#Microsoft#Technology#AI
Microsoft patched a Copilot Studio prompt injection. The data exfiltrated anyway.
Microsoft assigned CVE-2026-21520, a CVSS 7.5 indirect prompt injection vulnerability, to Copilot Studio.
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Data Science
Explore articles tagged with Data Science
#AI#Artificial Intelligence#AI Models
Why The US-China AI gap closed. The responsible AI gap didn’t
The assumption that the US holds a durable lead in AI model performance is not well-supported by the data, and that is just one of the uncomfortable findings in Stanford University’s 2026 AI Index Report, published this week. The report, produced by Stanford’s Institute for Human-Centred Artificial Intelligence, is a 423-page annual assessment of where […] The post The US-China AI gap closed.
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#AI#Machine Learning#AI Models
Five signs data drift is already undermining your security models
Data drift happens when the statistical properties of a machine learning (ML) model's input data change over time, eventually rendering its predictions less accurate. Cybersecurity professionals who rely on ML for tasks like malware detection and network threat analysis find that undetected data drift can create vulnerabilities.
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#AI#Enterprise AI#Business
Amazon S3 Files gives AI agents a native file system workspace, ending the object-file split that breaks multi-agent pipelines
AI agents run on file systems using standard tools to navigate directories and read file paths. The challenge, however, is that there is a lot of enterprise data in object storage systems, notably Amazon S3.
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#AI#AI Models#Machine Learning
As models converge, the enterprise edge in AI shifts to governed data and the platforms that control it
Presented by Box As frontier models converge, the advantage in enterprise AI is moving away from the model and toward the data it can safely access. For most enterprises, that advantage lives in unstructured data: the contracts, case files, product specifications, and internal knowledge.
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#AI#Anthropic#Claude
The one piece of data that could actually shed light on your job and AI
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
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#AI#AI Models#Machine Learning
OCSF explained: The shared data language security teams have been missing
The security industry has spent the last year talking about models, copilots, and agents, but a quieter shift is happening one layer below all of that: Vendors are lining up around a shared way to describe security data. The Open Cybersecurity Schema Framework (OCSF), is emerging as one of the strongest candidates for that job.
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#AI#Artificial Intelligence#Data Science
How Hershey applies AI across its supply chain operations
Artificial intelligence is moving beyond software and further into the physical side of business. Companies in food production and logistics are starting to use data systems to support day-to-day decisions, not long-term planning.
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#AI#AI Models#Machine Learning
Fixing AI failure: Three changes enterprises should make now
Recent reports about AI project failure rates have raised uncomfortable questions for organizations investing heavily in AI. Much of the discussion has focused on technical factors like model accuracy and data quality, but after watching dozens of AI initiatives launch, I’ve noticed that the biggest opportunities for improvement are often cultural, not technical.
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