Google and Rackspace are designing a server based on IBM’s upcoming Power9 processor, a sure sign that Intel is no longer the only game in town for cloud service providers.
The companies announced plans for the system, which they call Zaius, at IBM’s OpenPower Summit in Silicon Valley on Wednesday. It’s one of several new Power servers on show at the event.
They plan to submit the design to the Open Compute Project, meaning other companies will be able to use the design as well.
Getting insights out of big data is typically neither quick nor easy, but Google is aiming to change all that with a new, managed service for Hadoop and Spark.
Cloud Dataproc, which the search giant launched into open beta on Wednesday, is a new piece of its big data portfolio that’s designed to help companies create clusters quickly, manage them easily and turn them off when they’re not needed.
Enterprises often struggle with getting the most out of rapidly evolving big data technology, said Holger Mueller, a vice president and principal analyst with Constellation Research.
“It’s often not easy for the average enterprise to install and operate,” he said. When two open source products need to be combined, “things can get even more complex.”
Getting insights out of big data is typically neither quick nor easy, but Google is aiming to change all that with a new, managed service for Hadoop and Spark.
Cloud Dataproc, which the search giant launched into open beta on Wednesday, is a new piece of its big data portfolio that’s designed to help companies create clusters quickly, manage them easily and turn them off when they’re not needed.
Enterprises often struggle with getting the most out of rapidly evolving big data technology, said Holger Mueller, a vice president and principal analyst with Constellation Research.
“It’s often not easy for the average enterprise to install and operate,” he said. When two open source products need to be combined, “things can get even more complex.”
Getting insights out of big data is typically neither quick nor easy, but Google is aiming to change all that with a new, managed service for Hadoop and Spark.
Cloud Dataproc, which the search giant launched into open beta on Wednesday, is a new piece of its big data portfolio that’s designed to help companies create clusters quickly, manage them easily and turn them off when they’re not needed.
Enterprises often struggle with getting the most out of rapidly evolving big data technology, said Holger Mueller, a vice president and principal analyst with Constellation Research.
“It’s often not easy for the average enterprise to install and operate,” he said. When two open source products need to be combined, “things can get even more complex.”
For the second year in a row, Apple reduced prices for its expanded iCloud storage plans, putting costs in line with rivals like Google, Microsoft and Dropbox.
Apple announced changes to iCloud extra storage pricing earlier this month at the event where it unveiled new iPhones, the larger iPad Pro and a revamped Apple TV.
Although the Cupertino, Calif., company did not boost the amount of free storage space — as Computerworld speculated it might — and instead continued to provide just 5GB of iCloud space gratis, it bumped up the $ 0.99 per month plan from 20GB to 50GB, lowered the price of the 200GB plan by 25 percent to $ 2.99 monthly, and halved the 1TB plan’s price to $ 9.99.
“We are joining forces with Google Capital to help millions of organizations around the world securely adopt cloud computing, mobility and the Internet …
Getting insights out of big data is typically neither quick nor easy, but Google is aiming to change all that with a new, managed service for Hadoop and Spark.
Cloud Dataproc, which the search giant launched into open beta on Wednesday, is a new piece of its big data portfolio that’s designed to help companies create clusters quickly, manage them easily and turn them off when they’re not needed.
Enterprises often struggle with getting the most out of rapidly evolving big data technology, said Holger Mueller, a vice president and principal analyst with Constellation Research.
“It’s often not easy for the average enterprise to install and operate,” he said. When two open source products need to be combined, “things can get even more complex.”
Some departments in your company do not need cloud computing resources to carry high-performance tasks, right? Because Google has just formatted a service plan for such demands. Google launched Preemptible Virtual Machine, a new cloud service that allows to use computing resources at low costs. The offer is suitable for workloads with low priority and can, therefore, be interrupted.
The search giant introduced a new cloud platform that cost 70% less than the same default setting in Compute Engine. The Preemptible Virtual Machine can do well cheap, about $ 0.01 per instance/hour. The most affordable VM charges per hour can range anywhere between $ 0.03 per hour, up to $ 0.11 per hour or more. The problem is that the VMs may stop working when you need it or face peak periods.
The company argues, however, that the offer (in beta) serves very well the various computational tasks. The company cites, for example, some critical workflows that can be distributed among multiple virtual machines. However, it would be a bad idea to adopt the approach to process analysis, modeling, and simulations that require high computing power and instant answers.
To provide the service, Google will use the free capacity in its data center. At times when there is a peak in demand and Google needs more resources, virtual machines involved in Preemptible Compute Engine VMs are recalled and interrupts the current processing. Users receive a notice period of 30 seconds, which should be enough to save your work. Google said No Preemptible VM can run for more than 24 hours straight.
According to the Google post, “all machine types are charged a minimum of 10 minutes. For example, if you run your instance for 2 minutes, you will be billed for 10 minutes of usage. After 10 minutes, instances are charged in 1 minute increments, rounded up to the nearest minute. For example, an instance that lives for 11.25 minutes will be charged for 12 minutes of usage.”
According to Google, there are many that utilize cloud scalability and pricing model to calculate relatively intensive, but short-term assignments. It includes the coding of video, reproduction of visual effects and calculations based on large amounts of information, such as in data analysis, simulation, and genomics.
The solution is quite similar to that of Spot Instances offered by Amazon Web Services (AWS). The model of AWS differs in price. Google has a fixed cost while the competitor price varies according to demand.
The market leader AWS routinely cuts their cloud pricing. The company is facing tough competition with Google and Microsoft to maintain its lead in cloud computing and tries to woo more developers to come to its solutions with lower prices, more hardware offerings and more advanced technologies. Microsoft, on the other hand, progressed enough to be a serious threat to Amazon’s dominance in the market.
Some departments in your company do not need cloud computing resources to carry high-performance tasks, right? Because Google has just formatted a service plan for such demands. Google launched Preemptible Virtual Machine, a new cloud service that allows to use computing resources at low costs. The offer is suitable for workloads with low priority and can, therefore, be interrupted.
The search giant introduced a new cloud platform that cost 70% less than the same default setting in Compute Engine. The Preemptible Virtual Machine can do well cheap, about $ 0.01 per instance/hour. The most affordable VM charges per hour can range anywhere between $ 0.03 per hour, up to $ 0.11 per hour or more. The problem is that the VMs may stop working when you need it or face peak periods.
The company argues, however, that the offer (in beta) serves very well the various computational tasks. The company cites, for example, some critical workflows that can be distributed among multiple virtual machines. However, it would be a bad idea to adopt the approach to process analysis, modeling, and simulations that require high computing power and instant answers.
To provide the service, Google will use the free capacity in its data center. At times when there is a peak in demand and Google needs more resources, virtual machines involved in Preemptible Compute Engine VMs are recalled and interrupts the current processing. Users receive a notice period of 30 seconds, which should be enough to save your work. Google said No Preemptible VM can run for more than 24 hours straight.
According to the Google post, “all machine types are charged a minimum of 10 minutes. For example, if you run your instance for 2 minutes, you will be billed for 10 minutes of usage. After 10 minutes, instances are charged in 1 minute increments, rounded up to the nearest minute. For example, an instance that lives for 11.25 minutes will be charged for 12 minutes of usage.”
According to Google, there are many that utilize cloud scalability and pricing model to calculate relatively intensive, but short-term assignments. It includes the coding of video, reproduction of visual effects and calculations based on large amounts of information, such as in data analysis, simulation, and genomics.
The solution is quite similar to that of Spot Instances offered by Amazon Web Services (AWS). The model of AWS differs in price. Google has a fixed cost while the competitor price varies according to demand.
The market leader AWS routinely cuts their cloud pricing. The company is facing tough competition with Google and Microsoft to maintain its lead in cloud computing and tries to woo more developers to come to its solutions with lower prices, more hardware offerings and more advanced technologies. Microsoft, on the other hand, progressed enough to be a serious threat to Amazon’s dominance in the market.
If you’ve noticed Google doing a better job of understanding what you say using speech recognition on your smartphone lately, you’re not crazy. Google’s voice search has indeed become more accurate, thanks to advances in artificial intelligence, the tech company announced today.
“Today, we’re happy to announce we built even better neural network acoustic models using Connectionist Temporal Classification (CTC) and sequence discriminative training techniques,” Google Speech Team members Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk wrote in a blog post today. “These models are a special extension of recurrent neural networks (RNNs) that are more accurate, especially in noisy environments, and they are blazingly fast!”
The new models are working in the Google app for iOS and Android, as well as dictation on Android, which works inside of some third-party apps, the team members wrote.
From VentureBeat
Location, location, location — Not using geolocation to reach your mobile customers? Your competitors are. Find out what you’re missing.
Google has reported improvements in voice search not once but twice this year. Clearly the company has been investing in the underlying technology. RNNs are one increasingly popular approach to doing deep learning, a type of artificial intelligence, and Google is widely thought to have a deep bench in deep learning.
Speech could become more important as an input to searching the Web in the years to come. Baidu’s Andrew Ng, who is known for his work on the so-called Google Brain, last year predicted that within five years “50 percent of queries will be on speech or images.”
“In addition to requiring much lower computational resources, the new models are more accurate, robust to noise, and faster to respond to voice search queries — so give it a try, and happy (voice) searching!” wrote Sak, Senior, Rao, Beaufays, and Schalkwyk.
Read the full blog post for more detail on how the team managed to get the new performance gains.
