You tried to tell yourself I wasn't real': what happens when people with acute psychosis meet the voices in their heads?
Joe's experience with cannabis edibles resulted in acute psychosis, revealing the dangers of substance use and its impact on mental health.
Ketamine Use Disorder Is on the Rise
Increasing numbers of ketamine users are experiencing addiction, often unaware, with various reports linking it to recreational use and off-label prescriptions.
You tried to tell yourself I wasn't real': what happens when people with acute psychosis meet the voices in their heads?
Joe's experience with cannabis edibles resulted in acute psychosis, revealing the dangers of substance use and its impact on mental health.
Ketamine Use Disorder Is on the Rise
Increasing numbers of ketamine users are experiencing addiction, often unaware, with various reports linking it to recreational use and off-label prescriptions.
Popular AI Chatbots Found to Give Error-Ridden Legal Answers
Popular AI chatbots from OpenAI, Google, and Meta Platforms are prone to 'hallucinations' when answering legal questions.
Generative AI models trained for legal use may perform better, but caution is still needed in their deployment.
Study suggests that even the best AI models hallucinate a bunch | TechCrunch
Generative AI models are currently unreliable, often producing hallucinations, with better models achieving accuracy only 35% of the time.
Microsoft claims new 'Correction' tool can fix genAI hallucinations
Microsoft's new Correction tool addresses hallucinations in AI responses by revising inaccuracies in real-time.
Microsoft claims its new tool can correct AI hallucinations, but experts advise caution | TechCrunch
Microsoft introduces 'Correction,' a service to amend AI-generated text errors, raising skepticism about its effectiveness in addressing AI hallucinations.
Google Cloud's Vertex AI gets new grounding options
Google Cloud introduces grounding options to reduce hallucinations in generative AI applications.
Why RAG won't solve generative AI's hallucination problem | TechCrunch
Hallucinations in generative AI models pose challenges for businesses integrating the technology.
Popular AI Chatbots Found to Give Error-Ridden Legal Answers
Popular AI chatbots from OpenAI, Google, and Meta Platforms are prone to 'hallucinations' when answering legal questions.
Generative AI models trained for legal use may perform better, but caution is still needed in their deployment.
Study suggests that even the best AI models hallucinate a bunch | TechCrunch
Generative AI models are currently unreliable, often producing hallucinations, with better models achieving accuracy only 35% of the time.
Microsoft claims new 'Correction' tool can fix genAI hallucinations
Microsoft's new Correction tool addresses hallucinations in AI responses by revising inaccuracies in real-time.
Microsoft claims its new tool can correct AI hallucinations, but experts advise caution | TechCrunch
Microsoft introduces 'Correction,' a service to amend AI-generated text errors, raising skepticism about its effectiveness in addressing AI hallucinations.
Google Cloud's Vertex AI gets new grounding options
Google Cloud introduces grounding options to reduce hallucinations in generative AI applications.
Why RAG won't solve generative AI's hallucination problem | TechCrunch
Hallucinations in generative AI models pose challenges for businesses integrating the technology.
AI models frequently 'hallucinate' on legal queries, study finds
Generative AI models frequently produce false legal information, with hallucinations occurring between 69% to 88% of the time.
The pervasive nature of these legal hallucinations raises significant concerns about the reliability of using large language models (LLMs) in the field.
3 Research-Driven Advanced Prompting Techniques for LLM Efficiency and Speed Optimization - KDnuggets
Large language models (LLMs) like OpenAI's GPT and Mistral's Mixtral are being widely used for AI-powered applications.
Factually incorrect information, known as hallucinations, can occur when working with LLMs due to prompts and biases in training the models.
AI models frequently 'hallucinate' on legal queries, study finds
Generative AI models frequently produce false legal information, with hallucinations occurring between 69% to 88% of the time.
The pervasive nature of these legal hallucinations raises significant concerns about the reliability of using large language models (LLMs) in the field.
3 Research-Driven Advanced Prompting Techniques for LLM Efficiency and Speed Optimization - KDnuggets
Large language models (LLMs) like OpenAI's GPT and Mistral's Mixtral are being widely used for AI-powered applications.
Factually incorrect information, known as hallucinations, can occur when working with LLMs due to prompts and biases in training the models.