Lifeboat Foundation

If simulating the brain is proving tricky, why don’t we try decoding it?

“There’s a good reason the first flying machines weren’t mechanical bats: people tried that, and they were terrible.” — Dan Robitzski

In the current AI Spring, many people and corporations are betting big that the capabilities of deep learning algorithms will continue to improve as the algorithms are fed more data. Their faith is backed by the miracles performed by such algorithms: they can see, listen and do a thousand other things that were previously considered too difficult for AI.

Continue reading “The Cipher of Intelligence” »

In this video, we’ll be discussing big data – more specifically, what big data is, the exponential rate of growth of data, how we can utilize the vast quantities of data being generated as well as the implications of linked data on big data.

[0:30–7:50] — Starting off we’ll look at, how data has been used as a tool from the origins of human evolution, starting at the hunter-gatherer age and leading up to the present information age. Afterwards, we’ll look into many statistics demonstrating the exponential rate of growth and future growth of data.

[7:50–18:55] — Following that we’ll discuss, what exactly big data is and delving deeper into the types of data, structured and unstructured and how they will be analyzed both by humans and machine learning (AI).

James Hughes : “Great convo with Yuval Harari, touching on algorithmic governance, the perils of being a big thinker when democracy is under attack, the need for transnational governance, the threats of automation to the developing world, the practical details of UBI, and a lot more.”

In this episode of the Waking Up podcast, Sam Harris speaks with Yuval Noah Harari about his new book 21 Lessons for the 21st Century. They discuss the importance of meditation for his intellectual life, the primacy of stories, the need to revise our fundamental assumptions about human civilization, the threats to liberal democracy, a world without work, universal basic income, the virtues of nationalism, the implications of AI and automation, and other topics.

Continue reading “Waking Up with Sam Harris — #138 — The Edge of Humanity (with Yuval Noah Harari)” »

This video is the second in a two-part series discussing big data. In this video, we’ll be discussing how we can utilize the vast quantities of data being generated as well as the implications of linked data on big data.

[0:33–4:43] — Starting off we’ll look at, what exactly big data is and delving deeper into the types of data, structured and unstructured and how they will be analyzed both by humans and machine learning (AI).

[4:43–11:37] — Following that we’ll discuss, how this data will be put to use and the next evolution of data, linked data, and how it will change the world and the web!

Continue reading “The Evolution of Data (Linked Data) Needed For AI” »

Recently, there has been an explosion of interest in applying artificial intelligence (AI) to medicine. Whether explicitly or implicitly, much of this interest has centered on using AI to automate decision-making tasks that are currently done by physicians. This includes two seminal papers in the Journal of the American Medical Association demonstrating that AI-based algorithms have similar or higher accuracy than physicians: one in diagnostic assessment of metastatic breast cancer compared to pathologists and the other in detecting diabetic retinopathy compared to ophthalmologists.

While promising, these applications of AI in medicine raise a number of novel regulatory and policy issues around efficacy, safety, health workforce, and payment. They have also triggered concerns from the medical and patient communities about AI replacing doctors. And, except in narrow domains of practice, general AI systems may fall far short of the hype.

We posit that the applications of AI to “augment” physicians may be more realistic and broader reaching than those that portend to replace existing health care services. In particular, with the right support from policy makers, physicians, patients, and the technology community, we see opportunities for AI to be a solution for—rather than a contributor to—burnout among physicians and achieving the quadruple aim of improving health, enhancing the experience of care, reducing cost, and attaining joy in work for health professionals.

Alphabet’s healthcare and tech company Verily will use a sex-sorting computer vision algorithm to help Singapore battle mosquitoes.

Machine-learning algorithms are helping to unravel the quantum behaviour of a type of superconductor that has baffled physicists for decades.

Researchers used artificial intelligence to spot hidden order in images of a bizarre state in high-temperature superconductors.

Don’t know your machine learning from your evolutionary algorithms? Our handy A.I. buzzword guide is here to help.

This video is the first in a two-part series discussing big data. In this video, we’ll be discussing the importance of data and the role, it has played in advancing humankind as well as the exponential rate of growth of data.

[0:29–4:19] — Starting off we’ll look at, how data has been used as a tool from the origins of human evolution, starting at the hunter-gatherer age and leading up to the present information age.

[4:19–7:48] — Following that we’ll discuss, the many statistics demonstrating the exponential rate of growth and future growth of data.

Continue reading “The Exponential Growth of Data” »