The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 20 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Horizontal AI Suites Like Salesforce Einstein Are Just Marketing Fluff
“When we hear marketing terms like Einstein, or Sensei, or pick your other dead male inventor, That, that approach applied to a horizontal set of software problems simply doesn't make sense because the interesting stuff recruiting data or hiring data or our dat…”
Speed Matters More Than Quality or Optimization in Data Products
“Speed is more important than quality, which is more important than optimization.”
De Datta: All AI, machine learning, and data science is vertical-specific
“All data science And all AI and all ML is fundamentally vertically specific. Which is the dirty secret about AI and ML powered businesses. They are fundamentally vertical problems.”
AI and Machine Learning Buzzwords Have Zero Value in Enterprise Marketing
“AI and ML has zero value in marketing.”
Bloomreach Employs Zero Dedicated Data Scientists
“Yeah, so first of all, we don't have any data scientists. We only have engineers who understand data science.”
Bloomreach Touches 20% of All US E-Commerce Transactions
“We power almost 20% of e-commerce transactions in the U.S. At some point hit a Bloomreach server of, ah, of some kind.”
Cutting Autosuggest Latency Outperformed All Algorithm Accuracy Gains
“In, in the course of building the first versions of Autosuggest, they were, they returned data back at the level of about a 150 milliseconds. Today, they return data back at the level of 10 milliseconds. And the delta between that was more important than anyth…”
De Datta: Innovation mostly happens outside of your product
“And I think what I've learned from this is really that innovation mostly happens outside of your product.”
Raj De Datta: Data science software requires workflow or infrastructure integration
“At least in software, enterprise software, the value of data science is, is hugely valuable as a source of differentiation. But it's only valuable if presented along with either a workflow problem or an infrastructure problem.”
Raj De Datta: Data startups need not match tech monopoly salaries
“If you're an entrepreneur building a business around use of data and data science, You don't have to pay what the unnamed tech monopolists pay.”
De Datta: Every enterprise requires three core digital experience platforms
“The way we see the world is more and more every enterprise has three core platforms that power their digital experience, or their digital business.”
Raj De Datta: Software applications and data platforms have no value without each other
“Bloomreach has, is always, you know, I struggle to describe it about whether it's a software company or whether it's a data company, because really one without the other has no value.”
Raj De Datta: Consolidated data sources create massive platform dependency risk
“There is arguably no bigger platform dependency than if your data largely comes from a consolidated set of sources”
De Datta: SaaS plus data science demands a new customer success model
“But today, because this is a handshake between our SaaS environment and the customer's data, that, that handshake requires a completely different, ah, model for customer success and support. Because what we have learned in being a data science plus SaaS compan…”
Algorithms Are Useless If Users Cannot Interpret and Trust the Outputs
“That at the end of the day, if people can't interpret it, if people can't make sense of it, if people can't trust it, then it really doesn't matter what you did.”
Practical Enterprise ML is 20% Algorithms and 80% Systems Engineering
“So, you know, when you start getting into problem areas, you start to find that really that what you need to solve a practical problem is like, 20% algo and 80% systems, you know, in many cases.”
Bloomreach Monetized Demands for AI Explainability as a New Analytics Product
“At a certain point, our customers kept asking us, how is the algorithm making a decision about what to do? And so what we did is we built an analytics tool and sold something to them. So we effectively turned the question into a product, and then monetized the…”
De Datta: Adobe is Bloomreach's largest competitor with a $1.5B business in their space
“Yeah, at this point, you know, the companies at a scale where I would say our largest competitor is the Adobe stack. So Adobe has about a one and a half billion dollar software business in our space, and they're the leader in our space, and we admire them a lo…”