First model release supporting biometric data privacy; AI vs Dog Poop; What’s wrong with “explainable A.I."?

Major announcements made at NVIDIA GTC 2022

1. NVIDIA Hopper H100 Systems ‘transform’ AI?
2. Omniverse expands to the clouds?
3. Platform approach has created sustainable differentiation?
4. Accelerated digital twins platform
5. AI Enterprise 2.0 is now full stack??

The top layer is a set of pre-built AI systems to address specific use cases. Maxine is the company’s video AI system, Clara is designed for healthcare, Drive for the auto industry and Isaac is its simulator.?Check it out here

[FastCompany]? Google wants to use AI to cut the maternal mortality rate by half: They will record scans from an ultrasound wand as it glides over a pregnant woman’s stomach, and then analyze those images for potential fetal abnormalities or other signals that something is wrong.

[USC] Towards Acing the Turing Test: A Blueprint for Future AI and Robots that Learn Like Living Things: A DARPA-supported multi-institution team to outline how the machines of the future can achieve lifelong learning, just like humans and other animals.

[BusinessWire] Global Personal Artificial Intelligence and Robotics Market Report 2022-2027: AI and Robot Type, Components, Devices, and Solutions Analysis & Forecasts

[VB] Getty Images launches first model release supporting biometric data privacy in AI: While the laws in this area are still evolving, developers should begin with collecting data from legitimate sources and obtaining authorization for its intended use

[Haaretz]?AI vs Dog Poop: ‘Black Mirror’ as Town Eyes Autonomous Enforcement: A central Israeli city wants to buy an artificial intelligence system to help identify citizens who don’t clean up after their dogs or drive recklessly

[NYTimes]?How Native Americans Are Trying to Debug A.I.’s Biases: Data on Native communities are not at the levels needed for accuracy in A.I.-driven tools. A group is trying to solve that problem.

[MIT Sloan]?What’s wrong with “explainable A.I.”: In the past few years, companies selling A.I. software have increasingly looked for ways to offer some insight into how A.I. algorithms reach a decision.

[HBR] Overcoming the C-Suite’s Distrust of AI: Data-based decisions by AI are almost always based on probabilities (probabilistic versus deterministic). Because of this, there is always a degree of uncertainty when AI delivers a decision.

[ArXiv]? TinyMLOps: Operational Challenges for Widespread Edge AI Adoption: Deploying machine learning applications on edge devices can bring clear benefits such as improved reliability, latency, and privacy but it also introduces its own set of challenges.

This competition is a fast-paced simulation of a real-world project. Teams are to work collaboratively on a problem to provide a set of deliverables within a short timeframe. Don't miss this opportunity to make an impact,?register here

[??]? Fascinating how the human brain works and can be easily deceived

[??] Ants helped us to build Driverless cars!

[??]? Understanding the Fourier transform through a visualization

[??] Give yourself some credit.

For any collaboration inquiries, email me at [email protected]

Have a great weekend, see you next week. Steve