与「Changbin」相关的搜索结果

[EN] 끼 부리는 창빈 / 밥사효 EP.06 #효연# #HYO# #소녀시대# #GirlsGeneration# #창빈# #Changbin# #스트레이키즈# #StrayKids# #효연의레벨업# #HYOsLevelUp#

Translation isn’t always about changing languages. Sometimes, it’s turning words into meaning, meaning into clarity, and clarity into action. This International Translation Day, we’re thinking about how AI can help more people be understood. The language you speak shouldn’t decide how well your ideas come across. Comu does the literal kind of translation, too—with real-time transcription and translation, plus in-depth summaries across 113 languages. More voices heard. More ideas carried forward. Translate what matters.

It’s been 3 months since Wang Wang & her babies left the earth. Thanks for all the brave, kind, compassionate people keep speaking up for Wang Wang & her babies. We’re fighting this battle, if May take long time, but we will not give up. Due to the international community’s voice, I heard some protests against animal cruelty & the billboard to support justice for WangWang are resuming in some cities in China, the brave people marching on streets to demand justice for wang wang & her babies. But i won’t forget about you & your puppies. And I promise that every year on June 28, I’ll make a video for you to send you & your babies message. We’re still gonna fight for your justice, thanks for changing the world. We gonna keep pushing to get wang wang’s law passed. You’re a beautiful sweet angel, even I never met you, you’re in my mind everyday. May you & your babies rest in peace. You deserve to live with your babies, for now you don’t have to suffer any more. Let’s only share the good memories of Wang Wang to remember how sweet & gentle she is. What a loving brave dog mum she is. But we’ll continue to fight the justice for wang wang & her babies. #Rememberwangwang# #justiceforwangwang#

Salesforce acquires Listen Labs for ~$2b. But who gets the 💰? My usual breakdown below 👇 The company was founded in Sep-23 and had raised less than $100m. Investors will share ~$850m of profits on $96m invested, a ~10x blended. From a huge pivot to a unicorn valuation term sheet they refused, this is truly a wild story ✍️. In the end an incredible outcome for all involved. So let's dive in! 1) The boldest move: walking away from $1.5b 🎲 Listen Labs had a signed $125m Series C term sheet from Menlo at a $1.5b valuation... and walked away from it to sell to Salesforce at ~$2b. This takes a huge amount of courage: few founders turn down a signed unicorn-plus round. @itsalfredw and @florian_jue did it 2.5 years after founding. Huge congratulations are in order for the discipline and execution of the founders here. 2) Founders and team: a life-changing outcome in under 3 years 🥳 By my best estimates, founders and team still own over half the company. At $2b, that's ~$1.1b for them to share. Specifically, assuming a 15% option pool, that is ~$300m for the team and ~$750m for the two co-founders. And, as was the case with Hugging Face, this is all from a pivot. They originally built an AI customer-interview tool to understand why their viral app BeFake was growing, then realised the tool was the business! 3) Sequoia's Bryan Schreier did it again 👑 What few people know is that Bryan was an early backer of Qualtrics... the category Listen Labs is disrupting. Now he led both the seed and the Series A here. By my estimates, those two rounds will return ~$670m combined, or ~25x on ~$27m invested, in under three years. Pattern recognition and industry knowledge have their perks, it would seem! 4) Ribbit: 4x in 8 months ⚡ Ribbit led the $69m Series B in Jan-26 at ~$500m. At $2b, that's ~4x in 8 months. Unbelievable IRR and a great return on a meaningful cheque. 5) Neo does it again, congrats @apartovi 🎯 Listen Labs went through the Neo accelerator early on, which came with a $600k SAFE. On my estimates, that cheque is worth ~$25m+ today. This comes just three months after Cursor's acquisition (a cool >1,000x for Neo). What a hit rate! This one is very straightforward: it is a massive win for everyone. And so congratulations to all involved: Sequoia, Ribbit, Conviction, Pear, Neo and the team!

Hi, Tomorrow we are re-opening the Pro $200 subscriptions to new subscribers, but together with it we are also changing how we calculate the usage for it. In effect, if you do the math, it will net out at half the dollar in API spend compared to the old Pro $200 plan. Now that it's said, let me explain why this is happening and why you will still get more work done than if you were on the Pro $200 subscription one month ago. (a) We didn't want to compromise in other ways and are committing to not reintroducing the 5h limit, so that you can fully use the weekly usage when you want. (b) On the subscription, we guarantee that over time you always get more work done and with an increasing level of quality. This means that you will continue to get more value per dollar spent as a result of models getting more efficient and us passing down the improvements in the form of API price reductions. (c) We don't want to put an incentive on ourselves to artificially inflate the API list prices to make it look like you are getting a lot (and workaround it through discounts, etc). Instead we want to continue to both rapidly reduce prices and increase capabilities of models on the API. This week we introduced GPT-6 Sol and GPT-6 Luna at 50% of their previous price. Over time, we see prices go low enough that it makes sense for most to buy usage as needed without there being a significant gap between what you get in a subscription and what you get in the API for a dollar spent. (d) Tomorrow, we are adding more things to the subscription that won't draw on the usage, I won't reveal what that is yet. I wanted to be transparent before all the big announcements tomorrow. Lots of new exciting things are coming to the subscriptions that will make it super compelling, but I wanted to make sure to share this change ahead of time so you can all understand it before we shower you with good news. Codexingly, Tibo

Institutional clients are a core focus for Bitget's next phase, which means we're listening closely to what they actually need. Over the past few weeks, I've been sitting down with leaders from some of our key institutional partners for a new CEO Chat Series, where we talked about topics reshaping the market, from prime brokerage and fragmented liquidity to smarter collateral, tokenization at scale, and the changing expectations around institutional execution. Fire chat coming soon, stay tuned to @bitget

When I first saw JEV, as a former TikTok MLE, I knew modern recommendation and search systems could be revolutionized if it keeps evolving. JEV brings general-purpose semantic reasoning into a discriminative inference paradigm: arbitrary context in, calibrated structured decisions out. That matters because recommendation and search are exactly the kinds of decision systems that need to be both smart and fast. Times are changing. Here’s one example: with JEV + Perfectly, we use a complex query to understand AI researchers through their papers across a pool of 500 ECCV 2026 researchers, while achieving the same performance as one of Claude’s models.