AI fails

[swee'pea99]

Is this a fail?

"Sorry Dave, I did that."

 

[briantrumpet]

Maybe worth checking that AI is picking an appropriate photo for articles.

 

[matticus]

(I do hope that is for real!!! )

Shades of Jackie/Jockie Wilson on TOTP.

 

[briantrumpet]

(I do hope that is for real!!! )

Shades of Jackie/Jockie Wilson on TOTP.

Can I pretend that it is?

 

[briantrumpet]

OK, this is genuine I think. Chat GPT doing as good a job as it did for MattGPT.

 

[Ian H]

OK, this is genuine I think. Chat GPT doing as good a job as it did for MattGPT.

View attachment 14295

Perhaps it's distinguishing between newer and older definitions of 'gay'.

 

[Beebo]

I was always suspicious of Wogan.


View: https://youtu.be/OlH1af4siKQ?si=PasFPJ9Qzj-pEq2L

 

[briantrumpet]

 

[Ian H]

Private Eye.

 

[Psamathe]

Maybe, maybe not an AI fail but a development I find interesting:

Most weather forecasts get see are based on climate models, basically modeling the physics of the atmosphere from a gievn starting point.

Not a very reputabl;e forecaster (ECMWF is the European Centre for Medium-Range Weather Forecasts (https://www.ecmwf.int/en/about). The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation supported by 35 states.) has added a non-modelled forecast generated by AI.

Their description of the new forecast

"AI as applied to weather forecasting is radically different to the physics based techniques currently widely used. There is no need to explicitly simulate the physics of the atmosphere; this is currently implicit in the re-analysis training data used. The user may not even know the impact of the local or large scale physical effects upon the process.
The major difference between forecasting techniques is:
• traditional weather forecasting models assume a reasonably accurate physical model of the Earth system. The biggest unknown is the initial conditions from which to start the forecast.
• AI and ML do not explicitly handle the physics of the atmosphere. The aim is to define an empirical model that links observational data at one time with similar data for a short time later. Currently the empirical model has been developed (or trained) on reanalysis fields as observations and compared with reanalysis fields for the later time. Having found this empirical model it can be used iteratively to compute forecast fields at successive time steps into the future.
Before an AI forecasting system can be implemented it has to have been trained on a large amount of observed data. At ECMWF the AIFS is trained mainly to produce six hour forecasts."
(https://confluence.ecmwf.int/display/FUG/Section+2.2+Artificial+Intelligence+Model)

It doesn't replace their normal modelled forecasts but is additional.

So a comparison for next 2 weeks forecast (the AIFS bottom graphs are the AI forecast for cloud and rain
Note: the ECMWF HiRes covers limited time so the right side of the plots is NOAA GFS whereas the AIFS covers a longer period.

The light grey is total cloud cover the 3 darker greys towards to top are low, mid and high altitude cloud cover and the blue (at the bottom) is rain.

And for wind:

The yellow line is 20 kt marker, green plot is wind, red plot is gusts (looks like AIFS doesn't forecast gusts).

 

[briantrumpet]

https://www.nature.com/articles/d41586-026-01100-y

Got sore, itchy eyes? You’re probably one of the millions of people who spend too much time staring at screens, being bombarded with blue light. Rub your eyes too much and your eyelids might turn a slight, pinkish hue.

So far, so normal. But if, in the past 18 months, you typed those symptoms into a range of popular chatbots and asked what was wrong with you, you might have got an odd answer: bixonimania.

The condition doesn’t appear in the standard medical literature — because it doesn’t exist. It’s the invention of a team led by Almira Osmanovic Thunström, a medical researcher at the University of Gothenburg, Sweden, who dreamt up the skin condition and then uploaded two fake studies about it to a preprint server in early 2024.

Osmanovic Thunström carried out this unusual experiment to test whether large language models (LLMs) would swallow the misinformation and then spit it out as reputable health advice. “I wanted to see if I can create a medical condition that did not exist in the database,” she says.

 

[briantrumpet]

If this usage did stick, it'd be quite funny.

 

[briantrumpet]

A new report on the accuracy of AI overviews

https://futurism.com/artificial-intelligence/google-ai-overviews-misinformation

"The improvement between Gemini 2 and Gemini 3 may be papering over a more serious flaw. In the Oumi analysis, Gemini 2 provided answers that were “ungrounded” 37 percent of the time, meaning the AI Overviews cited websites that didn’t support the information they provided. But with Gemini 3, this jumped to 56 percent. On top of suggesting that the AI is pulling facts out of thin air, ungrounded responses make it difficult for users to verify the AI’s claim."

 

[Pblakeney]

A new report on the accuracy of AI overviews

https://futurism.com/artificial-intelligence/google-ai-overviews-misinformation

"The improvement between Gemini 2 and Gemini 3 may be papering over a more serious flaw. In the Oumi analysis, Gemini 2 provided answers that were “ungrounded” 37 percent of the time, meaning the AI Overviews cited websites that didn’t support the information they provided. But with Gemini 3, this jumped to 56 percent. On top of suggesting that the AI is pulling facts out of thin air, ungrounded responses make it difficult for users to verify the AI’s claim."

Are they using AI to check for accuracy? 🤣

 

[TailWindHome]

Will we use this thread when the AI boom becomes the next 'once in a generation' economic meltdown or start a new thread?

https://www.cnbc.com/2026/04/15/allbirds-bird-stock-shoes-ai.html