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[Em]Powering the Future: Transforming Ideas into Reality

This event is organized by MIT Industrial Liaison Program (MIT ILP) with special discounts for friends of MIT CSAIL and complimentary passes for CSAIL Alliances members.

Visit the official event page for full event details.

Save 70% with code ILP70CSAIL at checkout. 
CSAIL Alliances Members, contact your CRC for a fully complimentary pass.

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The Quant-essential Qualities: Insider Insights for Thriving in Algorithmic Trading

Abstract: The world of quantitative trading is notoriously siloed, secretive, and intensely competitive. In this talk, Hanna and Dan will offer an insider's perspective on quant trading, sharing insights from our firm, and outline the key qualities you can cultivate to excel in the industry.

 

Daniel Goldbach, Quantitative Developer

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CSAIL Alliances & FinTechAI@CSAIL Board Member Royal Bank of Canada (RBC) Borealis AI Group will be at CSAIL on 9/22 in Kiva to deliver a technical talk from Dr. Greg Mori as well as connect with interested students for job opportunities. 

Talk Title: Foundation Model Challenges and Opportunities in Financial Services

Monday 9/22 in Kiva 32-G449 12-1pm EST.  Food will be served so please register for accurate food order!

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A new software and hardware toolkit called SustainaPrint can help users strategically combine strong and weak filaments to achieve the best of both worlds. Instead of printing an entire object with high-performance plastic, the system analyzes a model, predicts where the object is most likely to experience stress, and reinforces those zones with stronger material (Credits: Alex Shipps/MIT CSAIL, using assets from Pixabay and the researchers).
CSAIL article

3D printing has come a long way since its invention in 1983 by Chuck Hull, who pioneered stereolithography, a technique that solidifies liquid resin into solid objects using ultraviolet lasers. Over the decades, 3D printers have evolved from experimental curiosities into tools capable of producing everything from custom prosthetics to complex food designs, architectural models, and even functioning human organs. 

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alt="A new study by MIT researchers shows the first method for machine learning with symmetry that is provably efficient in terms of both the amount of computation and data needed (Credits: iStock, MIT News)."
CSAIL article

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science parlance, the molecule is “symmetric,” meaning the fundamental structure of that molecule remains the same if it undergoes certain transformations, like rotation.