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Welcome to Renegades, a series spotlighting Asian Pacific leaders and creatives who are carving their own paths and defying stereotypes along the way.  This week, we sat down with rising actress Lisa Yamada. Best known for her work on Cruel Summer and All American, Lisa talks about her experience working on diverse projects, received wisdom throughout her career, and her love for the Twilight Saga. Be on the lookout for her latest project, I Wish You All The Best, based on the novel by Mason Deaver, which premiered at this year’s SXSW.

The best things in life are free / singing birds and laughing trees Gus Franco’s is located in the middle of Leechburg Road. This road is off of 28 North, about twenty five minutes from the heart of Pittsburgh. It’s peppered with pizza shops. Peppered is maybe too light of a word. Slathered in pizza shops? Leechburg road is covered in a layer of grease runoff from all the pizza shops.

A few weeks ago, we talked about the German word Torschlusspanik: the feeling that some metaphorical door is closing on your life, and there’s not much time left to do all the things you’d like to do. For me, this feeling kicks into high gear when I play the comparison game. Maybe it’s a friend who landed a book deal. Or got a big job promotion. Maybe it’s an Instagram influencer who quit her job to sail the world.

We’re on the last stretch. 3 more California shows then home. It’s been such a blast. My favorite part each night is looking out in the audience and trying to guess who is here just for Lucius or just for Dawes and watch them get introduced in real time to a bunch of music they didn’t know they would like. A lot of converts on a tour like this. Anyway, I thought I’d take the opportunity to dig up a few more questions from our Q&A chat.

The two most famous sports-related cocktails in the world are the Mint Julep, for which thousands of mint plants are sacrificed every Kentucky Derby, and the Pimm’s Cup, drunk by the tankful at Wimbledon each year. But lately the U.S. Open’s official drink, the Honey Deuce, has been making a strong case for placing third. It is far younger than those two drinks, having been introduced only 17 years ago by Open sponsor Grey Goose vodka.

Welcome to It’s A Shanda, one Northeastern Jew’s quest to find a decent bagel in Seattle (and beyond). If you’re interested in taking this journey with me, make sure you subscribe so you never miss a review. If you want to ensure I review any specific bagels (or want to let me know why I’m wrong), you can email me at seanmatthewkeeley@gmail.com. UPDATE: Little Market has closed. 😢 ORIGINAL: Every once in a while I return to a bagel place that I’ve previously reviewed and find myself reconsidering everything I thought I knew.

The purpose of The Living Fossils is to communicate how the application of evolutionary ideas can help explain the sources of psychological suffering and well-being, in the service of improving our understanding of mental health. Over 1,000 subscribers No thanksncG1vNJzZmismJq5qsLIp56fp6Ootq2%2Fjaysm6uklrCsesKopGg%3D

A few days ago, I had a conversation with a friend about the inherent weirdness of befriending celebrities on Facebook, and I observed how—at least for the most part—my Facebook friendships with actors have either come about after I’ve interviewed them or else they started when everybody was first joining Facebook and it was kind of a free-for-all. In most of the latter instances, those friends haven’t checked their accounts in probably a decade or more, so they don’t really count anyway.

Embedding models have become an important part of the LLM ecosystem, especially for retrieval-augmented generation (RAG) applications. However, embedding models are dominantly based on bi-directional encoders (e.g., BERT), which are different from encoder models (e.g., GPT, Llama, Mistral) which are used for generative tasks. A new paper by researchers at Quebec AI Institute (Mila) introduces LLM2Vec, an unsupervised technique that can turn any encoder-only LLM into an embedding model. This can be an important tool because it enables organizations to use their fine-tuned LLMs for embedding tasks, improving their accuracy and reducing the costs of creating custom embedding models.