Gartner on Gen AI. What’s Next?!

Making “GenAI Real” | How Walmart does ML | GenAI 50, the CyberSecurity Ecosystem MAP and “FOFO”, the “Keyword of the week”….

Making GenAI Real in the Enterprise

Looking forward to “Talking AI” with Carrefour’s CDAO at the Entropy Conference on Oct 4! Sebastien Rozanes and I will talk about how to make GenAI Real…in the Enterprise. You can register for it today for FREE. Thanks Meredith, Benedetta Cittadin & Sebastien for inviting us!

Register for FREE @ https://lnkd.in/g5CiFe8w

Gartner: What’s Next with GenAI?!

Gartner explained that its 2023 Emerging Tech Hype Cycle focused on 4 themes: Emergent AI, DevX, Pervasive Cloud & Human-centric security and privacy. But the Hype (pun intended) focused on the fact that the firm had placed Generative AI on the ‘Peak of Inflated Expectations.’ Here are 3 resources that might help distill what this REALLY means:

1. Venturebeat’s Sharon Goldman explanation of how the cycle works here
2. Gartner’s original piece here and their 4-part series podcast here.
3. And, if you prefer video, Yours Truly explaining how the Hype cycle works and relates with other research papers on our CarCast (scroll below the image!).

GenAI 50: The most promising Generative Artificial Intelligence companies

via CB Insights. Who’s missing?! see more here

The CyberSecurity Ecosystem MAP

Remember MAD?! (The Machine Learning, Artificial Intelligence & Data Landscape)….well there is now a NEW type…the CyberSecurity Ecosystem!

If you’re interested in learning more about this space, Francis Odum is the person to follow!

His Beginner’s Guide to Cybersecurity is terrific and he’s put a lot of work into trying to simplify the space for all of us. He put in 100+ hours of research with experts to simplify the $200B cybersecurity industry and I love that!

See it here and below!

CXO Talk: September 22!

Generative AI Strategy for the Enterprise. What are you doing on September 22?! I’ll be on CXO Talk to cover every Data, GenAI and #Analytics with hosts Michael Krigsman and QuHarrison Terry.

If you have questions about what you’d like us to cover, put them in comments! In the meantime, check out the last episode with my friend Bob Muglia below!

Need To Follow List?!

Thanks Rivery for having on the list of “Top Data People to Follow in 2023”. I’m typically the one that shares with the community the practitioners to know and follow! :) Honored to be in the presence of friends like Barr Moses, Benjamin Rogojan, Benn Stancil, Chad Sanderson, Chris Tabb, Cindi Howson, Daliana Liu, David Langer, Eric Kavanagh, Greg Coquillo, Jessica Talisman, Joe Reis, Jordan Goldmeier, Lauren Balik, Loris Marini, Mark Freeman II, Megan Lieu, Mehdi Ouazza, Sundas Khalid and Zhamak Dehghani!

More here.

How Walmart does Machine Learning

Here is how Walmart does Machine Learning. Join the conversation here.

My highlights below!

I’m big fan of real world evidence. Walmart’s CVP of Cloud Data Platform of Anil Madan and his team do a masterful job describing their journey in this piece. A few highlights for me:

1. Context: Walmart has a highly optimized supply chain that runs at scale to offer its customers shopping at lowest price. In the process, Walmart accumulates a huge amount of valuable information from its everyday operations. This data is used to build Artificial Intelligence (AI) solutions to optimize and increase efficiencies of operations and customer experience.
2. Scale: Each week, approximately 240 million customers and members visit more than 10,500 stores and numerous eCommerce websites in 20 countries. With fiscal year 2023 revenue of $611 billion, Walmart employs approximately 2.1 million associates worldwide. Walmart’s supply chain is extensive and complex, it works with over 100,000 suppliers worldwide, 150 distribution centers in United States, largest private fleet of trucks in the world with over 10,000 tractors and 80,000 trailers.
3. Guiding principles: Best of the breed, Speed and Scale, Cost Platform, Governance (compliance and responsible use of AI).
4. Key use-cases: 4a) Channel performance (Walmart provides its channel partners a tool which provides details on sales data, promotions, and control over shelf assortments along with actionable insights and recommendations), 4b) Search to drive high impact customer facing metrics such as Gross Merchandise Value (GMV), CTR (Click Through Rate), SAR (Search Abandonment Rate) etc. Key Search challenge: it’s temporal (over 90% of models degrade over brief period), 4c) Market Intelligence (insights into competitors pricing, assortment, and marketing strategies) 4d) Last Mile Delivery (intelligent driver dispatch system).
5. Lessons Learned: Best practices include Open source, Inner-sourcing, Prescriptive approach to certain use cases like MLOps and AI Governance, Cloud agnostic platform on top of Kubernetes.

How long will it take you to scale?

The SaaS Growth Report. Great job by Sid Jain and his team. Lots of data here. Interesting insights IMHO, include:

• Best-in-class SaaS reach the $1M ARR milestone in 9 months
• Best-in-class SaaS reach the $10M ARR mark in 2 years & 9 months.
• It’s harder than you think: ONLY 13% of startups reach the $10M ARR mark, even after 10 years in existence…

How the Modern TechStack for GenerativeAI is stacking up….

And Tailored CustomerJourneys via GenAI…and great resources from McKinsey & Company. More here.

EXTRAS

Who’s going to TED AI?!

October 17 & 18, San Francisco, hosted by Sam De Brouwer and Chris Anderson….in the Ferry Building in San Francisco.

Keyword of the week: FOFO

There was FOMO (Fear of Missing Out), FOMU (Fear of Messing Up)….and I just heard about FOFO from Jacco van der Kooij. “Fear of Finding Out” of finding out is a real thing. Read more about it on AdWeek here.