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Bernease Herman

Senior Data Scientist
WhyLabs.ai

Bernease Herman is a Sr. Data Scientist at WhyLabs, the AI Observability company, and a research scientist at the University of Washington eScience Institute. At WhyLabs, she is building model and data monitoring solutions using approximate statistics techniques. Earlier in her career, Bernease built ML-driven solutions for inventory planning at Amazon and conducted quantitative research at Morgan Stanley. Her academic research focuses on machine learning evaluation and interpretability with specialty on synthetic data and societal implications.

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Bernease Herman

Senior Data Scientist
WhyLabs.ai

Bernease Herman

Senior Data Scientist
WhyLabs.ai

Bernease Herman is a Sr. Data Scientist at WhyLabs, the AI Observability company, and a research scientist at the University of Washington eScience Institute. At WhyLabs, she is building model and data monitoring solutions using approximate statistics techniques. Earlier in her career, Bernease built ML-driven solutions for inventory planning at Amazon and conducted quantitative research at Morgan Stanley. Her academic research focuses on machine learning evaluation and interpretability with specialty on synthetic data and societal implications. Bernease serves as faculty for the University of Washington Master’s Program in Data Science program and as chair of the Rigorous Evaluation for AI Systems (REAIS) workshop series. She has published work in top machine learning conferences and workshops such as NeurIPS, ICLR, and FAccT. She is a PhD student at the University of Washington and holds a Bachelor’s degree in mathematics and statistics from the University of Michigan.

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Gregoire Grandchamp

CEO
NEXT beauty

Gregoire Grandchamp

CEO
NEXT beauty

Gregoire Grandchamp

CEO
NEXT beauty
 

Shawn Mcghee

President
Hollywood Feed

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Shawn Mcghee

President
Hollywood Feed

Shawn Mcghee

President
Hollywood Feed

 

Dr. Marcio Domingues

Consultant
R & D Crop Physiology

Dr. Marcio Domingues

Consultant
R & D Crop Physiology

Dr. Marcio Domingues

Consultant
R & D Crop Physiology
 
The Productivity Summit
31 Jan 2019
London, UK
Britain is in the midst of a productivity crisis. Analysis shows that output levels have barely risen since the last recession, and there is a long standing and now growing productivity gap between the UK and the likes of France and Germany. The Productivity Summit presents cross-industry case studies from UK businesses implementing productivity models and strategies, covering three main areas – systems and modelling, employee engagement and health and wellbeing. Living up to its name, The Productivity Summit offers an interactive and energetic programme intent on getting the most out of one day. Case studies from the UK’s leading brands include: How to measure productivityHow to actually implement flexible working and mental health programmes to drive productivityWhat a good productivity model looks likeHow to manage change internallyPractical steps to improve diversity and resulting impace on business productivityHow to improve non-financial compensation and benefits to compete for talentHow to prepare for Brexit and the impact it's going to have on productivityUsing internal champions to build productivity into company culture"I am currently exploring a number of ways to introduce further flexibility within our workplace...The Productivity Summit agenda is perfect for my areas of interest!" Andy Stoker, Director - Organisational Culture & Transformation, Cisco
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AI Hardware Summit Asia
4-5 Jun 2019
HILTON BEIJING CAPITAL AIRPORT, BEIJING, 100621
The AI Hardware Summit is the first and only conference dedicated solely to the ecosystem developing hardware accelerators for neural networks and computer vision.Join 200+ senior technology leaders from AI chip start-ups, semiconductor companies, system vendors/OEMs, data centers, end users, financial services, investors and fund managers, to build a comprehensive architectural roadmap of the emerging AI chip market.Take advantage of unique networking opportunities to meet key industry leaders 1-2-1, whilst also exploring:  Innovations and Optimizations of High-Performance Chip Architectures: GPUs, ASICs & TPUs, FPGAs…Alternative Approaches: hybrid digital/analog computing, neuromorphics & neuromemristive systems, quantum computing.The Role of Software: assistance software, software frameworks, ecosystems, and applications. Generating user-friendly native code and linking open source machine learning frameworks like TensorFlow & Caffe.Industry Developments: Start-up & Corporate R&D, Venture Capital and Corporate Venture Capital investment trends, strategic acquisitions & partnerships.Forecasts predict that the AI (chipsets) market is expected to grow from USD 7.06 Billion in 2018 to USD 59.26 Billion by 2025, at a CAGR of 35.5% from 2018 to 2025 (Business Wire, 2018), the chip market is no longer standing still. As we approach a paradigm shift in computing, there is little doubt that a combination of the processing units currently in development will accelerate AI research and development, far beyond the capabilities of current platforms.  There is need for sharing knowledge on the best way to turn this shift into an opportunity and roadmap the future ahead.
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