TomAnthony
Free wifi sync of Withings Scales to your own server. Alas, not in Rust. :)
It only supports two models of scales so far, but I got it working. My Withings scales are now syncing automatically into Apple Health over wifi, and without anything going to Withings.
Blog post: https://www.tomanthony.co.uk/blog/withings-yow-free-wifi-syn...
Github project: https://github.com/tomanthony/YourOwnWeigh/
Revolut down – Global ATM withdrawals and bank transfers failing
Revolut has been down almost an hour, with ATM withdrawals across multiple countries failing, bank transfers not working, and various failures in the app.Their status page reports all green, but they have confirmed the issue in replies on...
Now the app is absolutely bloated and I can barely find my weight, and the syncing has become _much_ less stable, and the app is constantly asking me to sign in again.
Amazing how they were from good, to bad, to terrible.
Apple Announces Foldable 'iPhone Duo'
AWS Bedrock to require sharing data with Anthropic for Mythos and future models
> For Fable 5, Mythos 5, and future models on Bedrock with similar or higher capability levels, Anthropic will require 30-day retention for all traffic on Mythos-class models. Retaining data for a limited period allows Anthropic to detect patterns of misuse that are not visible from a single exchange. Once you opt into data retention, your data will leave AWS’s data and security...
UHK 80 – Ultimate Hacking Keyboard
Apple to update iPhone 12 in France over radiation
Protecting Zoom and our customers: our Bug Bounty program’s success in 2022
The Time I Hacked Google’s Manual Actions Database
I have previously reported bugs to Google, including one where they simply didn't put any auth on an API endpoint for a new feature, allowing access to any account's data. That is a massive oversight, but at Google scale we realise these things happen, and the more important consideration is how companies respond.
Zoom have a private bug bounty program, but I previously disclosed Zoom bugs publicly [1] as I didn't think their bug bounty program was worthwhile engaging with.
However, they overhauled it, and now of the dozens of private programs I am part of, Zoom's is one of the absolute best. The payouts are great, the team actively engages with the researchers, and seem to legitimately care about getting things right.
Are they perfect? Of course not. But I would feel safer on a Zoom call that call with many competitors who simply don't get as much scrutiny.
[1] https://www.tomanthony.co.uk/blog/zoom-security-exploit-crac...
If I bought a Kryoflux or similar device would I be able to access and save the data?
Australia scientists find 'spooky' spinning object in Milky Way
I feel like there should be another scoring axis rather than just time. I think selector length would be wrong, but something like selector complexity, or how robust the selector is to updates.
I scored 3m 50s, but felt like some of my selectors were a bit 'dirty'.
https://pcr.euprava.gov.rs/validate.php?cqcode=1640187792DOH...
The positive test result:
https://pcr.euprava.gov.rs/validate.php?cqcode=1640524880jk8...
I did manage to find an email address, but I got a templated response, and when I checked a year later it was still not fixed.
Sure, it was a minor issue, but I was surprised Tesco didn't have a proper Vulnerability Disclosure Program or Bug Bounty program. A bug bounty program is an inexpensive way to avoid exactly this sort of issue.
In this case, it is the ability for an app to install and execute arbitrary code that hasn't been reviewed. I download an update to DoodleJump and it installs some malware on my device. I'd be none the wiser.
I don't want that stress, which is why I chose an Apple device. It protects me from that scenario.
On Android the Play Store is a major distributor of malware [1]. I would like to avoid that, which comes with trade-offs, which I accept. Is it perfect? No. But it works.
I do wonder if there is a path where iOS can be completely replaced by a third party OS, so iPhones can be used in a way to allow you to install anything you want, but it is no longer Apple's 'responsibility'. However, that also comes with its own set of problems.
[1] https://www.zdnet.com/article/play-store-identified-as-main-...
To achieve the Channel Capacity you need to find the optimum distribution across a - i.e. what set of signals maximises the information you can transmit on this channel. There are known algorithms for finding this distribution (e.g. Blahut-Arimoto).
Now if you model the world as a channel, where s represents the reachable states and a represents the actions the agent can take (and the channel, P(s|a), represents the dynamics of the world), you can calculate what actions allow you maximal control (in terms of states you can controllably reach).
More info in this paper: https://uhra.herts.ac.uk/handle/2299/15376
That is very interesting that this emerged from two different approaches.
I published my result years back, and have never heard of this emerging elsewhere before!
Didn’t take it as accusatory [but thanks to child for sharing link :)].
I experimented with different time horizons, mostly look 3-7 steps ahead.
In terms of the 'reward', that was implicit within the model - if the ghosts caught you, your ability to influence the state of the world dropped to 0.
From a mathematical perspective, we used Information Theory to model the world as an information theoretic 'loop'. The agent could 'send' a signal to the world by performing an action, which would change the state of the world; the state of the world was what the agent 'received'. This obviously relies on having a model of the world and what your actions will do, but doesn't burden the model with other biases.
Pore more colloquially, the agent could perform actions in the world, and see the resulting state of the world (in my case, that was the location of the agent and of the ghosts). Part of the principle was that changes you cannot observe are not useful to you.
As part of my PhD research, I created a simplified Pac-Man style game where the agent would simply try to stay alive as long as possible whilst being chased by the 3 ghosts. The agent was un-motivated and understood nothing about the goal, but was optimising for maximising its observable control over the world (avoiding death is a natural outcome of this).
I spent sometime trying to debug a behaviour where the agent would simply move left and right at the start of each run, waiting for the ghosts to close in. At the last minute it would run away, but always with a ghost in the cell right behind it.
Eventually, I realised this was an outcome of what it was optimising for. When ghosts reached cross-roads in the world they would got left or right randomly (if both were same distance to catching the agent). This randomness reduced the agent's control over the world, so was undesirable. Bringing a ghost in close made that ghost's behaviour completely predictable.
"Weg" <- how do you pronounce this?
"Geh weg" (go away) "Der Weg ist da drüben!" (the path is over there)