Three days later, Pucci, now 50, followed her in a car and started to yell at her about a man she was dating.
“You thought you’d get away with this. I am in your car. I am in your maps,” he shouted at her, according to the police records.
[...]
“The victim has not been able to drive certain speeds and on most recent occasions throughout this period, [the accused] has turned on ‘Valet Mode’ which immediately reduces the speed to 40km per hour causing significant safety issues for the victim on the road”, the police documents stated.
Of course this incident shows why I wouldn't want a car with this capability. Because when an asshole like Pucci can do it, the operator of the remote services can do it too!
That's the worst villain monologue I've ever heard, but unintentionally funny. Somehow appropriate for someone sharing his name with a JoJo's Bizarre Adventure villain.
This reminds me of the "I am in your walls" meme, just so much more creepy.
I really hate vehicles. But I especially hate those that aren't able to be change to an entirely local mode, with no non-GPS radio further than like 10 meters. But then again, that wouldn't make line go up since we can't charge for/control basic features, so it is becoming more and more a rarity.
I tend to agree that making the sugar measurements more robust is worth more than measuring the ketones at all. However, low sugar and high ketones can happen. And just getting notified when ketones pick up can be worth something too. The additional measurement is not useless seen from my perspective.
As an example: I was on a study that gave T1D patients Dapagliflozin (Farxiga). During the study, while on a long hike, I was hovering at low sugar and consequently insulin supply was mostly cut off for an extended period. As I started to to feel unwell, I measured ketones. I was briefed as preparation for the study to measure ketones when something seems wrong. Otherwise I wouldn't have thought of measuring ketones. Might not even have carried the kit.
On that occasion, the ketones were way above 1 mmol/l: a very high value. Protocol would have required me to call the study doctor due to the high level. Since it was a Sunday, I spared her, shot some insulin, ate a sandwich, and continued my hike. I could do that because I was not alone on that hike. I knew that if my situation deteriorated, somebody would be around to call rescue.
At the study debriefing I mentioned the incident and they said that adding to the effect of the Dapa, I was probably dehydrated, which led to the rare situation of both low sugar and high ketones.
All in all I think that if the sensor makers exhaust possible improvements for the glucose, it can make sense to add the ketone measurement as a safeguard. Having high sugar can have many reasons, and it often takes me a while to get to measuring ketones. Getting the signal of rising ketones, I would react faster a few times a year in situations where my insulin supply is broken.
Yes, this is true. There were also news about some Americans rationing insulin due to cost. Their blood sugar levels were normal, but they had high ketones and unfortunately died of DKA.
When I got first diagnosed, we were given ketone urine strips and told to use them, with the advance of glucometers, we forgot about ketone testing.
I used Ansel for a while, and I agree that Darktable is suffering from feature creep. Ansel right away had some usability improvements. But the amount of regressions introduced was wild. The anger you can read in the messaging was apparently also employed to cut code, and things got flaky. In the end some features I used stopped working in all releases I tried, and I went back to Darktable. Maybe Ansel is stabilizing now, and I should try again.
Yeah why is 10% success bad? What is the tradeoff between spent effort and missed cures if we try to tweak the success rate by killing prototypes earlier in the pipeline? While reading I was expecting a reasoned argument... that was stubbornly not coming around.
It's mostly that we have too many false findings pre-clinical trials, most drug targets validated in models that don't actually hold up in humans, so a huge share of the 90% failure is money and years spent testing candidates that were never going to work. That inflates the number of potential candidates that are likely wrong, due how we select them.
There are ways used right now that are working towards reducing those false findings by looking at actual humans, their biomarkers and whenever or not there's an associated molecule to the condition that we would like to pass onto others. It will not kill prototypes, instead it will discourage us from going through a prototype at all by going for better candidates instead.
You can say you don't want the bad guys to get the capability until and after the reality hits you. But this arrogant hope stands in the way of developing an effective response. The handlers of closed models would like you to be dependent on them for protection, this much is clear.
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