Lifeboat Foundation

For the first time ever, a single flexible fiber no bigger than a human hair has successfully delivered a combination of optical, electrical, and chemical signals back and forth into the brain, putting into practice an idea first proposed two years ago. With some tweaking to further improve its biocompatibility, the new approach could provide a dramatically improved way to learn about the functions and interconnections of different brain regions.

The new fibers were developed through a collaboration among material scientists, chemists, biologists, and other specialists. The results are reported in the journal Nature Neuroscience, in a paper by Seongjun Park, an MIT graduate student; Polina Anikeeva, the Class of 1942 Career Development Professor in the Department of Materials Science and Engineering; Yoel Fink, a professor in the departments of Materials Science and Engineering, and Electrical Engineering and Computer Science; Gloria Choi, the Samuel A. Goldblith Career Development Professor in the Department of Brain and Cognitive Sciences, and 10 others at MIT and elsewhere.

The fibers are designed to mimic the softness and flexibility of brain tissue. This could make it possible to leave implants in place and have them retain their functions over much longer periods than is currently possible with typical stiff, metallic fibers, thus enabling much more extensive data collection. For example, in tests with lab mice, the researchers were able to inject viral vectors that carried genes called opsins, which sensitize neurons to light, through one of two fluid channels in the fiber. They waited for the opsins to take effect, then sent a pulse of light through the optical waveguide in the center, and recorded the resulting neuronal activity, using six electrodes to pinpoint specific reactions. All of this was done through a single flexible fiber just 200 micrometers across — comparable to the width of a human hair.

Artificial intelligence has reached peak hype. News outlets report that companies have replaced workers with IBM Watson and that algorithms are beating doctors at diagnoses. New AI startups pop up everyday, claiming to solve all your personal and business problems with machine learning.

Ordinary objects like juicers and Wi-Fi routers suddenly advertise themselves as “powered by AI.” Not only can smart standing desks remember your height settings, they can also order you lunch.

Much of the AI hubbub is generated by reporters who’ve never trained a neural network and by startups or those hoping to be acqui-hired for engineering talent despite not having solved any real business problems. No wonder there are so many misconceptions about what AI can and cannot do.

Continue reading “Understanding the limits of deep learning” »

Thanks for your interest!

Thanks to SAP Italia for making this video available, the original video is at https://youtu.be/PLS5wGAM3R8 You can download all my slides at www.gerdcloud.net; direct link to the slides used here is gerd.fm/sapitaliagerd

Continue reading “Futurist Speaker Gerd Leonhard at SAP Executive Summit 2017: Exponential technological (r)evolutions” »

What’s Watson working on today? He’s working with 1–800-Flowers to help find the perfect bouquet out of trillions of combinations. He’s working with the New York Genome Center to help doctors find treatments as personal as DNA. And he’s working with Sesame Street to make education as unique as every child.

Working with Watson, we can outthink anything. http://ibm.co/2bTJ7BY

Artificial intelligence, machine learning, evolving algorithms — we know it can get confusing. So let’s take a look at AI and what it means.

Watson, IBM’s cognitive computing system, exhibited phenomenal capabilities while competing on the television quiz show Jeopardy! in February 2011. The grand debut and triumph at Jeopardy! drew the world’s attention to Watson, which achieved a milestone in artificial intelligence (AI) while denoting a new era in computing – a cognitive era. Six years later, Watson today seems to be everywhere, revolutionizing diverse industries while building IBM’s cognitive future.

Cognitive Computing Explained

The future of technology is radically different from the systems that have dominated the global IT industry for decades. New generation technologies are broadly grouped together using the terms AI and cognitive technologies. At IBM, these advanced techs are referred to as cognitive and defined as “systems that learn at scale, reason with purpose and interact with humans naturally.”

Continue reading “IBM And Watson: Ushering In A New Age Of Computing” »

It’s been almost two years since Google liquefied our brains with its Deep Dream neural network and the nightmare-inducing images the technology created. But now, a team from the University of California, Berkeley is sort of doing the opposite —emphasis on “sort of.”

Google announced that it will be turning to machine learning to help it identify objectionable content, which caused over 250 brands to freeze their ad spend with YouTube and Google display.

In a statement provided to Business Insider, Google said the new tools will “help enforce our revised policies and identify content that may be objectionable to advertisers.”

Google said it would also be offering brand safety reporting by working with third party partners, like Integral Ad Science and comScore.

Continue reading “Google will use artificial intelligence to identify objectionable content and sell ‘brand-safe’ ads” »

President Trump has vowed to bring back American manufacturing jobs. But the evidence is overwhelming that foreign-made robots are the future.