wrhn

Recent submissions

Comment · 3 years ago
I just got it to install git and clone (the non existent) repo https://github.com/openai/assistant, and am now browsing it’s own interpretation of a repo with a lot of python code, including directories like “training”, “output”, “parsing” and with files with content like this:

  import json
  from collections import Counter
  from typing import Any, Dict, List, Optional, Tuple

  import numpy as np

  from openai_secret_manager import get_secrets

  from assistant.constants import MAX_OUTPUT_LENGTH
  from assistant.utils.string_utils import strip_html
  from assistant.utils.text_utils import split_text_into_lines


  class Output:
      def __init__(
          self,
          generated_text: str,
          response: Optional[Dict[str, Any]] = None,
          score: Optional[float] = None,
      ):
          self.generated_text = generated_text
          self.response = response or {}
          self.score = score
On a side note it feels like each command takes longer to process than the previous - almost like it is re-doing everything for each command (and that is how it keeps state).
Comment · 3 years ago
Can’t help you with the keys or ID (yet), but I exclusively use the stored cards on my Apple Watch for payment. It is so reliable (in Norway) that I haven’t brought my wallet on normal days in 2+ years.

Even on vacation in Northern Europe (Belgium, Netherlands, France, Germany) and on a business trip to the US (California+Texas) this year, I very rarely had to use the physical cards. NFC just works. Everywhere.

I still bring the cards on important occasions or when going further than a normal drive, though - a testament to the fact that the day you’re longing for is not _quite_ here yet.

Comment · 4 years ago
This one? I remember it as an earnest description of the difficulties the WSL team had with the speed of NTFS - and I think it was one of the reasons for the switch to virtualisation in WSL2.

<https://github.com/Microsoft/WSL/issues/873#issuecomment-425...>

Comment · 5 years ago
I like the one about handling your priorities when under pressure: “Aviate, Navigate, Communicate” https://www.faa.gov/news/safety_briefing/2018/media/SE_Topic...
Comment · 5 years ago
When it comes to the problem of targeting, one interesting and promising tech is photochemical internalisation [https://en.m.wikipedia.org/wiki/Photochemical_internalizatio...], where you put the mRNA inside photosensitive molecules (and not lipids) and then shine some light on the tissue/organ where you want the mRNA delivered. Where activated by the light, the molecules then enter the cells, dissolves and deliver the mRNA. The Norwegian company PCI Biotech has a tech they call fimaNAc for doing this with naked mRNA.

https://www.pcibiotech.no/nucleicacids

This presentation has a lot of illustrations and explanations:

https://www.pcibiotech.no/s/PCI-Biotech-SMi-RNA-Therapeutics...

Comment · 10 years ago
I've had 920, 930 and I'm now using a 950 as my main phone: The hardware is superb, and I really like the OS (running Insider Preview Slow Ring). There has been a steady stream of Windows 10 Mobile Insider Preview updates throughout the last year, bringing both new features and stability. In user interaction and interface consistency it is now much closer to iOS (or what iOS tries to be) than Android is.

That being said, it is pretty obvious it is a minuscule platform; apps are often lagging behind their iOS/Android counterparts, and there are some obvious ones missing (like Snapchat and Pokemon Go).

It is kind of sad really; I think it would be healthy with more than two major players, and Windows 10 users will probably feel quite at home in Windows 10 Mobile.

Comment · 11 years ago
To the people suggesting ELK i just want to ask if you have actually used it in production? Like for real bughunting and investigating support requests?

As much as we absolutely love ElasticSearch for our other indexing needs, we find it quite hard to get the LK-part of the stack to deliver as promised. Kibana may serve up nice graphs and charts, but when you need to drill down into a large amount of log data, we often feel like loosing both overview _and_ detail.

It might very well be that we are to blame, and that we are just doing it wrong (tm) - but I would love to hear how other people are leveraging the ELK stack in production environments?

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