The Linux Foundation Announces the Acumos AI Challenge for Developers
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Seeking Innovative and Ground-Breaking Artificial Intelligence Solutions
SAN FRANCISCO, May 31, 2018 – The Linux Foundation, the nonprofit organization enabling mass innovation through open source, today announced the Acumos AI Challenge, sponsored by AT&T and Tech Mahindra. The Acumos AI Challenge is an open source developer competition seeking innovative, ground-breaking artificial intelligence (AI) solutions from students, developers, and data scientists. The Acumos AI Challenge will foster development of AI models for the Acumos AI Project, an AI project of The Linux Foundation and supported by The Linux Foundation’s LF Deep Learning Foundation.
AT&T and Tech Mahindra are awarding $100,000 in prizes, as well as the chance for finalists to travel to San Francisco to pitch their solutions during the finals on September 11, 2018. All eligible AI solutions will be available as open source in the Acumos Marketplace.
“We created the Acumos AI Challenge to recognize developers who are paving the future of AI development, and helping to accelerate AI adoption and innovation,” said Mazin Gilbert, VP of Advanced Technology, AT&T.
The Acumos AI Project is a federated platform for managing AI and machine learning (ML) applications and sharing AI models. AT&T and Tech Mahindra contributed the initial Acumos code, now freely available for download, to the new LF Deep Learning Foundation, a project of The Linux Foundation that supports open source innovation in artificial intelligence, machine learning and deep learning. With the Acumos platform, developers and data scientists gain a new industry standard for making AI applications and models reusable and easily accessible.
“This Challenge provides a fantastic opportunity for developers to start to dig into Acumos in order to ramp up adoption and collaboration,” said Linux Foundation Executive Director Jim Zemlin. “The Acumos AI project was started by the LF Deep Learning Foundation community in order to provide a platform for developers and data scientists to freely share AI models and applications, so they are reusable and easily accessible.”
The Acumos AI Challenge is seeking AI solutions across all uses cases. Examples include, but are not limited to:
- 5G & SDN – Apps that improve the overall performance and efficiencies of 5G networks and Software-Defined Networking.
- Media & Entertainment – AI models targeting a media or entertainment use case. Examples include solutions for broadcast media, internet, film, social media, ad campaign analysis, video and image recognition, speech and sound recognition, video insight tools and more.
- Security – AI apps around network security use cases such as advanced threat protection, cyber security, IoT security, etc.
- Enterprise Solutions – AI models targeting an enterprise use case, including solutions for Automotive, Home Automation, Infrastructure and IoT.
The top three teams will each receive $25,000 cash, plus a trip to the finals in San Francisco in September. The team that wins the finale will take home an additional $25,000 grand prize, for a total of $50,000.
“The Acumos AI Challenge is an opportunity for the AI development community to create cutting-edge solutions with Acumos,” said Ashish Julka, Senior Vice President, Tech Mahindra. “We can tackle large problems with Acumos, and this initiative will yield innovative ideas to accelerate AI adoption across enterprises, and help them stay efficient and profitable.”
The Acumos AI Challenge is accepting submissions between May 31 – August 5, 2018. The competition is open to U.S., District of Columbia and Puerto Rico residents of a majority age. Teams are required to submit a working AI model, test dataset and a demo video under three minutes. Teams can register for the Challenge beginning May 31, 2018. We encourage you to register early so that you can begin to plan and build your solution and create your demo video.
The Linux Foundation is hosting the Acumos platform and Acumos Marketplace and is focused on nurturing an active, large community around the project. To learn more, visit https://www.acumos.org.
About The Linux Foundation
The Linux Foundation is the organization of choice for the world’s top developers and companies to build ecosystems that accelerate open technology development and industry adoption. Together with the worldwide open source community, it is solving the hardest technology problems by creating the largest shared technology investment in history. Founded in 2000, The Linux Foundation today provides tools, training and events to scale any open source project, which together deliver an economic impact not achievable by any one company. More information can be found at www.linuxfoundation.org.
The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage.
Linux is a registered trademark of Linus Torvalds.
The post The Linux Foundation Announces the Acumos AI Challenge for Developers appeared first on The Linux Foundation.
Make ISO from DVD
In this case I had an OS install disk which was required to be on a virtual node with no optical drive, so I needed to transfer an image to the server to create a VM
Find out which device the DVD is:lsblk
Output:NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINT sda 8:0 0 465.8G 0 disk ├─sda1 8:1 0 1G 0 part /boot └─sda2 8:2 0 464.8G 0 part ├─centos-root 253:0 0 50G 0 lvm / ├─centos-swap 253:1 0 11.8G 0 lvm [SWAP] └─centos-home 253:2 0 403G 0 lvm /home sdb 8:16 1 14.5G 0 disk /mnt sr0 11:0 1 4.1G 0 rom /run/media/rick/CCSA_X64FRE_EN-US_DV5
Therefore /dev/sr0 is the location , or disk to be made into an ISO
I prefer simplicity, and sometimes deal with the fallout after the fact, however Ive repeated this countless times with success.dd if=/dev/sr0 of=win10.iso
Where if=Input file and of=output file
I chill out and do something else while the image is being copied/created, and the final output:8555456+0 records in 8555456+0 records out 4380393472 bytes (4.4 GB) copied, 331.937 s, 13.2 MB/s
Recreate postrgresql database template encode to ASCIIUPDATE pg_database SET datistemplate = FALSE WHERE datname = 'template1';
Now we can drop it:DROP DATABASE template1;
Create database from template0, with a new default encoding:CREATE DATABASE template1 WITH TEMPLATE = template0 ENCODING = 'UNICODE'; UPDATE pg_database SET datistemplate = TRUE WHERE datname = 'template1'; \c template1 VACUUM FREEZE;