Joy is a competitive super power. Alysa Liu retired from figure skating at 16. She was tired of not not having fun, tired of being consumed by her sport. She came back two years later with a new goal: to have as much fun on the ice as possible. And now she’s an Olympic gold medalist. Liu won her first national title when she was just 13. But by 16, after competing in the 2022 Olympics, she decided she’d had enough and stepped away. She said pressure and losing her identity trying to be an elite athlete made it all miserable. But then, she said she went on a ski trip that reminded her just how much fun she could have doing a sport. Something in her brain clicked. Maybe she could bring fun to figure skating. Maybe she could approach it in a way that could be full of joy and life and love. She unretired at 18 and won a world championship the next year. At 20, she was ready to face these Olympic games differently than in 2022. Liu went into the women’s figure skating final in third place. After her short program, she said: “Even if I mess up and fall, that’s totally okay, too. I’m fine with any outcome, as long as I’m out there.” One of the greatest competitive advantages is having fun. People love to romanticize the athlete, artist, or entrepreneur who has a chip on their shoulder, fueled by anger and resentment. But the truth is that if you’re not having fun, you are not going to last long at whatever it is you do, and you certainly won’t get the best out of yourself. There’s a foolish idea that you either have to be full of intensity or full of joy. But that’s nonsense. It’s no surprise one of the first things out of Alysa’s mouth after her free skate was: “That was so much fun!” Joy and intensity can coexist, and in the best performers, they almost always do. Alysa is unapologetically authentic and true to her values. She has said where she used to skate to win and be technically perfect, she now uses competition as a chance to show her art, to have fun, and to put herself out there. She’s a fierce athlete with an infectious sense of joy in her sport. And she broke USA's 24-year gold medal draught in women’s figure skating doing it. Excellence requires focus, determination, a little bit of crazy, at times obsession, and living a mundane lifestyle that many people would find boring. But excellence also requires that you find deep joy in your craft, that you learn how to have fun while working hard. What makes for excellence—and not just in sports, but in anything—is the combination of intensity and joy. It’s the latter that makes the former sustainable.

okay i will admit, this impresses me more than the mathematical proofs

The Cancer Episode > My diagnosis and prognosis > What this means for How to Take Over the World > A few thoughts on death > See below for links to GoFundMe, etc.

History suggests that experts consistently underestimate exponential technologies. Biology won’t be the exception.

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-myt…

Biology already had more ideas than it could test in the lab, and the development of new AI models will only further stress that bottleneck. Since 2023, our work at Tetsuwan has been focused on fixing to the biggest problem in lab automation so that we can use it to blow that bottleneck open. Lab automation will be necessary to turn in silico ideas into in vitro results, but today, lab automation is prohibitively costly for most workflows. Moving water from point A to point B could be an instruction that contains as many as 25 instructions (liquid classes are hard...). Formalizing experiments and removing all of the tacit & implicit details that surround them is a process that is far too slow & expensive to be worth it for the vast majority of experiments. As @owl_posting writes, "Most experiments can be automated, but are not worth doing so." We realized this back in 2023. Lab automation does not work for most experiments, and this fact would serve as a massive obstacle to attempts to automate biology research. So, we created a standard language for wet lab experimentation (technically two). We call them the Procedure Description Language (PDL) & the Variable Description Language (VDL). PDL & VDL give us a common way to specify experiments and their context. Once an experiment is expressed in a concrete syntax, our compiler, Ariadne, turns that specification into a set of instructions for the robot. But users don't need to know this language or do any programming themselves to move their experiments onto automated platforms. Our software platform, ResearchOS, abstracts for lab automation knowledge, allowing researchers to easily & rapidly configure their experiments for automation- all they need to get started is a PDF. Our team has spent the last two years iterating with pilot partners to develop this new way to communicate with lab robots. In the past few months, we've shared our progress on ResearchOS (read more on our blog!), including: - Agentic experimentation... letting agents run their own experiments using lab robotics - Off-deck module support, including the integration of 6DoF arms - Support for driver libraries, allowing cross-platform code generation Autonomous science does not work unless lab automation works, and the biggest constraint on wet lab automation today is how we approach automation engineering. ResearchOS is the answer, and Tetsuwan's first step in building an autonomous lab that any researcher or agent can easily send their experiments to, and get the resulting data in return. Of cloud labs, Armer, Letronne, & DeBenedictis (2023) write, "The cost to enter is high (>$250k for general access to Emerald Cloud Lab, or >$100k to automate and run a single method at Strateos), and the contract lengths are long (one year minimum". Autonomous labs do not work unless the automation engineering works, otherwise the unit economics are horrendous. We've made the automation engineering work. In the future, you don't need your own research lab to experiment, just an internet connection.

i think i see "new knowledge" on a relative spectrum instead of absolute binary category each piece of knowledge has some relative similarities and differences too all other existing knowledge, and you can point to many of those similarities and differences, and the amount of those determines its novelty some mathematical results can just be highly trivial solutions to an easy equation, while Grothendieck basically transformed algebraic geometry using new mathematical sublanguage compared to previous mathematical sublanguages but even localising the similarities and differences seems observer relative, as pointed to by the Blind men and an elephant analogy in the limit just the fact that everything is expressed in language is giving a trivial similarity

Neural networks do math by rotating shapes. We found a shape-rotating calculator hidden inside an LLM – and it’s used for more than just math! (1/6)

High-quality documents based on Claude’s constitution, combined with fictional stories that portray an aligned AI, can reduce agentic misalignment by more than a factor of three—despite being unrelated to the evaluation scenario.