GetReady4AI

Grant Gustafson1

Most orgs begin with one or a couple of nodes - later on, they will scale out. Bright Cluster Manager will make managing and monitoring scale easy

Peter Burris9

https://www.crowdcha... What criteria do you use when deciding where to locate your AI workloads, in the cloud or on-premises?

5 Votes Vote

David Floyer

#Wikibon Key for deciding where to place it is where the data is. Moving AI compute to where the data is is must more cost effective and latency effective.

4 Votes Vote

Peter Burris6

https://www.crowdcha... What are you doing to reduce the time-to-value of your AI application deployments?

Mike Leone

there is a massive need to reduce time-to-value right now - a majority of organizations are taking over a year to see value in their AI/ML initiatives. Solutions that can reduce that time and validate it with public case studies will quickly be put on the short list.

(edited)

David Floyer

#Wikibon Improving all elements of the workflow, from data, through modeling, through inference implementation, and refining

3 Votes Vote

Lucas A. Wilson

There are lots of ways to improve time-to-value in the #AI workflow. Our work in the @DellEMC #HPC and #AI Innovation Lab on distributed #deeplearning can help with one part of the process: https://community.em...

Varun Chhabra

@MikeLeone_IT that's very consistent with what we see in conversations with our customers.

Peter Burris3

What’s your greatest constraint in successful AI deployment?

3 Votes Vote

Karl Connolly8

Amazon has a similar lab environment for partners and customers who want to leverage their AI technologies. For new partners how is the Dell EMC experience differentiated?

Kevin Gray

Karl, we would love to host you at our HPC & AI Innovation Lab in Austin to see for yourself.

Armando Acosta

Karl, great question, we can offer our partners expertise

Kevin Gray

@Kevinjgray58 Karl, we would love to host you at our HPC & AI Innovation Lab in Austin to see for yourself

Armando Acosta

Sorry hit send too soon, we can work with partners on the use case, choosing the correct framework and libraries. Plus, we can help you understand how to get that AI workload into production at scale.

Jonathan Siegal

Karl - You are always welcome to visit our state of the art lab..:)

Armando Acosta

Karl, let me know if we can talk, partners a

Karl Connolly

Thanks, I would like to evangelize this offering to our partners, many of whom are keen to mine data, but don’t know how to get started. The idea of an AI bundled solution eliminates a major hurdle, however, a cost analysis of this versus AWS or Azure would help. Got one?

Peter Burris5

https://www.crowdcha... Which constraint is most limiting your use of AI today?

Mike Leone

infrastructure cost and lack of trained staff serve as the big roadblocks right now

Dave Vellante

.@plburris The new innovation cocktail = Data + #AI + Cloud scale so constraints are primarily data quality & accessibility (i.e. no stovepipes), AI skills & resources (talent)...access to cloud scale is pretty much table stakes by now but the other two are significant barriers

David Floyer

AI is a new technology, and needs to be tested first in relatively bounded applications

Varun Chhabra

@dfloyer agreed. Organizations are at various stages of the AI adoption journey, but almost all start with some sort of sandboxed environment at first.

Philip Hummel

@dfloyer Starting with a really well defined use case, usually a piece of software is so important.

jameskobielus

It's actually a set of technologies with long vintage. What's new about AI is the extent to which it's been deployed into operational business applications and infrastructure, and the extent to which it's the core focus of developers for all types of disruptive apps

jameskobielus

@dvellante Access to automation throughout the AI pipeline is as critical as cloud-scale. It's all about speeding up the DevOps cycle for these AI-driven apps, bringing greater consistency, industrializing the process 24x7 in enterprise development/IT shops.

Robin Holden Wolf7

@NVIDIAI & Dell Ready Solution Highlight: Dell EMC PowerEdge R740xd and C4140 servers with 4 NVIDIA Tesla V100‑SXM2 Tensor Core GPUs. With 640 tensor cores, the Tesla V100 was the first to break the 100 teraFLOPS barrier for deep learning performance! https://www.emc.com/...

Dell EMC Accelerates Artificial Intelligence Adoption for Digital Transformation
Dell EMC announces the availability of new Ready Solutions for AI, with specialized designs for Machine Learning with Hadoop and Deep Learning with NVIDIA. The Dell EMC Ready Solutions simplify AI environments, deliver faster, deeper insights than th...

7 Votes Vote

Peter Burris1

What AI use case are you most interested in?

Nick Brackney6

#AI may be one of the hottest trends in 2018 but @KeithManthey explains why ultimately it’s all about the data and the ability of the system to extract value from it. #DataCapital #Iwork4Dell
https://blog.dellemc...

Pandas, Caviar, and Deep Learning | Direct2DellEMC
Analytics is redefining the world. Data is the new oil. Artificial intelligence (AI) is everywhere It feels like we hear some variant of these phrases too

6 Votes Vote