Lifeboat Foundation

AI designed badly will indeed have detrimental impact for decades to come. We do have a crisis in AI world. Where are the women? With AI today, we’re developing the underlying foundation for AI in the future. And, without women in a large half of that development; we run a huge risk of failure by designing a foundation that only connects with maybe 40% of the world. That means 60% of missed opportunity is left on the table plus lets face it women totally understands how (better than anyone else) to incorporate feelings & thoughts together.

This post has been updated.

There’s no doubt Stephen Hawking is a smart guy. But the world-famous theoretical physicist recently declared that women leave him stumped.

Continue reading “Inside the surprisingly sexist world of artificial intelligence” »

Dubai is definitely on my bucket list to see in my lifetime.

Dubai’s museum of Future zooms you into world of artificial intelligence.

“The future belongs to those who can imagine it, design it, and execute it. It isn’t something you await, but rather create.”

Continue reading “Dubai Museum of Future: The future is bright, it’s here!” »

In celebration to the Chinese New Year — here are the dancing bot dance team.

Here’s an idea for next year’s Super Bowl halftime show.

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Here is a concept to think about when we’re 20 or 30 years into the future — imagine a world where humans and all living things in it are truly Singular, and the new AI & Humanoid robots are alive and well. Will AI (including Robots) ever need therapy, will AI ever get stressed out or have panic attacks, will any humans know what AI is thinking once we give AI more independence?

I ask these questions because as we enhance and evolve AI to be like humans and interpret and process emotions, feelings, and interact like humans; will AI expeience fully the struggles of everyday life like some humans do? And, when needs counseling or therapy will they go to another AI or will they see a human therapist?

As we evolve AI; we must look at the full longer picture around AI including how human do we really wish to make AI.

Continue reading “What does artificial intelligence see when it watches political ads?” »

Someday this could happen as well as US congress, Supreme Court, the UN, Nato, IAEA, WTO, World Bank, etc.

IBM’s AI researchers seem to favour recreational drug use, free university education and free healthcare.

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Stanford University PhD candidate, Song Han, who works under advisor and networking pioneer, Dr. Bill Dally, responded in a most soft-spoken and thoughtful way to the question of whether the coupled software and hardware architecture he developed might change the world.

In fact, instead of answering the question directly, he pointed to the range of applications, both in the present and future, that will be driven by near real-time inference for complex deep neural networks—all a roundabout way of showing not just why what he is working toward is revolutionary, but why the missing pieces he is filling in have kept neural network-fed services at a relative constant.

There is one large barrier to that future Han considers imminent—one pushed by an existing range of neural network-driven applications powering all aspects of the consumer economy and, over time, the enterprise. And it’s less broadly technical than it is efficiency-driven. After all, considering the mode of service delivery of these applications, often lightweight, power-aware devices, how much computation can be effectively packed into the memory of such devices—and at what cost to battery life or overall power? Devices aside, these same concerns, at a grander level of scale, are even more pertinent at the datacenter where some bulk of the inference is handled.

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Meet Otto, the robot that draws.

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Autonomous cars have finally arrived, and they’re pretty remarkable. Here’s a look at the best on the line.

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What if computers could recognize objects as well as the human brain could? Electrical engineers at the University of California, San Diego have taken an important step toward that goal by developing a pedestrian detection system that performs in near real-time (2−4 frames per second) and with higher accuracy (close to half the error) compared to existing systems. The technology, which incorporates deep learning models, could be used in “smart” vehicles, robotics and image and video search systems.

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