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We are thrilled to announce an incredible partnership with @MakersMark! To honor America's 250th anniversary, Maker's Mark has created a limited-edition bottle featuring the brand's signature hand-dipped red wax, accented with a white wax dip and a blue rendition of its iconic seal. Beginning June 1st, the bottle will be available at select retailers nationwide and a portion of proceeds will benefit the Farmer Veteran Coalition. We are deeply grateful for Maker's Mark's support of our organization and the farmer veteran community. Read more: #farmerveterancoalition# #MakersMark# #America250#
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For the past few summers, we partnered with @MakersMark on our Family Forever contest, with winner families receiving $5,000 to help elevate their family reunions
Celebrating the women who lead, inspire, and make a difference every day ✨ Thank you to everyone who joined us for Women's Empowerment Night presented by @MakersMark!
co-founders Dhaval Adjodah and Owen He with a16z's Martin Casado on recursive self-improvement, and how to tell when it's real: A lot of RSI pitches are really just people using AI to build better AI. Tech has always worked that way. You needed computers to build chips. Steam engines got better once you could get coal faster. Dhaval and Owen's bar is higher. The model has to improve itself: its weights, its harness, even the prompt that tells it what to work on next. And the gains have to hold up when you count what they cost. They track everyone's experiment spend on a "bleeder board," and one engineer, the Viceroy of Variance, has the job of breaking their results. Over the past few months, they've started seeing early signs of their system getting better and cheaper at the same time. 0:55 Why most RSI pitches miss 2:25 Optimizer vs. optimizee 5:10 The RSI equation: performance over cost 6:50 Why a closed loop does not mean takeoff 8:40 Humans are agents inside the system too 9:25 The denominator trap: progress divided by capital raised 11:40 Training GPT-2 for $100 13:40 Most RSI papers fail when replicated 16:40 Why you have to co-optimize 17:40 Why inference is the first problem 20:15 The agent rewrites its own prompt 22:20 "It's not a belief. It's happening." 25:00 Why they haven't published 27:50 Intelligence is a vector and Amdahl's law 29:45 The garden hose theory of RSI YouTube: @makermaker_ai @_dval_ @martin_casado
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