#uc migration

[unity-launcher]

Best Practices for Unity Catalog Migration Using Unity Launcher

Unity Catalog migration can be a complex process, but it can be made easier by following a few best practices. This article will discuss some of the most important things to keep in mind when migrating your Unity Catalog using Unity Launcher.

Best practices to follow during Unity Catalog migration

Plan your migration carefully. Before you begin your migration, you need to have a clear plan in place. This plan should include your migration goals, the scope of your migration, and the resources that you will need.

Use Unity Launcher. Unity Launcher is a powerful tool that can help you automate and simplify your Unity Catalog migration. It can also help you avoid common pitfalls.

Back up your data. It is important to back up your data before you begin your migration. This will help you protect your data in case something goes wrong.

Test your migration. Once you have completed your migration, it is important to test it thoroughly. This will help you ensure that your data has been migrated correctly.

Monitor your migration. After your migration is complete, you should continue to monitor it. This will help you identify and resolve any issues that may arise.

Common pitfalls and how Unity Launcher helps avoid them

There are a number of common pitfalls that can occur during Unity Catalog migration. Some of these pitfalls include:

Data loss. Data loss can occur if your migration is not performed correctly.

Data corruption. Data corruption can occur if your migration is not performed correctly.

Migration errors. Migration errors can occur if your migration is not performed correctly.

Unity Launcher can help you avoid these pitfalls by automating and simplifying your migration process. It can also help you identify and resolve any issues that may arise.

Conclusion

Unity Catalog migration can be a complex process, but it can be made easier by following a few best practices. By using Unity Launcher and following the tips in this article, you can help ensure a successful migration.

Celebal Technologies is a leading provider of Unity Catalog migration services. We can help you plan, execute, and monitor your migration. Contact us today to learn more.

[tara-maclays-gf]

i love how in season 4 both buffy and the initiative are patrolling on the uc sunnydale campus. like yeah, sure, in high school all the demons were in graveyards, but now we’re in college they’ve migrated to the campus, filled with lots of civilian trafic and very few demons they actually find on patrol

[spacetimewithstuartgary]

This rocky planet around a white dwarf resembles Earth — 8 billion years from now

Existence of Earth-like planet around dead sun offers hope for our planet's ultimate survival

The discovery of an Earth-like planet 4,000 light years away in the Milky Way galaxy provides a preview of one possible fate for our planet billions of years in the future, when the sun has turned into a white dwarf, and a blasted and frozen Earth has migrated beyond the orbit of Mars.

This distant planetary system, identified by University of California, Berkeley, astronomers after observations with the Keck 10-meter telescope in Hawaii, looks very similar to expectations for the sun-Earth system: it consists of a white dwarf about half the mass of the sun and an Earth-size companion in an orbit twice as large as Earth’s today.

That is likely to be Earth’s fate. The sun will eventually inflate like a balloon larger than Earth's orbit today, engulfing Mercury and Venus in the process. As the star expands to become a red giant, its decreasing mass will force planets to migrate to more distant orbits, offering Earth a slim opportunity to survive farther from the sun. Eventually, the outer layers of the red giant will be blown away to leave behind a dense white dwarf no larger than a planet, but with the mass of a star. If Earth has survived by then, it will probably end up in an orbit twice its current size.

The discovery, to be published this week in the journal Nature Astronomy, tells scientists about the evolution of main sequence stars, like the sun, through the red giant phase to a white dwarf, and how it affects the planets around them. Some studies suggest that for the sun, this process could begin in about 1 billion years, eventually vaporizing Earth's oceans and doubling Earth's orbital radius — if the expanding star doesn't engulf our planet first.

Eventually, about 8 billion years from now, the sun's outer layers will have dispersed to leave behind a dense, glowing ball — a white dwarf — that is about half the mass of the sun, but smaller in size than Earth.

"We do not currently have a consensus whether Earth could avoid being engulfed by the red giant sun in 6 billion years," said study leader Keming Zhang, a former doctoral student at the University of California, Berkeley, who is now an Eric and Wendy Schmidt AI in Science Postdoctoral fellow at UC San Diego. "In any case, planet Earth will only be habitable for around another billion years, at which point Earth's oceans would be vaporized by runaway greenhouse effect — long before the risk of getting swallowed by the red giant."

The planetary system provides one example of a planet that did survive, though it is far outside the habitable zone of the dim white dwarf and unlikely to harbor life. It may have had habitable conditions at some point, when its host was still a sun-like star.

"Whether life can survive on Earth through that (red giant) period is unknown. But certainly the most important thing is that Earth isn't swallowed by the sun when it becomes a red giant," said Jessica Lu, associate professor and chair of astronomy at UC Berkeley. “This system that Keming's found is an example of a planet — probably an Earth-like planet originally on a similar orbit to Earth — that survived its host star's red giant phase.”

Microlensing makes star brighten a thousandfold

The far-away planetary system, located near the bulge at the center of our galaxy, came to astronomers' attention in 2020 when it passed in front of a more distant star and magnified that star's light by a factor of 1,000. The gravity of the system acted like a lens to focus and amplify the light from the background star.

The team that discovered this "microlensing event" dubbed it KMT-2020-BLG-0414 because it was detected by the Korea Microlensing Telescope Network in the Southern Hemisphere. The magnification of the background star — also in the Milky Way, but about 25,000 light years from Earth — was still only a pinprick of light. Nevertheless, its variation in intensity over about two months allowed the team to estimate that the system included a star about half the mass of the sun, a planet about the mass of Earth and a very large planet about 17 times the mass of Jupiter — likely a brown dwarf. Brown dwarfs are failed stars, with a mass just shy of that required to ignite fusion in the core.

The analysis also concluded that the Earth-like planet was between 1 and 2 astronomical units from the star — that is, about twice the distance between the Earth and sun. It was unclear what kind of star the host was because its light was lost in the glare of the magnified background star and a few nearby stars.

To identify the type of star, Zhang and his colleagues, including UC Berkeley astronomers Jessica Lu and Joshua Bloom, looked more closely at the lensing system in 2023 using the Keck II 10-meter telescope in Hawaii, which is outfitted with adaptive optics to eliminate blur from the atmosphere. Because they observed the system three years after the lensing event, the background star that had once been magnified 1,000 times had become faint enough that the lensing star should have been visible if it was a typical main-sequence star like the sun, Lu said.

But Zhang detected nothing in two separate Keck images.

"Our conclusions are based on ruling out the alternative scenarios, since a normal star would have been easily seen," Zhang said. "Because the lens is both dark and low mass, we concluded that it can only be a white dwarf."

"This is a case of where seeing nothing is actually more interesting than seeing something," said Lu, who looks for microlensing events caused by free-floating stellar-mass black holes in the Milky Way.

Finding exoplanets through microlensing

The discovery is part of a project by Zhang to more closely study microlensing events that show the presence of a planet, in order to understand what types of stars exoplanets live around.

"There is some luck involved, because you'd expect fewer than one in 10 microlensing stars with planets to be white dwarfs," Zhang said.

The new observations also allowed Zhang and colleagues to resolve an ambiguity regarding the location of the brown dwarf.

“The original analysis showed that the brown dwarf is either in a very wide orbit, like Neptune's, or well within Mercury’s orbit. Giant planets on very small orbits are actually quite common outside the solar system,” Zhang said, referring to a class of planets called hot Jupiters. “But since we now know it is orbiting a stellar remnant, this is unlikely, as it would have been engulfed.”

The modeling ambiguity is caused by so-called microlensing degeneracy, where two distinct lensing configurations can give rise to the same lensing effect. This degeneracy is related to the one Zhang and Bloom discovered in 2022 using an AI method to analyze microlensing simulations. Zhang also applied the same AI technique to rule out alternative models for KMT-2020-BLG-0414 that may have been missed.

"Microlensing has turned into a very interesting way of studying other star systems that can't be observed and detected by the conventional means, i.e. the transit method or the radial velocity method," Bloom said. "There is a whole set of worlds that are now opening up to us through the microlensing channel, and what's exciting is that we're on the precipice of finding exotic configurations like this."

One purpose of NASA's Nancy Grace Roman Telescope, scheduled for launch in 2027, is to measure light curves from microlensing events to find exoplanets, many of which will need follow up using other telescopes to identify the types of stars hosting the exoplanets.

"What is required is careful follow up with the world's best facilities, i.e. adaptive optics and the Keck Observatory, not just a day or a month later, but many, many years into the future, after the lens has moved away from the background star so you can start disambiguating what you're seeing," Bloom said.

Zhang noted that even if Earth gets engulfed during the sun's red giant phase in a billion or so years, humanity may find a refuge in the outer solar system. Several moons of Jupiter, such as Europa, Callisto and Ganymede, and Enceladus around Saturn, appear to have frozen water oceans that will likely thaw as the outer layers of the red giant expand.

"As the sun becomes a red giant, the habitable zone will move to around Jupiter and Saturn's orbit, and many of these moons will become ocean planets," Zhang said. "I think, in that case, humanity could migrate out there."

IMAGE: Images of the area of the microlensing event, indicated by perpendicular white lines, years before the event (a), shortly after peak magnification of the background star in 2020 (b) and in 2023 after its disappearance (c). The planetary system with a white dwarf, an Earth-like planet and a brown dwarf cannot be seen; the point of light in (c) is from the background source star that is no longer magnified. Credit OGLE, CFHT, Keck Observatory

[brybryby]

I’m working really hard on releasing my post about Waylon’s Korean-coding, coming from the lens of someone who is a product of Asian migration to the US. (I’m really excited for it! I hope it’s educational)

[EDIT]: here’s a list of things I will address:

- Model Minority Myth

- the “feminine Asian man” stereotype in the US

- comp sci at UC Berkeley

- Asian emigration to the US

- notions of gender/masculinity in 20th century America

There will be a slight delay—during my deep dive, I realized that there’s a history of characters with Asian surnames who have shown some type of resistance/rebellion against Murkoff, which I thought was interesting and definitely worth analyzing. That being David Annapurna, Melissa Cho, and Ethan Sriskandaraja. Their contributions to the game are subtle, but I think they mean a lot to the overall lore—especially David’s parallels with Waylon.

I’m finding it very meaningful. It will hopefully come very soon!

[darkmaga-retard]

Kamala Harris, the presumptive Democratic Party nominee has a track record of pushing for illegal aliens to practice law in California.

According to a report by John Binder for Breitbart News, Harris was a leading advocate for allowing illegal alien invaders to become licensed lawyers in the state of California. It should be noted California is affectively sanctuary state illegal aliens are allowed to reside and move across the state with virtual impunity

Vice President Kamala Harris, now running for the Democratic nomination for president, was once a top champion for allowing illegal aliens to become licensed attorneys in the sanctuary state of California.

BackIn 2014, the California Supreme Court issued a ruling where all members of the court decided to allow illegal alien Sergio Garcia — a Mexican national – to the State Bar thereby granting him the ability to become a licensed attorney in the Golden State.

At that juncture, Harris was California Attorney General and was the leading advocate for lead to attorney. This has created a troubling precedent, where thousands of illegal alien statewide become licensed attorneys

According to report by the Sacramento Bee:

Despite his efforts, Garcia attracted the attention of California’s top law enforcement officer — then-Attorney General and now-presidential candidate Kamala Harris — in 2012. At the time, Garcia was enduring a yearslong and publicized struggle to become the first licensed undocumented attorney in the nation. To Garcia’s surprise, Harris came out in support. She went on to submit a written brief backing his legal case and even provided a lawyer from her office to argue for him in front of the state Supreme Court. Vice president Harris’ endorsement “made the difference” in the case and eventually led to a unanimous California Supreme Court decision in Garcia’s favor, according to Kevin Johnson, dean of UC Davis’ law school and one of the attorneys who represented the State Bar of California for Garcia.

[joselialopes]

“And when I first showed him my scar, he said it was interesting. He used the word ‘textured’. He said ‘smooth’ is boring but ‘textured’ was interesting, and the scar meant that I was stronger than whatever it was that had tried to hurt me.”

BIOGRAPHY | CONNECTIONS | MUSINGS | PINTEREST | SPOTIFY

STATS

Name: Joselia “Jo” Lopes Silva Faceclaim: Bruna Marquezine Gender & Pronouns: Cis woman & she/her Sexuality: Pansexual Age: 30 Birthday: June 3, 1993 Zodiac: Gemini sun, Leo moon, Virgo rising Education: BSW, UC-Riverside Occupation: Addiction Counselor (Social Worker) Neighborhood: Bighorn Hills + open-minded, adaptable, passionate - hot-headed, flaky, impulsive

BIOGRAPHY

tw: drug mention, alcoholism, abortion

also tw I say “daddy” one billion times and I’m so sorry that’s just what Joselia would say

Daddy was always a free spirit. He and Mama married young– him 17 and her 16– and he promised her the world. He painted a beautiful picture of a long, successful career as a football player, a big move to America, and a life where she seldom had to lift a finger. But Gisele Lopes Silva was always more grounded than her husband. She didn’t want all of that, really, just a man who loved her and happy kids. Still, Daddy was determined to shoot for the stars and, in the end, he landed pretty close. Roberto Silva qualified for the Campeonato Brasileiro Series at 19 and he swore up and down it was a straight shot to US Nationals from there. Mama got pregnant with Roberto Jr. that winter, 1984, and five years later in 1989 they had Miguel. With two babies, Mama’s asking Daddy to retire and get a real job graduated from passing remarks to deadpan questions to begging. 

They were doing okay, what with Grandma helping with the boys while Mama worked, but Gisele was wise. She knew it wouldn’t last long. Besides, she’d rather have Daddy around the kids than him be some big, international soccer star. It was a fight she didn’t have the energy for but every now and then, and Daddy became an expert at weasling out of it– bringing home expensive gifts, magazines about life in America, VHS tapes of sitcoms. Money was tight, though, and it was Daddy’s magic-making that made the room dividers in the living room that hid Jr.’s cot feel enchanted, like a portal to another world instead of a family bursting at the seams. In retrospect, Jr. says Mama resented him even then. She was caught in the trap of working all day in the factory and coming home to cook and clean, all the while the boys tugged on Daddy’s pant legs and clamored on top of him and asked to hear the story of his trip to San Fransisco for the hundredth time. 

Mama says that having Joselia in 1993 changed everything. She was finally getting somewhere with Daddy– touting the baby, the only girl, as the reason why he should quit chasing this crazy dream and get a real job. Settle down and give them all the life they deserved. Of course, the very next year was the beginning of the San Jose soccer club. The Earthquakes wanted Daddy on their inaugural team, and Daddy leaped at the chance to move to California– the land of opportunity. According to Daddy, getting recruited to the U.S. was the best thing that ever happened to him. Mama was just grateful that he finally got a kick in the ass to make something of himself. In 1994, the family migrated to San Jose to start their new life. 

Daddy always talked about those first few years like they were something out of a fairytale– all blue skies and palm trees and balmy breezes. Long days of doing what he loved, coming home to a slice of Brazil in Mama’s cooking and Jr.’s singing and the artifacts they’d managed to bring with them. Mama isn’t so romantic about it all. Sure, it was nice to not be so strapped for cash. But it was lonely, she says– hardly anybody else spoke Portuguese, and Daddy was alright with his English but Mama struggled. She could hardly make it through trips to the grocery without aid, and she missed her mother. But, Daddy was happy, which had been the point all along, right?

Daddy’s first season with the Earthquakes was a building year– at least, that’s what all the players would say when they would crowd around the kitchen table, drinking and talking and making messes that Mama stayed up well into the night cleaning up. But the kids loved it, crowding around the table with wide eyes and hanging on every word they said. It was this way that Joselia learned English; When her kindergarten teacher wrote home and asked where she’d learned to say “damn it all to hell!”, Daddy just laughed and laughed and laughed. 

Season two was better. By the end of it, everybody was talking about the Earthquakes, and Daddy was even named in a couple articles as a player to watch. That was 1996, a year he still calls the best of his life. Joselia remembers the whole family travelling to LA and Washington, DC and Dallas to see Daddy play. It was exactly what Daddy always promised– traveling the world, staying in fancy hotels, a balanced diet of stadium hot dogs and room service. Even Mama loosened up on their trips, had a glass or two of champagne and got giggly. It was like they were really in love, then. Life should’ve been like that forever– and it would’ve been, if Daddy hadn’t gotten injured.

Three games before the end of the 1997 season, an ill-timed slide tackle caused Daddy’s leg to break in two places. Mama, Jr., Miguel, and Joselia were watching from home, and everything instantly devolved into chaos. Mama screamed and immediately called the neighbor to come watch the kids while she rushed to the hospital. The three kids planted themselves in front of the TV, watching any and all coverage they could find on the local channels, and praying to every saint they knew. 

Daddy put on a brave face, at first. He had high hopes, unreasonable expectations that he’d be as good as new after surgery. But then came the minimum two years of physical therapy, and by the time he was in any condition to run again, they were so far behind with medical bills that Mama put her foot down. He had to get a job– they had to get back on their feet before he started his crazy training regimen. His old teammates still came around back then, and one of them even pulled some strings and got Daddy a job as a daytime bartender at a pub near the training facility. 

But there’s always a point in time where the sympathy runs out. People can’t hold pity forever. The guys stopped coming around, Coach stopped inviting him to closed practices. Mama was never gentle with him– she said that was that, it was time to move on. Find a new dream. Joselia wouldn’t know until much later, but underneath all of his bravado, Daddy was incredibly sensitive. He didn’t take to normal life well, and started mixing his pain meds with a few too many drinks. At first, it was an inconvenience. He would get too drunk and forget to pick up Jr. from school, he would leave Miguel an hour or two longer after school than he meant to. Most nights would end in whispered arguments behind Mama and Daddy’s door– Jr. learned to press a glass to the wood young, but he’d never tell Miguel and Joselia what was said unless it was really bad.

It got really bad when Joselia was in middle school. Jr. was twenty-one and still home, fulfilling the role of oldest child and peacekeeper while he saved up for college. Plus, the income he brought in from his grocery store job helped keep them afloat when Daddy overslept and missed his shifts, which was becoming more and more frequent. Jr. kept them together, with Miguel’s help– they would divide and conquer, Jr. going to Daddy and Miguel going to Mama. But when Daddy started gambling and they lost the apartment, Mama was done. 

Joselia was thirteen when Mama moved them into a new apartment and refused to give Daddy the key. Jr. had to drag her, kicking and screaming, refusing to leave Daddy behind. She’d let him in at night, and Mama would wake her up yelling every morning that she woke up to discover him on the couch. He can’t be trusted! she would say, pleading with Joselia to keep him out. Everybody else had enough of his broken promises, except Jo. She loved him so much that she moved with him to Philly at fifteen, pledged the next decade of her life to following Daddy around, dreaming big dreams with him and picking him up when he fell.

It was difficult leaving Mama and her brothers behind, but Joselia was so hurt that they could be so cruel to Daddy that she buried the grief under anger. Life with him was the same as always– high highs and low lows. On good days, they’d catch a game in the city and share a hotdog and Daddy would tell Jo-Jo all about how he was gonna become a soccer coach. If you can’t do, you teach, he said, and she believed him. She always believed him, and that belief carried her through the bad days, when he would stumble home angry at four a.m., cursing her Mama and her Grandma and the world, vomit dribbling down his chin and too-heavy footsteps.

It took an extra year, but Joselia graduated high school. Her part-time waitressing job became full-time, and her steady paycheck made up for the weeks and months that Daddy was out of work. Mama sent money every couple months with express instructions not to let Daddy touch it– but she always did, and he always blew it on a scratch-off or a round for all his friends. He was chaos personified, but Joselia wasn’t afraid of his self-destruction. Mostly, she was afraid of who she’d be without his fantastical tales and his believing the best in her and his promises that he’d take care of her, one day. 

Joselia met Matthew Foster in Philly, at a show for some grungy band she was just drunk enough to enjoy. Their whirlwind romance felt like home– the ups and downs, the unbridled passion and the teeming rage felt like what Joselia reckoned love was supposed to be. Daddy wasn’t consistent or stable, and he loved her more than anybody in the world– So must Foster. Midnight screaming matches faded into afternoon picnics and so on. He never said so, but Joselia knew he loved her– he showed it dozens of ways, whether by making the best food she’d ever eaten in her life (aside from stadium hotdogs, of course) or by buffing out the same dent in her car over and over from the damn apartment gate. 

They were young and dumb and it felt like everything. Daddy hated him and loved him, depending on the day– and when things were going right for everybody and the three of them drank and watched Daddy’s old matches, well, that was the best feeling in the world. It was after one of those days and a couple of Foster’s custom-made cocktails that they decided to get married at the courthouse. They didn’t have a ring or a dress or a care in the world, and somewhere in a box covered in a thin layer of dust, Joselia has a picture from that day: her in one of Foster’s button downs and a Dodgers hat, him in his usual tshirt and jeans combo, all bright smiles hanging off one another.

Being married didn’t stave off the fighting at all. If anything, it made it worse– gave them each more ammunition to launch at each other, and made it a hell of a lot harder to untangle from the mess. They fell into a familiar pattern– a couple of good days, maybe a week, a fight where they swore they were broken up for good this time, and a couple days later they’d make up. Anything was fair game on these breaks– and it’s not like Joselia had a ring or anything to stop her from seeing other people, so she did. Nothing that stuck, but a couple one or two night flings before she surrendered to Foster’s gravitational pull again.

When Joselia found out she was pregnant after a week “off”, she panicked. She wasn’t going to tell Foster, she was just going to take care of it on her own– but they had such a good day, and she was half convinced they could make it work. They were perfect, they only fought so hard because they loved each other so much. He bolted after that, and in retrospect, she couldn’t blame him. Joselia still harbors that hurt on especially lonely nights, revisits the feeling of waking up and seeing his shit gone, the days-late realization that she’d never see him again.

But it was okay, because there was always Daddy to take care of, and with no Foster and no baby to distract her, Joselia poured all of her energy into him. She was twenty-five and working the same waitressing job she’d had since graduation, spending her weekends taking care of her drunk father– and with nothing else in Philly, reality stung. She started to resent Daddy the same way Mama always had– she resented being the stable one, she resented not being able to fall apart because it’d hurt them both when that’s all she really wanted to do.

A decade late, Joselia’s breaking point finally came when Daddy wrapped her truck around a streetlight. He survived, thank God, but he had a broken arm and a couple of years in jail and mandated therapy. With no other choice, Joselia made her way back to California and turned up on Mama’s doorstep, tail between her legs. The rush of apologies for years of hating her, of thinking Mama was selfish and wrong for abandoning Daddy, was crushed in her mother’s arms. She was home, for real this time, and reconnecting with Mama and Jr. and Miguel helped Joselia figure some things out.

It wasn’t perfect, and she still felt an unreasonable degree of protectiveness over Daddy– they kept in touch, between letters and phone calls– but Jo decided to enroll in college. Better late than never. She started at UC-Riverside and declared Social Work as her major, staying home with Mama until she graduated at 29. It was a big deal, because Jr. had enlisted at 22 and Miguel had gone to trade school. Joselia was the first in their family to graduate college, a fact that Daddy cried about on the phone the morning of her graduation– a fact she still holds with pride.

Her fresh start extended to Colorado Springs, where Joselia took her very first “real” job a year ago as an Addiction Counselor for a nonprofit serving unhoused and at-risk individuals. It was Jr.’s idea, originally, and Joselia ended up loving it– finally her life experience was helpful with something, and the tough love she always should’ve given to Daddy was a requirement. It’s such the perfect fit, in fact, that she was promoted after only a year and transferred to the Providence Peak location. Joselia was hesitant at first to leave Colorado Springs and the comfort of Jr. right down the street, but it was high time for her to forge her own path. She made it up to Philly one more time, to visit Daddy and to clear out the rest of her shit from a storage unit, and is now settling into her new routine.

[codemerything]

I still prefer Chrome**

I have used a lot of browsers: Microsoft Edge, Firefox, Firefox Developer Edition, UC Browser, Brave and Chrome I always find myself coming back to Chrome? Why? WHY CHROME? My recent UX with Firefox made me write this.

I decided to take some time to understand why I always return and this is a breakdown of why I always migrate back to Chrome:

Eco-System: I am knees-deep into the Google Eco-System, I love the synchronization of my data, and I don't need to insert passwords for most apps, on Youtube, I can pick up from where I left off with ease, and I never have to click on "sync now" which is something I noticed when I migrated to Firefox and the other browsers I had took a long time to reflect what I did on my laptop on my mobile. It just wasn't as smooth as I'm used to, you know.

Speed: This may not apply to most of you but something I noticed Chrome browser's response time is really quick compared to Firefox which I have been using for a month, this may be due to my laptop's specs but it just wasn't as smooth as Chrome. Sometimes even clicking on forms will take a noticeable second but this never happened in Chrome.

Features: I love Firefox, and I love how secure it is, I love that they're really cool themes, Developer Edition was really made for Developers, and so many features I can't really list right now but you can read Loa's post on Firefox to know more - LINK; but I can't group tabs on Firefox, listen, I know it's such a small thing but I love being organised and grouping tabs has become a huge part of sorting information based on topic and this feature was taken away from Firefox, I tried to use it like that but I would find myself clearing all my tabs or closing the browser to start from the top and I really held onto it for a long time but I had to let go.

Conclusion: This isn't an "I hate Firefox, Chrome is the best" type of post, I know Chrome sucks especially with privacy and security and every time I was on Firefox I never felt that or had that in the back of my head because of all the privacy settings embedded in the browser but I just find Chrome more convenient, and it works for me.

[jacethegaymer]

Hey everyone

Okay so what I know the latest origin update (tbh idek why EA still updates origin if they don’t give a shit about it)

That it removed the key setting code that’ll prevent it from getting the migration to the EA app.

For the people who have the EA app account and have the sims 2 ultimate collection, (like on the account)

Does the sims 2 ultimate collection still work good and if it does

Will transferring to the EA app, will my Downloads folder be safe and intact when transferring to the app?

Tbh I think I need to just accept my fate and go to the EA app but I’m scared and very anxious cause I’m afraid I won’t be able to play sims 2 UC and that’ll literally be the end of my simblr and my Megahood series and I really don’t want that to happen at all.

[intricatefantasy]

March 8, 2023

The 8th of March has always been a significant date to me because it’s my mother’s birthday. When Tim told me months ago that he was getting us concert tickets for a show on March 8th, my response immediately was that it was my mom’s birthday. Luckily, I scheduled around it by having taken my mom to a birthday brunch this past Saturday, and it turns out, my dad took her on a surprise trip for her birthday anyway. 

I had slept at Tim’s on Tuesday night since we were planning on leaving to Berkeley right after I finished work on Wednesday. I wanted to sleep at his place after the concert again because of the convenience of it post late night transit back to the city. I just didn’t want to lug my things into work, so bringing all my things over Tuesday night helped work our way around that. 

He picked me up after work, and then we went to Philz coffee so I could caffeinate once more ahead of a night out. We took Bart to Downtown Berkeley, and took a walk around the UC campus to enjoy our last bit of sunlight for the next seven days. Northern California is undergoing another atmospheric river this weekend, and it’s projected to rain for a week straight. Both Tim and I are the happiest when we get to be outdoors, so we tried to make the most of the sunshine that greeted us in the East Bay. 

I did have a bit of a temper and was grumpy for a moment in our walk, only to realize later it’s because I was HANGRY. My mood quickly shifted once our food was served at the restaurant we ate in after the walk. We had dinner at a place next to the venue of the concert we were going to watch. The place was called Imm Thai Street Food. I ordered fried tofu, and a soup called Su Kho Thai, but without the noodles of course. Tim got the fried pumpkin and a bowl of tom kha tofu. It was absolutely delicious, and I wouldn’t mind eating there again if I happen to be in the area once more. 

When we finished dinner, it was around 6:30. The doors of the concert venue opened at 7PM, and neither of us like being that early to a concert. We wound up browsing Goodwill and Half Price Books, and then when we both were bored, we decided to just get in line at the venue. I hadn’t watched a concert at the UC Theatre yet, but Tim had a plan to get there early, secure a table, and hang there during the opening band before migrating to the floor when Ottoboke Beaver, the headliner, began their performance.

Gaile and Chris made the drive over from Petaluma and met us at the concert venue. It was a surprise when we mentioned the show to Chris, and he knew the artist and expressed so much excitement at the chance to see them with us. It’s so great that my best friend’s husband and my boyfriend get along really well - Gaile and I couldn’t have planned for this connection to be any more natural. Gaile & Chris wanted to stay seated throughout the concert, but Tim and I made it down to the floor for half of Ottoboke’s performance.

There’s no better way of observing a concert than being inside the crowd, joining the massive throng of bodies just pulsating to the music. And really - are you at a punk show if you aren’t screaming and jumping up and down? My favorite part of any concert is being able to just close my eyes, feel the sound radiate through my body, and lose myself in that perfect moment - lights flashing, body just giving in to the rhythm. It’s such a joy to bask in the art with the community of people who love the music just as much as you do. 

I ran into Nolan, Sarah, and Kai at the show as well. There’s always some kind of understanding when you see people you know at a concert of a smaller artist. It’s like this mutual acknowledgement of taste. Running into friends at shows just confirms my own bias that my friends are all pretty damn cool. 

It was an incredible show, and I left still buzzing. We hung around Berkeley for a half hour after the concert, just chatting with everyone. And as always on every fun night out, I didn’t take any pictures. Instead, just have this one photo outside of the UC Theatre that I remembered to snap as we were walking away after the concert.

We just took Bart back home after, but I was still buzzing from the concert, and even if we got back home around 11:15 PM, there was no way I was falling asleep. Tim and I sat up talking about our future goals and dreams, and what we envisioned for ourselves in the next couple of years. And after that... well, lets just say I am currently having the best sex of my life. What a way to end the night!

[unity-launcher]

Contact today Unity Launcher: Effortless Hive to Unity Migration on Databricks (celebaltech.com)

[rosecoloredknight]

Ask game~ 31 ...btw you seem so kind,please protect yourself ,don't let people play with your heart , you deserve all the best :)🌸

some songs for your playlist 💫:wye oak -civilian,jome cinnamon and jorge ben jor -chove chuva

31. Something you did and you are proud of?

Im really proud of that time i stood up for a UC (unaccompanied child) after he was struck by the at risk UC i was assigned under my care that day the incident transpired.

Quick backstory: a couple weeks ago we received this UC that migrated from Nicaragua, which is not unusual, we receive UC from a variety of countries down from the South America regions. However, this UC at the time was the youngest (five years old) and would not listen to instructions, run away from classes, and aggressive towards others and himself, which immediately marked him as an at-risk UC, meaning 1 on 1 supervision only.

Oh, almost forgot, the UC had an brother as well who was there (seven years old) whom was also placed on a 1 on 1 care for the same reason, heck i even accompanied that UC to the hospital when he was put to sleep due to destroying his room and attacking the other Youth Care Workers. I worked from 2pm to 4am that day ugh because we got released (kicked out) of the hospital after he was visited by a mental health specialist and we waited in the visitor room till one of the directors came.

Agh- back to the point. Supervisors realized that both UC respinded well to me so they started placing them under my care.

However, kids are unpredictable, especially an at-risk one so it's difficult to prepare for the mood swings. I'm so sorry for all of this but if you're still reading this, thank you for your patience.

The at-risk UC attacked an another UC, but i was able to lessen the blow by grabbing the UC arms as he strucked the other UC.

Qhat ended up happening was that the supervisors, did not let me write an IR (Incident Report) right away, which is a must in the protocol/policy, and where trying to aggressively admit that i coached the kid into thinking he was hit which was extremely disrespectful to me because right away i knew they just didn't want to document the incident and where being irresponsible. I ended up standing my ground, called them out, and told them "if im wrong, the video, (which there was a camera outside when ot happened) will prove that, but we're going to agree to disagree here." And they just left it as it was.

The next day, i spoke to the director who oversees the supervisors and ycw and she told me that i did everything right and that i should have been allowed to submit the IR immediately.

Before work started, the supervisors reiterated that and they definitely got in trouble. I was really proud of myself because i stood up against them in defense of a UC who was attacked but they didn't want to acknowledge it.

Its a rollercoaster but there you go.

Hopefully i made sense.

*****

Thank you so much for saying that ♥️ I'll do my best in protecting my heart and not allowing those who don't care about my friendship or effort continuing to be a part of my life.

Also, NEW MUSIC!!!?! yay!! I'll be sure to write them down and give them a shot 😊😊

Again, I appreciate this ask, thank you.

—

Send me a number!!

[sciencespies]

Butterflies: 195 ways to help California's painted ladies

https://sciencespies.com/nature/butterflies-195-ways-to-help-californias-painted-ladies/

Butterflies: 195 ways to help California's painted ladies

By documenting hundreds of new nectar plants for painted ladies, scientists have renewed hope these charismatic butterflies may prove resilient to climate change.

Every spring, swarms of the colorful butterflies can be spotted in Southern California as they make their way from western Mexico to the Pacific Northwest to breed. Some years, the number of migrating butterflies is in the millions.

Additionally, California is home to resident painted lady populations that require food sources year-round.

Though they are a major North American butterfly species, there is a lack of baseline data to quantify a decline in painted ladies. However, scientists believe they are being negatively affected by hotter, drier weather and habitat loss.

“The lack of rainfall in Southern California likely impacts the butterflies’ ability to move through the state, potentially decreasing nectar sources and causing them to die without reproducing,” said Jolene Saldivar, UC Riverside ecologist who led this effort to identify new painted lady nectar plants.

“There’s so much to be learned about these butterflies before drought and climate change damage them irreparably,” Saldivar said. This study, which identifies 195 new nectar plants for the species, is now published in the journal Environmental Entomology.

To obtain this result, the UCR team sorted through more than 10,000 images of painted ladies in California shrublands, supplied by community scientists through the iNaturalist website. Any images in which the butterflies did not have mouth parts extended and were not obviously feeding were omitted from analysis, as were any images of caterpillars.

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The newly discovered nectar sources may offer Southern California gardeners wanting to support the species a wide range of options.

“Much of what we identified could responsibly be planted during a drought,” said Erin Wilson-Rankin, study co-author and UCR associate professor of entomology.

Of the top 10 most frequently observed plant species, seven are native to California. These include yellow-flowered rubber rabbitbrush, blue wild hyacinth, common fiddleneck, Fremont’s pincushion, black sage, wild heliotrope and desert lavender, which belongs to the mint family.

These butterflies also readily feed on showy ornamental plants common to California landscaping, such as lantana, butterfly bush and rosemary, as well as flowering weeds.

“It’s an uber generalist insect, not picky at all,” Saldivar said.

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Painted lady caterpillars consume plants, but they are not known to eat any agriculturally important species, nor are they known spreaders of any illness. They serve as good sources of prey for insects, spiders, birds, wasps and reptiles, and mature butterflies can pollinate some of the many plants they visit.

“It might be getting tougher for painted ladies in some places, but these butterflies will feed on what flowers are available — even a few plants in a window box could help them,” Wilson-Rankin said.

Saldivar says she believes the results of this paper may encourage community scientists, whose contributions to knowledge should be celebrated and promoted.

“Adding a photo and a little information to a community science website or through an app on your smartphone might seem minor, but in the big picture, it helps inform us about ecological processes we’d otherwise be very challenged to learn about,” Saldivar said.

#Nature

[govindhtech]

Intel Data Center GPU SqueezeLLM Inference With SYCLomatic

Turn on SqueezeLLM for Efficient LLM Inference on Intel Data Center GPU Max Series utilizing SYCLomatic for Converting CUDA to SYCL.

In brief

Researchers at the University of California, Berkeley, have devised a revolutionary quantization technique called SqueezeLLM, which enables accurate and efficient generative LLM inference. Cross-platform compatibility, however, requires unique kernel implementations and hence more implementation work.

Using the SYCLomatic tool from the Intel oneAPI Base Toolkit to take advantage of CUDA-to-SYCL migration, they were able to immediately achieve a 2.0x speedup on Intel Data Center GPUs with 4-bit quantization without the need for manual tweaking. Because of this, cross-platform compatibility may be provided with little extra technical effort needed to adapt the kernel implementations to various hardware back ends.

SqueezeLLM: Precise and Effective Low-Precision Quantization for Optimal LLM Interpretation

Because LLM inference allows for so many applications, it is becoming a common task. But LLM inference uses a lot of resources; it needs powerful computers to function. Furthermore, since generative LLM inference requires the sequential generation of output tokens, it suffers from minimal data reuse, while previous machine learning workloads have mostly been compute-bound. Low-precision quantization is one way to cut down on latency and memory use, but it may be difficult to quantize LLMs to low precision (less than 4 bits, for example) without causing an unacceptable loss of accuracy.

SqueezeLLM is a tool that UC Berkeley researchers have created to facilitate precise and efficient low-precision quantization. Two important advances are included into SqueezeLLM to overcome shortcomings in previous approaches. It employs sensitivity-weighted non-uniform quantization, which uses sensitivity to determine the optimal allocation for quantization codebook values, thereby maintaining model accuracy.

This approach addresses the inefficient representation of the underlying parameter distribution caused by the limitations of uniform quantization. Furthermore, SqueezeLLM provides dense-and-sparse quantization, which allows quantization of the remaining parameters to low precision by addressing extremely high outliers in LLM parameters by preserving outlier values in a compact sparse format.

Non-uniform quantization is used by SqueezeLLM to best represent the LLM weights with less accuracy. When generating the non-uniform codebooks, the non-uniform quantization technique takes into consideration not only the magnitude of values but also the sensitivity of parameters to mistake, offering excellent accuracy for low-precision quantization.

Dense-and-sparse quantization, which SqueezeLLM employs, allows for the greater accuracy storage of a tiny portion of outlier values. This enables precise low-precision quantization for the dense matrix by lowering the needed range that must be represented by the remaining dense component.

The difficulty is in offering cross-platform assistance for low-precision LLM quantization

The method in SqueezeLLM provides for considerable latency reduction in comparison to baseline FP16 inference, as well as efficient and accurate low-precision LLM quantization to minimize memory usage during LLM inference. Their goal was to allow cross-platform availability of these methods for improving LLM inference on systems like Intel Data Center GPUs, by enabling cross-platform support.

SqueezeLLM, on the other hand, depends on handcrafted custom kernel implementations that use dense-and-sparse quantization to tackle the outlier problem with LLM inference and non-uniform quantization to offer correct representation with extremely few bits per parameter.

Even though these kernel implementations are rather simple, it is still not ideal to manually convert and optimize them for various target hardware architectures. They predicted a large overhead while converting their SqueezeLLM kernels to operate on Intel Data Center GPUs since they first created the kernels using CUDA and it took weeks to construct, profile, and optimize these kernels.

Therefore, in order to target Intel Data Center GPUs, they needed a way to rapidly and simply migrate their own CUDA kernels to SYCL. To prevent interfering with the remainder of the inference pipeline, this calls for the ability to convert the kernels with little human labor and the ability to more easily modify the Python-level code to use the custom kernels. They also wanted the ported kernels to be as efficient as possible so that Intel customers could benefit fully from SqueezeLLM‘s efficiency.

SYCLomatic

SYCLomatic offers a way to provide cross-platform compatibility without requiring extra technical work. The effective kernel techniques may be separated from the target deployment platform by using SYCLomatic’s CUDA-to-SYCL code conversion. This allows for inference on several target architectures with little extra engineering work.

Their performance investigation shows that the SYCLomatic-ported kernels achieve a 2.0x speedup on Intel Data Center GPUs running the Llama 7B model, and instantly improve efficiency without the need for human tweaking.

CUDA to SYCL

Solution: A SYCLomatic-Powered CUDA-to-SYCL Migration for Quantized LLMs on Multiple Platforms.

First Conversion

SYCLomatic conversion was carried out in a development environment that included the Intel oneAPI Base Toolkit. Using the SYCLomatic conversion command dpct quant_cuda_kernel.cu, the kernel was moved to SYCL. They are happy to inform that the conversion script changed the kernel implementations as needed and automatically produced accurate kernel definitions. The following examples demonstrate how SYCL-compatible code was added to the kernel implementation and invocations without

Change Python Bindings to Allow Custom Kernel Calling

The bindings were modified to utilize the PyTorch XPU CPP extension (DPCPPExtension) in order to call the kernel from Python code. This enabled the migrating kernels to be deployed using a setup in the deployment environment. Python script:

Initial Bindings Installation CUDA Kernel Installation in the Setup Script

1. setup( name="quant_cuda", 2 .ext_modules=[ 3. cpp_extension.CUDAExtension( 4. "quant_cuda", 5. ["quant_cuda.cpp", "quant_cuda_kernel.cu"] 6. ) 7. ], 8. cmdclass={"build_ext": cpp_extension.BuildExtension}, 9. )

Changed Setup Script Kernel Installation to Bindings

1. setup( 2. name='quant_sycl', 3. ext_modules=[ 4. DPCPPExtension( 5. 'quant_sycl', 6. ['quant_cuda.cpp', 'quant_cuda_kernel.dp.cpp',] 7. ) 8. ], 9. cmdclass={ 10. 'build_ext': DpcppBuildExtension 11. } 12. )

The converted SYCL kernels could be called from PyTorch code when the kernel bindings were installed, allowing end-to-end inference to be conducted with the converted kernels. This made it easier to convert the current SqueezeLLM Python code to support the SYCL code, requiring just small changes to call the migrated kernel bindings.

Analysis of Converted Kernels’ Performance

The ported kernel implementations were tested and benchmarked by the SqueezeLLM team using Intel Data Center GPUs made accessible via the Intel Tiber Developer Cloud. As described earlier, SYCLomatic was used to convert the inference kernels, and after that, adjustments were made to enable calling the SYCL code from the SqueezeLLM Python code.

Benchmarking the 4-bit kernels on the Intel Data Center GPU Max Series allowed us to evaluate the performance gains resulting from low-precision quantization. In order to really enable efficient inference on many platforms, this evaluated if the conversion procedure might provide efficient inference kernels.

Table 1 shows the speedup and average latency for matrix-vector multiplications while using the Llama 7B model to generate 128 tokens. These findings show that substantial speedups may be achieved with the ported kernels without the need for human tweaking.

In order to evaluate the latency advantages of low-precision quantization that are achievable across various hardware back ends without requiring changes to the SYCL code, the 4-bit kernels were benchmarked on the Intel Data Center GPU. Running the Llama 7B model without any human adjustment allows SqueezeLLM to achieve a 2.0x speedup on Intel Data Center GPUs compared to baseline FP16 inference, as Table 1 illustrates.KernelLatency (in seconds)Baseline: fp16 Matrix-Vector Multiplication2.584SqueezeLLM: 4-bit (0% sparsity)1.296Speedup2.0x

When this speedup is contrasted with the 4-bit inference results achieved on the NVIDIA A100 hardware platform, which achieved 1.7x speedups above baseline FP16 inference, it can be shown that the ported kernels outperform the handwritten CUDA kernels designed for NVIDIA GPU systems. These findings demonstrate that equivalent speedups on various architectures may be achieved via CUDA-to-SYCL migration utilizing SYCLomatic, all without requiring extra engineering work or manual kernel tweaking after conversion.

In summary

For new applications, LLM inference is a fundamental task, and low-precision quantization is a crucial way to increase inference productivity. SqueezeLLM allows for low-precision quantization to provide accurate and efficient generative LLM inference. However, cross-platform deployment becomes more difficult due to the need for bespoke kernel implementations. The kernel implementation may be easily converted to other hardware architectures with the help of the SYCLomatic migration tool.

For instance, SYCLomatic-migrated 4-bit SqueezeLLM kernels show a 2.0x speedup on Intel Data Center GPUs without the need for human tweaking. Thus, SYCL conversion democratizes effective LLM implementation by enabling support for many hardware platforms with no additional technical complexity.

Red more on Govindhtech.com

[xtruss]

'We Are In The Worst Crisis We Have Known Since The Civil War'

When the city of Detroit went up in flames in 1967, it was the most deadly civil uprising of the century

— May 15, 2024 | Kirstin Butler | American Experience

Troops on Detroit’s Linwood Avenue in 1967. © Tony Spina/Detroit Free Press via ZUMA Press.

The frame brims with human emotion: fear, dismay, resignation. Defiance. A Black man stares down three white armed National guards, his arms crossed and hip cocked. Smoke clouds the sky above them. This particular street scene in July 1967 was captured in Detroit, but it might have been taken in so many of the 150 cities where racial strife consumed the country that same year. Urban uprisings across the United States resulted in scores of deaths and millions of dollars of damage; entire city blocks were reduced to rubble. “The simple fact is this: We are in the worst crisis we have known since the Civil War,” said a television journalist in September of that year.

The roots of Detroit’s discontent went back decades. Blacks came to the city en masse during the Great Migration, growing from a population of around 5,000 in 1910 to 480,000 in 1960. That nearly 100-fold increase, however, wasn’t accompanied by expanding opportunity. Restrictive redlining practices consigned them to only a few neighborhoods, meaning a third of the city’s population lived in overcrowded, substandard housing. Black Detroiters also had fewer economic opportunities. They struggled to get work that paid as well as their white counterparts, and as the city began to lose jobs with the collapse of the automotive industry, Blacks were often the first fired. And the community’s relationship with the Detroit police had long been fraught, with Black residents on the brunt end of disproportionately harsh treatment.

In these conditions—de facto segregated housing, schooling, employment, and a history of police brutality—Detroit resembled other inner cities that had already erupted in protest in the years leading up to 1967. In 1964, the Harlem and Bedford Stuyvesant sections of New York broke out in violence after a white police officer shot and killed a Black 15-year-old. The next year, 1965, civil unrest consumed the Watts neighborhood of Los Angeles for nearly a week after a run-in between residents and police; 1966, more uprisings in Chicago and Cleveland followed the same pattern. And before Detroit combusted in mid-summer 1967, already 33 cities were in turmoil, with Newark, New Jersey suffering worst so far. In that city, white police officers beat a Black cab driver in full view of a public housing project. Twenty-six people died in the six days of public uproar and official crackdown that followed.

All of these urban rebellions made one thing clear: racism wasn’t just a southern problem. “We think of the civil rights movement and Jim Crow, the heart of it being in the South,” notes UC Berkeley professor john a. powell [sic]. “But you had cities all across the country up in flames. And those reactions to the continued oppression of blacks, it was never just spontaneous. It was always responding to some state-formed oppression.”

“Those Reactions To The Continued Oppression of Blacks, It Was Never Just Spontaneous. It Was Always Responding To Some State-Formed Oppression." — John A. Powell

These currents were all swirling in Detroit. In June, a Black Vietnam veteran had been killed by a gang of white youths after he took his pregnant wife to a public park bordering a white neighborhood. Then, in the early hours of July 23rd, the police broke up a party taking place at an illegal social club in a predominantly Black neighborhood on the city’s west side; the building doubled as headquarters for the United Community and Civic League, a local activist group. The club’s patrons had gathered to celebrate the return of two veterans from Vietnam, but instead found themselves being shoved roughly into paddy wagons. As the arrests continued, a large crowd gathered, protesting the officers’ treatment of the arrestees; someone eventually threw a brick at a police cruiser. Others joined in with bottles and sticks. Someone smashed the window of a nearby store, and looting began. Fires spread. By the next day, flames had devastated entire blocks.

Law enforcement responded harshly. “You cannot fight violent criminals with non-violent methods,” said a spokesperson for the Detroit Police Officers Association. “We had a war and I think you have to attack a war with warlike weapons and under warlike conditions.” Michigan governor George Romney called in the National Guard. Its young, untrained guardsmen, however, fomented more chaos. Five days later, 43 people had died, with hundreds more injured—at the time the most deadly civil uprising of the century.

Even as Detroit still burned, Johnson announced the formation of a presidential commission to study the chaos engulfing the country. He posed three questions to its 11 members: ‘What happened? Why did it happen? What can be done to prevent it from happening again?’ Led by Gov. Otto Kerner Jr. of Illinois, the National Advisory Commission on Civil Disorders—known colloquially as the Kerner or Riot Commission—conducted an on-the-ground assessment in 23 cities where disturbances had taken place, including Detroit. It interviewed 1,200 witnesses and officials, including residents, mayors, police chiefs and Black Power representatives.

The commission was a nearly all-male, all-white panel, and yet when it issued its final analysis, it offered a sweeping statement about the origins of the tinder stoking each urban conflagration. “Segregation and poverty have created in the racial ghetto a destructive environment totally unknown to most white Americans,” read the report’s introduction. “What white Americans have never fully understood—but what the Negro can never forget—is that white society is deeply implicated in the ghetto. White institutions created it, white institutions maintain it, and white society condones it.”

Ultimately, however, few of its recommendations for addressing these structural forces were implemented. “The Kerner Commission comes down and concedes that the country is broken,” professor powell told American Experience, “and that we should make rapid and radical change.” Yet, as is often the case with presidential commissions, political exigencies—in this case, the ire of white voters who ultimately elected law-and-order candidate Richard Nixon to the presidency—consigned its findings to history, rather than to the future.

“We’ve had many lost opportunities,” powell observes, while still noting the report’s ongoing relevance. “Kerner Commission—at best—is an opportunity postponed. I think if we do move forward, we will have to come back to that commission.”