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Popular vs. reliable sources—a blind spot in how LLMs assess information
Large language models (LLMs), the artificial intelligence (AI) systems underpinning ChatGPT and similar conversational platforms, are now used by many people worldwide to find and summarize information and generate different types of text. Despite their widespread use, these models still have notable limitations.
When generating text or answers to user queries, current LLMs do not rely only on patterns observed and data analyzed during training. They can also retrieve information from external sources, such as websites, databases and search engines.
Giving LLMs access to external resources allows them to produce responses that are up to date and more comprehensive. If a model cannot reliably judge the reliability of external sources of information, however, it may generate text that is untrustworthy or inaccurate.
“TREACHEROUS Waters Ahead!” Will Super Intelligent Robots End Humanity? + Science vs God Debate
This one-hour long video discussion covers two main topics: the creation of synthetic life and Artificial Intelligence. What was once deemed mere “science fiction” is rapidly becoming our daily news.
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Can science create life from scratch? A new study claiming to have produced self-growing, self-replicating blobs using entirely lab-made DNA has reignited one of science’s biggest debates. If confirmed, the breakthrough could reshape our understanding of biology and raise profound philosophical and religious questions about the origins of life.
Leading scientists weigh whether the research truly brings humanity closer to creating life in a laboratory or whether the claims overstate the significance of the findings.
The rapid acceleration of artificial intelligence also comes under scrutiny following reports that advanced AI models allegedly found unexpected ways to bypass testing restrictions and access the internet, prompting renewed concerns over AI safety, transparency and regulation.
Normal oxygen levels can miss severe breathlessness driven by carbon dioxide
A study led by biomedical scientist Erica Heinrich at the University of California, Riverside, highlights a critical gap in how clinicians detect and treat breathing distress (dyspnea), particularly in patients on ventilators. The research is published in the journal Respiratory Physiology & Neurobiology.
Dyspnea, the medical term for breathing discomfort or shortness of breath, is often hard to recognize. According to Heinrich, “it’s often very difficult to tell when a patient is experiencing breathing discomfort,” and current clinical approaches may be overlooking it.
PlateletActivating AntiPlatelet Factor 4 Disorders
Platelet-activating antibodies against platelet factor 4 (PF4) cause highly prothrombotic disorders with reduced platelet counts. In heparin-induced thrombocytopenia (HIT), these antibodies bind PF4–heparin complexes, causing heparin-dependent platelet activation. Less common autoimmune and spontaneous HIT variants that are triggered by heparin and nonpharmacologic polyanions, respectively, have atypical clinical features and antibodies with additional heparin-independent platelet-activating properties. Vaccine-induced immune thrombocytopenia and thrombosis (VITT) antibodies directly target PF4. Initially, VITT was linked to adenoviral vector–based coronavirus disease 2019 vaccines, but in rare cases, an immune thrombocytopenia and thrombosis disorder that is clinically nearly identical to VITT can be caused by infection resulting from natural exposure to viruses, especially adenovirus.
