From procedural knowledge to self-organizing networks, here's how AI agents are using memory to adapt to their environments. The post Beyond context windows, here is how the memory of AI agents is evolving first appeared on TechTalks.| TechTalks
The Hierarchical Reasoning Model uses a simple and two-tiered structure to beat large transformers on reasoning tasks with fewer parameters and compute budget. The post New brain-inspired AI model shows a more efficient path to reasoning first appeared on TechTalks.| TechTalks
Researchers jailbroke Grok-4 using a combined attack. The method manipulates conversational context, revealing a new class of semantic vulnerabilities.| TechTalks - Technology solving problems... and creating new ones
LegalPwn, a new prompt injection attack, uses fake legal disclaimers to trick major LLMs into approving and executing malicious code. The post New prompt injection attack weaponizes fine print to bypass safety in major LLMs first appeared on TechTalks.| TechTalks
AI models are often overconfident. A new MIT training method teaches them self-doubt, improving reliability and making them more trustworthy. The post A new way to train AI models to know when they don’t know first appeared on TechTalks.| TechTalks
Researchers discover critical vulnerability in LLM-as-a-judge reward models that could compromise the integrity and reliability of your AI training pipelines. The post LLM-as-a-judge easily fooled by a single token, study finds first appeared on TechTalks.| TechTalks
A new paper argues that "emergent abilities" in LLMs aren't true intelligence. The difference is crucial and has implications for real-world applications. The post Are LLMs truly intelligent? New study questions the ’emergence’ of AI abilities first appeared on TechTalks.| TechTalks
To make AI more human-like, must we sacrifice its power? A new study shows why LLM efficiency creates a gap in understanding. The post Why LLMs don’t think like you: A look at the compression-meaning trade-off first appeared on TechTalks.| TechTalks
Anthropic's study warns that LLMs may intentionally act harmfully under pressure, foreshadowing the potential risks of agentic systems without human oversight. The post Anthropic research shows the insider threat of agentic misalignment first appeared on TechTalks.| TechTalks
Chain-of-thought tokens don't reflect genuine reasoning in LLMs is misleading. They're navigational aids devoid of true cognitive processing or reliability. The post Why we misinterpret LLM ‘reasoning’ first appeared on TechTalks.| TechTalks
There is significant doubt about the trustworthiness of chain-of-thought traces in large language models, challenging developers' reliance on them for AI safety. The post Anthropic study reveals LLM reasoning isn’t always what it seems first appeared on TechTalks.| TechTalks
Sakana AI's Continuous Thought Machine enhances AI's alignment with human cognition, promising a future of more trustworthy and efficient technology. The post How Continuous Thought Machines learn to ‘think’ more like us first appeared on TechTalks.| TechTalks
Stanford's "Think, Prune, Train" framework enables LLMs to enhance reasoning skills through self-generated data, leading to more efficient and smarter systems. The post Can LLMs learn to reason without RL or large datasets? first appeared on TechTalks.| TechTalks
Recent research by Meta shows ML models can understand intuitive physics by watching videos, promising advancements in building general-purpose AI models. The post How AI learns intuitive physics from watching videos first appeared on TechTalks.| TechTalks