Here’s a little video I created inspired by this post.
If 2018 was the year of AI & ML, then 2019 is going to be the year of AI/ML Operationalization. I see this all the time with customers: AI requires a lot of teams to work together that traditionally have not worked together.
Here’s an interesting article on the five things that all great companies do successfully adopt AI. Listed last, but certainly not least, in the list is having a Data Driven culture. Aside from the fact that it subliminally promotes my podcast, the importance of company culture cannot be overstated.
From the article (emphasis added):
Data-driven Culture Without a strong, data-driven organizational culture, none of the above can ever be successful. Some of the world’s largest companies like Amazon, Google, and Facebook have embraced data as part of their organization’s culture. Here are some things they, and the aforementioned customers, do well:
- Treating data as an enterprise asset.
- Creating a central data strategy (a Data Hub) to integrate all types of data
- Strong data governance & data lineage.
- ML-enabled data cataloging to find data efficiently.
- Robust Master/Reference data management.
- Mixing IT-led and self-service data preparation & wrangling capabilities.
- Implementing self-service exploration capabilities to visually interact with data.
Data is an asset, potentially a very lucrative one and likely one that will either drive your business into the next decade or drive you out of business before the next decade.
If you think that the excitement around AI lacks merit, then you may want to reconsider that point of view after reading this article from Forbes.
AI and machine learning are breathing new life and business opportunities into that tired old phrase, “automating paper-based processes.” Consider this trio of forecasts that IDC predicted to happen by 2022: Sixty percent of G2000 enterprises will be AI-enabled AI will help over 50 percent of enterprise application workflows […]
Now that AI has “escaped the lab,” there are two main questions: what’s next and how is next?
One of the more pressing questions that I am occasionally asked by customers and non-AI believing developers is “AI is great and all but who else besides Microsoft, Google, Netflix, etc is actually using it?” What they’re really asking is “How can AI really benefit my business if I’m not [insert large tech company name here]?”
Here’s a thoughtful piece from Data Science Central that explores that very question.
We know we’ve entered the era of exploitation of AI/ML but the $64 Billion question is how far along the curve are we and who exactly has implemented and will implement? By the way, $64 Billion is a reasonable estimate of global market spend in roughly four or five years, about 6 times where we are today. And that investment should yield about $4 Trillion in business value in that same time frame according to Gartner.
Summary: Adoption of AI/ML by larger companies has more than doubled since last year according to these survey results from McKinsey and Stanford’s Human-Centered AI Institute. This new data gives us a much better idea of which global regions and which industries are adopting which AI/ML techniques. We know […]
It’s been nearly a year since the end of the road for Toys R Us. I recorded a Data Point last year about the mixed feelings of getting good deals on stuff from the store vs picking clean the bones of an old friend. (Listen here).
CNBC has an interesting video from last March about the rise and fall of an iconic American retailer. I disagree with the assertion that “no one saw” the big box retailers coming or the rise of Amazon. I was at the forefront of the dot com boom at Barnes & Noble in the 90s and had friends who worked at Toys R Us’ early efforts to create an online store. They saw this coming – senior management just couldn’t believe they could be bested by anyone.
Get ideas about how to build engaging conversational applications using this fun retail example that leverages services from across Microsoft.
Ben Lamm. Ben is the CEO of Hypergiant – a Dallas-based startup that Tony himself invested in! They’re working with big brands and businesses to bring in technology to solve real business problems. For example, Hypergiant recently teamed up with TGI Friday’s to create an AI-powered mixologist, appropriately dubbed Flanagan. Flanagan offers the customers the experience of personalized drink recommendations while simultaneously collecting more data about their preferences. It’s a win-win that enhances customer connection, and ultimately, customer loyalty.
In this episode of The Tony Robbins Podcast, host Ana dives into artificial intelligence and machine learning. Ana talks with Ben about these types of practical applications of artificial intelligence and machine learning, and we explore other opportunities for businesses to leverage the tech to best meet their customers’ needs. Because most industries are using outdated practices. And as we enter this new era of AI solutions, it’s time to initiate change and encourage your team to start thinking forward.
While not a highly technical talk, it’s an interesting perspective on how to position AI to business decision makers.
Business Wars is a podcast that chronicles the fight for your business, taking a peek behind the shiny logos and press releases to uncover the gritty details behind the scenes.
Fascinating stories made better with amazing audio production values and killer narration.
Below is Episode 1 of an 8-part series on the brutal business battle between Netflix and Blockbuster, and later HBO.
It all started around 1997, with a guy named Marc Randolph and his mathematician friend Reed Hastings. Randolph and Hastings knew they’d have to take on Blockbuster, but what they didn’t anticipate was that their business model would take on network television and eventually change the entire movie industry.
This was an 8-year total war that left innumerable casualties in its wake: thousands of hollowed out buildings and economic losses in the billions.
Press the play button below to listen here
The term Data Estate cropped up a little over a year ago, but what exactly does it mean?
Is it marketing-speak or something more profound?
In this DataPoint, I elaborate on the term “Data Estate” in front of an actual estate in Potomac, MD.
Press the play button below to listen here or visit the show page at DataDriven.tv
In this DataPoint, Frank talks about the term “Data Estate” in front of an actual estate.