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AI/ML: Shiny Object or Panacea?


October 17, 2018 - 0 Comments

Anthony McKinney Cisco AI MLGuest Blogger 

This week we welcome guest author Anthony McKinney, Data Center Specialist Army Tactical/SOF at Cisco, as he discusses artificial intelligence and machine learning.

 

Collaborator: Michelle Tschudy, US Public Sector/DoD

 

You can’t swing a CAT 6 cable lately without hitting someone who is talking about artificial intelligence and machine learning (AI/ML). But just like many new technologies, AI/ML means different things to different people. Yet it’s likely that each person describing it has a beneficial understanding of it, at least in terms of how it helps their specific job or mission.

Advances in the field of AI/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). And also why we’d like to invite you to join us at GMXGTC18 October 22-24 where we’ll take a deeper dive into its benefits. But first, let’s take a quick look at some issues and opportunities you’ll hear being discussed in the AI/ML community.

What is artificial intelligence/machine learning?

Actually, a better question would be “what are they,”meaning what is artificial intelligence followed by what is machine learning (and what else is implied that isn’t part of the term). AI/ML is not just a single technology play, but in reality:

  • Depends on specific aspects of AI like deep learning, machine learning, inferencing, and training
  • The specific mission area requires apportionment of the appropriate technology to best meet the business and/or mission requirements
  • In relation to defense, the DoD should build appropriate programs that reward industry sharing such technologies.

Defining AI/ML also requires a quick look at potential issues. For example, 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).

Yet even these could be turned into a positive. From a ‘half glass full’ view, these four factors, when working together as a unified system, could further enhance AI.

And you probably know that there are best of breed companies that build products with unique differences, based on specific customer needs. Just as in research science, experimenting with new technologies like AI/ML often leads to unexpected yet very beneficial solutions that can better utilize the basic elements of the technology.

Can partnerships enhance artificial intelligence?

Companies that work well with partners and establish models for the mutual benefit of themselves and their customers will excel in the complex challenges that AI introduces. A good example of this type of collaboration is The Partnership on AI. It is one of the newer organizations specifically focused on improving AI for the global good. With its 70+ partners sharing data and working on common challenges, it is much more likely that experimentation will lead to additional AI value for customer needs.

What about Security?

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.

Intuitive Data Centers

Cisco has been advancing data center technology with software for enhancing management and functionality to support our customers’ needs and improve their business outcomes. And in reference to Karpathy’s model from the blog above, Cisco Compute and Infrastructure are built to leverage the intelligence that is produced from data and algorithms, all while working with other hardware and software vendors to optimally tune end-to-end solutions.

Cisco’s AI/ML solution, which will be showcased at the GPU Technology Conference at the end of October, is a new addition to the family of solutions which Cisco and partners work on to support the needs of customers like you. The Cisco GPU Accelerated Data Center is one of the solutions that will enable customers to expand their missions, through AI/ML that includes the ideal software and solution partners, but also ensures a secure, simplified, and easily managed experience.

You’re Invited! Join Cisco at GTC DC

If you’ll be attending GTC DC later this month, be sure to drop by and talk with our architects at one of our demo stations, or even request a private meeting to discuss your specific business needs. If you haven’t registered yet, enjoy this 25% off discount code at GMXGTC18. And remember, government employees can register for free.

Resources

Video: watch and learn about AI/ML and UCS.

Learn how machine learning is key to improving daily business services.

See the topics at this year’s GTC DC event.

 



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