyes closed, zero muscle tension anywhere in his body. After the head bounce settles he is a motionless heap draped over the desk, held perfectly still through the end of the shot, clearly out cold. Anime woman: bright adult face with clean 2D cel-shaded features, mischievous grin, tongue pressed to the corner of her mouth during the wind-up. The swing is committed and athletic: full-body rotation, arms extending through the arc, a small follow-through past the contact point before she checks the pan. After the hit her posture opens into a brief proud stance, then she pivots and runs with lively bouncing steps and a visible giggle that lifts her shoulders. Eyes stay alive with micro-saccades throughout. Playful older-sister prank energy, posture upright and comedic. PHYSICS The frying pan carries visible metal mass and inertia: it lags a fraction behind her hands at the start of the swing, whips through the arc with accelerating momentum, and stops dead on contact with a small vibration through the pan face and her forearms. The man's head falls as pure dead weight accelerated by the strike: fast drop, hard contact with the desk, one small five-centimeter rebound, then final settle with zero further motion. The desk registers the impact: a nearby energy-drink can jitters, the mouse shifts a centimeter. His torso folds forward behind the head and settles as a limp mass, no residual muscle movement afterward. Her hair and clothing trail the swing rotation with natural delay and settle after the follow-through. Her footsteps show clear weight transfer on the sneak and the exit run. LIGHTING Primary sources: warm 3200K practical desk and room lamps from upper left, cool monitor glow illuminating the man's face and hands, red PC case lighting under the desk. Soft natural falloff into the background. The pan catches a brief warm lamp glint as it whips through the swing arc, and the contact shadow of the pan and her arms sweeps across the man's back at the moment of impact. AUDIO Clear adult feminine Japanese anime voice with accurate lip sync delivering exactly: 「おやすみなさい！」 A sharp air-whoosh as the pan whips through its arc, ending in a single bright comedic metallic BONK on contact, followed immediately by a solid wooden thud as his head hits the desk and a lighter second tap on the bounce landing. Continuous quiet keyboard taps and mouse clicks up to the hit, then silence from the desk. Computer-fan hum, faint game audio from the speakers, quiet room tone, distant city ambience through the window. Her light footsteps on the floor, then a short bright giggle as she runs. Only the listed sounds and the single spoken line. STYLE Photorealistic cluttered apartment interior combined with a crisp, clean 2D cel-shaded adult anime character. Warm practical lighting mixed with cool monitor and red PC accents, natural contact shadows, light cinematic grain. Wholesome slapstick gaming-comedy tone, the energy of a classic anime frying pan bonk. POSITIVE LOCKS Camera remains completely locked and stationary for the full 15 seconds, identical framing first frame to last. The man keeps facing his monitors until the strike and is knocked out cold on the exact contact frame: head drops hard and fast, forehead smacks the desk, one small five-centimeter bounce, then final rest, body limp and motionless through the end of the shot. Single pan strike only, swung hard and fast with full-body rotation, the arc completed in 0.4 seconds. Anime woman is clearly adult (22+), modest casual gaming-themed clothing, 2D cel-shaded style only. Only the one scripted Japanese line is spoken.

Odette · Swirling Snow Prima Ballerina of the Korolevskiy Troupe #GenshinImpact# #Odette# In Snezhnaya, the land of frost and ice, it often takes quite a bit of persuasion to get someone to go to the opera house or theater. On bitterly cold days, most would rather stay by the hearth than traipse across the snow just to catch a performance. Many, however, make an exception for Odette's ballet performances. Whenever her name appears on a show publicity poster, the lines start forming at the ticket window. Those standing patiently in line are not there because of her sweet smile, for she almost never smiles at the audience. Nor are they drawn by any warmth in her manner — once the curtain falls, she does not remain onstage for even a second longer. Instead, they have come for the dance performance itself. The instant Odette rises to the tips of her toes, even Snezhnaya's howling winds seem to fall still. Every step she takes is so precise, it takes the breath away from everyone in the theater. To her fans, that cold demeanor of hers only makes her more alluring. This young lady who has captivated so many onstage is also a member of the Fatui. Her days are divided between the troupe and the Fatui. Her dance practices begin in the early morning, while her training with the Fatui usually stretches late into the night. Her own practices and urgent missions fill whatever time that remains. In the practice room, she stretches to her limits before rising into dance. At the training grounds, she swiftly moves on to her next task after bringing down her opponents. Day after day, she continues like the dancer of a music box, turning without end, as though she never tires, as though she never needs rest. A friend once asked her, "Don't you ever get tired, going back and forth like that between ballet performances and the Fatui?" Odette cocked her head in response, seemingly in thought. Then she gave her answer, one that could not be any plainer: "But I'm already used to it."

BOOM! 34 People, Including The Janitor: A 1963 IBM Memo Explains Why A 125-Billion-Parameter AI Now Runs On Your Gaming PC, And How To Use It On August 28, 1963, Thomas J. Watson Jr., the head of IBM, sent a short memorandum to seven of his top executives. "Last week CDC had a press conference during which they officially announced their 6600 system. I understand that in the laboratory developing this system there are only 34 people, 'including the janitor.' Of these, 14 are engineers and 4 are programmers, and only one person has a PhD., a relatively junior programmer." Then the sentence that has echoed through computing ever since: "Contrasting this modest effort with our own vast development activities, I fail to understand why we have lost our industry leadership by letting someone else offer the world's most powerful computer." Imagine being one of those seven executives. You run the most powerful technology company on the planet. You have thousands of engineers, rooms full of PhDs, and budgets beyond counting. And a man named Seymour Cray, working with a few dozen people in a lab in the woods of Chippewa Falls, Wisconsin, has just built a machine about three times faster than your best, the IBM 7030 Stretch. To the outsider, Watson wrote, Cray's laboratory "appeared to be cost concious, hard working, and highly motivated." He even kept the typo. The Computer History Museum still holds the scan, courtesy of the IBM Corporate Archive. The memo is real. The numbers are real. The sting is real. The Woods Lab That Beat The Giant Seymour Cray had asked CDC's CEO for a lab free of headquarters interference. He got one in his hometown. With Jim Thornton and a small crew, he built the CDC 6600: silicon transistors from Fairchild, a reduced instruction set before anyone named RISC, ten peripheral processors handling the housekeeping so the central processor could stay on the math. The machine ran at 10 MHz. It weighed about six tons. It was the world's fastest computer from 1964 until its own successor took the crown. Small. Frugal. Highly motivated. History repeats this lesson every few decades, and the vast ones forget it every time. Legend says Cray read Watson's memo and replied, "It seems like Mr. Watson has answered his own question." The line appears in textbooks, slides and oral histories. I have never seen a primary source for it. It survives because everyone who has worked on a small team knows the truth inside it: the size of the room was the advantage. A 125-Billion-Parameter Mind Under Your Desk It is happening again this week. On October 4, 2026, a free, open-source project called Strata landed near the top of open source sites and stayed there into Monday morning with hundreds of points. Strata does one thing: it runs a 125-billion-parameter AI model, Qwen3.8-Flash-Next, on an ordinary gaming PC. In its author's words, this is "a large, smart AI model that usually needs a server." The published requirements are plain. A graphics card with 12 GB of memory or more. 32 GB of system RAM, with 64 GB enough to run every size. About 80 GB of free disk, preferably an SSD. Windows 10 or 11, or Linux. NVIDIA or AMD. MIT license for the tool itself. An OpenAI-compatible and Anthropic-compatible programming interface on your own machine at And, again in the author's words: "Nothing leaves your PC." On an RTX 5070 with 12 GB and 64 GB of RAM, the author measured 94 tokens per second writing answers with the fastest compressed size, and more than 2,000 tokens per second reading a long prompt. On an RX 9070 XT the same size wrote at 60 tokens per second. The author estimates a 24 GB card such as an RTX 3090 should write in the 100 to 140 tokens-per-second range. One commenter reported 124 tokens per second on an RTX 4090 with 128 GB of RAM. Your mileage will vary with quantization, RAM speed and what else is open on the machine. The point stands: a server-class parameter count is answering on consumer silicon. Consider what that means. The model chats, writes code, reads pictures and works with coding agents. The tools you already use can point at a local address instead of a metered cloud. Nobody can switch it off, raise the price overnight, or read its mail. The Frugal Trick Cray Would Have Loved A model this size will not fit on a gaming card alone. Strata spreads the work across the whole machine. Think of a kitchen. The few things you use constantly stay on the counter. Everything else waits in the pantry. In Strata's case the "experts" that the model calls most often stay in graphics memory. The rest live in system RAM. The SSD holds the large lookup tables. A small helper guesses the next few words; the big model checks them in one pass. The result is the same answer, delivered sooner, on hardware you already own. Vast data centers are one way to run a mind. The modest machine under your desk is now another. Why This Matters To You Earlier this year I founded a Zero-Human Company on a 12-year-old MacBook in my garage: AI agents as the staff, local models as the regulators, salvaged archives as the raw material. The limit has always been the size of the mind I could run locally without asking permission. That limit just moved. Personal AI is the new invention of fire. The people who own the minds on their own desks will write their own rules. A reader with a gaming PC can now staff a small company of AI agents with a model in the same weight class as systems the giants rent out by the token. This is the worst it will ever be. How To Hire It Here is the playbook, drawn from Strata's public README and install docs as of this writing. Follow those docs for the latest flags and model menu. Licenses for the model and each compressed build are separate from Strata's MIT license; read them before you rely on the system for anything important. Step 1. Check your hardware. You need a supported NVIDIA GeForce RTX 20/30/40/50-series card, or a supported AMD Radeon card, with at least 12 GB of VRAM. Confirm 32 GB of system RAM or more. Free about 80 GB on an SSD. Update your graphics driver from NVIDIA or AMD. Step 2. Get Strata. Clone or download the repository at Unzip it. On Windows, double-click START-HERE.bat. On Linux, run ./setup.sh inside the Strata folder. If you already use a coding assistant on that machine, you can paste the project's AI setup prompt and let it drive the install from docs/AI_SETUP.md. Step 3. Answer the installer's questions. It will ask which model size to download, how much context to keep, and whether you want image input. Press Enter for the recommended answers if you are unsure. The download is roughly 70 GB; if it stops, run the installer again and it continues. Step 4. Pick a size that fits your RAM. With 32 GB, start with the Coder build, which drops half the experts and is tuned for code. With 48 GB, IQ2_XS or Q2_0. With 64 GB, IQ2_XS is the author's recommended default; IQ3_S is smarter and slower. With 96 GB or more you can try the larger Unsloth builds. Smaller sizes are faster. Larger sizes keep more quality. Step 5. Wait through the first start. The first launch can make the PC slow or unresponsive for one to three minutes while Strata loads tens of gigabytes into RAM. That is normal. Do not close the window. Your browser should open the Strata app at Step 6. Point your tools at home. In any app that accepts an OpenAI-compatible provider, set the base URL to Any API key and any model name will work for the local endpoint. For Anthropic-style tools, use For Codex CLI and the OpenAI Responses API, use /v1/responses. Thinking effort can be set to off, low, medium or high; off is fastest, high is for hard questions. Step 7. Keep it on your desk. By default Strata binds to localhost. Leave it there unless you know why you need otherwise. If you ever expose it to another machine, the docs say to set an API key. For a Zero-Human Company roster, treat this local endpoint as the shared mind: one CEO agent for strategy, one engineer agent for code, one researcher for archives, one archivist for files, and one night janitor that cleans logs and memory while you sleep. Wire them through the same OpenAI-compatible address. The org chart fits on one machine the way Cray's lab fit in the Wisconsin woods. Step 8. Know the limits. Heavy compression trades some quality for speed. The largest sizes may page from the SSD and slow down if RAM is tight. You are running a third-party binary and a third-party model on your own hardware; that is the point, and it is also a responsibility. Close other memory hogs if the disk light never stops blinking. Read the troubleshooting doc before you open an issue. Watson had thousands of people and could not understand how 34 beat him. You may need one gaming PC and one evening. The Pattern Every few decades a frugal team builds something the giant said required a cathedral. In 1963 it was a supercomputer in Chippewa Falls. In 2026 it is a 125-billion-parameter mind under a glass side panel, glowing cyan and magenta on a desk that also holds a coffee mug and a slide rule of a different kind. The memo is sixty-three years old. The question is the same. Who will you hire, and on whose machine will they work?

a lab in the netherlands scanned couples during orgasm and stumbled onto the strangest finding in sex research. when women wore socks, the orgasm rate jumped from 50% to 80% the researchers weren't studying socks. the scanning room was cold, some women complained, socks were offered. suddenly the success rate exploded and the team realized they'd accidentally run the most important experiment of the study the mechanism showed up right on the brain scans. female orgasm requires the amygdala, the brain's fear and threat detection center, to power down. cold feet kept the threat system quietly online. warm feet let it switch off. that tiny bit of physical discomfort was enough to block the entire cascade - her brain cannot climax and scan for problems at the same time. the systems are neurologically mutually exclusive - socks are a stand-in for the real variable: comfort. temperature, privacy, no time pressure, no risk of interruption, nothing pinching or hurting. every small discomfort is a tax on the fear center - this is why the same technique works one night and fails the next. the variable that changed wasn't your hands. it was her nervous system's threat level - the environment is doing foreplay before you touch her. warm room, locked door, no rush, phone away men study techniques for years and lose to a cold room. her nervous system decides if orgasm is possible before your skills ever enter the conversation. handle the amygdala first. the socks were never about socks

Why I don't take melatonin to fall asleep: - Melatonin suppresses the onset of puberty. In kids and babies it's released all day and night and that tonic release holds back the hormones that trigger puberty - It helps you fall asleep but won't help you stay asleep. Many people wake 3-5 hours later unable to get back down - It's a hormone sold over the counter and completely unregulated. Tested brands ran from 15% of what's listed on the bottle to 400 times more Consult a healthcare professional before adding or removing anything. @hubermanlab

Nothing like enjoying my Starbucks on a nice fall NYC morning before Zeta Live $ZETA. I can’t wait to hear first hand what @dsteinberg10000 has in store for us this morning. We tried or I should say @wealthmatica tried to figure it out last night and we still have no idea. The keynote can’t come quick enough! I suggest everyone watch the keynote on @ZetaGlobal X account this morning. It feels like he may be laying down quad aces or maybe even a straight flush!