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We have had a similar system implemented in the UK for a few years now (can't even remember how long). I recall an alarm going off on my phone I don't recall too much fanfare in the lead up to it to be honest. I found it quite amusing how the press were making a big deal about in in Australia... There were some issuing health warnings about it, Of course,, I didn't get it while back here, but I guess it was a not much in the press period.

My response was the short response and omitted things like path dependent or independent simulations, etc. Regardless of the AI model the fundamental coding concepts are more or less the same. Take for example, an agentic model. It takes the input, uses mainly neural networks to work out the response, and instead of responding by describing the output as in a LLM, it performs actions automatically. This is the bit that is discrete coding. As an example, you may have agentic AI that automagically responds to client service calls. At the end of the call it determines it can refund the client. Instead of telling a customer service rep the refund is within corporate policy and should be done, it informs the client and arranges a refund against the card or client bank account without human intervention. The same for a robot. It uses neural networks to read its environment and interactions and determine what to do, The discrete bit is then instructing the servo motors (or whatever hardware) to do something such as coordinating taking another step etc, The differences between your LLM and more specific AI use cases are the data sets they are trained on, the guard rails in place and the outputs being directed. And the results feedback loop as well.

I believe that is a known fault. A few other interesting points: The alert can appear even if you're on a phone call or using another app. It works on most modern phones, tablets, and some smartwatches. Older phones or devices with unsupported operating systems may not receive it, or may display headings such as "Presidential Alert" or "Extreme Threat Alert" instead of "AusAlert".

Mine worked okay, was loud and clear. However stupidly it came with headline text of "Presidental Warning" WTF? Made me almost immediately reject the message. Phone is a cheap android on Telstra.

I can't believe the people whinging about it and wanting to know if they can opt out. Hopefully just a minority. On a similar subject, whilst on my recent NZ trip, my phone sounded an unusual alarm at around 4AM. It was an earthquake warning. I assumed it was from a government service but it was not. It was actually from Google, which uses its millions of Android phones to detect P or Primary waves. For some people, the alert sounded before the quake could be felt. Why phones woke thousands before 5.9 magnitude Taumarunui earthquake "The Android Earthquake Alerts system uses the accelerometers built into millions of smartphones to detect the first seismic waves generated by an earthquake. Known as primary, or P-waves, these travel faster than the stronger secondary (S) waves that typically cause the most noticeable shaking and damage. This data is automatically anonymised and reported in the background to Google, and once there are enough matching reports, an alert gets pinged out to all Android users who might be affected. Depending on the estimated strength of the earthquake, users receive one of two alerts. A 'Be Aware' notification is sent for earthquakes below magnitude 4.5, while larger events trigger a louder 'Take Action' alert designed to grab people's attention, even if their phone is on silent. The system is not an earthquake predictor, but rather rapidly detects an earthquake after it begins and uses the difference in speed between the initial P-waves and the slower, more destructive shaking to provide advance warning to people further from the epicentre. The technology is now available in more than 90 countries, although its effectiveness depends on how many Android devices are nearby."

We showed our kids some youtube of the Goodies, they thought we were insane for watching this. yet they watched shows with a talking slice of pizza theat was friends with a hotdog and a talking flying. tiger.

We should not be too dismissive of what we experienced. After all, it was a test. The system was being tested to see if it worked. It was the 'beta' version. I suppose we should congratulate the testers for making it clear that they are seeking feedeback. Did you receive the test? If you did not, what equipment do you have? Where were you at teh time of the test? Actually, a bloke came into the shop just after 2:00pm and was asked if he had heard the alarm. 'Nah. I left my phone in the car.'

Not sure if rearranging would help at this stage. They need to start bolting them down for the storm that's going to hit in four months time.

The alarm was a bit of an anticlimax after all the hype on the radio about it. I was getting ready to hold my ears for the event but it just sounded like a budgie chirping in a tree about twenty metres away. And that was with the phone on full volume. With the radio on, you could barely hear the alarm. Taking into account it was only a test, the finished product will probably be a lot more effective. It will need to be a lot louder and longer for a start. The text was in very big print, so easy to read.

Rearranging the deck chairs on the Titanic??????

I remember back to the 2000 Olympics in Sydney. A farmer whose place was under an incoming flight route planted a big paddock with canola and a ceral grain in the design of the logo. The logo could be seen from on high.

Rejoice rejoice. Step 1 of saving our state. Most corrupt government in our history.

Jacinta Allan served as the 49th Premier of Victoria and leader of the Victorian Labor Party from 2023 to 2026. Her tenure ended on 28 July 2026 when she resigned ahead of a leadership challenge from her deputy, Ben Carroll.

Canola time was always a pretty time to fly.

City Slicker is so Passe'. You've been in the country too Long. Canola Is a bright colour. It comes up as a Desktop on my PC regularly.. Nev

"I asked my wife why she didn't want me to get a tattoo. She said she didn't like drums and bagpipes."

I didn't want to start a new thread to discuss the testing of the Emergency Warning System, so I'll comment here. Did the phones of all around you sound the alarm? I was in a shop with about ten people. The shop was within a few hundred metres of the TELSTRA tower and in straight line view. Some of the phones sounded the alarm and some didn't. Also, I had announced the impending arrival of 2:00pm a few minutes before. Later that evening I watched a clip about the event from the Channel 9 News. It reported similar results in a city, probably Sydney. What got my goat up about that clip was that it purported to show a farmer standing in a field receiving the alarm. Problem was that the farmer was standing in a field of flowering canola Canola does not get to the stage depicted until about September. I wonder which city slicker produced the clip.

As is my knowledge of programmming. Thanks for your input, but it shows that the average person will never properly understand how this tool works. Also, your response dealt with Large Language Models. Aren't ther other ways that AI is used such as finding correlations from, say data colleced from sensors measuring physical events?

This is you being quick?

Isn't that the MAGA plastic surgery look?

How does it decide how the probability maps should be altered to get a better result?

I don't have a lot of time, so. I will try to be quick (given I have only skimmed the posts since OME asked the question). The algorithm is not predictive in the sense of predicting the future. The predict what you meant by what you typed, and whether or not their response will make sense. For example, if you asked how many legs a dog normally has, it will predict that 4 is the correct answer; not that my some genetic mutation caused by increasing radiation in the atmosphere, they will grow 5 legs in the future. Well, not unless you ask it, anyway. But even if you did, it would use existing data to try and predict the correct answer based on the data it has, not to perform its own scientific analysis and determine for itself. It may take the factors and apply it to an existing theory to mimic scientific analysis and intelligent conclusion drawing, but it is not doing that itself. In terms of AI implementation, it is likely to be a lower level language such as C or C++ = not python because it is too slow; the end point AI functions can be done in Python, but that is on a precomputed large dataset - usually. The algorithm will be surprising small.. usual Bayes theorem or something similar. It is able to be repeated over billions of nodes - or data points. The code will likely be recursive in building the precomputed data set to apply simpler probability maps across the data you provide. And it will likely be recursive in using that map to answer your question. By recursion we mean the same code calls itself.. So, you will be able to crawl heterogenous data sets, over and over using the same code developing deep nested stacks (well, heaps to be accurate) of responses from which it will map as many of the different types of data that can be used to probably represent what ever bit of data it actually is. Tagging data is old these days.. That is what these maps do. This of something like if you type the number 4 into your LLM. That is easy, because it is represented by whatever coding mechanism you are using... and there are only a handful of coding mechanisms - ASCII, EBCDIC (not used anymore) UTF-8, UTF-16 and a few others. But, they are translated to the discrete representation of 4 to AI. No thinking required. Now, say you provide it a scanned doc, which contains the number 4 somewhere. It has to read all of the pixels and look at the shape of each character to determine if it is a letter, number, whitespace, part of a diagram, etc. Say it worked out it was a digit. Now it was to work out what digit it is? It has to look through its maps/nodes and get the most likely digit it is.. it predicts what digit is is because it spits out a probability index of what it has been taught what that digit could possibly be, across any digit which it may match. Is it a 4, or is it a H.. It also has to take into account font. As you know, a 4 can be represented very differently in different fonts... So, the sort answer to your question is that there will be a set of probability algorithms that will read data, build probability maps, and then apply the same probability algorithms to inputs and compare to what it has learned. Machine learning means it constantly refines its probability maps. The technical implementation is likely to to be a lower level language (a lot of Python maths/stats libraries are written in C++).. and there will be a lot of recursion.

I did a search in case I missed it being posted, but Bill Oddie of Goodies fame (and later a wildlife show presenter) passed away yesterday aged 85.

Yes, that’s why I never won Lotto. To be fair that wasn’t really a good test of the methodology. Lotto results are ultimately random, so there was no long term pattern to them that the algorithm could have been trained on to predict the next draw. Had there been an underlying bias it’s possible that the algorithm could eventually have improved the odds in my favour by picking a set of numbers that more likely than not contained next week’s winning numbers. That was my aim at the time. It didn’t work but the programming was fun. While my finite state machine approach was a far less sophisticated AI model than the technology behind ChatGPT or Claude, the principle of using a data set to train an algorithm to mimic human learning by modifying itself by trial and error until it can produce answers to questions that appear logical and intelligent remains the same. Of course it doesn’t mean that the answers are right.

She must be Russian.