The robots are coming
The transport companies are rapidly exploring a wide range of other next generation technologies in the pursuit of digital transformation. The most popular are machine learning (37 per cent), robotics (37 per cent) and 3D printing (29 per cent).
The robots are coming, like it or not. I can certainly see why people are spooked by this, I am too. But they are fascinating at the same time. Just 25-30 years and after 2050 there won’t be any difference between a real person walking around and a robot, android. Let’s hope that way more positive things come from them than bad. In the future, maybe the only thing that can do battle with a robot… is another robot?
Hopefully these violent delights don’t have violent ends.
Boston Dynamics, the company known for its “nightmare-inducing” backflipping robots, has unveiled two new videos that show them autonomously navigating through different terrains, including an office and a lab, and jogging in a grass field.
The clips released the progress that Atlas, a humanoid robot, and SpotMini, a doglike robot, have made. SpotMini, for example, is using cameras to identify and move past obstacles, such as office furniture.
‘Nightmare- Inducing’ robot’s are now able to do backflips
“During the autonomous run, SpotMini uses data from the cameras to localize itself in the map and to detect and avoid obstacles,” Boston Dynamics said in the video description. “Once the operator presses ‘GO’ at the beginning of the video, the robot is on its own.”
Meanwhile, Atlas’ jump over the downed tree trunk isn’t elegant in the way an Olympic hurdler is, but it more than gets the job done. If that isn’t shocking enough, SpotMini continues its venture outside near grills, walking along a concrete path. That probably isn’t what most people envision when they think of a fun-filled BBQ with friends and the family dog.
The videos, which have racked up a combined 1 million views, are the latest to show off these robots, who have terrified plenty of people. One of them is tech exec Elon Musk, who has repeatedly warned about the perils of artificial intelligence.
In November, when Boston Dynamics showed off Atlas doing backflips, he said that was just the beginning.
“This is nothing,” Musk tweeted. “In a few years, that bot will move so fast you’ll need a strobe light to see it. Sweet dreams…”
Even Boston Dynamics’ founder, Marc Raibert, has acknowledged that its robots can cause fear. In February 2017, he showed off the wheeled version of one of its robots and described it as “nightmare-inducing.”
“This is the debut presentation of what I think will be a nightmare-inducing robot if you’re anything like me,” Raibert was quoted as saying.
Boston Dynamics’ robot can open doors
Boston Dynamics, which was sold from Google to Japanese tech conglomerate SoftBank for an undisclosed sum last year, has not revealed what it eventually plans to do with its robots. (Boston Dynamics)
On its website, the company, which got its start at the Massachusetts Institute of Technology, says it is “changing your idea of what robots can do” and prides itself “in building machines that both break boundaries and work in the real world.”
When “Westworld” becomes a reality (or is it already?) and the robot uprising finally occurs, at least we’ll know (probably) where it started.
The second SpotMini robot trots over and releases its black arm, which grabs onto the door handle and proceeds to open the door.
The arm then maneuvers around the door, which opens entirely, and the polite SpotMini allows its robot friend to enter the room first, before following suit.
Musk, who has said he believes artificial intelligence could be the cause of World War 3, has repeatedly asked for governments around the world to regulate artificial intelligence and robotics, much like society does with other sectors, such as food and drugs.
The tech leader said at the time that we’ve “Got to regulate AI/robotics like we do food, drugs, aircraft & cars.”
Source: Fox News
Robotics and machine learning set to transform the supply chain, suggests Inmarsat research
Transport and logistics businesses are investing in Internet of Things (IoT)-based smart technologies to help them take advantage of the wealth of opportunities that the Fourth Industrial Revolution offers. This is according to research data collected by Inmarsat, the world’s leading provider of global mobile satellite communications, which reveals that the sector is prioritising IoT, machine learning and robotics to increase efficiencies across the supply chain.
Inmarsat’s ‘The Future of IoT in Enterprise’ report, featuring responses collected by Vanson Bourne from 100 large global transportation companies, found that respondents see IoT as the top priority in their approach to digital transformation, with 36 per cent having already deployed IoT-based solutions, and a further 45 per cent expecting to roll the technology out by 2019.
The research further revealed that transport companies are rapidly exploring a wide range of other next generation technologies in the pursuit of digital transformation. The most popular are machine learning (37 per cent), robotics (37 per cent) and 3D printing (29 per cent).
The supply chain looks set to be one of the biggest beneficiaries of this drive towards digital technologies, with 14 per cent already reporting visibility and efficiency improvements in their supply chains and a further 65 per cent expecting to achieve this in future.
Commenting on the findings, Mike Holdsworth, Director of Transport at Inmarsat Enterprise, said: “The industry is clearly making significant strides towards digital transformation, with IoT-based solutions, used in conjunction with robotics, automation and machine learning, helping to transform the way that goods are manufactured, stored and delivered. Companies that proactively invest in these technologies will be able to facilitate more secure and profitable operations across their supply chain.
“Connected machines that can quickly locate and retrieve stock, self-navigate through any environment and make automatic route corrections based on real-time information updates will prove invaluable for any logistics organisation,” he continued. “Smart robots and unmanned aerial drones that work without rest breaks, carry heavier loads and quickly bypass areas of heavy traffic or congestion will be hugely important. They will enhance supply chain management, while their ability of to self-diagnose faults and schedule predictive repairs will be vital for minimising down-time and reducing maintenance costs.”
Holdsworth concluded: “Data-driven smart machines that use sensors to transmit and receive information will need to remain in constant communication through every stage of the worldwide supply chain to be effective. However, this can be especially challenging in ‘blackspots’ with little to no mobile coverage. For logistics companies to access the full value of IoT based solutions, the importance of reliable, continuous connectivity cannot be underestimated, and this is only achievable through a dedicated satellite communications technology.”
Inmarsat’s L-band services offer a global satellite network that provides critical connectivity for with up to 99.9% uptime, allowing reliable end-to-end communications between smart machines, robots and device sensors across any region on Earth. This ensures that even in the most isolated or hostile environments, transport and logistics companies maintain real-time synchronisation between their assets and are able to gather all valuable data needed to make necessary workflow improvements that will drastically increase their chances of success in a competitive digital world.
Illustration Photo: Robots used at Amazon fulfillment centers (credits: SDOT Photos / Flickr Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0)
Investment in Artificial Intelligence (AI) Technology Projected to Triple by 2020 With Market Value of $1.2 Trillion
The artificial intelligence (AI) market is projected to continue experiencing significant growth through 2020, with venture capitalists and tech companies investment in the sector tripling according to Forrester Research.
With this growth, it is projected the market value is projected to be $1.2 trillion annually by 2020 with Global GDP annual growth rate of 3.5%. Technological advancements will enhance cognitive learning capabilities and innovators in the space will continue developing cutting-edge solutions, including various applications for mesh technologies not limited to the Internet of Things (IoT) and evolved tracking devices. Additionally, it should be noted that AI has capabilities to benefit every industry in some form or fashion as big data and advanced analytics become more prevalent in strategic planning. The AI and IoT markets continue to grow rapidly across many verticals while creating a rising demand for high-performance technology and services.
Illustration Photo: Photo showing two industrial robots that can solve the Rubik’s Cube. Roboterzelle is a project by the Johannes Kepler University’s Institute for Robotics. (credits: Vanessa Graf / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0)
DARPA selects research teams to explore paradigm-changing approaches to Machine Learning and Artificial Intelligence
Machine learning (ML) and artificial intelligence (AI) systems have significantly advanced in recent years. However, they are currently limited to executing only those tasks they are specifically designed to perform and are unable to adapt when encountering situations outside their programming or training. DARPA’s Lifelong Learning Machines (L2M) program, drawing inspiration from biological systems, seeks to develop fundamentally new ML approaches that allow systems to adapt continually to new circumstances without forgetting previous learning.
First announced in 2017, DARPA’s L2M program has selected the research teams who will work under its two technical areas. The first technical area focuses on the development of complete systems and their components, and the second will explore learning mechanisms in biological organisms with the goal of translating them into computational processes. Discoveries in both technical areas are expected to generate new methodologies that will allow AI systems to learn and improve during tasks, apply previous skills and knowledge to new situations, incorporate innate system limits, and enhance safety in automated assignments.
The L2M research teams are now focusing their diverse expertise on understanding how a computational system can adapt to new circumstances in real time and without losing its previous knowledge. One group, the team at University of California, Irvine plans to study the dual memory architecture of the hippocampus and cortex. The team seeks to create an ML system capable of predicting potential outcomes by comparing inputs to existing memories, which should allow the system to become more adaptable while retaining previous learnings. The Tufts University team is examining a regeneration mechanism observed in animals like salamanders to create flexible robots that are capable of altering their structure and function on the fly to adapt to changes in their environment. Adapting methods from biological memory reconsolidation, a team from University of Wyoming will work on developing a computational system that uses context to identify appropriate modular memories that can be reassembled with new sensory input to rapidly form behaviors to suit novel circumstances.
“With the L2M program, we are not looking for incremental improvements in state-of-the-art AI and neural networks, but rather paradigm-changing approaches to machine learning that will enable systems to continuously improve based on experience,” said Dr. Hava Siegelmann, the program manager leading L2M. “Teams selected to take on this novel research are comprised of a cross-section of some of the world’s top researchers in a variety of scientific disciplines, and their approaches are equally diverse.”
While still in its early stages, the L2M program has already seen results from a team led by Dr. Hod Lipson at Columbia University’s Engineering School. Dr. Lipson and his team recently identified and solved challenges associated with building and training a self-reproducing neural network, publishing their findings in Arvix Sanity. While neural networks are trainable to produce almost any kind of pattern, training a network to reproduce its own structure is paradoxically difficult. As the network learns, it changes, and therefore the goal continuously shifts. The continued efforts of the team will focus on developing a system that can adapt and improve by using knowledge of its own structure. “The research team’s work with self-replicating neural networks is just one of many possible approaches that will lead to breakthroughs in lifelong learning,” said Siegelmann.
“We are on the threshold of a major jump in AI technology,” stated Siegelmann. “The L2M program will require significantly more ingenuity and effort than incremental changes to current systems. L2M seeks to enable AI systems to learn from experience and become smarter, safer, and more reliable than existing AI.”
Photo: Today’s machine learning and AI systems are limited to executing only tasks they are specifically programmed to perform, without being able to adapt to new situations outside of their training. DARPA’s L2M program aims to generate new methodologies that will allow these systems to learn and improve during tasks, apply previous skills and knowledge to new situations, incorporate innate system limits, and enhance safety in automated assignments. (credit: DARPA)
Artificial intelligence as the next phase of human evolution
AI could dramatically enhance human life as it evolves and will impact technology in ways we can’t comprehend yet. Illinois University developed a robot that had the IQ of a four year old child. A development that is “pretty scary” and perhaps indicative of the human evolution path to come.
AI can also enhance accuracy in surgery, he said, by separating cancerous cells from healthy cells and pinpointing where treatment is needed. A supercomputer has already been developed that can tell with 96% accuracy whether a patient is likely to die by reading data including blood pressure to oxygen levels.
Liquid data that can transform the human body.
Scientists have been able to transfer data, including genetic information, onto human cells and DNA, which could pave the way for future treatments. The data can be synthesised into liquid form, with 490bn gigabytes of data on a single gram.
The current predictions state that by 2020 all the data used in the world will amount to 40 trillion gigabytes. This could be stored on just 82 grams of DNA – the size of an egg.
2025 Coming next the robot marketing and 3D Internet, hologram shops, robots, cyborgs, responsive tech and wacky self-moulding objects, etc. after the AI….2050.…2100.… THE FUTURE
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