GetReady4AI

Rodrigo Gazzaneo

it's a conversation about productivity and outcomes. Focus on the activities that generate value, automate and consume other steps on the process.

Armando Acosta

Great question, I understand data scientist are taking the DIY approach, yet that doesn't equal fastest time value. We offer speed, agility and tools that enable the data scientist to build an environment within 5 clicks of a mouse.

Lucas A. Wilson

I think build your own will always be an option for some (just like in #HPC). In the end it all comes down to where your company wants to spend - a baseline configuration that can be extended later or bare metal.

jameskobielus

@Armando75 That's not the case. Data scientists are very much adopting the new generation of prebuilt DevOps platforms to drive team productivity through the AI pipeline. See my #Wikibon study: https://wikibon.com/...

Rodrigo Gazzaneo

@Armando75 exactly. TTV. Time to value. That's the KPI.

agreed. There is no one size fits all approach. However, it's important to understand the tradeoffs of either approach.

Rodrigo Gazzaneo

@jameskobielus I have a very interesting experience on that. I worked with a Data Science team that adopted #agile #devops #PaaS early on 2014.

Grant Gustafson

@broomio these data scientists are like master guitarists and when we say 'easy', it's like showing them how to play folk songs. will this ready solution be flexible enough to meet all of their needs or will they have to tweak? I'm thinking large orgs, not start ups in AI

jameskobielus

That's overstating the average data scientist's jack-of-all-trades "unicorn" bonafides. Most are statistical modeling specialists in larger teams with data engineers, programmers, governance specialists, and others in increasingly DevOps workflows.

jameskobielus1

Curcuru discussing the pressure that AI places on enterprise storage. Need flash storage that supports nanosecond AI performance: create a seamless instantaneous decision/response re customers and other stakeholders.

Peter Burris12

https://www.crowdcha... What do you think is the most important aspect of this "Get Ready for AI" announcement?

John Furrier

I think the notion of scaling value from AI in operational data was a great high order bit

Jim Franklin

Definitely the data at scale with the right tools set for outcomes.

the ability to scale infrastructure as AI requirements scale over time is super important. We are seeing the tip of the iceberg in terms of the performance requirements of AI workloads.

Mike Leone

enabling organizations to quickly and easily deploy an AI technology stack that can scale to meet the demands of their organization

To be honest, I'm from the data scientist / engineering side of the house. It was a bit too much marketing for me; however, I'm getting some contacts for follow-up that I am sure will be useful. Thanks for the invite.

Dave Vellante

.@plburris key to me is making infrastructure invisible. To data wonks infrastructure is practically irrelevant (Until it breaks)...

Jay Boisseau

Dell Ready Solutions for AI: customers now have expertly-designed, easy-to-deploy, easy-to-use AI solutions that leverage on-prem cost advantages and data locations. Dell services can further accelerate the time-to-insight and maximize results & ROI.

David Floyer

#Wikibon Using AI and Advanced Analytics in real-time is key to improving and automating high-value decisions - nice example from MasterCard.

The Data Science Provisioning Portal. Optimizing the entire software and hardware stack for your particular use case is the make-or-break consideration in full-stack AI readiness to deploy.

(edited)

Jim Franklin0

Thanks Nick for advancing AI #GetReady4AI

Rob Callery

Speed / simplicity of deployment.

jameskobielus0

Nick Curcuru, VP analytics at Mastercard, discussing core vs edge deployment of AI-ready infrastructure.

https://www.emc.com/collateral/analyst-report/esg-technical-review-dell-emc-aug-2018.pdf

Check out the @esg_global validation of the @DellEMC Ready Solutions for #AI where we highlight ease of use and performance benefits https://www.emc.com/... #GetReady4AI

(edited)

6 Votes Vote

Balachandran Rajendran

This is a great article. Thank you ! #GetReady4AI

Dave Vellante1

Don't forget - there's a formal Chat after this video ends - an "Ask me Anything" #AMA Chat

Amol Choukekar6

165 million transactions, Wow !!!.. now that is scale...

Nick Brackney

yeah when I hear the scale of credit card processors I find it hard to get behind the crypto guys since they can't touch that scale.

In a previous employer, I saw even higher transaction rates. Having that balance between what to persist and what to put into flash was key. Also understanding the bottleneck was mandatory.

3 Votes Vote

Yes, i couldn't quite believe how massive that number is when i heard it the first time. And when one considers how much of the world still runs on cash, one can only imagine how much larger that number can get.

I worked with healthcare solutions, blockchain, and IOT sensors.

What is Flash?

https://www.dellemc....

jameskobielus5

Garima Kochhar of #DellEMC discusses their sophisticated engineering and tuning of AI-ready solutions. Deep learning hardware/software stacks ready for Hadoop, for Nvidia, etc. She's in Dell EMC HPC & AI Innovation Lab in Austin. Exoscale engineering.

The best part is that the lab helps us solve real-life customer problems - we collaborate with our customers on their AI challenges using the infrastructure in the lab.

Armando Acosta

The AI innovation lab is all about helping customers accelerate POCs to show the value back to the business

@broomio what is the cost for that service? Do they have initial conversations for free?