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Women Leading The AI Industry: “It can be used by dangerous people to create danger and by responsible people to accelerate positive change” with Alexandra Shadrow, and Tyler Gallagher

In college was the first time I started to ask myself, “who made my clothes?” and “what are they made of?” The answers disturbed me from both an environmental and ethical standpoint, so I decided I was going to shop 100% pre-owned.

I set out to create a solution where I would be recommended the perfect selection (via AI), and where all sellers would have an equal playing field — where visibility was based on quality and accuracy rather than time spent on platform.

We are in the process of releasing our innovative “dating-app” shopping interface, which really exemplifies all of the machine learning that happens behind the scenes.

Scalable: AI technology improves over time which means that as we collect more data our models become better and increases the barriers to entry for competitors.

have a lot more money, technology and user data and so they can create a moat around themselves that smaller companies cannot cross.

For example if a woman is identified as plus size though she prefers regular sizes, will this impact her confidence?

As you know, there is an ongoing debate between prominent scientists, (personified as a debate between Elon Musk and Mark Zuckerberg,) about whether advanced AI has the future potential to pose a danger to humanity.

In sustainable fashion we have a saying: “clothes won’t change the world, the people who wear them will.” My position with AI is the same.

If that’s not clear enough — no I do not think it is a danger, but I think it can be used by dangerous people to create danger and by responsible people to accelerate positive change.

Transparency laws about the ways companies use data must be imposed so that consumers have a true choice of whether or not to be patrons.

Each week hundreds of thousands of gallons of water are saved, and tens of thousands of pounds of clothing are kept from landfills.

Accuracy in matches means less waste because the right buyer can then house each pre-owned item, diverting their spending from the production of new products and diverting the item from landfill.

Have real conversations with co-workers about closing the gender gap, post on social media, and bring it up at networking events.

“In life, you only get what you ask for.” Relovv currently has 1,000 volunteer interns and affiliates who produce content and promote the brand.

If we hadn’t created a program that asked people to volunteer we would have never grown on a low $1.00 CAC.

Regal Assets is an international alternative assets firm with offices in the United States, Canada, London and Dubai focused on helping private and institutional wealth procure alternative assets for their investment portfolios.

With offices in multiple countries, Regal Assets is uniquely positioned as an international leader in the alternative assets industry and was awarded the first ever crypto-commodities license by the DMCC in late 2017.

Regal Assets is currently the only firm in the world that holds a license to legally buy and sell cryptos within the Middle East and works closely with the DMCC to help evolve and grow the understanding and application of blockchain technology.

Emerging Memories And Artificial Intelligence

We had several interesting speakers talking about various types of artificial intelligence and the role that new non-volatile memories will play in both training AI models and implementing them in the field using inference engines.

He also explored a very tight coupling between processing and memory, especially with Spintronic devices that can combine memory and logic functions that can perform both memory read/write and AND/OR logic operations.

This technique can be applied for direct neural network training and involves forward inferences based upon previous training, back-propagation of errors from these inferences to correct the matrix of weights used for the inference step.

Sylvain Dubois from Crossbar (an exhibitor at the workshop) talked about using near-memory computing accelerators for faster machine learning using Crossbar’s RRAM technology in a highly parallel memory array.

As a demonstration of this approach the company built a USB stick with what the company calls its Crossbar XPU to show significant improvements in object look-up speed (OLUPS) compared to and ARM processor operating at much higher operating frequency as shown below.

Dr. Corcoran pointed out that going even further to create truly life-like images and better image analysis (for example for driver monitoring) will require considerable processing and memory resources.

My talk finished the day talking about how emerging memories enable the AI market and projections for the resulting growth of emerging memories, such as MRAM and 3D XPoint, based upon a recently finished report on emerging memory growth.

If you are in the San Francisco Bay Area and are interested in learning more about the role of emerging non-volatile memories in artificial intelligence application and in networking with storage professionals, storage users and other interesting parties you might be interested in the Storage Valley Supper Club meeting, September 18, 2019 at Techcode.

The 2019 Stanford Workshop gave lots of insights on how various AI operate and how new memory technologies can be integrated into AI systems and memory/storage architectures to enable the next generation of data center and client applications.

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Artificial Intelligence in Radiology

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