why aren't all 7 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
Prediction Not checkable as stated
Kiela: Companies Will Stop Trying to Build In-House AI Within Years
“Very often they think they can do it in house.
And so I think that belief is probably going to go away in the next couple of years where people realize that this stuff is a little bit more difficult than they,
Initially thought.”
Prediction Not checkable as stated
Kiela: Top-Down Enterprise AI Budgets Will Dry Up After Failed Pilots
“That money is temporary and it's going to dry up. And so it's, we're going to have a couple of cool pilots and demos, and then at some point it doesn't work and we will move on to the next hype train.”
Insight
Kiela: Enterprise AI Demands End-to-End Retrieval Models Over Parametric Monoliths
“And so we think that's not what we now call a language model. So it's not one big parametric monster. It's something a bit more elegant that has the retrieval kind of built in. It's a retrieval augmented language model and is strained end to end so that it can…”
Insight
Kiela: Enterprises do not need model fine-tuning when RAG is available
“You don't have to fine tune your model. It feels very intuitive. We have this great data set. We own it. It's our data. So we need to do something useful with it. So we need to fine tune our own language model. And so the companies who are offering that servic…”
Opinion
Kiela: First-Generation LLMs Are Not Ready for Enterprise Deployment
“We think language models are great first generation technology, but they're not quite ready. We see a lot of frustration in the market around that.”
Insight
Kiela: 95% of Enterprise AI Use Cases Fall into Three Buckets
“I think if you look at the landscape of use cases that we see right now, there are roughly three big buckets. So one is around information discovery and information synthesis... Then there's a lot of hierarchical summarization use cases... And then there's a l…”
Prediction Not checkable as stated
Kiela: By 2030, Workers Will Manage Fleets of AI Co-Pilots
“What I think is going to happen is that there's a couple of CEOs on the stage here, and I'm sure there's a couple of CEOs in the audience, so we will all be our own CEO of our little company of AI co-pilots that are going to be doing a lot of very boring, mund…”