Categories
Uncategorized

Grace Hopper PitcHer Contest -2018

IMG_2935

Yesterday I attended Grace Hopper’s inaugural PitcHer contest.  The goal of this pitch competition is to support, encourage, and provide new funding opportunities to women entrepreneurs. The top ten finalist competed for a grand total of $65,000.  I was elated to find that the first place prize went to my personal favorite, Shakeia Kegler.  Her business idea accompanied by her amazing stage presence sealed the deal! After chatting with her at the end of the event it was clear that she is a brilliant and down to earth woman with much to offer to the startup community. I was lucky enough to get a selfie with her at the end of the event! I’d love to invite her to Startup Milwaukee Week this year or next! Below are bios/business summaries of the winners.

 Shakeia Kegler – First Place!

Shakeia Kegler is from Saint Petersburg, Florida, and is the eldest of five girls. After graduating from high school in 2011, she joined the U.S. Navy. While enlisted, she gained experience in purchasing, compliance, and quality assurance while earning a bachelor’s degree in business management and her Lean Six Sigma Certifications.

After her honorable discharge, Shakeia worked as a compliance and contract specialist in the government, contracting department of a pharmaceutical company. Her experience in both the Navy and government led her to found GovLia in 2017. GovLia is a cloud-based platform that simplifies state and local government procurement processes to help increase small business participation in order to foster economic opportunity and growth for diverse companies and communities.

Hannah Meyer – Second Place

As COO of Pie for Providers, Hannah builds tools that aim to measurably and significantly strengthen small childcare businesses and empower the entrepreneurs that operate them. She is committed to not only building a profitable and scalable business, but doing so in a way that leads to better outcomes for women business owners, parents, children, and their communities.

Hannah holds an MBA from the University of Chicago Booth School of Business, and was awarded the Tarrson Fellowship for social entrepreneurs by the University of Chicago. She was also a Summer Associate at Ashoka in the Social Financial Services Department. Prior to coming to the University of Chicago, Hannah earned an MPPA from Northwestern University.

Charu Sharma – Third Place

Charu Sharma is the Founder & CEO of NextPlay.ai. While working at LinkedIn, Charu started a mentorship program for women at the company as a passion project. This eventually inspired her to start NextPlay and to create meaningful mentorship relationships, especially for women and underrepresented minorities. NextPlay’s investors and advisors include 500 Startups, LinkedIn’s SVP Engineering, Techcrunch’s former CEO, and Microsoft’s former Chief Design Officer.

Companies like Square, Lyft, Asurion, and Splunk use the NextPlay mobile app to build sticky and measurable mentorship programs. After six months of using NextPlay’s app, mentees felt that their preparedness to achieve their goals at their companies had doubled, and mentors reported that they significantly developed their critical leadership and coaching skills. Collectively, the number of employees who strongly recommended working for their companies increased by 25%.

Charu previously built two startups. She has educated one million women on how to start their own businesses through her nonprofit, books, and documentary film “Go Against the Flow.”

Samantha J. Letscher – Audience Favorite

Sam Letscher is the Co-founder and CEO of Bossy, a platform that connects feminist consumers with women-owned businesses to drive revenue to women entrepreneurs. She launched Bossy in Chicago in the spring of 2017 while pursuing her bachelor’ degree in Integrated Engineering Studies at Northwestern University.

Sam is inspired by products, services, experiences, brands, and workplaces built by women, for women, and from which women profit. She is now a recent college graduate with a bachelor’s degree in human-centered design and entrepreneurship.

Sam lives in Chicago where she is building and bootstrapping Bossy while working part-time in local politics. She strives to always stay curious and optimistic.

https://ghc.anitab.org/2018-pitcher/2018-finalists/

Categories
Uncategorized

Grace Hopper 2018 – Training generative adversarial networks: A challenge?

Our-text-conditional-convolutional-GAN-architecture-Text-encoding-pht-is-used-by-bothToday I had the pleasure of attending a very interesting workshop on generative adversarial networks. The goal of the workshop was to teach attendees about deep learning and Generative Adversarial Networks (GANS).  In the lab we used PyTorch, an open source deep learning framework, used to demonstrate and explore this type of neural network architecture. The lab was comprised of two major parts an introduction to both PyTorch and GANs followed by text-to-image generation.

The first part of the lab began by importing torch modules, creating a simple linear transformation model creating a loss function to understand the difference between our model and the ground truth.

Next we ran our model on a GPU! Earlier in the session we learned that GPUs work well for deep learning because they are inherently parallel.
With GPUs, trained neural networks can occur in minutes.

We then began to focus more on GANs. The facilitators of the workshop shared that GANs are getting widespread attention in the deep learning community for their image generation and style transfer capabilities.
This deep learning technique uses two neural networks in a adversarial way to complete its objective.

One network is called the generator and the other the discriminator. The discriminator network is trained with a dataset comprised of real data and output from the generator network, and its objective is to discriminate between the two. The generator network’s objective is to fool the discriminator into classifying its output as real data. While training the generator is updated to generate data that mimics the real data and fool the discriminator.

In this part of the lab attendees were tasked to :

  • Feed data into PyTorch using Numpy
  • Create a multi-layer network
  • Configure the generator and discriminator network
    • Learn how to update the generator network

The second part of the lab  we built upon the popular Deep Convolution Generative Adversarial Network (DCGAN)  to enable text to image generation. This part of the lab was based on the paper Generative Adversarial Text to Image Synthesis by Reed et, al.  Captions of images were encoded and concatenated with the input noise vector before being propagated to the generator. Then the encoded caption was concatenated again with a feature map in the discriminator network after the fourth leaky Rectified Linear Unit (ReLU) layer.The goal of the second half of the lab was to create a text to image model by using the GAN+CLS technique.

We demonstrated the capability of our model to generate plausible images of pizzas and broccoli from detailed text descriptions/captions. While this was just a case for learning purposes its clear that there are many powerful applications to this deep learning technique.

Categories
Uncategorized

Don't Just Consume Technology.. Produce it.

Its important to not only be consumers of technology but producers as well.

“A new study released Friday sheds light on this issue. The State of Black America 2018, a report published annually by the National Urban League, compares how black and white people fare in a number of areas, including housing, economics, education, social justice, and civic engagement.

This year’s report pays particular attention to black Americans’ access to jobs in the tech industry and STEM (science, technology, engineering, and mathematics) fields. The study reveals that while black people are one of the racial groups most likely to use smartphones and have created thriving communities on platforms like Twitter, those high rates of usage haven’t translated into employment.”

https://www.vox.com/technology/2018/5/4/17318522/state-of-black-america-2018-national-urban-league-silicon-valley-race

Categories
Uncategorized

30 and Under

Silicon Valley is home to some of the hottest venture capital firms worldwide. In the valley, the stakes are high. To be a successful investor, you need a keen business sense and attention to detail, a forward-thinking outlook, and a strategic eye for investment. 135 more words

via 30 AND UNDER: Rising stars in Silicon Valley tech who find hot startup deals and manage millions of dollars — Tech Insider