Brazil’s attorney general is seeking a probe into possible insider trading in the country’s currency markets around the announcement of US tariffs on Brazilian goods.
Source: Bloomberg Markets.
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Legal advocates and attorneys general argue practice poses accountability issues and contributes to a climate of fear
The head of US Immigration and Customs Enforcement (Ice) said on Sunday that he will continue allowing the controversial practice of his officers wearing masks over their faces during their arrest raids.
As Donald Trump has ramped up his unprecedented effort to deport immigrants around the country, Ice officers have become notorious for wearing masks to approach and detain people, often with force. Legal advocates and attorneys general have argued that it poses accountability issues and contributes to a climate of fear.
Source: World news | The Guardian.
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Winners: Team Collier
INDIANAPOLIS — Napheesa Collier was the biggest of the All-Stars on Saturday as her Team Collier beat Team Clark 151-131 at Gainbridge Fieldhouse. The Minnesota Lynx forward scored an All-Star Game-record 36 points as her squad dominated throughout.
The players spent a lot of the weekend sending a message that they want to get paid more by the league, as both sides are in the midst of collective bargaining. The city of Indianapolis embraced hosting the game, and the fans showed out in full force despite team captain Caitlin Clark being sidelined by injury.
Much more dialogue will come throughout the rest of this season on labor negotiations, and the injury status of marquee players such as Clark will be a continuing topic.
But here, we grade the individual performances of the 22 All-Stars on the court (and Friday’s participants in the 3-point contest and the skills challenge). Indianapolis gets an A-plus for all it did to publicize the game and turn downtown into a celebratory space. Which players got the other top grades?
Jump to: Team Collier | Team Clark | 3-point contest | Skills challenge
Napheesa Collier, F, Minnesota Lynx
Grade: A+This was as close to a one-woman show as an All-Star Game could be for MV-Phee. She was 13-of-16 from the field and 6-of-6 from the foul line. This game doesn’t count toward regular-season stats, but Collier is shooting 94.6% (105-of-111) from the free throw line this season. Collier, who leads the league in scoring (23.2 points per game), is the season MVP favorite for the first-place Lynx. So, perhaps Saturday was just a prelude to her picking up that trophy in a couple of months.
Skylar Diggins, G, Seattle Storm
Grade: A+A native of South Bend, Indiana, Notre Dame legend Diggins was terrific in the All-Star Game back in her home state. She had the first triple-double — 11 points, 11 rebounds and 15 assists — in WNBA All-Star Game history and seemed to have a great time doing it. Diggins, making her seventh All-Star Game appearance, is averaging 17.5 points and 5.8 assists this season for the Storm.
Kelsey Plum, G, Los Angeles Sparks
Grade: APlum had a hot start and for a while looked as if she might contend for MVP, before Collier ran away with it. The longtime Las Vegas Aces star now in her first season in Los Angeles finished with 16 points, 5 rebounds and 3 assists. And she gets extra credit for some of fun antics, such as guarding former Aces teammate A’ja Wilson all the way down the sidelines and out of bounds on one comical sequence in the first half.
Nneka Ogwumike, F, Seattle Storm
Grade: AShe was nearly perfect from the field — going 7-for-8 — and that included 2-of-2 from behind the arc. Ogwumike had a career-high 30 3-pointers last season, and she is sure to break that mark this year with 27 on the season already. The 10-time All-Star also had seven rebounds and three assists.
Allisha Gray, G, Atlanta Dream
Grade: B+Last year’s double winner of the 3-point contest and skills challenge competed in both events again this season. That’s impressive, even if she didn’t successfully defend either title. Then Gray, who is averaging a career-high 18.4 PPG this season, put up 18 points Saturday, going 5-of-12 from behind the 3-point arc.
Courtney Williams, G, Minnesota Lynx
Grade: B+Williams and her Lynx “Studbudz” teammate Natisha Hiedeman made the most of being everywhere and enjoying everything on All-Star Weekend. So, Williams gets extra credit for that. She also had work to do: Williams competed in the skills challenge and in Saturday’s All-Star Game, in which she finished with 13 points, 5 assists and 2 rebounds.
Paige Bueckers, G, Dallas Wings
Grade: BIn her first All-Star Game, the Rookie of the Year favorite and No. 1 draft pick made her mark by facilitating, just as Clark did last season. Bueckers had eight assists to go along with six points.
Alyssa Thomas, F, Phoenix Mercury
Grade: BThis might seem like a high grade considering Thomas had just six points. But consider how efficient she was: 3-of-4 from the field, 4 rebounds, 4 assists and plus-14 in 13 minutes of play. Thomas, the face of the Connecticut Sun for so long, has become a favorite of Phoenix’s X-Factor fan base and has helped make the Mercury a potential title contender.
Kayla McBride, G, Minnesota Lynx
Grade: B-A replacement player for Atlanta’s Rhyne Howard, “McBuckets” is another player with Indiana connections, as she also starred at Notre Dame. McBride helped lead the Lynx to the WNBA Finals last year, and she is a big part of them being in first place now. She posted 15 points Saturday, but she gets dinged a little for going 4-of-12 from the field
Breanna Stewart, F, New York Liberty
Grade: B-It was a fairly quiet All-Star Game for Stewart, who won her third WNBA title last year and is trying to help the Liberty repeat. Stewart went 4-of-8 from the field for 8 points to go with 4 rebounds and 2 assists. But she gets extra credit for passing to injured Rhyne Howard on the bench and allowing her to take a shot.
Angel Reese, F, Chicago Sky
Grade: B-Reese, the league’s leading rebounder, had just six points, but she still grades in the Bs thanks to nine rebounds and finishing plus-17 in her 17 minutes of play. Plus, Team Collier was so good that we just don’t think anyone should get an average grade. — Michael Voepel
Losers: Team Clark
Kelsey Mitchell, G, Indiana Fever
Grade: AThe Fever fan favorite has been on an efficient scoring run in the regular season that carried over to the All-Star Game. She led Team Clark with 20 points on 8-of-13 shooting and also tallied 2 rebounds, 2 assists and 2 steals. And no one has more of an appreciation for the resurgence of the Fever franchise than Mitchell, who is in her eighth season in Indiana and has seen the best of times blossom after the worst.
Kiki Iriafen, F, Washington Mystics
Grade: AThe rookie and No. 4 draft pick was dynamic and fun in her first All-Star appearance, getting a double-double with 17 points and 10 rebounds. She was 7-of-15 from the field. Iriafen has been a big part of the Mystics’ better-than-expected 11-11 season.
Kayla Thornton, F, Golden State Valkyries
Grade: AIn her 10th campaign, Thornton is having a career year as she has helped launch the Valkyries expansion franchise. This was her first All-Star Game appearance, and she made the most of it with 15 points, 11 rebounds and 5 assists.
Gabby Williams, F, Seattle Storm
Grade: A-Making her first All-Star appearance in her seventh WNBA season, Williams made her presence felt. She finished with 16 points and five assists. Her talent on defense wasn’t on display at the All-Star Game, but expect it back as soon as the regular season resumes.
Brionna Jones, F, Atlanta Dream
Grade: B+Jones is known for her quiet, dependable efficiency, and that described her in this All-Star Game. She played just 12 minutes but went 5-of-6 from the field for 11 points while adding 3 rebounds and 3 assists. A replacement player for Satou Sabally, Jones capitalized on her opportunity. And she has been a very good addition to the Dream this season.
Sabrina Ionescu, G, New York Liberty
Grade: B+Ionescu made a huge contribution to All-Star Weekend with another exciting performance in winning the 3-point competition, and we want to give her some extra credit for that here. On Saturday, she was 4-of-8 from the field for 12 points to go with seven assists.
Aliyah Boston, F, Indiana Fever
Grade: B-She has been a tower of strength for the Fever since she was drafted No. 1 here in 2023. So, it was nice to see Boston get a lot of love from the Gainbridge Fieldhouse crowd for this game as she posted 9 points, 6 rebounds and 2 assists.
Sonia Citron, G, Washington Mystics
Grade: B-Like Iriafen, No. 3 draft pick Citron got a chance to be an All-Star as a rookie. She also took part in the 3-point shooting contest Friday, and Sabrina Ionescu shared part of her 3-point winnings with her. Citron registered 11 points, 2 assists and 2 rebounds in the All-Star Game.
Brittney Sykes, G, Washington Mystics
Grade: B-Sykes was the replacement for Caitlin Clark and had an overall good night — except for behind the arc, where she was 0-for-9. Still, Sykes had 16 points, 7 assists and 3 rebounds. This season, she has been a good mentor for fellow All-Stars Citron and Iriafen, who are rookies with the Mystics.
A’ja Wilson, F, Las Vegas Aces
Grade: CThe three-time MVP has dealt with some injury issues this season and didn’t want to play a lot in the All-Star Game. She was in for 12 minutes and finished 2-of-4 from the field for 4 points to go with 2 rebounds and 2 assists. Now, it’s back to trying to figure out how to help bring more consistency for the 11-11 Aces.
Jackie Young, G, Las Vegas Aces
Grade: NoneThe two-time WNBA champion and two-time Olympic gold medalist — back in her native state of Indiana, where she grew up in Princeton then starred at Notre Dame — played just one minute due to dealing with an injury. — Voepel
3-point contest
Friday’s festivities had a New York flavor. The Liberty‘s Sabrina Ionescu won the 3-point shooting contest for the second time in three years, while teammate Natasha Cloud took home the skills challenge title.
It’s the second time in WNBA history that players from the same team have won both competitions, which have been held at every All-Star Game since 2019, but the first time that has happened with two different players. In 2024, Allisha Gray of the Atlanta Dream won both competitions, but she was unable to successfully defend either title Friday.
Sabrina Ionescu, New York Liberty
Grade: AAfter sitting out last year, Ionescu returned to show why she and four-time winner Allie Quigley are the only acceptable answers for the WNBA’s 3-point contest GOAT.
For anyone else, Ionescu’s score of 25 in the first round — tied for second best of the night — would have been a highlight. Ionescu made 13 of her last 16 shot attempts, including a deep 3. For Ionescu, that was just a warmup.
In the final, Ionescu missed her first two shots and her last three, which led her to say she was “pretty disappointed” because she “missed a few easy ones.” Everyone else was amazed by Ionescu making 11 consecutive shots at one point, including the deep 3, reminiscent of her record score of 37 during the 2023 final.
Ionescu settled for a 30-point round, giving her two of the three times WNBA players have scored 30-plus in the 3-point contest since the current format was adopted in 2021. Quigley, with a round of 30 in the finals, was fittingly the other player to reach that mark.
Allisha Gray, Atlanta Dream
Grade: A-Going last as the defending champ, Gray set up the anticipated showdown of the past two winners by making four shots and the money ball from each of the last three racks. That tied Ionescu’s score of 25 in the opening round. Gray got on a similar roll from the left wing in the finals, going 5-for-5 after making the deep 3 from that side, but it was already too late to catch Ionescu. Gray missed her first four shots of the finals and went 0-of-5 from the top of the key. Gray’s score of 22 points in the finals nonetheless matched the best round by anyone but her and Ionescu.
Kelsey Plum, Los Angeles Sparks
Grade: BThe middle of Plum’s round put her in the early lead. She made three from the top of the key, the right deep 3 and four of five from the right wing. Had Plum made her final shot, worth two points, she would have made things really interesting for the two finalists. Instead, Plum finished third behind the two previous champions.
Sonia Citron, Washington Mystics
Grade: B-The lone rookie in the field might have needed to move her money ball rack. Citron made four of her high-arching shots from the left wing and all five from the top of the key but went 1-of-5 from the right wing with double points for all shots. Simply flipping the two wings would have given Citron a couple more points and pushed her out of last place. For that spot, Citron’s score was more than respectable.
Lexie Hull, Indiana Fever
Grade: B-The Fever’s only player to compete Friday was a late replacement for teammate Caitlin Clark, who had to withdraw due to injury. Early on, it looked like Hull’s shot — reliant on a large vertical jump — might not translate to the 3-point contest. She had just three points through the first two racks before making one of the deep 3s. Hull caught fire down the stretch, making eight of her last 10 shots — including four of five from the money ball rack — but it wasn’t enough to reach the finals. — Kevin Pelton
Skills challenge
Natasha Cloud, New York Liberty
Grade: AI thought Cloud was out of the finals after she needed all three attempts on both 3-point shots, but she managed to race through the final pass and the hoop for a layup just ahead of Erica Wheeler’s time of 37.5 seconds. Cloud ended with the night’s two best times, displaying a mastery of both skill and the strategy that can separate winners from losers in the skills challenge.
Erica Wheeler, Seattle Storm
Grade: A-The longtime member of the Indiana Fever got a huge cheer from the crowd when she referred to her home-court advantage in the competition. It looked like that might be enough to carry the 2019 All-Star MVP to victory, overcoming a gaffe in the opening round. Focusing on fundamentals and making her first shot or pass, Wheeler had enough cushion to advance even though she smoked her first layup attempt. In the finals, Wheeler set the bar for Cloud, but slowing down when she needed multiple attempts at the above-the-break 3-pointer cost her.
Allisha Gray, Atlanta Dream
Grade: B-The defending champ, Gray moved quickly through the course — perhaps too fast for her own good. Gray was already trying to move on to the next station when she missed her first chest pass and had to double back. Gray needed all three attempts, leaving her too far behind to reach the final round despite strong shooting.
Courtney Williams, Minnesota Lynx
Grade: CAfter a strong start with bounce passes, Williams wasn’t clean enough the rest of the round. Williams needed multiple attempts on her outlet passes and shots, leaving her with a score of 42.0 seconds that surpassed only Diggins. Ahead of playing in Saturday’s All-Star Game, that left Williams time to focus on her livestream with Natisha Hiedeman.
Skylar Diggins, Seattle Storm
Grade: C-Diggins’ opening round reflected an issue with the skills challenge rules that the NBA and WNBA haven’t rectified after the San Antonio Spurs were disqualified at NBA All-Star Saturday Night for attempting to exploit it. Because players move on with no penalty after three missed shots (or passes), there’s no actual benefit to making the last shot — as Diggins did from all three locations. The time Diggins spent on those attempts doomed her to the first round’s slowest time. — Pelton
Source: www.espn.com – TOP.
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I Tested 100+ Pickleball Paddles to Select the Best at Every Level
How I Test Pickleball Paddles
I’m not an expert player (I’m somewhere between a 4.0 and a 4.5 on the USAP’s Player Skill Rating), but I’ve now tested more than 100 paddles on indoor and outdoor courts over the past three years. At one point I played in a weekly pickleball league, though I don’t anymore. I also test the paddles against a Slinger pickleball machine which is very helpful, as the machine consistently fires balls with a lot of spin and power. After playing with piles of paddles—and having players of various skill levels try them and share their thoughts—I feel confident that this guide has a paddle recommendation for you, whether you’re a beginner or a pro pickleball player.
What Size Paddle Do You Need?
Pickleball paddles are restricted by a size formula similar to the one airlines use: The paddle can’t be longer than 17 inches and the combined length and width of the paddle cannot exceed 24 inches. A standard paddle is 16 inches long and 8 inches wide, but some elongated paddles use the full 17 inches and tend to have more power than wider options. There is no restriction on the thickness of the paddle; thin paddles can be about one-third of an inch thick, while thick paddles can be up to three-quarters of an inch thick.
What Does “Pop” Mean?
You’ll see me using this term a few times in this guide. “Pop” is the pickleball parlance for how aggressively the ball bounces off the paddle face—you can think of it as an analogue to how “bouncy” a basketball is.
What Is Dwell Time?
The latest buzzword in pickleball circles is “dwell time,” which means how long the ball stays in contact with the face of the paddle before bouncing back off. Because your body is providing torque when you swing, the longer the balls sits—time measured in nanoseconds—on the face of the paddle the more spin will be created and the harder your shot will be to return. It gets very nerdy very quickly. I would love to speak about the dwell time of the paddles I’ve tested, but my personal sense of the number of nanoseconds the ball is in contact with the paddle is not appropriately fine-tuned.
How Much Do Pickleball Paddles Weigh?
There is no rule about a pickleball paddle’s weight, but almost every paddle hovers around 8 ounces. I went out of my way to test the biggest range of paddles I could find and ended up testing paddles that were within about an ounce of each other. Light paddles tend to be about 7.5 ounces, whereas heavyweight paddles are about 8.5 ounces. More important is the distribution of that weight—paddles that offer more power tend to be top-heavy. I prefer paddles with a balanced feel.
Are All Pickleball Paddles the Same Shape?
Pickleball paddles tend to look fairly similar shapewise. In my testing, I tried several outliers, including a Joola paddle with a rounded shape more like a tennis racket, and several Selkirk paddles with a cutout between the paddle face and handle designed to minimize air resistance. I think the standard shape is still best.
What Are Pickleball Paddles Made Of?
Old-fashioned wooden paddles still exist, but inexpensive fiberglass paddles are how I started playing. You can nab a beginner set for $30 (see “Best for Beginners”), and it could be six months before you feel the need to upgrade. That said, the paddles recommended here tend to have a carbon-fiber face, which is stiff and light, offering lots of pop. I also tested some graphite paddles, which are cheaper, heavier, and softer than carbon fiber. If your budget doesn’t allow you to start with carbon fiber, I’d recommend starting with cheap fiberglass and then jumping to carbon fiber. Note that when I mention materials, I mean what’s used for the face of the paddle—nearly all paddles have a similar honeycomb-shaped polymer core. Pricier paddles tend to cut that core in a way that creates even gaps on the edge and use heat-pressing to seal the face to the core.
Source: Wired.
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*A hard look at effort-based pricing and the hidden cost of being a paying beta tester
*Let me be crystal clear from the start: I’ve cancelled my Replit subscription, and I won’t be coming back. Not for the $10 credit they’re dangling like a carrot, not for the promises of “improved pricing transparency,” and certainly not to continue being an unwitting contributor to their model training while paying premium prices for the privilege.
This isn’t just about money. It’s about respect, fairness, and the fundamental question of who benefits when paying customers become unpaid quality assurance testers for AI systems that will ultimately compete against us.
When Michele Catasta, Replit’s President & Head of AI, posted their explanation for the pricing model change, he mentioned they’ve been “reading all the feedback” and “learned a lot from it.” But here’s what they apparently didn’t learn: when paying customers cancel en masse, that’s not feedback—that’s a market rejection.
I cancelled my subscription not because I couldn’t afford the new pricing, but because I refuse to participate in a system that fundamentally misunderstands the relationship between a service provider and their customers. Replit’s new “effort-based pricing” model isn’t just expensive—it’s exploitative.
The Training Tax: Paying for Our Own Replacement
Here’s the uncomfortable truth that Replit’s blog post conveniently glosses over: every time their AI agent fails to understand context, makes an error, or requires correction, we—the paying customers—provide the feedback that makes their system better. We debug their debugging. We teach their teacher. We train their trainer.
And we pay for every single interaction.
This isn’t a bug in their pricing model—it’s a feature. They’ve successfully externalized the cost of model improvement to their user base while maintaining ownership of all the intellectual property we help create. It’s a brilliant business strategy, if you can stomach the ethics of it.
When I pay $0.40 for an image change that fails, I’m not just paying for compute time. I’m paying for the privilege of generating training data that will make Replit’s next model iteration more valuable. When I spend $20-40 on a “higher intelligence” task that produces broken code, I’m not just paying for effort—I’m paying to be a quality assurance tester for a system that will eventually be good enough to charge the next customer even more.
The Effort Illusion
Replit’s justification for effort-based pricing rests on a fundamental misunderstanding of what customers actually want. They claim they’re charging for “effort” rather than results, as if the amount of computational work their system performs is somehow relevant to the value I receive.
This is like a restaurant charging you based on how many times the chef had to taste the soup, rather than whether the soup actually tastes good. The effort is the restaurant’s problem, not mine. I’m paying for a working meal, not for the chef’s learning process.
But here’s where the analogy breaks down: at least the restaurant doesn’t ask me to come into the kitchen, taste the failed attempts, provide detailed feedback on what went wrong, and then charge me for the privilege of improving their recipes.
The Predictability Problem
One of the most insidious aspects of effort-based pricing is how it transforms the development experience from creative exploration into anxious cost calculation. Every prompt becomes a gamble. Every iteration carries the risk of an unexpected bill.
This isn’t just about budgeting—it’s about the fundamental nature of creative and technical work. Programming, like writing or design, requires experimentation, iteration, and yes, failure. The best solutions often emerge from exploring dead ends, trying different approaches, and refining ideas through multiple attempts.
Effort-based pricing turns this natural creative process into a financial liability. It creates a chilling effect where developers self-censor their exploration, simplify their requests, and avoid the kind of deep, iterative work that produces truly innovative solutions.
The Lock-In Trap
Perhaps most troubling is how effort-based pricing creates a new form of vendor lock-in. Not through technical integration or data portability issues, but through sunk cost psychology. The more you invest in getting Replit’s AI to understand your project, your coding style, your preferences, the more expensive it becomes to start over with a different tool.
This isn’t accidental. It’s a calculated strategy to increase customer lifetime value by making switching costs prohibitively high. Every dollar you spend training their model to work better for you is a dollar that makes leaving more expensive.
The Market Reality Check
Replit’s leadership seems to believe they’re operating in a vacuum, where customers have no alternatives and will accept any pricing model they impose. This is a dangerous delusion in a rapidly evolving market.
While Replit was busy alienating their core user base with unpredictable pricing, competitors were building more transparent, customer-friendly alternatives. The AI coding assistant market is exploding with options, many of which offer predictable pricing, better performance, or both.
The irony is that Replit’s effort-based pricing model is training their customers to evaluate alternatives—and finding them wanting in comparison.
The Community They’re Losing
What makes Replit’s pricing strategy particularly shortsighted is how it targets the very community that made them successful in the first place. Students, educators, indie developers, and small teams—the people who evangelized Replit, created content about it, and built the vibrant community around it—are exactly the people who can’t absorb unpredictable $200+ monthly bills.
These aren’t just customers; they’re the foundation of Replit’s ecosystem. They’re the ones who create tutorials, answer questions in forums, and recommend the platform to others. They’re the early adopters who validate new features and provide the social proof that attracts enterprise customers.
By pricing out this community, Replit isn’t just losing revenue—they’re losing their soul.
The Enterprise Mirage
The implicit message behind effort-based pricing is clear: Replit is pivoting to enterprise customers who can absorb higher, unpredictable costs. This is a common trajectory for developer tools—start with a community-friendly model, build market share, then extract maximum value from enterprise customers.
But this strategy ignores a crucial reality: enterprise customers are also developers. They read the same forums, follow the same thought leaders, and pay attention to community sentiment. When a tool alienates its community, enterprise customers notice.
Moreover, enterprise customers are often more sophisticated about vendor evaluation. They’re more likely to demand predictable pricing, better support, and clearer value propositions. Effort-based pricing fails on all three counts.
The Feedback They’re Not Hearing
Replit’s leadership claims they’re listening to feedback, but their response suggests they’re only hearing what they want to hear. The real feedback isn’t in the polite forum posts or carefully worded feature requests—it’s in the cancellation emails, the migration blog posts, and the conversations happening in developer communities outside their control.
The feedback is simple: we don’t want to pay to train your model. We don’t want unpredictable pricing. We don’t want to be treated as beta testers for a system that will eventually replace us. We want tools that respect our time, our budgets, and our intelligence.
For developers still using Replit, my advice is simple: diversify your toolchain. Don’t put all your development workflow eggs in one basket, especially one with unpredictable pricing and a history of sudden changes.
For Replit’s competitors, this is an opportunity. The market is full of frustrated Replit users looking for alternatives. Build transparent pricing, respect your community, and remember that developers are customers, not training data sources.
For Replit itself, it’s probably too late. They’ve made their choice, and the market is responding accordingly. But if they’re genuinely interested in feedback rather than just damage control, here it is: go back to predictable pricing, stop charging customers to train your models, and remember that your community made you successful.
The Bigger Picture
The Replit situation is a microcosm of a larger problem in the AI industry: the normalization of extractive business models that socialize costs while privatizing benefits. We’re seeing this pattern everywhere—AI companies that train on public data, charge users for access, and then use user interactions to improve their models.
This isn’t sustainable, and it’s not ethical. As developers, we have the power to reject these models by choosing alternatives that respect our contributions and our wallets.
I won’t be touching that 10$ credit. Why should I pay them to be a product tester when I’m supposed to be a customer? The fundamental relationship is broken, and no amount of credits or blog posts will fix it. Replit had something special—a platform that democratized coding, fostered creativity, and built a genuine community. They traded it for a pricing model that treats customers as training data sources and community members as revenue optimization targets.
The market will remember this choice. Developers have long memories, and we talk to each other. Word spreads quickly in our community about which tools respect us and which ones exploit us. Replit made their choice. Now we’re making ours.
*Find yourself a bunch of other clowns to pay for your houses and cars. There are plenty of other offerings in the market that can change an image for 25 cents to the dollar. *
p.s. I am aware of the part of the TOS where they say they don’t use private data to train your model. But I urge you to read the next sentences of that section as well, before you storm to the comments.
Source: DEV Community.
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Best Upgrade
Like the Joy-Con 2s, there’s a sense of continuity from the original Switch to the new generation’s Pro Controller. At a glance, it’s essentially the same—a more conventional controller in the mold of those used on Xbox or PlayStation, perfect for Switch 2 games that don’t require the unique features of the Joy-Cons. However, this is crammed with clever adjustments and design tweaks that make it feel substantially different from its predecessor.
Chiefly, it feels smaller in the hand thanks to slimmed-down grips that sit at a slightly tighter angle. It only weighs 11 grams less than its predecessor—235 versus 246—but seems much lighter. Subtler but still impactful tweaks include larger face buttons, and smoother, more responsive thumbsticks—although these still don’t use Hall effect or TMR technology, meaning drift remains a risk. It feels great to hold, though, thanks to an almost seamless design, a choice that has the benefit of leaving few ridges or component joins where hand sweat can accumulate after long play sessions.
The big changes are the addition of a 3.5-mm audio jack at the base of the controller, allowing a headset or mic to be connected—tying in perfectly with Nintendo’s social gaming push with its integrated GameChat feature, accessed through the new, central C button—and the addition of new GL and GR buttons on the underside. These inputs can be customized on a per-game basis—simply hold down the Home button, and they can be remapped on the fly. Modifications are remembered per user, per game, which puts the “pro” in Pro Controller. These upgrades come at a literal cost, but this is one of the best ways to play on Switch 2.
Wired/TiredWired- Programmable buttons
- Integrated audio jack
- Feels great to hold
Tired- Pricey
- Still no Hall effect thumbsticks
Source: Wired.
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The 9 Best Coolers for Cold Beer on Hot Days
The first thing to consider when buying a cooler is how you’re going to use it. If you aren’t heading out for days at a time, you probably don’t need an expensive high-end cooler. All the coolers we’ve recommend above are capable of holding things at a safe temperature for a day, provided you keep them in the shade. Similarly, if you’re navigating rugged terrain, you might want beefy wheels—and if you’re just going to the beach, you might not need them.
Hard-sided coolers: These range from the old green Coleman coolers—once a staple of every camping trip—to Yetis, which cost as much as cars did when Coleman started making coolers. You might wonder why the Yetis are so expensive. That I can’t answer, but Yeti did upend the cooler industry by introducing rotational molding, or “rotomolding,” where melted plastic is molded over foam insulation in one piece. Rotomolded coolers offer seamless, uniform density in their walls and lids, which drastically improves a cooler’s performance. In contrast, those ancient, affordable plastic coolers we’ve all used have thinner walls, leaky seams, and less insulated lids. Whether you need the extra insulation depends on what you’re doing and how hot it is when you’re doing it. Want to learn more? Our In-House Know-It-All has a more thorough insulation explanation.
Hard-sided coolers generally have the luxury features you want, like leakproof lids and drain plugs, and some are even bear-resistant (check this list of bear-proof products if you’re headed into ursine country). The downside is that these coolers are generally huge and heavy.
Soft-sided coolers: Soft-sided coolers include everything from well-padded, impressively insulated sling bags (like the Yeti Hopper Flip above) to roll-down, dry-bag-style coolers perfect for those mild beach days. The best soft coolers are easier to carry, pack away easily when not in use, and have a versatility that traditional hard coolers lack. (I have used dry-bag-style coolers as, well, dry bags.) Ice doesn’t last as long, but for short outings where you don’t need a large cooler, these are what we recommend. Our older pick was discontinued; we’re on the hunt for another.
Electric coolers: Sure, they’re not necessary, but if you’re headed out on longer adventures and have access to power, you’ll never have to worry about your ice melting.
Other Features to Look For:
- Drain plug: This greatly simplifies life by making it easy to drain the water out of your cooler. If you’re buying a large cooler, make sure it has one of these.
- Divider: One of our top tips for long-term cooler use is to have two coolers: One you treat as a fridge and hardly ever open, and another for drinks. If that’s not possible, you can achieve some of the same by getting a cooler with a dividing wall in it. That way you can pack one side tightly with ice to keep that meat at a low temp, and use the other side for chilling beverages with cubed ice.
- Wheels: Coolers get heavy and wheels are awesome. They won’t always work (good luck wheeling your cooler over tree roots), but when they do, they are completely worth it.
Source: Wired.
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Emerging-market borrowers are tapping the euro bond market at the fastest pace in over a decade, capitalizing on the rising demand for diversification away from the US dollar.
Source: Bloomberg Markets.
