Welcome to Paranormality magazine. Each week, Paranormality magazine explores all 40 subjects, from phantoms to UFOs, and every cryptid creature in between. Each week, you are treated to a collection of well-researched and investigated stories, interviews and reports on cutting-edge paranormal projects and topics they know you crave. And here in the podcast, I share stories from the magazine to give you just a taste of what you receive in every issue. I'm Darren Marlar and this is Paranormality magazine. In this episode, we begin with a story of high strangeness from South Africa. Chaz CMP brings us an article entitled Have You Any Water? It was December of 1951 outside of Parle, South Africa, on the Drakenstein Mountain when another bizarre encounter occurred. Today, there is a tunnel that passes through this mountain range, but in the 1950s, one had no choice but to make the much longer journey over the mountain. The witness who was identified as Henry made one such trip in his pickup truck one warm summer evening. He'd been working on his truck and wanted to test it out to ensure the job was finished. A quick trip up and down the mountain was all that he had in mind. Henry drove toward the top of the mountain until he reached a plateau near the peak. He decided that this large flat area was best to turn around, but before he did, he took a moment around 11.15 p.m. to take in the beauty of the evening. The moon was in the sky that night, partly obscured by the surrounding peaks casting their large shadows of darkness across the plateau. Henry was about to begin his descent back down the mountain when he saw a man emerge out of the darkness, waving and walking toward him. The man walked up to Henry's truck and asked him, Have you any water? Henry informed the man that he did not have any, but the man insisted that he was in desperate need of some. At this, Henry told the man that there was a stream a little further down the road that they could use. The man asked how far this stream was, and after being reassured it was nearby, he hopped in Henry's truck. As the two men drove toward the stream, Henry quickly observed his new passenger. The man sitting next to him looked human. He was wearing an off-white lab coat, regular trousers and shoes. His head was topped with neat brown hair and he was clean shaven. Overall, he looked to be about 40 years old. However, Henry also noticed a few strange things about the man's appearance. His forehead seemed to be slightly protruded and his hands had long, delicate fingers that Henry described as looking almost effeminate. He was also remarkably short at under five feet tall. Henry also said the man's accent was bizarre, and while he admitted that South Africa was home to a lot of bizarre accents, he was certain that this one was more strange than usual. When they arrived at the stream, Henry asked the man if he had a container to hold water to which the man replied, no. At that, Henry remembered he had an emergency oil container in the back of his truck that they could use. When the oil can was reasonably cleaned and filled with water, the two men got back in the truck. Henry navigated a difficult three-point turn on the narrow road and the two men were off, heading back toward the plateau. When they got there, the man instructed Henry to drive a little further into the shaded area from which the man had originally emerged. As they drove into the darkness, Henry saw a large metal sphere that hung about 100 meters off the ground. It was perched on four legs with a ladder descending from underneath it. The sphere was between 10 and 15 meters in diameter, but not very tall, only being about 4 meters in height, including the legs. The small man got out of Henry's truck, walked over to the craft's ladder, and invited Henry to come aboard. Henry was hesitant, but the man waved at him in reassurance, and the two ascended the ladder. Inside the craft, Henry observed what seemed to be a large, circular room. There were four other men inside that looked similar to Henry's new companion, but they appeared to be a few years younger. Henry then noticed one of the men was lying on the floor of the craft, and the others were crowded around him. It became clear that the man lying on the floor was injured. Henry's guide informed him that the man had suffered burns upon entering the atmosphere when one of their windows had broken. Henry offered to get the local doctor to help them, but the man refused. The other four men continued about, as if Henry wasn't even there, and only the original visitor spoke to him. Henry next noticed a strange panel in the center of the room, and here's how he described it. In the middle of the room, I spotted some levers, something like those in a railway signal box. They seemed to be about one meter in length, the tops ending in a sort of two-pronged, forked handle, just like the handbrake in old motor cars. From where I was, I could not see how many, but maybe eight in two rows. They protruded from the interior of the object below the floor. I could see the rectangular slits through which they protruded. Behind the levers I could see some sort of table, more like a console. I thought there might be some dials, some instrument panels, but saw nothing like that. This being my job, instrumentation engineering, I noticed everything very clearly. He also noticed that there were seats around the walls of the craft that seemed to be covered in some kind of leather. The craft was well lit, but Henry could not see any light source. There were windows circling the craft that were two feet by three feet in size and were square shaped with rounded corners. He also noted that none of its windows were broken. The floors were metallic and slippery, and had some kind of strange pattern that he could not quite recall. While he observed, he noticed the men moving about their injured comrade, and they seemed to be holding strange devices. After giving the water to one of the other men in his group, the original visitor came back to where Henry was standing. The short man then asked Henry if there was anything he wanted to know. As an engineer, Henry's first question was, where are the engines? The man told him there were none, and that the craft used a type of gyroscope that spun heavy metals around it. The spinning of this liquid metal would create an independent gravity field for the craft, and that is how it functioned. Henry then asked where the men came from. In response, the short fellow simply pointed upward, out the window to the stars. He would not elaborate further. Henry then remembers climbing back down the metal ladder and returning to his truck, speculating that his entire time aboard must have been no more than 15 to 20 minutes. He thought about the craft and the strange small man his entire way home, and that night he fell into a deep sleep. He slept so deeply in fact that the next day he was unsure if the event was a dream or not. So he returned to the plateau. He found no craft there, but there was an indentation in the ground where its legs had once stood. He then thought to check the back of his truck, where he discovered that his oil can was gone. Imagine moving into a home with your family in the dead of winter, when suddenly bizarre things start to happen. Strange things, terrifying encounters that recur, defying all logic that one can explain. This next story is about a young family whose dream home became a terrifying nightmare. Molly Briggs tells us about Gary Indiana's Portal to Hell. In November 2011, Latoya Ammons for three kids and their grandmother moved into 3860 Carolina Street in Gary, Indiana. Settling into their new home should have been a time of great promise and new beginnings. Unfortunately, the horrifying events that would eventually occur would terrify and confuse each member of the Ammons family. Shortly after moving in, the family immediately witnessed thick black flies appearing in growing numbers, swarming an area of the house that was too cold for them to survive in. Confused and disgusted, they would swat them away, killing them, only to see the flies return later in full force. The presence of flies is not uncommon within a home or structure that is rife with paranormal or demonic activity. That is not to say, however, that flies are definitive proof of the devil himself. It's simply a feather to add to this paranormal story's cap. Another shady situation was a shadowy figure seen by the children's grandmother. The woman had seen a strange entity pacing the floor one night. As she moved toward the dark, ominous figure, all she found was a pair of soggy footprints where the shadow had been. At this point, it feels reasonable to say that most people would have gathered their things and said goodbye to this creepy cabana by now, moving out faster than a rat through a drainpipe, but not the Ammons family. Armed with a Bible, holy water, crucifixes and candles, they chose to stay and fight whatever dark entity had taken over their new home. Ultimately, it would be a decision they would regret. Four months after they moved into the home, a horrifying, unexplainable event would set the unwelcome wheels of terror in motion. While the family was grieving the loss of a loved one, many people within the home witnessed Latoya's 12-year-old daughter levitating above her bed. Faithful friends and family members dropped to their knees and prayed hard for the bedeviled child to be safely delivered back to her bed. Once their prayers were answered, the terrified people spilled from the home like a cup of water overflowing never to return. Swallowing their pride and reaching out for help, Latoya and her mother quickly found that finding someone to exercise 200 demons from a home was a task much easier said than done. Two psychics sensed that at least 200 demons were residing inside the Gary Indiana home. The activity in the house was so threatening that both psychics suggested the only thing the family could do for their safety was to move. Most churches in the Gary Indiana area denied the desperate women the slightest help with their demon problem. They did however offer some holy advice. The cowardly clergy told the women to clean the home, preferably with ammonia and bleach. They were then told to smear oil down and around all doors and windows for extra measure. One may ask, why stop there?  That sounds like an equally efficient recipe for getting rid of rascally demons. It wasn't long after that whatever was possessing the home seemed to be affecting the children. While playing in the living room one afternoon one of the young boys spoke in whispers.  Some reports vary, however it is speculated that during that same event the other children joined in until ultimately they began attacking each other and their grandmother physically. It's said that while chanting the children's eyes would start to bulge and their natural effervescent childlike smiles would creepily turn up into an unnatural grin. All family members felt the effects of the dark entities haunting the Ammons home. The smallest of the three children had taken to communicating with a boy who could only be seen by him. In one horrifying encounter the youngest Ammons child was picked up by an unseen force and thrown across the room. As time passed the activity in the home increased, making a regular daily routine impossible. The children missed many days of school which ushered in the assistance of multiple doctors and DCS caseworkers. On one of the memorable visits to the doctor's office the doctor noted the children's delusional behavior and bizarre disturbing statements. As the children stood in the office with family and office staff present including a nurse and a DCS worker the youngest child flew into the air. The origin of the force that propelled the boy could not be seen. The same child then commenced to walk up a wall. The boy defied gravity and flipped directly over his grandmother. Following the alarming event medical staff were seen fleeing from the room leaving the family more desperate than ever. Feeling as if their hands were tied DCS together with the authorities removed the three children from the home. Although Latoya Ammons had thought to a certain degree that she could beat the heady demon the state of Indiana had enough. The final act of the pure evil lurking within Latoya Ammons home was to separate her from her kids. It would prove to be the cruelest act of all. In an effort to come to a clearer understanding of what may be happening within the home DCS and the police made multiple trips to the house to investigate. Officers noted that an oily substance was found dripping from the blinds covering windows inside the home. After the blinds were cleaned and dried the oil returned with no explanation as to the source. One worker haphazardly dragged her hand across the slick shades smearing her palm and fingers with the ominous oil which curiously turned parts of her hand white. Police investigating the home reported witnessing apparitions as well as experiencing radio malfunctions. Just prior to leaving the home for good Latoya Ammons agreed to be subjected to a good old fashioned exorcism. A religious act done only by a priest and by the explicit permission of a bishop. Three exorcisms later Latoya was feeling more like herself. After a short time she moved away from what some have called the demon home and straight to Indianapolis quickly regaining custody of all three children. As for what eventually happened to what some media outlets have dubbed the Portal to Hell house, it was bought by a fairly well-known ghost hunter for $35,000. After filming a documentary about Latoya Ammons' story, the ghost hunter had the structure torn down for public safety. A curious move to say the least. Was the tear down an effort to save curious investigators from potential mental or physical harm or was it to ensure that future filming of the now infamous property would be impossible? We may never know. One of the particulars of this strange case begs the question of whether or not the spirit world can actually affect our physical bodies. During the filming of the documentary many people became ill. One investigator suffered major organ failure, another experienced uncontrolled violent behavior and yet another was prone to fly into a rage without any conscious intention of doing so. These are just a few examples of strange instances occurring in or around the home, just after or during an investigation. Albert Einstein said, energy cannot be created or destroyed. It can only be changed from one form to another. This may be a quote to revisit when questioning the existence of malevolent entities.  Want more paranormality? Subscribe to Paranormality magazine and each month get it delivered digitally or via mail in our print version. Paranormality magazine is a collaborative endeavor featuring works from people like you who have a passion for all things mysterious and unexplained. Our goal is the pursuit of knowledge gathering captivating stories from our own team of writers, researchers and investigators as well as from writers such as yourself. Each monthly issue also includes a list of paranormal, horror, UFO and cryptozoology events around the country. Incredible paranormal themed artwork, articles and writing sent in from our readers, suggested books and podcasts to consume and more. Visit paranormalitymag.com and subscribe today for as little as $3.99 a month. That's paranormalitymag.com Paranormalitymag.com Seeing as this is October the month of Halloween, I thought it might be fun to bring you an article by J.A. Kirk from Paranormality magazine entitled The Evolution of Halloween Costumes. Greetings fellow seekers of the supernatural and lovers of the eerie. As the harvest moon rises and the spectral winds begin to whisper, our minds turn to Halloween that bewitching night when the boundaries between the living and the dead blur. To truly appreciate the modern marvel that is the Halloween costume, we must journey back to the ancient Celtic festival of Sauen which sparked the end of the harvest season and the beginning of winter. During this time the Celts believed that the veil between our world and the spirit realm grew thin, allowing the souls of the departed to return. To ward off malevolent spirits and to blend in with the supernatural entities, the Celts donned elaborate costumes made from animal hides and masks carved from gourds. These disguises were as much a means of protection as they were a form of celebration. With the spread of Christianity, Sauen evolved into All Saints Day and All Hallows Eve or Halloween. Costume traditions persisted, but they gradually absorbed Christian influences. People began to dress as saints, angels, and demons using costumes as a way to educate and entertain during religious festivals. The 18th and 19th centuries witnessed the rise of Gothic literature and the emergence of the macabre in mainstream culture. Literary works like Mary Shelley's Frankenstein and Bram Stoker's Dracula inspired fascination with the supernatural and monstrous. As a result, Halloween costumes took on darker and more sinister themes. People embraced their inner monsters, vampires, and ghosts with morbid delight. The 20th century ushered in a new era of Halloween costumes influenced by popular culture. Iconic figures from film, television, and comic books became sources of inspiration. The 1930s saw the emergence of classic horror movie monsters like Frankenstein's monster, Dracula, and the mummy as beloved costume choices. The post-World War II period brought with it the baby boom and a surge in children's Halloween celebrations. Superheroes, beloved cartoon characters, and space explorers became the favorite attire for young trick-or-treaters. This era marked the transition from homemade costumes to store-bought ensembles, giving rise to the commercialization of Halloween costumes. The 1960s marked a period of DIY creativity. Halloween costumes became a canvas for self-expression and political statements. People embraced the freedom to craft their own costumes, often drawing inspiration from psychedelic art, iconic musicians, and cultural phenomena. The 1980s witnessed the resurgence of horror in pop culture. Slasher films like Halloween, A Nightmare on Elm Street, and Friday the 13th dominated the silver screen. This led to a resurgence of classic horror figures as popular costume choices. The 1980s also brought about the influence of video games with characters like Mario and Luigi becoming Halloween staples. In the 21st century, Halloween costumes have fully embraced the influence of pop culture. From beloved movie characters like Harry Potter and the superheroes from the Marvel and DC universes to trending memes and viral sensations, costumes have become a reflection of the times. The rise of cosplay, a subculture dedicated to dressing as fictional characters, has further blurred the lines between Halloween and fan conventions. Cosplayers spend months crafting intricate and detailed costumes, elevating the art of costume creation to new heights. As we look to the future, it's clear that Halloween costumes will continue to evolve. Technology, including 3D printing and smart fabrics, will enable even more creative and immersive experiences. Virtual reality and augmented reality may offer entirely new ways to transform into fantastical beings for Halloween night. The evolution of Halloween costumes mirrors the changing cultural landscape. From ancient traditions rooted in mysticism to modern expressions of pop culture and personal creativity, costumes have become an integral part of the Halloween experience. As we embrace the unknown and venture into the supernatural this Halloween, let us also celebrate the ever-changing art of costume creation. Happy Haunting UFO slash UAP slash Alien disclosure has gained quite the traction over the years. One part of social media seems to be flooded with videos of lights and objects in the sky, while the other part is inundated with videos of testimony from government whistleblowers and experts claiming aliens exist. Whatever you believe, one thing that holds true is that this is not a new phenomenon. For decades people have been talking about the existence of non-terrestrial life forms. UFOs and strange beings have been painted in caves, ancient structures and renaissance art. People have been experiencing these phenomena for centuries. And one of those people happens to be Deborah D. Roke, who wrote an article for Paranormality Magazine entitled Close Encounters of the Third and Fifth Kind. I was in ninth grade when I first encountered a UFO. It was a school night, though I cannot tell you the date or day. My father and younger sister were sleeping. My mother and I were the only ones awake. I do not remember what I was doing awake, but I recall it was past my bedtime. My mother was outside hanging clothes out to dry. It was not unusual for her to take advantage of the still hours of the night to do laundry. We lived in Miami, near the Miami-Dade College North Campus, and if you lived in Miami during the 90s, then you know the scariest thing around was not Paranormal. It was the streets. This is why it always surprised me that my mother did her laundry outside at night, knowing it was risky. Suddenly I hear my mother yell my name, Deborah! I was startled because I never heard her call out my name like that before. Then I hear her call it again. I became concerned and ran outside to where she was by the clothesline. She took my hand, pulled me close, wrapped her left arm around my left shoulder, and crouched down to my height, pointing her right hand to the sky. She asked, Do you think that's an airplane? I remember feeling annoyed and thinking she called out my name hysterically just for an airplane. Yes, Mom, it's an airplane. She wasn't pleased with that answer. She said, No, look again. An airplane doesn't move that slow. So I stared at it. And that's when reality started to creep in. I wasn't staring at an airplane. I was staring at a UFO. I can't remember if we said anything, but the next thing I knew we were running through the house and out the front door to the porch. We stepped out to the driveway. There it was, hovering, silent, bright, colorful. There were so many colorful lights that appeared to dance as they blinked in pattern. It was saucer-shaped. I do not remember the color of the rest of the craft. Maybe it was silver? Maybe it was black? I was too taken by the experience to even notice. I remember it hovered low, no higher than what a helicopter hovers when it searches for suspects. I also remember it hovered silently. Helicopters and airplanes have engines that hum. It also hovered motionless. It didn't tremble. It was as if something invisible suspended it. I don't know how long we stood out there just staring. All I know is that my amazement and wonderment slowly turned into absolute fear. I began thinking about all the alien movies and abduction documentaries I had seen. The most impactful one being the McPherson tape, which had terrified me because at the time I didn't know it was a found footage film. I thought it was a real documentary. So when I saw this UFO in front of me, I believed I was going to be abducted. As the fear sat in, I ran inside my house and sat in a corner of my kitchen where the refrigerator met the wall. I tucked my knees in and shivered so strongly that my teeth chattered. I was frozen with fear. Soon after I sat in the kitchen, my mom ran inside and went to get the camcorder to record the object in the sky. She struggled to get the camcorder working. It was big, bulky, and she was not tech-savvy. I stayed in my corner praying and hoping we wouldn't be abducted. As soon as she got the camcorder working, my mom ran outside but came back almost as fast as she went out. It's gone, she said. She couldn't understand how it could be gone so quick, being that it moved so slow and hovered so still. She was disappointed. I was relieved. I went to bed that night feeling wary. I climbed up to my bunk, and before I went to sleep I looked outside my window toward the sky to make sure nothing was out there and fooled myself into feeling safe. I fell asleep. The next day my mother and I told my father what we saw. She even grabbed the camcorder and recorded a light in the sky that morning, convinced it may be the UFO we had seen last night. My father, an atheist and skeptic, didn't believe us. He said it was probably some sort of government aircraft. I told my friends at school who only considered believing me because my mother was a witness. My family didn't know what to think when we told them. They believed we saw something, but they chalked it up to the government too. I started looking out my window every night after that day, and I did see more activity as the years passed, except I told no one. As an adolescent and young adult, when I travel or go out at night I'd look to the skies where I would occasionally see things. Again, I told no one. I kept it all to myself. It was my personal secret, and each sighting was a confirmation that what I saw wasn't just an anomaly. It wasn't a government craft. It was something else, something bigger, something unknown, something personal, something unique, something only for me. I was disappointed. Disappointed at the lack of answers. Disappointed at the lack of trust. Disappointed at the lack of support. I couldn't understand why people didn't believe me. Why would I lie about this? What did I have to gain? I wasn't running and telling the tabloids or news. I was just trying to share a story with those I loved. But I was dismissed. Twenty years later, the disclosure went viral. I suddenly felt validated by the universe. I also realized that I was a part of thousands, if not millions, of people who shared similar stories and felt an equal sense of disappointment, stigma, judgment, and isolation, along with amazement, curiosity, and wonder. I felt seen and heard, though it wasn't my voice being used. Fast forward to today, where I'm learning more about what these experiences mean on a more personal level. After my most recent experience, I've reached a point where I'm no longer afraid of these encounters. I moved into my apartment last July with my husband and daughter. A couple of months passed before I began to see a light shine through my sliding glass door in the middle of the night. It happened for a few nights. What I found odd about the light was how bright it was and how it seemed to shine from the top rather than the bottom or side, which would indicate a car was either exiting or entering the community. The fact that the light came from the top weirded me out, but not enough to investigate. After a few days, I began to hear a droning and melodic hum. I would wake up to this sound for a couple of nights. I knew it wasn't a truck, car, or the sound of the air conditioner. Something told me it was something else, but I didn't worry about it and would fall back asleep. This lasted a few weeks until I saw them. I woke up one night and looked toward the corner of my room by the sliding glass door. There they were, two beings, one sitting on the floor with its knees tucked in, the other standing behind it. Both were looking at me. I remember staring at them for a few seconds. Some light shined through the window and allowed me to see some details. I noticed the one standing was about the same height as my light switch. I also noticed their skin color was a reddish-brown color. Their heads were large and oval, but it wasn't the typical elongated egg shape we're used to seeing in films. Their heads were wider. The chin wasn't long though, it still looked somewhat pointed. The eyes were large, black and shiny as usually depicted. I recall them looking at me and me looking at them, but I didn't feel startled or scared. I just told myself to go back to sleep, so I did. In the morning I told my husband and he was amazed. He said that I most likely had a connection with them since they visited me all those years ago. I told him it felt like what I saw was real, but I wondered if it was a lucid dream. I suppose I'll never truly know. What I do know is that I am not alone, pun not intended. I am a part of a community of individuals who have had similar experiences. Now I welcome these experiences and even seek them out. How? A close encounter of the fifth kind. I've done a CE5 meditation, not one guided by anyone. I did it on my own, using my intuition and experience. It did not disappoint, but that is a story for another day. Please know, if you have had a UFO, abduction or alien visitation experience, that you are a part of a growing community. Feel free to reach out to me and share your story. Additionally, if you are having a hard time reconciling the encounter and are still battling feelings of confusion, disappointment, stigma and judgment, I can help with that too. Keep looking toward the skies. As they say, the truth is out there. Thanks for listening to Paranormality Magazine. Get more information about the magazine and subscribe to our monthly publication at ParanormalityMag.com. That's ParanormalityMag.com or click the link in the show description.  We might feature you in our next issue. If you have a paranormal podcast, you can add it to our website so our readers can find your show. And artists, if you'd like your work to be featured in our magazine or on our back cover, contact us. Again, our website is ParanormalityMag.com. I'm Darren Marlar and I'll have more paranormal for you next time from Paranormality Magazine. Hey weirdos, be sure to click the like button and subscribe to this channel and click the notification bell so you don't miss future videos. I post videos seven days a week and while you're at it, spread the darkness by sharing this video with someone you know who loves all things strange and macabre. If you want to listen to the podcast, you can find it at weirddarkness.com slash listen.


Hey girlfriends, I'm Bianca Renee and you're watching Bianca Renee today and today I'm gonna try some brand new hair products I just got released, you know I had to be the first to get my hands on it. Today's video is sponsored by Sally Beauty And I am one of the first people to try the entire new Bond bar collection. They have expanded the line. So now there are one two three four five six seven eight nine ten Products in total. Let me chill out my lights for a second So you can actually see these white bottles and let me put them all in order. So you watch my previous bond bar video I only used number three four five and six and I honestly thought why would they start the line at number three? And I should have known that they were plotting for some more products So instead of starting with number three the pre shampoo then the shampoo then the conditioner and the styler We're gonna add some steps before that. So now we have zero one and two before your three four Know what you're thinking next is five wrong four P Then five six seven and eight The full bond bar collection now let's go over what the new ones are Zero is our bonding primer the bonding primer is supposed to help reduce breakage after one use We're always down for lessening breakage Repairs and helps generate new bonds for stronger hair Revitalizes hair strength while instantly helping to repair and smooth hair When used in a regimen with number three the pre bonding shampoo It says to apply to dry hair in small sections from roots to ends until the hair feels damp Leave on for ten minutes. Do not rinse Then follow with number three bonding pre shampoo. Okay, let's do it You know, I'm not really one to do small sections ever, but you know, I'll try my best small section Roots breakage repair the breakage Make my hair stronger.  It smells like the the other ones. So if you like How the bonding products smell because you bought number maybe three four five six smells the same Smoothing this in really want to get your ends. That is how you get Longer hair by length retention. It feels super lightweight. It's like let me Like literally water So light Was my other section see this is why I don't section bond bar is a line created by Sally beauty So it's sold exclusively at Sally beauty if you guys want to try this for yourself, Sally does have a Two-hour shipping so you could get this today if you wanted to now that I'm going to let the bonding primer sit I'm here for ten minutes. What comes after number zero? Three that's what I'm going to use next number three You only go to step one and two if you have color-treated hair And you're literally in the middle of dyeing your hair on bar number one is the bonding booster bond bar number two Bonding recovery if you aren't using step one and two because you aren't coloring your hair Then you just go straight to step three like me now that it's been ten minutes I'm going to add my bond bar number three the bonding crew shampoo before rinsing out number zero I'm going to add this number three right on top. I love how creamy and smooth this is So I still apply Generously, so I don't want to forget the edges top of my head my ends the back just get it all Completely covered Now we're gonna let this sit for ten minutes Once again, which I much rather do out of the shower if you have very damaged hair You could do this once a week. If not like me Maybe every other week at least once a month So my challenge for you guys this week is to kind of do the opposite of what we just did and really give your hair like A whole self-care day. It's very common for your wash routine to be a whole day thing anyways But if you have damaged hair, I really want you to take this challenge seriously and take this time to really focus on Repairing your hair. So what does that mean?  Does that mean doing a big chop that mean getting a trim getting rid of those split ends those dead ends? Or is your hair so dry that it's been begging you for a hair mask? This is going to be the time for you to truly take 15 to 20 minutes to do a deep conditioning treatment this week Consider it a vacation day for your hair. Spoil it. Now one of the time for me to get in the shampoo and rinse this out I'm going to be adding the bonding shampoo number four But if you have color-treated hair, they have another new product for you. This is the bond bar Number four pee. This is a bonding purple shampoo Significantly brightens all blonde lightened and gray hair Neutralizes brassiness after one use you do not have color-treated hair use the regular number four the bonding shampoo You don't need to get both just get the one that makes sense for you and your hair And then after you use your shampoo to rinse all this out you they would grab number five the bonding conditioner But they have a new product, which is number We're skipping To number eight number eight is the bonding hydration Mask though this is supposed to improve wet detangling by up to 90% after one use that seems to be the common theme an intense Moisture treatment that adds volume That's what I need and smooth hair I think I'm going to personally skip number five because I have already tried this and I know I love it and it works Great and instead of the conditioner. I'm going to add number eight the bonding hydration mask So I'm going to go from number four to number eight. Let's go try it. Okay fresh off the shower just rinsed out number zero and Three and then washed it out with number four the shampoo And now I'm going to try number eight the bonding hydration mask on my wet hair Apply a generous amount to clean damp hair from roots to ends leave on for a minimum of Ten minutes and then rinse. Let's do it very creamy, but still smells good very like light scent roots to ends Now this also says to improve wet detangling for up to 90% after one use I did not detangle in the shower So let's see how it does Not bad Didn't do any detangling in the shower But it still felt really smooth even after shampoo Detangled side one Here is my shedding and next side probably could have used even a little less than I did Let's try that out that much There you have it We are Detangled now, let's put this up in a way And I'm going to let it sit in a shower cap for another ten minutes rinse it out and then come back to style Okay, just rinsed out the deep conditioner now. It's time to style So I have already used number six the bonding styling cream. It can be used on its own I always prefer a little bit of holds I'm going to be adding a gel after this a little bit I'm almost using it like a leave-in conditioner even though my hair is already very moisturized From that deep conditioner. We are looking good and shiny for my gel of choice I'm going to add some of the texture ID styling custard Ooh, you know what I need to do first. Let me make sure that this gets along So I'm going to add a little bit of this cream in my palm and then I'm going to add a little bit of the custard Put them on top of each other and rub this together To see how it reacts All right good. See how it's still nice and smooth That means they're going to get along without any flaking So let me add my custard on top.  Bond bar number seven This is the bonding concentrate. It's supposed to increase shine Minimize fly aways and protect against heat damage up to 450 degrees Fahrenheit So I could use this either two ways I can either use this right now as like a heat protected before I diffuse or I can use it when my hair is dry as like a finishing shine spray to help reduce fly aways Maybe I'll do both but let's use it as a heat protector right now. Let's see how this does Come to a little dropper. Oh You know how many drops I need. I Don't think it has a smell. Let's just Smooth it on top as a heat protectant My hair is about to be so shiny Now I'm going to diffuse my hair with the ion lust supercharged diffuser and come back and I'm back It's been a full day of washing my hair. I had to stop and you know eat some food, but Here is how my hair looks after a full wash day of bonding It looks really pretty Very nice. My hair is super soft Very moisturized very defined super shiny just for fun Let's add a little bit of the bond bar bonding concentrate to minimize fly aways and add shine Let's check out the fly aways Not really much to begin with But I have a little bit see what it does Smooth it on top I think that the bonding products are gonna speak more for those you that have damaged hair that have color-treated hair I think once I do decide to dye my hair again I'll even need these products even more than I do now my hair is relatively healthy So it is just making my hair look like extra shiny extra defined looks really elongated actually But I'm still all about the health of my hair But I think for me and my healthy hair I will probably commit to doing this once a month if you have color-treated hair I would say every other week if you have damaged hair Like really damaged here. You might even want to do this once a week It really just depends so I would say to give it a try and see how much your hair Really needs so now let me give you a little cheat sheet that bond bar gave me to share with you That will show you an option for your personalized routine So as you can see here if you have color-treated hair you might want to use all of them if you have blonde hair You want to use these if you have thick hair use these curly hair coily hair thick hair dry hair oily hair Or just use steps 3456 is a good recommendation for all hair types So let me go ahead and give you guys a little screenshot and now you know which ones you need So if you have already started using bond bar, please leave a comment down below Let me know how it's working on your hair. Sally beauty has gotten so many positive responses So many people have left reviews saying that just after one use their hair is so shiny and so soft So I love all the positive feedback that you guys have given me hope I was able to clarify Which product does what so you could figure out a personalized system for your hair I'll put a link in my description box. You guys can shop all these products Please use my link and if you have any questions leave them down below. I'll see you guys next time Thanks for watching beyond grenade today


So, hey everyone. Thank you for coming in. So, the topic that we're trying to address here is optimizing the long test run times using AI ops. So, oftentimes as contributors to open source projects, most of us have made pull requests to GitHub repositories. And they tend to get into CI CD tests, which oftentimes take up so many resources that we cannot possibly run all tests or just have backlog. So, to answer all those questions, how do we do that? And where do we come from? Why are we doing this? We are here to talk more about the optimal stopping point tool. So, I would like to introduce my colleague, Hema. Hello everyone. I'm Hema Viradi and I'm working as a senior data scientist at Red Hat. Both Akanksha and I are part of the emerging technologies data science team, which is part of the CTO office at Red Hat. And I'm based out of California and the United States. And my name is Akanksha Duggal. I'm also a senior data scientist in the emerging technologies group. And I come from Boston. So, to give you an overview of what we're going to talk about today, so we start with talking about AI for CI, which is the main project. And the optimal stopping point tool is a subset of this project. And I'm going to also go over what is the motivation behind this project and what's the solution that we've come up with, what all data sources we are using along the process, going over the workflow, presenting insights and a final demo where we'll walk you through all the steps that we've taken along. So, to start introducing this AI ops toolkit called AI for CI, I would like to mention there's a problem that we're trying to address here so that there's a need of automated and AI driven monitoring when it comes to the testing data. There's tons and tons of open source testing data that is being generated but not collected or put to use. So we see that there's a lack of AI driven metrics in the open source community health. So that brings us to the opportunity of leveraging these data sets that are being made available by lots of open source communities. And there's tons of open operations data, for example, test grid, prowl and GitHub have so much data that we could put into use and find out some interesting metrics that could in return benefit the community health. I lost my cursor guys, sorry. So the solution that we've come up with is coming up with an open source AI toolkit that helps us in collecting and analyzing all the CI CD data that is being made available. Then as a part of this project, we've also made machine learning models that help resolve various use cases. So one of the use cases that we try to solve here is called time to merge. So every time you make a pull request, oftentimes it takes super long to be reviewed or merged to the main code base. So this particular model is going to make a prediction, which will just put a comment on your PR every time you make it. It's going to make a prediction of how long will it take for your pull request to be merged. Similar to this, the main topic of this presentation is the optimal stopping point classifier, which will help you understand how long should it ideally take for your test to finish running. And what is an optimal stopping point after which it should be technically safe to just terminate that test or maybe restart it or inspect why it was acting like that. And just save up on some resources for it be cloud sources or engineers. These are also your resources that you must want to save for the right set of things. And another ML service that we have here is called the build log classifier. So we all know that there are tons and tons of logs that are being generated in Proud. And it's oftentimes difficult to just go through one so many logs. So what we would like to do here is just classify these Proud logs on the basis of the type of failure they belong to. And also as a part of this major project, we have KPI and metric dashboards. These are interactive dashboards that you could look at and see all the metrics that you have so far. And all in all, with this project, the aim is to foster an open AI ops community that helps leverage all these amazing data sources that we have. So as a part of this project, we so far have collected tons of data from various data sources like test grid, Proud, GitHub. And we've collected metrics and created KPI dashboards. We have machine learning services that support CI CD processes and are also integrated with GitHub projects. And it's super easy to use. And finally, it's also a resource for everybody in the community to utilize. There are templates, notebooks, scripts that anybody can just put to use directly without it's just for free, basically. So to come back on the topic that we're trying to address, I would like to mention why we are doing this. So this is a graph of various tests that were collected from a GitHub repository called code QL. So this is the distribution of the run duration of all these tests. So we see that most of the tests that were run, they finished running within the first minute of running. So that makes us believe that technically it shouldn't be taking so long for these tests to finish running. However, when we started to look at the failing test specifically, we saw that there are couple outliers that take up all the resources or take sometimes infinite amount of time to finish running. So wouldn't it be a good idea to just come up with a point after which we know it's probably just holding resources or blocked somewhere. It could be an outage or any reason for that matter. So the aim here is to find out the bottlenecks and just point out where it could be going wrong. So the ML solution that we've come up with is that sometimes these tests are taking long and we would like to find an optimal stopping point after which this test is most certain to fail. And hence, in return, we want to just save and allocate our resources in the best fashion. Talking about the data sources, so we all know GitHub is home to a lot of open source projects and a lot of people make contributions on a daily basis to these repositories. So we are collecting our data from GitHub. We've also looked at Prow, which is a Kubernetes base CI CD system. It has a lot of data that is being collected. A lot of checks that run on PRs are oftentimes reported back to Prow, which is also a good place to scrape data from. Then TestGrid, which is also another platform that helps people visualize their CI processes. A lot of communities, even besides Red Hat, are keeping their data on TestGrid, which is easy to visualize. But still, we think that we can come up with a better tool, scraping all this data from the back end and coming up with more insightful metrics and KPIs. So now, I think I'm going to give it over to Hema. She'll elaborate on the solution approach that we've taken here. Thanks, Akanksha. So now that we have a brief understanding of what the problem is at hand, let's take a look at the approach that we tried to take in order to come up with this optimal stopping point model. So first off, as we saw, the different data sources that Akanksha went over, the first step is of course to start collecting these kind of data from our CI CD tests. So the main data source that we are looking at right now is GitHub. And in GitHub, you would have noticed that whenever you make a certain PR to your repos, it usually shows a bunch of checks that are happening at the back end part of the review process. And for example, you have pre-commit checks, you have your file-linting checks, and apart from this, there can be many other checks that happen. And for any PR to get merged, these are some kind of prerequisites. So a test has to be successful in order for the PR to get merged eventually. And all of these are also sort of defined under workflows, which are part of GitHub actions. So that's how we're getting these kind of data sets from various repositories. So as an initial experiment, we look at a particular repository of interest. We see GitHub actions have been enabled for that repo. And then we go and look at the different workflows that have been set up for it.  And all the checks within it can also be obtained through that API. And that's how we get all those test durations and those kind of features that we start seeing from that data. So once we have all of this data ready, we start moving on to feature engineering. So in any ML model approach that we look at, you need to start identifying what are those important, relevant features that can be used as an input for your model. So here we're going to look mainly at those test durations, where Akanksha showed us the plot of those different durations. And what we try to do here is, for a given test, we kind of see the entire distribution of how long that test is taking to run. And we further try to bucket them into different time range intervals. So for example, zero to 10 seconds, 10 to 20, and all the way up till the completion of the test is where we try to further split and divide the test durations. And within each of those intervals, we try to find how many tests are likely to fail in those time ranges. And we try to basically calculate those percentage of failures over time. And once we do that kind of approach of calculating those durations and splitting them into those different buckets, what we do is finally try to reach to that optimal stopping point prediction. So to do this, as I was talking about that percentage of failures that we like to calculate in those time intervals, what we do is we've defined a threshold, where here it is 75%. So we say that in those time ranges, if we see that the threshold of is a percentage of failure is more than 75%, we say that anything beyond that is likely that the test is holding up resources and it's likely to fail. Now this threshold is just a default value that we came up with. But again, it's customizable. We can tweak it as per the needs depending upon how the workflows and checks have been set up. But this is just some initial kind of approach that we sort of started implementing to further define what that point in time would look like. And once we have that final sort of interval or that time slice at which it's going to have a greater chance of failing, we eventually want to integrate this back to the GitHub actions. So we would like to use the help of GitHub bots here. So what the bot will eventually do is whenever you have a PR open, the bot is going to sort of run the model at the back end. And then the bot is going to leave a comment on that PR saying, hey, this test is likely going to fail at this particular timestamp, you should probably stop it so that the rest of the checks do not get affected because of it. And it's still a work in progress, but that's ultimately the plugin that we would like to enable for these different repositories where you have a lot of checks to be passed. And there's like, you know, it's a big PR, maybe, and you have a lot of developers who are being put on it to review it. But they kind of don't have an idea as to why that certain test is failing and you probably want to move on to the next phase of your review. So eventually that's what the bot leaving a comment is trying to overcome and help out with identifying that pain point for your developers. And so how does this entire kind of workflow set up look like eventually is you have your PRs getting open to a repo. We go ahead and have that optimal stopping point running at the back end. So in this graph what we see here is you'll have all those test duration buckets on the x-axis and on the y-axis is the percentage of failing. So as you see, as the first range is basically taking zero to ten seconds and then you'll have all the other ranges beyond that until the test gets completed. And then you see there, you know, the percentage of failure. So over time slowly the percentage of failure tends to keep spiking and rising. So anything beyond that 70% we say that you know hey it's gonna eventually fail. Or if we set the threshold to like 60 then it's probably going to fail beyond that 50, 60% time range. And then if we correlate that back on to the x-axis you'll actually know that time interval at which it was going to fail. So maybe it was around like one minute ten seconds or something like that. So that's kind of how the output is going to look like. And then finally this is what the GitHub action bot is going to eventually integrate as part of our service. It'll leave a comment saying that you know it predicted that for this particular check that is happening beyond 50 seconds is when you should terminate it else it's going to hog up your resources. But if you won't stop at this it's the idea is that we can also allow users to take some actions based on that. So we would like to also have some kind of capability of you know asking the user like should I go ahead and stop this test or giving them some set of actions that they can perhaps take and help part of their CICD process. But as a very low hanging fruit we basically want to leave some kind of comment to provide more feedback for the repositories and for the PRs that are being opened in different repositories. And now we can move quickly to a small demo. So in this demo we're just going to go over kind of like the code and a little bit of the workflow that we follow. So I'll give it to Akansha to start with the initial part of it. Awesome. Alright so just for this demo purposes we've like started to look into this repository called CodeQL and similar to any of your repositories this also has couple pull requests. If you take a look at any of the open pull requests that we have here we see that there are some checks some haven't completed yet, some were completed couple seconds ago. So things like these oftentimes take a lot of time because there are so many checks and workflows that are being run. If you go to actions you can see more details about each of these checks and each of the runs that were made how many will fail etc. So what we aim to do here is to get all of this data in Jupyter Notebooks which is the home ground for most of the data scientists to start exploring the data and find insights out of them. So if we start looking at this notebook the main agenda here is to just scrape and get all the information that we get from the actions tab from GitHub. So after we get that information we just try to put it in a decent format that we can finally use to perform some evaluations and once we have collected all of this we try to just put them together into different formats and like classify them by passing and failing tests because it's easier to make a prediction once we know how both data sets look like and once we have the passing and the failing data frames ready we try to split them up into train and test data and further move towards the optimal stopping point prediction. So he was going to go over the approach that we followed to find out the optimal stopping point. So once we collected the data in the previous notebook so just to mention Jupiter notebooks are if you're not familiar with they are basically an interactive way of writing your Python code. Why we call it as a notebook is because it's like you have everything sort of broken down in a cellular format like this. So this will be like a first cell that you run and then usually the outputs also get printed one after the other depending upon how you write your code. So it's a preferred tool for most data scientists. So if you're not familiar about it you can go read more about the project Jupiter you'll get to know how this tool has been used. So that's kind of how this code looks like in that notebook format. But yeah moving on to start our analysis we go ahead and take those CSV files that we saw in the previous code and once we get those two different sets of data. So you have one for all your passing tests and then you have one for all your failing tests. So we kind of read them separately. And we kind of looked at it from two different approaches. The first approach is was an experimental approach. We don't use this actively right now but it was something that we researched a bit and did some analysis on top of it. So I won't go too much into detail but the idea in this approach is we try to look at the distribution like a statistical distribution of how the run times look like.  We try to see how many tests are within those different buckets that we see here. So we have about 20 in the zero to less than three seconds time range and so on. So that's kind of where we try to figure out the distribution pattern of it. And we do the same thing for both passing and failing tests. So statistical distributions, there are some libraries in Python which will automatically define the best distribution based on the values that you have. So here it's trying to fit like these different type of distributions for the data set that we have. And then it tells you which one is your best type of distribution and based on those distributions further we try to find out the intersection point for your passing distribution and failing distribution and that intersection point is essentially what we map to as our optimal stopping point on the x-axis. So that was approach one. But we wanted to move on to a different approach which is more favorable for us which is based on the probabilities of tests failing rather than just looking at the distribution but more on from a probability standpoint because ultimately that's what you want to predict. So as we were talking about those buckets again here you see some tests are even going all the way up to like you know infinite timestamp which is not something that you want. You want to get rid of those kind of long-running tests. So after you understand that distribution we go ahead and try to plot the percentage of failure. So that's kind of what this ultimate approach that we want to focus on. So we set a threshold of 70 after observing a lot of tests we came up with that threshold. This is just one test that we're showing this for but over time you're going to have multiple repositories, you're going to have multiple checks, multiple tests. So each data set is going to look different but this is in this particular code at least it's one test for one particular repository. So that's just something to keep in mind that that threshold may not make sense in some situations but at least it's some kind of a starting point for us to look at. So that's where we can visualize it better. These are just a more from a more data scientist perspective we're trying to normalize the values rather than look at the raw values. We're trying to scale the values and things like that. So these are just some couple of more ways where you can normalize your values and try to do the analysis on top of it.  And yeah ultimately we kind of use this threshold values on this and then we try to intersect it on this x-axis and then we find out what time duration or what timestamp does that correspond to and that's the point beyond which you should not be letting your tests run for for so long. So that's the overall kind of a goal of this particular code and coming back to our slides if you want to engage more if you want to learn more about this you can scan the QR code here it'll take you to our github repo so we track all of our work there if you have suggestions feedback open for any contributions or even just you know opening an issue if you want to learn more about it so please go ahead and do that. And we also have another project called AI for CI which akanksha mentioned at the beginning of the talk so that's a more larger open source initiative which is a collection of all these models that we're building so one of them which we presented today another model is the time to merge model that some of our colleagues worked on so in that model we are basically predicting what the what is the amount of time that it takes for a certain pr to get merged in a project and why we we don't want to give this to scare people that you know it's going to take so long for a pr to merge but the motivation for doing this is if you have new contributors for any open source project they might be hesitant to participate and contribute code because they don't really know if that PR is going to be reviewed or not so for any of those first time contributors the goal is if if you're able to predict and tell them hey the PR is going to get merged in a couple of days it gives them maybe more confidence to contribute to your project and the second advantage is it can also help you know community managers to look at their project and say okay it's taking a lot of time to review PRs do we need to change something how do we make it more efficient things like that so that's kind of how we came up with these different ways to consolidate these models so if you want to learn more about that I would encourage you to look at the AI for CI repo and you'll find all of these resources there like the notebooks the dashboards we've built the data sources and so on so please go ahead and do that and these are again some more references to all of our repositories and with that I would like to stop here but thank you all for attending and if you have any questions we have a couple of minutes to take them yes yes yeah yeah yeah that's a good question so just repeating the question again the question was how well would this work for a smaller github repository so if you have a smaller repo a less mature project I'm assuming where you have smaller unit tests how accurate this would be is that your question yeah how much data do you need yeah so I would say for any machine learning model the generic answer is more data is better so I don't want to default at that answer but I would definitely say that it might not be fairly accurate but at least over time if we keep you know trying and seeing that it's predicting at somewhat near accuracy then it would be a good start but of course if that particular check or that particular test is also found in other repos we can also use that as our training data set so it doesn't have to be coming just for your particular repo but if it's a test that is very specific to your repo then maybe the training data sets cannot be as large as expected but I would say it's definitely generic enough that we can try to find you know data sets from other repositories which might have similar checks and maybe use that to better train the model so that would be one way to approach it yeah do you want to add to that yeah I think just to add to that I think the more we retrain and the more feedback we get from the repositories and the more number of tests that we run that's the feedback that we look for in any sort of machine learning model so that we know how well the model is predicting and we can probably just retrain it on the new data that is being made available by new PRs and tests being run so I think that would be useful does that answer your question yes yes so repeating the question it was so if you're taking tests from different repos and using that to train your model how do you kind of map and figure out which if the data is accurate right so yeah so some of these checks like for example in that screenshot you saw there was a check for file linting or there was a check for pre-commit check so those are more generic so those kind of are standardized to some point to some extent so even if you're collecting from different repos we can have some confidence that these data is going to look similar but yes some of the other checks are more customized maybe for a particular repository so it might not work well for the others so in those situations we might have to eliminate those kind of data just so that the model is not training on the wrong thing so it's kind of like an experiment of you know checking which data sets is it able to learn better versus which one it's not so that's something we might have to look at further yeah yes yeah that's definitely okay that's definitely a good question I'm going to repeat it please correct me if I understand it wrong so you mean to ask that now that at this point we're making predictions for long running tests but what about the shorter running tests that that finish quickly is it even accurate that it finished so early right is that the question yes short running tests and false negatives that's a good question but as of now we are just looking at the long running tests but that is one of the use cases that we would also like to address but it's a part of prowlogs because if you don't get any information from run duration the best place to go look for more info is proud right like where do you go look for your logs particularly for these tests do you have logs that are being generated for these tests like is there a place that you go to okay okay yeah but for most of the test especially for open shift repositories they are linked back to proud and oftentimes when they don't get an answer the engineers who are working on these projects they go back to proud look at the logs and try to understand why particular thing was happening in certain ways and that's where like we also have like a very initial project that we did on prowlog classifier which would help you understand why why certain things are happening because it mainly just classifies all these logs into categories as to what category they belong to in terms of failures and passing and what could be the possible reason if they are behaving a certain way so that's another use case but this use case is mainly focused on the long-running test go for it yeah thank you for that plug in oindrilla also to add on to that at this point it's a work in progress but what we aim to do here with this initiative is that anybody who wants to use this tool can have a customized file where you can just put in what you want from this tool to do so starting from what is the threshold that you would like to specify it could be anywhere between 75 to 95 whichever thing you want to specify and also the next step here would be to have a tool that will automatically terminate all these tests but this is only something that we we can do if the user or the repository owner lets us do so this is something that we would want to add to this tool but definitely something that the owner has to take a call for so you can specify all these parameters and if once you specify it the GitHub action will automatically run on all the incoming pull requests in the future so that's the plan but most of the things are still work in progress but we were happy to just present whatever we had so far looks like we're out of time I would like to thank you all again for joining us please feel free to reach out for questions even later during the conference thank you


Everybody forced here up in 2022 Spectre football hobby 4 box half case number 30 random team style check out these results anytime elitonsportscards.com Thanks for joining everybody and good luck All right, here we go. The call the calls on the Niners game earlier. I don't know. I know they won by I know the Eagles on my four scores Smoking on that burrow pack, baby.  That's fixed NFL refs has been the same all season Jalen hurts 89 of 99 brilliance patch card Eagles. Oh, man. You guys are gonna have fun with Sam on Tuesday night when he's breaking here again And Texans radiant rookie patch auto pink Damian Pierce Nice hit Texans 23 to 25 26 of 30 dolphins rookie Eric is a conma easy Denny Gray Niners rookie silver St. Sovin Kamara 58 of 75 brilliance Jersey card Patriots lawyer Malloy 28 of 30 on the auto. There you go Pats God Justin Ross rookie to 75 chiefs Ricky Hassan haskins Titans Jason Taylor 6 of 15 max impact three color patch card. That's pretty dope. 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Oh, yeah, I know what you want 20 of 25 triple patch rookie falcons Drake London For the birds I'm a root for the birds and the chiefs. How about that Sam Howell 21 at 35 rookie patch auto neon green for the commanders Let's go Rihanna Yeah, Riri's pretty cool. So that's I'm about it. That's my that's in my wife who we were rooting for is Rihanna. I can guarantee you that much I guess my wife probably go for the Eagles because She was born in Pennsylvania and both her brothers The Phillies still so Algear to 75 rookie for the Falcons. I guess I will go for the birds, I guess for whatever it's worth like kind of If they win or lose right after I'll be like, okay, cool Darnell Mooney Isaiah Spiller 51 of 75 triple jersey Chargers rookie and Ravens Ray Lewis Super Bowl auto You gotta hit okay and make sure it doesn't switch You go Ravens on the Ray Lewis Yeah, from right here everyone's saying reps are the MVP I don't know man. Somehow Niners fans earlier are saying there the refs is why they lost I think I mean you lost because you're well the biggest reason is you're starting quarterback got hurt That's the big reason Eagles might have been better. We won't really know Because the game changed so much after that It's who a 10 of 25 for the Dolphins Jalen waddle silver for the Dolphins 11 of 99 Kyle pitch Jersey card Falcons. I'm sorry. You can hang this one. I'm sorry She's a 55 with the penny So you want okay? That's one of the like more popular one of those Super Bowl autos 59 of 60 Patriots lawyer Maloy auto although lawyer Maloy's It's like a whole law firm in here now all these lawyers Eagles don't have a chance in the Super Bowl Evan Neal rookie 250 for the Giants I just don't agree with that like in the slightest. Oh that guy not that guy Justin Herbert 5 out of 15 patch card for the Chargers Rebs be on one lately in every single sport. I Know LeBron acted like a baby last night, but that was a pretty bad missed call 59 of 125 RPA Titans Malik Willis. Oh Someone in twitch illegal. Yeah, we're just complaining my god 37 of 99 Chargers Justin Herbert She's talking about baseball or something now. Yes Rookie specters John met you the third Texans 30 of 50 My favorite food I do like sushi love me some sushi Demi and Pierce 69 of 99 rookie patch card for the Texans and Packers full-spectrum auto AJ Dylan on car. There you go Packers Streamer AJ Dylan 12 of 35. Oh his reaction was for sure over I think it was a culmination for LeBron James. He was just tired of all the I'm being a of being like 39 and being like the best player in the Lakers by far and Having been having great games every night 59 to 75 gasicky dolphins and then That press got it's it's a lit. It's it's legitimately funny 50 not a 99 Kyle Hamilton rookie monumental patch for the Ravens Do Castro and twitch is like the biggest hater I've ever seen right now Just a salty person 65 125 RPA Matt Corral Panthers Dude, it's like the player haters ball and chat tonight. Hey, hey, hey, hey, hey Tyler Algear rookie 16 is 75 for the Falcons It's like one Thornton silver rookie Patriots We got Seahawks DK Metcalf 10 of 75 Max Impact Jersey card Zemir white 7 of 60 RPA for the Raiders That's that was the that was like what? Like the do the Bengals effing Jamar down there somewhere That's like that was like they're one of their best plays and I focus them are so good Stupid Connor 4 of 60 Jags rookie Yeah, yeah Kelsey will be doc Justin Jefferson 24 25 two-color patch card for the Vikings I'm not gonna talk about that either 42 is 75 RPA Titans Malik Willis again two Willis RPAs You go mag that as well for your Titans champ Bailey 4 of 15 commanders on the die-cut Wavelength dangerous for the Broncos 21 to 25. Let's ride Kenneth Walker the third 18 to 25 next era rookie patch for the Seahawks The Saints are just gonna have to hit the hard rebuild button and do like a for real tank. I think the Saints Cordero Patterson full spectrum auto Vikings Falcons 14 of 35 Vikings Vikings Vikings Rob H falcons Ryan V. That's a random at the end Guy Garrett Wilson rookie 26 and 99 Jets Stefan digs Chiefs Skymore 73 is 75 rookie triple jersey card and on the back is a James Cook 19 at 35 neon green RPA for the bills Nice one Buffalo Good stuff there on the cook. Let's do this random two randoms here one for points one for the auto All right first random is 600 points random to everybody next is Vikings Falcons Cordero Patterson full spectrum auto look Five and one six times six times on both first is points top spot get some one two three four five and six Jeffrey s and six times on the Patterson auto one two three four Five and six. It's going to the Falcons quick recap here Got relics of Skymore Damian Pierce Justin Herbert Justin Jefferson Kenneth Walker the third Kyle Pitts DK Metcalf Kyle Hamilton This is Isaiah Spiller Drake London Terry McLauren ladenian Tomlinson Cooper cup Jason Taylor Alvin Camara and Jalen Hertz autos now a lawyer Maloy AJ Brown is Jersey number to 20 11 to 20 Wanda Robinson Sam Howell AJ Dylan full-spectrum auto there Matt Corral lawyer Maloy again James Cook Zamir White Damian Pierce That's running backs there get autos Super Bowl auto Ray Lewis for the Ravens On-card Steve Young numbered seven of eight for the Niners there icons auto and two Malik Willis RPA's for the Titans 59 of 125 42 of 75 That's gonna do it. Thanks again everybody. We're on to impeccable now


Did you feel like he needed that from a confidence perspective?  I mean, it's always nice when you've had a few where they haven't been in line with what you've done all year to bounce back and do that. But how do you struggle, would I be concerned about him moving forward? No. But look, anytime you're in the season and you're grinding and you have a bump along the way, it's nice to go out there and have one like he did today. I thought he was really good. Do you have an update on Marinaccio? Any further word on him? No. We'll talk about that now after. Aaron, just the accomplishment of sweeping a doubleheader of players. Managers always say sweeping doubleheaders is hard no matter who you're playing with. The circumstances are just what do you think about what you guys did today? Yeah. I mean, I know it's Susan views it as very challenging. So and today, you know, 6-1, it was close. It felt close all game, you know? They had some traffic. They had some opportunities to really get back in it. And whether it was Clay coming in, making a big pitch, Kane getting out of an inning, Nestor at some point had some traffic. So yeah, it's not easy. It's the highest league in the land. It's hard to win any game. It's definitely hard to win two in a day. So but a good day.  We've got to talk through everything now.