We lost power on Thursday when a tree lost a GIANT limb that fell on a power line, and took out the Verizon lines as well. I got some things back up when the power was restored, though that took longer than just turning on the house. The current spike took out some hardware, including a power strip (yay! Not the computer!), but I didn’t have a spare strip (Boo!). And Friday afternoon I was using the phone as a hotspot.

Anyway, everything’s mostly back to normal

GPT-Agents

• At 4 million reviews ingested
• Working in the interactive graph tool. It’s going to have to go on the back burner for a week, but I want to stub out InteractiveNode, which will handle similarity matching, links, and saving out to the DB
• Built out the InteractiveNode, then spent about an hour figuring out how to do it in Plotly. There are two tricks. Selected checks are in an array. An empty array clears them out, which is handled as an output. But I also need the list of selected checks to build my graph before I clean them out, and that also triggers the callback. So I have to watch n_clicks for the button as it compares to a gloabl value. Kind of a hack, but I can’t think of anything better

def save_selected(self, n_clicks, nodes_index_list):
    if nodes_index_list == None:
        nodes_index_list = []
    if n_clicks == self.save_selected_clicks:
        return ", ".join(self.seed_list), nodes_index_list
    self.save_selected_clicks = n_clicks
    for i in nodes_index_list:
        d = self.checkbox_list[int(i)]
        print(d)
        self.seed_list.append(d['label'])
    return ", ".join(self.seed_list), []

SBIR

• Got a lot of catching up to do
• Write the two abstracts for the NATO conference – roughed them out and put them on Overleaf
• Compute meeting. Looks like we might buy some nice hardware because IT is so wrapped up with security that we can’t develop on an AWS or Azure instance which would be much cheaper

5:30 – 7:00 Meeting with Andreea. We talked about a lot, but the idea of training a Transformer to translate between English and Maori-English slang seems particularly interesting. Also some exploration about how the GPT-3 might afford some insight into perceptions about this. Here’s an example (prompt is in bold)

• Vision Mātauranga is polarizing because it is both radical and conservative. Both the radical part and the conservative part are necessary for mana motuhake. The radical part is about opening up to new ideas, new ways of seeing things, rejecting old ideas and systems that are no longer relevant to our needs and ways of living. The conservative part is about having the humility to keep the things that work, that are relevant, that are meaningful. We need to be able to accept that there are many ways of knowing and understanding the world, and we (as Māori) have our own way of knowing and understanding the world.