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WildFaces announces US$20 million grant for Ethical AI

Like any technology, AI can be used for good or evil and indeed there is a deep concern in society about the possibility of this powerful new technology being misused. Being deeply committed to the ethical use of AI, WildFaces recently announced a $20 million grant to support organizations that wished to implement projects that ostensibly promoted the positive use of AI.

In announcing the Grant, WildFaces' co-founders Ivy Li and Dr Rustom Kanga said, “As we approach our quarter century in the Multi-sensory AI business we want to ensure that we help people understand how AI can be used to help humanity”.

The Grant can be used to help organizations that want to use AI in a positive way to help society. The first 3 grants have already been allocated for:

✓ An organization that helps to find lost and stolen children. In 
   this project the system will help to find children in a crowd 
   who may be separated from their guardians in real time thus 
   reducing the ensuing trauma and stress for both the children 
   and the parents.

✓ A local government organization that is attempting to keep 
   its township clean by detecting rubbish dumping. The 
   variations in multiple forms, ways and places where rubbish 
   is dumped meant that there was no large dataset for training 
   an AI system. They are going to use WildFaces' unique 
   Intuitive AI technology which requires NO Deep Learning 
   and No GPUs.

✓ A local government organization that wants to keep its citizens safe by managing crowds 
   during events. They want to make sure they keep known hooligans away while protecting 
   the privacy of their citizens making use of their existing cameras infrastructure.

Powering Ethical AI for a Safer, Cleaner, Kinder World

So far, all these grants have been given to organizations in Asia but there is no geographic restriction as long as the organization can demonstrate that the project will promote Ethical AI and that it cannot be fulfilled with their existing capabilities and resources.

Of course there are rules and terms for eligibility and use of the grants. Organizations that feel they have a worthy project can apply to The WildFaces Foundation: http://wildfaces.ai/contact

WildFaces and Lenovo cement a deep partnership

Lenovo, a leading manufacturer of computers of all varieties from edge computers to large servers has announced its “CrossWave Program” under which it will offer solutions from key ISV partners through its own price book. WildFaces is honoured to be the only partner included in this program that offers Multi-sensory AI solutions (video, sound and smell) and the only one headquartered outside the USA (as all of you would know we are an Australian company).

Lenovo’s customers will get the benefit of their robust engineering, lower lifetime costs and their capability to provide high quality support around the world. This combined with the unique and comprehensive capabilities of the WildFaces software will provide Lenovo customers with world-beating solutions.

Lenovo sales people will be able to offer their customers the entire range of WildFaces software – all 300+ applications for 30 different industries. These include autonomous response systems for very sophisticated customers but also a range of simple easy to implement applications which their channel partners can offer their smaller customers.

All Lenovo’s customers can now get the total hardware-software solution with the same superior warranty and ongoing support that they have come to expect from Lenovo.

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About WildFaces:

WildFaces’ patented “On-The-Move” Artificial Intelligence (AI) based analytics system, WildAI, provides video, sound and smell analytics from moving sensors/ cameras on drones, moving robots and body-worn cameras. Such systems have been implemented on numerous government and commercial sites worldwide.

Applications range from anonymized tracking (with privacy protection) and traffic congestion management to sound and smell analytics.

WildAI requires minimal training, is computing light (does not require GPUs) and can be deployed very quickly. It:

Operates in real-time even when the sensor is “On-the-move”.

Requires little data training – no labelling, no deep learning

Is infrastructure light – fewer cameras required

Is computation light

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