Name: NVIDIA Info Session & Tech Talk @ UC Berkeley
Start: 2020-01-23T17:30:00-08:00
End: 2020-01-23T19:30:00-08:00
Location: Wozniak Lounge

NVIDIA Info Session & Tech Talk @ UC Berkeley

NVIDIA

<H2><A HREF="https://nvidia.wd5.myworkdayjobs.com/en-US/UniversityJobs?source=schoolucberkeley" TARGET="_blank" TITLE="NVIDIA" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer"><STRONG>NVIDIA</STRONG></A></H2>
<H4>INFORMATION SESSION AND TECH TALKS</H4>
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<H4 CLASS="MsoNormal">Come join us for on Thursday, January 23, 2020 at UC Berkeley's Wozniak Lounge. Explore the future of AI computing in an engaging, informative talk with Dr. Ryan Prenger. One lucky winner will even walk away with an <A HREF="https://www.nvidia.com/en-us/geforce/graphics-cards/rtx-2080-super/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer"><SPAN>NVIDIA® GeForce® </SPAN><SPAN>RTX 2080 SUPER</SPAN><SPAN>™</SPAN></A>!</H4>
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<P CLASS="MsoNormal"><STRONG>When:</STRONG> January 23 (Thursday)</P>
<P CLASS="MsoNormal"><STRONG>Time:</STRONG> 5:30 p.m. – 7:30 p.m.</P>
<P CLASS="MsoNormal"><STRONG>Location:</STRONG> Wozniak Lounge (Soda Hall)</P>
<P CLASS="MsoNormal"><STRONG>Who it’s for:</STRONG> All UC Berkeley EECS students</P>
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<H4><STRONG>AGENDA</STRONG></H4>
<P CLASS="MsoNormal">5:30 p.m. – 5:45 p.m.     | Get acquainted, grab refreshments</P>
<P CLASS="MsoNormal">5:45 p.m. – 6:45 p.m.     | Dr. <SPAN>Ryan Prenger (</SPAN>Senior Deep Learning Researcher at NVIDIA)</P>
<P CLASS="MsoNormal">6:45 p.m. – 7:00 p.m.     | Info & Q&A for Internship/New College Graduate opportunities</P>
<P CLASS="MsoNormal">7:00 p.m. – 7:30 p.m.     | Raffle & mingling</P>
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<P CLASS="MsoNormal"><EM>Snacks and refreshments will be provided.</EM></P>
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<H4>SPEAKER INFORMATION</H4>
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<H4><STRONG>Dr. Ryan Prenger<BR>Senior Deep Learning Researcher at NVIDIA</STRONG></H4>
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<H4><STRONG></STRONG><STRONG>Applied Deep Learning Research at NVIDIA</STRONG></H4>
<P>Abstract: Ryan will be talking about the work going at NVIDIA in the Applied Deep Learning Research group, and how they’re using deep learning to solve real problems. This will include how they’re using deep learning to redefine graphics rendering, how they’re scaling up the world’s largest language models by distributing them across more than 500 GPUs, and how they’re using invertible neural networks to turn slow serial problems into fast parallel ones for speech synthesis.</P>
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<P CLASS="MsoNormal">Bio: During his physics PhD at UC Berkeley, Ryan started studying neuroscience and training neural networks. This was back in 2004, before they were cool. After graduating, Ryan spent 5 years doing machine learning on cyber-security problems at Lawrence Livermore National Lab...but he can’t talk about that. From 2014 to 2017, Ryan worked at Baidu where he worked on Deep Speech 1 and 2, doing speech recognition and NLP in both English and Mandarin, despite not speaking Mandarin. Since August 2017, Ryan has been working on deep learning for audio denoising, speech synthesis, and logic synthesis at NVIDIA. He also has excellent t-shirts.</P>
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<H3>About NVIDIA:</H3>
<P>NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU computing ignited the era of AI. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. Our life’s work is to amplify human imagination and intelligence. Make the choice to <A HREF="https://nvidia.wd5.myworkdayjobs.com/en-US/UniversityJobs?source=schoolucberkeley" TARGET="_blank" TITLE="join us" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">join us</A> today.</P>

Wozniak Lounge

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NVIDIA Info Session & Tech Talk @ UC Berkeley

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NVIDIA Info Session & Tech Talk @ UC Berkeley

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