Lifeboat Foundation

I still see AI as a supportive solution to handle more standardized operations still requiring oversight by people. As long as hacking exist the level of allowing systems to own and manage processes without people oversight is not going to happen until hacking is resolved.

It is predicted that the use of AI in health care will grow tenfold in the next five years, and not all of the medical applications will be for doctors. The technology is accelerating drug discovery, increasing compliance and even tracking changes in markers of ‘youthfulness,’ empowering people to better manage their own health.

Agree with Zuckerberg it’s a bad move on all tech fronts to ignore the developing countries and other less connected areas of 1st & 2nd world countries which is usually lower income areas. Also, VR & AR are going to be the experience that is going to be the platform where applications (including enterprise apps & platform services such as BI, etc.) are going to be and want to be in order to make the user experience and productivity more effective.

Facebook chief Mark Zuckerberg has warned the mobile industry not to ignore the unconnected, as he laid out plans use artificial intelligence to help bring remote parts of the world online.

The enigmatic CEO used a keynote speech at Mobile World Congress in Barcelona to express “disappointment” that the mobile industry was focused on areas like 5G rather than connecting those lacking in connectivity.

Continue reading “Zuckerberg warns on mobile future” »

Still not sold on the whole robotics at this point; still not at the level where it needs from a multi-functional capability state plus still too jerky and most are more like a CPU on wheels.

TORONTO, ON –(Marketwired — February 23, 2016) — ­­ Astro Boy may be a fictional character, but Pepper the Robot is its real-­world incarnation. Pepper –­­ the world’s first humanoid robot –­­ will join exhibitors like MasterCard, Fluid, Vizera and Eyris, as they interact with industry experts as part of The Retail Collective Lab, sponsored by MasterCard, at this year’s Dx3 Trade Show and Conference.

MOFFETT FIELD, California — Within five years, companies could begin in-orbit manufacturing and assembly of communications satellite reflectors or other large structures, according to Made in Space, the Silicon Valley startup that sent the first 3D printer to the International Space Station in 2014.

As Made in Space prepares to send a second 3D printer into orbit, the company is beginning work with Northrop Grumman and Oceaneering Space Systems on Archinaut, an ambitious effort to build a 3D printer equipped with a robotic arm that the team plans to install in an external space station pod, under a two-year, $20 million NASA contract. The project will culminate in 2018 with an on-orbit demonstration of Archinaut’s ability to additively manufacture and assemble a large, complex structure, said Andrew Rush, Made in Space president.

NASA’s selected the Archinaut project, officially known as Versatile In-Space Robotic Precision Manufacturing and Assembly System, as part of its Tipping Points campaign, which funds demonstrations of space-related technologies on the verge of offering significant payoffs for government and commercial applications. Archinaut was one of three projects NASA selected in November that focus on robotic manufacturing and assembly of spacecraft and structures in orbit.

Continue reading “NASA, Made in Space think big with Archinaut, a robotic 3D printing demo bound for ISS” »

The clang of metal, breathtaking speed and tons of adrenaline! Watch a futuristic video of battle robots in ultimate fighting in Moscow. The iron warriors are clashing without mercy for the right to face foreign competitors.

The Russian capital is holding an international competition ‘Bronebot-2016’ for battle robots, February 21–23. “Attention! The show contains scenes of total robot carnage,” the banner reads.

Brings a lot of possibilities.

Robotic reasoning.

Paper demonstrates autonomous underwater vehicles can be pre-programmed to make independent decisions.

Google Brain software engineer Quoc Le shares his belief that artificial intelligence and deep learning will shape the future of the world.

The “unbeatable” bot still has much to learn from human players.

Whether in the brain or in code, neural networks are shaping up to be one of the most critical areas of research in both neuroscience and computer science. An increasing amount of attention, funding, and development has been pushed toward technologies that mimic the brain in both hardware and software to create more efficient, high performance systems capable of advanced, fast learning.

One aspect of all the efforts toward more scalable, efficient, and practical neural networks and deep learning frameworks we have been tracking here at The Next Platform is how such systems might be implemented in research and enterprise over the next ten years. One of the missing elements, at least based on the conversations that make their way into various pieces here, for such eventual end users is reducing the complexity of the training process for neural networks to make them more practically useful–and without all of the computational overhead and specialized systems training requires now. Crucial then, is a whittling down of how neural networks are trained and implemented. And not surprisingly, the key answers lie in the brain, and specifically, functions in the brain and how it “trains” its own network that are still not completely understood, even by top neuroscientists.

In many senses, neural networks, cognitive hardware and software, and advances in new chip architectures are shaping up to be the next important platform. But there are still some fundamental gaps in knowledge about our own brains versus what has been developed in software to mimic them that are holding research at bay. Accordingly, the Intelligence Advanced Research Projects Activity (IARPA) in the U.S. is getting behind an effort spearheaded by Tai Sing Lee, a computer science professor at Carnegie Mellon University’s Center for the Neural Basis of Cognition, and researchers at Johns Hopkins University, among others, to make new connections between the brain’s neural function and how those same processes might map to neural networks and other computational frameworks. The project called the Machine Intelligence from Cortical Networks (MICRONS).

Continue reading “IARPA Project Targets Hidden Algorithms of the Brain” »