NetAppAI

Accelerate Your Journey to AI
Welcome to this archived live chat featuring AI experts from NetApp, NVIDIA, Wikibon, and the broader industry community. Check out the video replay and chat discussion, and visit the following link for more information: netapp.com/ai

Where do you think AI will have the biggest impact over the next year? (select one)

Peter Burris
https://www.crowdcha... What are the most interesting AI uses cases that you’ve worked on or heard about?

Darrin Johnson
Seed corn - use of DL to identify kernels of corn most likely to germinate increasing yields while driving down costs.
Mike McNamara
I love the inhaler example that Monty has talked about. Both my kids suffered for Asthma. I wish they had smart inhalers 10+ years ago.
Matthew Butter
I gotta go chatbots.
Dave Vellante
1. self driving cars; 2. diagnosing disease probabilities; 3. the future of warfare; 4. prioritizing responses to cyber attacks that have the highest impact; 5. predicting buyer patterns in retail to optimize sales
Brian Dowdy
Social Chatbots; specific example I saw was for those going through severe depression and are seeking assistance.
Sundar Ranganathan
automating customer care calls in call centers, drive-thrus ...
Peter Burris
AI --> lowest energy manufacturing. Good for profit; good for the planet.
jameskobielus
Autonomous transportation platforms. Intelligent robotics to power autonomous mobility for the disabled, elderly, etc.
Premal Savla
Self Driving cars- just take me to work and home
jameskobielus
Swarming AI-powered intelligent coordinating devices, not just for warfare but for precision agriculture, architectural surveys, law enforcement, etc.
Becky Elliott
Drought planning
David Floyer
The most impactful in the next five years will be Autonomous Cars. The scariest is AI in warfare
Darrin Johnson
"Seamless data management" is really the key in creating efficient AI workflows.
jameskobielus
I'd break out "seamless" in this context as automated and accelerated data analytics DevOps pipelines, in which AI workflows drive continuous ingest, modeling, training, and serving of AI models into business apps.
Mike McNamara
agree, managing data from edge to core to cloud is key
Premal Savla
Agree, the AI work flow is complex and this is just the begining
Darrin Johnson
@jameskobielus You are spot on. I would add a key element which is the need for seamless edge integration whether data ingestion from the edge to driving production models to the edge plus "rinsing and repeating."
Sundar Ranganathan
Important point this. Organizations' data generally spans multiple environments/data centers. on-premises, cloud, and even edge devices in IoT apps. You want to easy data management.
Premal Savla
comprehensive data management for AI is a must
Mike McNamara
For details on edge to core to cloud, read this white paper https://nt-ap.com/2v...
@SundarRanganat4
Matthew Butter
FYI AI is having a huge impact on social media, especially when it comes to scaling customer support over social.
John Furrier
AI for social is a great NLP application using entity extraction and community detection with LM can enable AI to be more valuable for all systems and people
Tony Paikeday
absolutely - we also see more enterprises using AI to mine insights from their call center recordings - can help with sentiment analysis, improving customer experience, reduce churn, etc.
John Furrier
we use ML for extracting insights from these chats and all Cube videos as we have full transcripts on all of our content. Soon we will make the leaderboard more about reputation and real influence not how many followers someone has
John Furrier
community and impact of content on social is our key focus on influence and reputation in context
John Furrier
@TonyPaikeday @MatthewButter lots of automation is coming that users actually want for support and soon other value activities. I'm with you guys
Matthew Butter
Well I know Southwest has 40+ people whose sole job is to monitor social media and monitor for customer support opportunities. Chatbots will eventually reduce those numbers drastically.
Cecelia Taylor
Southwest prides itself with it's customer service. I don't necessarily think that they will decrease the numbers of people working, but chatbots will allow them to scale their efforts to offer better and more personalized experiences for their customers.
jameskobielus
Right. AI-driven multichannel customer contact infastructures are automating a lot of first- and second-level support, thereby reducing costs, speeding issue resolution, and capturing key customer/sentiment insights in real time.
jameskobielus
Right. AI is driving both outbound customer service scenarios such as that, plus lots of inbound applications in digital channels to improve responsiveness, routing, resolution, experience, etc.
Tony Dunn 😎
@furrier @TonyPaikeday @MatthewButter ML/AI crucial for social analytics moving forward to extract/overlay context and intent rather than just influence and reach
Tony Paikeday
@dunntony I would love to get that kind of insight from my own team's efforts :)
Peter Burris
https://www.crowdcha... Will AI be used primarily to extend existing applications or catalyze new classes of application?

Darrin Johnson
Short answer is "Yes". It will help both. NVIDIA's Inception program which includes more than 3000 startups is a testament to both scenarios.
jameskobielus
AI is being used to extend existing apps--most notably in data integration/curation, metadata-driven search engines, IT operations management, and security incident and event management
Peter Burris
The tooling, method, metrics implications of legacy+AI and greenfield+AI are very, very important.
David Floyer
The key for AI business value is automation of business processes. Most business processes impact systems of record. New AI/Advanced applications will need to feed existing systems of record to achieve levels of impact.
Dave Vellante
many examples where machine intelligence can improve existing apps - take email for example, automated voice response systems, other customer service apps, service management apps, CRM, HCM apps...logistics and supply chain...
Andrew Horton
(part 1) that's one of the difficult questions a customer needs to ask up front. "what problem am I trying to solve". You can absolutely try and disrupt a new market while also remaking existing business processes.
David Floyer
AI within the datacenter will again be systems that automate decisions (e.g., take multiple alerts and take action as a result)
Andrew Horton
(part 2) If you can't answer the question of "what should I do first?" then that means you need some outside help.
Peter Burris
https://www.crowdcha... What challenges are companies facing as they put AI into practice?

Peter Burris
Tooling is improving rapidly. We hear talent more frequently. Comments?
Mike McNamara
Do-it-yourself integrations are complex.
Darrin Johnson
Two key challenges - data science talent and infrastructure. Fortunately having great infrastructure like ONTAP AI enables data scientists to be more efficient/effective.
jameskobielus
Companies face the challenge of how you build out an optimized hardware/software stack for a wide range of AI workloads. Should there be different workload-optimized stacks? Which of these stacks are best deployed in managed public clouds vs. on-premises?
Sundar Ranganathan
Enormous Compute and storage needs
David Floyer
Acceptance that moving the compute to the data is a long-term strategy.
jameskobielus
Companies also face the challenge of how you benchmark the dizzying range of AI hardware/software stack permutations against each other, given the wide range of workloads, deployment scenarios, etc now and potential.
Tony Dunn 😎
structured visibility across massive data sets, timely access to predictive analytics
Andrew Horton
data prep. The accuracy of your models is only as good as the data you feed it. I might have 10PB of data but if it hasn't been cleaned yet then its useless
Tony Paikeday
ML will help combat the $18B opiod epidemic, enabling benefits providers to detect patterns from hundreds of discrete features in customer Rx data that can detect fraud, waste, and abuse, saving lives and money.
John Furrier
AI for good is huge and it's not just a throwaway philanthropy initiative. There is real projects having impact here
Mike McNamara
The Opioid epidemic is a huge problem, and AI/ML can help solve that costly (lives, money) problem.
jameskobielus
AI's social-transformative power is both in its ability to drive these insights, and its reliance on a deep open-source stack. AI for "social good" efforts thrive on open-source tools, platforms, data, etc. And voluntarism by data science subject matter experts.