Results


Protecting people with the Internet of Things Access AI

@machinelearnbot

Most of us will know the age old saying, we want to be "safe and secure" – that's ourselves, our family, and our work colleagues in all aspects of life. However, our understanding of what it means to be safe and secure, especially when considering today's modern digital age and in particular the growing era of the Internet of Things (IoT), isn't the same as it once was. For sure, the natural evolution of innovation, technological or otherwise, continues irrespective of the accelerating awareness and adoption of the interconnection of consumer and industrial devices which makes up the IoT. The world of Industrial Internet of Things (IIoT) is also evolving at a similar pace and now more than ever is bridging into consumers' lives on an individual level. So much so that it is becoming more difficult to differentiate the IoT from IIoT, outside of those in the industry of course.


Another state is going to unleash self-driving cars

@machinelearnbot

Self-driving cars are being tested all over the United States. New York City, Sacramento, and San Francisco are just some of the places you can see autonomous vehicles on the road. Waymo, Google's self-driving car division, has been a leader of the tech. They recently partnered with Intel to further hone what their vehicles can do. The CEO of Waymo, John Krafcik, recently wrote a Medium post detailing where the company will be testing their cars next: Michigan.


The cognitive effect on automotive: Internet of Things Blog

@machinelearnbot

The automotive industry is experiencing a paradigm shift. Today's vehicles are no longer just for transport. Instead, they are moving data centres with the potential to offer consumers access to in-car services like on-the-go toll and parking payments, weather data, automatic route calculation and much more. In the week that Frankfurt hosts its well-renowned international motor show, IAA 2017, the automotive industry is buzzing with talk of self-driving cars, in-vehicle concierge services and ever-increasing personalization for drivers. To understand how ready the automotive industry is to accept cognitive technology like this, the IBM Institute for Business Value surveyed 500 automotive executives, original equipment manufacturers and suppliers for their perspectives.


Key Applications of the Smart IoT to Transform Transportation

@machinelearnbot

The applications of the Internet of Things (IoT) have been growing dramatically in recent a few years. According to IDC, the transportation sector will be among the first to see a significant growth from the IoT, and the global IoT market in the transportation sector is expected to reach $195 billion by 2020. The smart IoT is dramatically accelerating the pace of innovation and transforming the way of operations in transportation and infrastructure. The ubiquitous deployment of smart, connected sensors and things, combined with artificial intelligence (AI) and big data analytics, can enable us to gather insightful knowledge, make real-time and even predictive computing to help us reaching better decisions and developing better plans to improve the safety, efficiency, and reliability of smart transportation. Here we take a look at some important applications of the IoT in intelligent transportation systems and smart cities.


General Motors will soon test self-driving cars in New York City

@machinelearnbot

Cruise Automation wants to make self-driving cars in New York City a reality as soon as 2018. The self-driving car wing of General Motors has announced plans to test Chevy Bolts in an area of Manhattan spanning five square miles, beginning as early as next year. Previously, the company has evaluated how its vehicles perform in an urban setting by testing them out on the streets of San Francisco. In May 2017, New York Governor Andrew M. Cuomo detailed a one-year pilot program that would give automakers the opportunity to apply for permission to test self-driving cars in New York starting in 2018. Cruise Automation has submitted a request, which is expected to be granted, according to a report from CNN. Pedestrians will likely pose the greatest challenge for the Bolts let loose on the streets of Manhattan.


The Big Data Boom Automobile Magazine

@machinelearnbot

With the help of Microsoft, last year Toyota created a new data analytics division called Toyota Connected to bring Internet-connected services into the car. Earlier this year, Renault-Nissan inked a deal to leverage Microsoft's Connected Vehicle Platform and its Azure cloud architecture to collect vehicle sensor and usage data in order to develop "connected driving experiences." Ford recently invested $182 million in Pivotal, a cloud-based software company, in part to create analytics tools and a cloud platform to support the automaker's Smart Mobility initiative. Cadillac introduced the first production vehicle-to-vehicle communication system on its 2017 models, and last year, Audi launched a Traffic Light Information vehicle-to-infrastructure system that lets its cars know how long a light will stay red or green to help improve traffic flow.


Machine learning and data are fueling a new kind of car, brought to you by Intel

@machinelearnbot

The automobile is being dismantled, reimagined, and rebuilt in Silicon Valley. Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. In particular, it shows how valuable on-the-road data is likely to be in the evolution of automated driving. While the price tag might seem steep, especially with so many players in automated driving today, Mobileye has some key technological strengths and strategic advantages. It's also developing new technologies that could help solidify this position.


Connected Cars - Best Companions of Smartphones !!

@machinelearnbot

Mercedes-Benz models introduced this year can link directly to Nest, the Internet of Things powered smart home system, to remotely activate a home's temperature controls prior to arrival. ParkMe covers real time dynamic parking information and guide drivers to open parking lots and meters. Mercedes-Benz models introduced this year can link directly to Nest, the Internet of Things powered smart home system, to remotely activate a home's temperature controls prior to arrival. ParkMe covers real time dynamic parking information and guide drivers to open parking lots and meters.


Digital Engineering: Convergence of Disruptive Technologies

@machinelearnbot

Due to globalization, design & engineering companies face increasing competition and major disruptions in their core products and business models. The Summit addressed the transformation to Digital Engineering in this constrained environment; explaining how the convergence of disruptive technologies helps companies to fully capture the benefits of digitalization. Engaging an audience of about 700, various topics were discussed: supply chain complexity, the role of robots in powering e-commerce and supply chains, intelligent automation, connected mobility etc. Global companies are investing in operating systems for connected vehicles, opening a range of new consumer services and vehicle management features.


Machine Learning at HPC User Forum: Drilling into Specific Use Cases

@machinelearnbot

Dr. Weng-Keen Wong from the NSF echoed much the same distinction between the specific and general case algorithm during his talk "Research in Deep Learning: A Perspective From NSF" and was also mentioned by Nvidia's Dale Southard during the disruptive technology panel. Tim Barr's (Cray) "Perspectives on HPC-Enabled AI" showed how Cray's HPC technologies can be leveraged for Machine and Deep Learning for vision, speech and language. Fresh off their integration of SGI technology into their technology stack, the talk not only highlighted the newer software platforms which the learning systems leverage, but demonstrated that HPE's portfolio of systems and experience in both HPC and hyper scale environments is impressive indeed. Stand-alone image recognition is really cool, but as expounded upon above, the true benefit from deep learning is having an integrated workflow where data sources are ingested by a general purpose deep learning platform with outcomes that benefit business, industry and academia.