All posts tagged: Hallucinations

Amazon Web Services (AWS) Launches Automated Reasoning Checks in Preview to Combat AI Hallucinations

Amazon Web Services (AWS) Launches Automated Reasoning Checks in Preview to Combat AI Hallucinations

Published by Webster

Amazon Web Services (AWS) launched a new service at its ongoing re:Invent conference that will help enterprises reduce instances of artificial intelligence (AI) hallucination. Launched on Monday, the Automated Reasoning checks tool is available in preview and can be found within the Amazon Bedrock Guardrails. The company claimed that the tool mathematically validates the accuracy of responses generated by large language models (LLMs) and prevents factual errors from hallucinations. It is similar to the Grounding with Google Search feature which is available on both the Gemini API as well as the Google AI Studio. AWS Automated Reasoning Checks AI models can often generate responses that are incorrect, misleading, or fictional. This is known as AI hallucination, and the issue impacts the credibility of AI models, especially when used in an enterprise space. While companies can somewhat mitigate the issue by training the AI system on high-quality organisational data, the pre-training data and architectural flaws can still make the AI hallucinate. AWS detailed its solution to AI hallucination in a blog post. The Automated Reasoning checks …

Is Hyderabad the new Bengaluru? X user’s claim sparks mixed reactions, some call it ‘hallucinations’ | Bengaluru

Is Hyderabad the new Bengaluru? X user’s claim sparks mixed reactions, some call it ‘hallucinations’ | Bengaluru

Published by Parlour News

The Bengaluru-versus-other-cities rivalry has found a new contender in Hyderabad. A post on X, accompanied by images showcasing Hyderabad’s impressive tech parks and high-rises, has declared, “Hyderabad is the new Bangalore.” Housing prices in Hyderabad saw an 11 per cent increase in 2023.(X/@venkyHQ) X user Venkatesh Gupta, a product manager, has ignited a debate on the platform, drawing responses that range from agreement to staunch dismissal of the comparison. Check out the post here: How did the X users react? The post sparked mixed reactions from X users. While some hailed Hyderabad as superior, with comments like “Yes, Hyderabad is perfect” and “Hyderabad is better than Bangalore,” others dismissed the claim outright. One user criticized the comparison, calling it a “fool’s paradise” and accusing the poster of being in “hallucinations.” (Also Read: Ghee over beer? Rameshwaram Cafe adds a Bengaluru twist to Bandland 2024) Hyderabad: Fastest growing real estate markets Recently, Hyderabad emerged as India’s fastest-growing real estate market, outpacing Bengaluru, Mumbai-MMR, Delhi-NCR, Ahmedabad, and Chennai. According to Knight Frank India’s India Prime City Index, …

DataStax CTO Discusses RAG’s Role in Reducing AI Hallucinations

DataStax CTO Discusses RAG’s Role in Reducing AI Hallucinations

Published by Webster

Retrieval Augmented Generation (RAG) has become essential for IT leaders and enterprises looking to implement generative AI. By using a large language model (LLM) and RAG, enterprises can ground an LLM in enterprise data, improving the accuracy of outputs. But how does RAG work? What are the use cases for RAG? And are there any real alternatives? TechRepublic sat down with Davor Bonaci, chief technology officer and executive vice president at database and AI company DataStax, to find out how RAG is being leveraged in the market during the rollout of generative AI in 2024 and what he sees as the technology’s next step in 2025. What is Retrieval Augmented Generation? RAG is a technique that improves the relevance and accuracy of generative AI LLM model outputs by adding extended or augmented context from an enterprise. It allows IT leaders to use generative AI LLMs for enterprise use cases. Bonaci explained that while LLMs have “basically been trained on all the information available on the internet,” up to a certain cut-off date, depending on the …

Microsoft’s new safety system can catch hallucinations in its customers’ AI apps

Published by Webster

Sarah Bird, Microsoft’s chief product officer of responsible AI, tells The Verge in an interview that her team has designed several new safety features that will be easy to use for Azure customers who aren’t hiring groups of red teamers to test the AI services they built. Microsoft says these LLM-powered tools can detect potential vulnerabilities, monitor for hallucinations “that are plausible yet unsupported,” and block malicious prompts in real time for Azure AI customers working with any model hosted on the platform.  “We know that customers don’t all have deep expertise in prompt injection attacks or hateful content, so the evaluation system generates the prompts needed to simulate these types of attacks. Customers can then get a score and see the outcomes,” she says.  Three features: Prompt Shields, which blocks prompt injections or malicious prompts from external documents that instruct models to go against their training; Groundedness Detection, which finds and blocks hallucinations; and safety evaluations, which assess model vulnerabilities, are now available in preview on Azure AI. Two other features for directing models toward …

We Tried Google’s Gemini AI Chatbot and Found It to Be More Capable but Still Prone to Hallucinations

Published by Webster

Google has come a long way with its generative artificial intelligence (AI) offerings. One year ago, when the tech giant first unveiled its AI assistant, Bard, it became a fiasco as it made a factual error answering a question regarding the James Webb Space Telescope. Since then, the tech giant has improved the chatbot’s responses, added a feedback mechanism to check the source behind the responses, and more. But the biggest upgrade came when the company changed the large language model (LLM), powering the chatbot from Pathways Language Model 2 (PaLM 2) to Gemini in December 2023. The company called Gemini AI its most powered language model so far. It also added AI image generation capability to the chatbot, taking it multimodal, and even renamed it Gemini. But just how much of a jump is it for the AI chatbot? Can it now compete with Microsoft Copilot, which is based on GPT-4 and has capabilities? And what about the instances of AI hallucination (a phenomenon where AI responds with false or non-existent information as facts)? …