This sets unrealistic expectations for AI and leads to misuse. It also slows progress toward building new AI applications.
This first article in a series explains the core AI concepts behind running LLM and RAG workloads on a Raspberry Pi, including why local AI is useful and what tradeoffs to expect.
We’ve explored how prompt injections exploit the fundamental architecture of LLMs. So, how do we defend against threats that ...
When it comes to deploying local LLMs, many people may think that spending more money will deliver more performance, but it's far from reality.  That's ...
Transformer Weekly: New Claude Mythos model details leaked, Anthropic wins injunction against DoD blacklisting and ...
First set out in a scientific paper last September, Pathway’s post-transformer architecture, BDH (Dragon hatchling), gives LLMs native reasoning powers with intrinsic memory mechanisms that support ...
How LinkedIn replaced five feed retrieval systems with one LLM model — and what engineers building recommendation pipelines ...
Burner accounts on social media sites can increasingly be analyzed to identify the pseudonymous users who post to them using AI in research that has far-reaching consequences for privacy on the ...
In this tutorial, we build a hierarchical planner agent using an open-source instruct model. We design a structured multi-agent architecture comprising a planner agent, an executor agent, and an ...
Cybersecurity researchers have disclosed details of a new cryptojacking campaign that uses pirated software bundles as lures to deploy a bespoke XMRig miner program on compromised hosts. "Analysis of ...
If you look at job postings on Indeed and LinkedIn, you’ll see a wave of acronyms added to the alphabet soup as companies try to hire people to boost visibility on large language models (LLMs). Some ...
This desktop app for hosting and running LLMs locally is rough in a few spots, but still useful right out of the box. Dedicated desktop applications for agentic AI make it easier for relatively ...