In honor of Johann Sebastian Bach’s birthday, which might be his 333rd, Google created associate AI Doodle on the homepage of their search to honor him and celebrate trendy technology. Created by Google’s Magenta and try groups, the Doodle lets users produce their own music by exploitation machine learning to harmonize melodies. Magenta was chargeable for the machine learning facet of the project whereas try created the flexibility to use it within the application. The machine-learning model, known as Coconet, analyzed 306 of Bach’s original anthem harmonizations thus it absolutely was ready to produce a consonant tune with the user’s notes. This exposes the ground for discussion on AI in music and whether or not or not it will produce music sort of a human and what meaning for artists within the trade. several debates have surfaced around this issue once it involves AI being a vicinity of the music trade and therefore the credibleness of it. This is Google’s initial dive int...
Artificial Intelligence: Does the AI silver bullet really exist?
Guest Author: Anthony McKinney, knowledge Center Specialist, Army Tactical/SOF at Cisco.
During his time in the U.S. Navy, Anthony served operational tours as a Surface Warfare Officer and SEAL Officer leading units on deployments to South America, the Mediterranean, and the Middle East. He has totaled 30 years combined Active and Reserve Service, and retired in 2016 as a Navy Captain.
Collaborator: Michelle Tschudy
Recently the U.S. Department of Defense (DoD) released the DoD AI Strategy which lays out approach and focus areas for adopting Artificial Intelligence (AI) “to advance our security and prosperity”. One will quickly grasp by reading the 17 page summary that no silver bullet solution awaits.
AI strategies for the DoD
The Strategy sets an approach in place for the myriad challenges that improve the DoD’s ability to “operationalize” AI. This Strategy identifies the cross-organizational, even cross-cultural interactions needed to enhance AI for DoD. Several analogies come to mind, such as the telephone, the television, or the automobile, that were practical when they were first introduced, but think of how each one has matured as the technology has advanced within these systems.
So too, will the technology supporting AI. And similar to the DoD AI Strategy, the companies that establish an open technology framework will enable the end customer to establish a technology foundation that persists longer through software updates and reduces the need for a rip and replace approach.
What is AI/ML?
Actually a better question would be “what are they,” meaning what is artificial intelligence and what is machine learning (and what else is implied that isn’t part of the term).
AI/ML isn't simply one technology play, however in reality:
Guest Author: Anthony McKinney, knowledge Center Specialist, Army Tactical/SOF at Cisco.
During his time in the U.S. Navy, Anthony served operational tours as a Surface Warfare Officer and SEAL Officer leading units on deployments to South America, the Mediterranean, and the Middle East. He has totaled 30 years combined Active and Reserve Service, and retired in 2016 as a Navy Captain.
Collaborator: Michelle Tschudy
Recently the U.S. Department of Defense (DoD) released the DoD AI Strategy which lays out approach and focus areas for adopting Artificial Intelligence (AI) “to advance our security and prosperity”. One will quickly grasp by reading the 17 page summary that no silver bullet solution awaits.
AI strategies for the DoD
The Strategy sets an approach in place for the myriad challenges that improve the DoD’s ability to “operationalize” AI. This Strategy identifies the cross-organizational, even cross-cultural interactions needed to enhance AI for DoD. Several analogies come to mind, such as the telephone, the television, or the automobile, that were practical when they were first introduced, but think of how each one has matured as the technology has advanced within these systems.
So too, will the technology supporting AI. And similar to the DoD AI Strategy, the companies that establish an open technology framework will enable the end customer to establish a technology foundation that persists longer through software updates and reduces the need for a rip and replace approach.
What is AI/ML?
Actually a better question would be “what are they,” meaning what is artificial intelligence and what is machine learning (and what else is implied that isn’t part of the term).
AI/ML isn't simply one technology play, however in reality:
Depends on specific aspects of AI like deep learning, machine learning, inferencing, and training
The specific mission space needs allocation of the acceptable technology to best meet the business and/or mission necessities
In respect to defense, the DoD should build appropriate programs that reward industry sharing such technologies.
Watch: The Artificial Intelligence and Machine Learning (AI/ML) Solution
In his blog on Deep Reinforcement Learning: Pong from Pixels, Andrej Karpathy speaks of four factors that can hold back AI:
1. Compute (Servers)
2. Data (conditioned/normalized)
3. Algorithms
4. Infrastructure (underlying OS, Protocols, Software, Networking).
From a half glass full view, these four factors, when working together as a unified system, would further enhance AI.
You probably recognize that there area unit better of breed corporations that build product with distinctive variations, based on specific customer needs.
However just as in science, experimentation often leads to solutions where the technology is much better suited.
Advances in the fields of AI and ML are one of the reasons we recently launched the Cisco GPU accelerated data center to enable workloads like desktop & app virtualization,
virtual workstations, and accelerated analytics (learn more at Cisco AI/ML).
In his blog on Deep Reinforcement Learning: Pong from Pixels, Andrej Karpathy speaks of four factors that can hold back AI:
1. Compute (Servers)
2. Data (conditioned/normalized)
3. Algorithms
4. Infrastructure (underlying OS, Protocols, Software, Networking).
From a half glass full view, these four factors, when working together as a unified system, would further enhance AI.
You probably recognize that there area unit better of breed corporations that build product with distinctive variations, based on specific customer needs.
However just as in science, experimentation often leads to solutions where the technology is much better suited.
Advances in the fields of AI and ML are one of the reasons we recently launched the Cisco GPU accelerated data center to enable workloads like desktop & app virtualization,
virtual workstations, and accelerated analytics (learn more at Cisco AI/ML).
Partnership on AI
Companies that work well with partners and establish models for the mutual benefit of themselves and the customers will excel in the complex challenges that AI introduces.
A good example of this sort of collaboration is that the Partnership on AI.
Companies that work well with partners and establish models for the mutual benefit of themselves and the customers will excel in the complex challenges that AI introduces.
A good example of this sort of collaboration is that the Partnership on AI.
It is one among the newer organizations specifically targeted on rising AI for the worldwide smart.
With its 70+ partners sharing knowledge and dealing on common challenges, it is much more likely that experimentation will lead to additional AI value for customer needs.
Securing data and access
One of the most critical issues for employment of AI across enterprises is the ability to protect data and limit access to those with a “need to know”. This could be companies who use their intellectual property to maintain a market lead over competitors, or nation states whose sovereignty and influence on a broader stage may be impacted.
One of the most critical issues for employment of AI across enterprises is the ability to protect data and limit access to those with a “need to know”. This could be companies who use their intellectual property to maintain a market lead over competitors, or nation states whose sovereignty and influence on a broader stage may be impacted.
Obvious from the beginning, there is no silver bullet for AI, but through advances in products like Cisco’s Deep Learning server, and with the vast array of partners supporting customers’ needs from HQ out to the tactical edge, you are equipping yourself with a secure and investment protected solution to address the evolution of AI.
Comments
Post a Comment
Please do not enter any spam link in comment box.