Laura
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- Goldman Sachs1h 23m
Watch Live: 2020 Goldman Sachs Gives Analyst Impact Fund Finals
Eric Lane, Julian Salisbury, David Solomon, Stephen Scher, John Rogers, Asahi Pompei, Anne Black, Mabel, Abe, Olu, Anna Skoglund, Chris Johnson, Kim Posnett, Priyanka Pasi, Gauri, Mina Flynn, Jennifer Yume, Matthew, Av, Anshul Sugabi, Ruchand, Prashant, Khalil Razi, Carlos, Earl Hunt, Sarah Condon, Laura, Kia Williams, Arthur, Carrie Halio, Bridget Martinez, Alistair
The 2020 Analyst Impact Fund Finals engaged 733 Goldman Sachs analysts to evaluate non-profit proposals addressing critical global challenges like healthcare, climate change, and equity through a hybrid virtual and in-person format. Six finalist teams pitched their organizations, with Serum winning the $250,000 first-prize grant and an additional $25,000 "fan favorite" award, while Black Girl Ventures and CHaN secured second and third place respectively. This fifth annual competition has facilitated over $2.1 million in total grants to 69 nonprofits since its inception, serving as a key mechanism for junior talent to drive philanthropic impact and cross-office collaboration.
- Jane Street1h 18m
Lindsey Kuper: Abstractions for Expressive, Efficient Parallel and Distributed Computing
Lindsey Kuper, Ron, Laura, Kunle Olokutun, Asante Toney, Neil Conway, Peter Alvaro, Carl, Nikki Vazou
The presentation outlines a unified framework for deterministic parallel computing that utilizes Lattice Variables (LVARs) and Conflict-Free Replicated Data Types to ensure correct distributed executions while enabling high-performance acceleration in Julia and Python through non-invasive domain-specific languages. Complementing these runtime systems, the speaker details a formal verification approach for safety-critical neural networks that employs lazy ReLU splitting within SMT solvers to manage the exponential complexity of non-linear activations. Future research aims to democratize solver development by integrating lattice theories directly into SMT architectures and verifying LVAR constraints through advanced type systems.