I use prezi video. But it’s very clunky. So really I use Canva for creating the slides and then Prezi video.
This seems much much better.
If it’s as good or better I’ll drop Prezi and switch completely. Pricing seems good, I don’t share the same opinion of many commenters here. Perhaps because I’m on zoom all day both in 1:1 and 1:many including workshops where I’m the speaker then I might be the right ICP
Do you have samples of time-based cohort analysis? Most other solutions out there struggle to do the steps to generate time-based heatmaps and line graphs of cohort analysis. Averages, medians, and anything that can be done on a spreadsheet by a high schooler, GPT does well with.
In our experience Dot can come up on the fly with cohort analysis charts if the underlying data is well structured. In most cases however, some level of explanation, example or data preparation is needed for robust and repeated cohort analysis. Also for good query performance it's usually best to precalculate some things.
Every time I try to do time-series cohort analysis or Lifetime LTV expandability on many of the analytics tools out there I get frustrated and up resorting to Tableau. It took mixpanel a decade to finally get some of it right but it's still too simple. I don't like tableau but it sure beats doing custom SQL queries all the time. How do you handle cohort analysis?
Paper contributes to debate about abilities of large language models like GPT-3
Evaluates how well GPT performs on the Turing Test
Examines limits of such models, including tendency to generate falsehoods
Considers social consequences of problems with truth-telling in these models
Proposes formalization of "reversible questions" as a probabilistic measure
Argues against claims that GPT-3 lacks semantic ability
Offers theory on limits of large language models based on compression, priming, distributional semantics, and semantic webs
Suggests that GPT and similar models prioritize plausibility over truth in order to maximize their objective function
Warns that widespread adoption of language generators as writing tools could result in permanent pollution of informational ecosystem with plausible but untrue texts.
The blackout in 2003 in NYC had no looting or violence.
The blackout in Maracaibo Venezuela in 2019 had 350 stores looted and 550+ people arrested.
The difference was the economic and social challenges in 1977 in NYC and 2019 in Venezuela. A recession and high unemployment.