Tootfinder

NYC-based Protege, which prepares and sells real-world datasets like lab results and sports footage for AI training, raised a $25M Series A led by Footwork (Natasha Mascarenhas/The Information)
https://www.theinformation.com/articles/one-year-old…

The One-Year-Old Startup Notching Data Deals For Model Makers
Companies like Scale AI and Surge have proven there’s a market for human-labeled data, like professionals’ answers to complex math or law questions, that AI research labs can use to train their models. Now, a young startup is tapping a similar opportunity, linking large model makers and AI ...

"In theory, AI model makers could eliminate hallucinations by using a dataset that contains no errors."
I think someone has fundamentally misunderstood the technology. Developing a model using a 100% correct training dataset does not mean that the resulting AI will be able to correctly answer questions that were not in the training data.
Over-fitting is a thing.

OpenAI says models are programmed to make stuff up instead of admitting ignorance
: Even a wrong answer is right some of the time

What is the best (and safest) way to trigger a GPIO pin on a Raspberry Pi from a 5V microcontroller?
(An Arduino, in this case.)
I think the answer is a level shifter, but there's also an optoisloator/optocoupler, and of course a few resistors (though that one is probably the least safe.) A relay could work but seems like silly overkill.
#microcontroller

Evaluating the Quality of Open Building Datasets for Mapping Urban Inequality: A Comparative Analysis Across 5 Cities
Franz Okyere, Meng Lu, Ansgar Brunn
https://arxiv.org/abs/2508.12872

Evaluating the Quality of Open Building Datasets for Mapping Urban Inequality: A Comparative Analysis Across 5 Cities
While informal settlements lack focused development and are highly dynamic, the quality of spatial data for these places may be uncertain. This study evaluates the quality and biases of AI-generated Open Building Datasets (OBDs) generated by Google and Microsoft against OpenStreetMap (OSM) data, across diverse global cities including Accra, Nairobi, Caracas, Berlin, and Houston. The Intersection over Union (IoU), overlap analysis and a positional accuracy algorithm are used to analyse the simil…

Fun fact: Did you know you can play "Zork" & any number of classic Infocom games using #Microsoft #Copilot as a z-emulator? Visit https://copi…

Microsoft Copilot: Your AI companion
Microsoft Copilot is your companion to inform, entertain, and inspire. Get advice, feedback, and straightforward answers. Try Copilot now.

Drei chinesische Gruppen als Angreifer auf Sharepoint-Server identifiziert
Eine Analyse von Microsoft nennt drei verschiedene Gruppen aus China als Angreifer auf die jüngste Sharepoint-Lücke. Dabei dürfte es aber nicht bleiben.

Measuring Informativeness Gap of (Mis)Calibrated Predictors
Yiding Feng, Wei Tang
https://arxiv.org/abs/2507.12094 https://arxiv.org/…

Measuring Informativeness Gap of (Mis)Calibrated Predictors
In many applications, decision-makers must choose between multiple predictive models that may all be miscalibrated. Which model (i.e., predictor) is more "useful" in downstream decision tasks? To answer this, our first contribution introduces the notion of the informativeness gap between any two predictors, defined as the maximum normalized payoff advantage one predictor offers over the other across all decision-making tasks. Our framework strictly generalizes several existing notions: it subsu…

“The Ring has passed to the dominion of Men… and Men promptly sold it to Google Ads.”
“There is no evil in the world that cannot be containerized…”
The Council of Elrond, reimagined in /etc/middle-earth.conf
Elrond (Linus Torvalds):
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“Strangers from distant distros, you have been summoned to answer the threat of the Cloud. Never before has such open source stood together. The time of the monolith is over. The microservice rises.”
Ganda…

Query Answering under Volume-Based Diversity Functions
Marcelo Arenas, Timo Camillo Merkl, Reinhard Pichler, Cristian Riveros
https://arxiv.org/abs/2509.11929 https://

Query Answering under Volume-Based Diversity Functions
When query evaluation produces too many tuples, a new approach in query answering is to retrieve a diverse subset of them. The standard approach for measuring the diversity of a set of tuples is to use a distance function between tuples, which measures the dissimilarity between them, to then aggregate the pairwise distances of the set into a score (e.g., by using sum or min aggregation). However, as we will point out in this work, the resulting diversity measures may display some unintuitive be…

Mittwoch: Autonomy-Schadenersatz für HP, Sharepoint-Angriffe aus China
Übernahmeschäden geringer als beklagt Microsoft nennt Sharepoint-Angreifer Sportmodell von Opels E-SUV IT-Fachkräfte für EU Apple gegen Spyware im Iran