Hello again!

Everyone thought the stupid Brit had faded away, well…not so fast :slight_smile:

I was disappointed to discover that my tame beekeeper was more interested in Gott über den Bienen so my acoustic gathering project got undermined by propolis - gods work, truly, it was quite distinctive in the recordings unsurprisingly

now that AI is taking leaps and bounds courtesy of Microsoft and Google should we reconsider how this could be used in an open source community manner?

I asked ChatGpt4 its opinion on my previous efforts - well! now I discover I was climbing the impossible beehive!

Am thinking of taking up this fascinating work, put my money where my mouth is…plus bees are the worlds’ workers doing God’s work [as my neighbour should know].

Any future in AI and beehives?

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I would not count on all things written in the internet and so particular not on bee biology expert knowledge chatty (not?) has. There are a lot of frequency assumption – what happens in the bee hive at which dominat frequency – especially a time ago from people selling a bee sound app. I would doublecheck the facts so that we do not spend time on the wrong place.

So I would definitive count on this recommendation:

  1. Collaborate with bee experts


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Hey John, I’m also trying to figure out how to measure/analyze sound data (ML). I’d love to connect and maybe brainstorm together. Having read the peer lit. on honeybee sound, it’s clear to me that we’re not sure where to position microphones within a hive and if there are differences based on this … so that’s where I’m starting. Can we chat?

maybe even better: quadruple-check! because LLMs are producing mistakes by design (because they pick random tokens every once in a while as described by stephen wolfram in his essay “What Is ChatGPT Doing … and Why Does It Work?”).

and if it has to be LLM-ai, we should start to check out LAION, a public non-profit organization (e.V.) from hamburg/germany, that

“provides datasets, tools and models to liberate machine learning research. By doing so, we [they; mois] encourage open public education and a more environment-friendly use of resources by reusing existing datasets and models.”