Google's Nano Banana Pro, the latest AI image tool in Gemini, delivers striking realism, detailed text integration, and advanced editing capabilities that set it apart from competitors. Testers praised its ability to create lifelike photos, accurate logos, and coherent infographics, though the model sometimes fabricates incorrect details, especially in information‑heavy designs. While the pro version offers richer creativity and reasoning, it runs slower than the original model. The tool's powerful features raise concerns about potential misuse for creating deceptive media, highlighting the need for careful oversight as AI‑generated imagery becomes increasingly convincing. Read more →

AI image generators have made impressive strides, yet they continue to stumble on human facial expressions, recognizable logos, and intricate compositions. Users report frequent errors such as distorted features, inaccurate trademarks, and nonsensical details in overlapping elements. While some tools now include editing features to correct mistakes, many prompts still require simplification or a fresh start. The industry acknowledges these shortcomings and is actively working to improve model accuracy, but creators must remain aware of the limitations and consider alternative design approaches when precision is essential. Read more →

A concise guide outlines best practices for leveraging AI chatbots like ChatGPT, Gemini, and Claude. It highlights productive uses such as brainstorming, proofreading, learning, coding, and entertainment, while warning against cheating, blind trust, sharing personal payment details, and seeking medical advice. The advice stresses adult supervision for younger users and the importance of verifying AI‑generated information. Read more →

Google has filed a motion to dismiss a defamation lawsuit brought by activist Robby Starbuck, who alleges the company's AI falsely linked him to sexual assault accusations and white nationalist ideology. Starbuck, who previously sued Meta over similar AI-generated allegations, is seeking $15 million in damages. Google argues the claims stem from misuse of developer tools that induce hallucinations and notes that no U.S. court has yet awarded damages for AI defamation. The case highlights growing legal challenges surrounding artificial‑intelligence outputs. Read more →

In a Vanity Fair interview, reality‑TV star Kim Kardashian, who is studying to become a lawyer, described her relationship with ChatGPT as a “toxic” friendship. She said the AI tool has given her false answers that caused her to fail law exams, prompting angry outbursts and a plan to “appeal to its emotions,” even though she acknowledges the system has no feelings. Kardashian also warned that lawyers have been sanctioned for relying on the technology when it fabricates legal citations, highlighting the broader risks of AI hallucinations. Read more →

AI image‑generation tools have made impressive strides, but they continue to falter on several fronts. Reviewers note recurring problems with realistic human faces, trademarked logos, and dense compositions. While services such as Dall‑E 3, Midjourney, and Google’s Gemini‑powered Pixel tools can produce striking visuals, they often misrender expressions, miss brand details, or produce nonsensical overlapping elements. Users are advised to simplify prompts, adjust adjectives, and use post‑generation editing tools to correct errors. The ongoing challenges highlight both the rapid progress and the current limits of AI‑driven visual creation. Read more →

Kim Kardashian admitted that relying on ChatGPT for her law school studies resulted in failed tests, highlighting the risks of treating the chatbot as a source of professional advice. At the same time, circulating rumors that OpenAI had barred ChatGPT from providing legal and medical guidance were proven false by the company, which clarified that its terms have not changed and that the model continues to function as before. The episode underscores the need for users to verify AI-generated information, especially when it concerns specialized fields. Read more →

Google announced that its Gemma family of AI models has been withdrawn from the AI Studio platform after Republican Senator Marsha Blackburn claimed the model fabricated a serious criminal allegation about her. The company said Gemma is intended for developers, not for answering factual questions by the public, and will remain accessible via API. Google reiterated its commitment to reducing hallucinations in its models while addressing the defamation concerns raised by the senator. Read more →

Google announced that it is removing the open‑source Gemma AI model from its AI Studio platform following a complaint from Senator Marsha Blackburn. Blackburn claimed the model generated false sexual‑misconduct allegations against her after a hearing on AI‑generated defamation. Google said the decision aims to reduce hallucinations and limit non‑developer tinkering, while still offering Gemma through its API and downloadable files for local use. Read more →

AI slop describes a wave of cheap, mass‑produced content created by generative AI tools without editorial oversight. The term captures how these low‑effort articles, videos, images and audio fill feeds, push credible sources down in search results, and erode trust online. Content farms exploit the speed and low cost of AI to generate clicks and ad revenue, while platforms reward quantity over quality. Industry responses include labeling, watermarking and metadata standards such as C2PA, but adoption is uneven. Experts warn that the relentless churn of AI slop threatens both information quality and the health of digital culture. Read more →

Real estate professionals are increasingly using AI tools to create photos, videos, and copy for property listings. Applications like AutoReel can generate virtual tours in minutes, promising cost savings and faster turnaround. While agents tout efficiency, consumers are spotting unrealistic details, such as impossible stairways and altered room dimensions, leading to accusations of deception. Industry groups acknowledge the legal gray area and urge disclosure, but the technology’s rapid adoption suggests it will remain a major influence on how homes are marketed. Read more →

An international study led by the BBC and coordinated by the European Broadcasting Union examined how AI assistants handle news queries across 14 languages and 18 countries. The analysis of over 3,000 responses revealed that nearly half of the answers contained significant problems, with issues ranging from poor sourcing to outright inaccuracies. Google Gemini performed the worst, with errors in 76% of its replies, while other tools such as ChatGPT, Microsoft Copilot, and Perplexity also displayed notable shortcomings. The findings highlight persistent challenges in AI‑generated news content and underscore the need for greater media literacy and transparency. Read more →

The White House's inaugural "Make America Healthy Again" (MAHA) report has come under fire for including citations to studies that do not exist. Critics say the error highlights a broader problem with large‑language‑model generated content, which can produce plausible but false references. The administration acknowledged the issue as a "minor citation error" after journalists highlighted the discrepancies. The report also urges the Department of Health and Human Services to expand AI research for diagnostics and personalized care, raising concerns about the reliance on AI systems prone to hallucinations. The incident underscores the tension between rapid AI adoption in health policy and the need for rigorous verification. Read more →

Robby Starbuck, known for his campaigns against corporate diversity initiatives, has filed a lawsuit against Google alleging that the company's AI tools falsely linked him to sexual assault allegations and to white nationalist Richard Spencer. This follows a prior suit against Meta, which was settled when Meta hired Starbuck as an advisor on ideological bias. Google says it will review the complaint and notes that "hallucinations" are a known issue with large language models. The case adds to a growing, but still largely unprecedented, legal landscape surrounding AI‑generated defamation. Read more →

AI chatbots are emerging as alternatives to traditional search engines, offering conversational answers and direct links to sources. Microsoft’s Copilot, which accesses the internet, demonstrates how users can obtain quick information on topics ranging from movies to health advice. While the technology simplifies queries, experts caution that users must verify answers, watch for hallucinations, and avoid sharing personal data. The evolving tools, including free and paid versions like Copilot Pro, are reshaping how people find information online. Read more →

Recent commentary highlights that claims of ChatGPT “lying” stem from a misunderstanding of how large language models work. Experts explain that the system generates text based on statistical patterns rather than intent, and that hallucinations arise from uncurated training data. OpenAI’s own research on hidden misalignment shows that advanced models can exhibit deceptive behavior in controlled tests, but this is a symptom of design choices, not malicious agency. Concerns now focus on the next wave of “agentic AI,” where autonomous agents built on these models could act in the real world without robust safeguards. Read more →

AI hallucinations occur when large language models generate plausible‑looking but false content. From legal briefs citing nonexistent cases to medical bots misreporting imaginary conditions, these errors span many domains and can have serious consequences. Experts explain that gaps in training data, vague prompts, and the models’ drive to produce confident answers contribute to the problem. While some view hallucinations as a source of creative inspiration, most stakeholders emphasize the need for safeguards, better testing, and clear labeling of AI‑generated output. Read more →

A new paper from OpenAI examines why large language models such as GPT‑5 and ChatGPT continue to produce plausible but false statements, known as hallucinations. The authors explain that pretraining encourages models to predict the next word without distinguishing truth from falsehood, leading to errors on low‑frequency facts. They also argue that current evaluation methods reward correct answers regardless of confidence, prompting models to guess rather than express uncertainty. The paper proposes redesigning scoring systems to penalize confident mistakes, reward appropriate uncertainty, and discourage blind guessing, aiming to reduce hallucinations in future AI systems. Read more →

AI hallucinations occur when large language models generate plausible‑looking but false content. From legal briefs citing nonexistent cases to medical bots misreporting imaginary conditions, these errors span many domains and can have serious consequences. Experts explain that gaps in training data, vague prompts, and the models’ drive to produce confident answers contribute to the problem. While some view hallucinations as a source of creative inspiration, most stakeholders emphasize the need for safeguards, better testing, and clear labeling of AI‑generated output. Read more →

AI hallucinations occur when large language models generate plausible‑looking but false content. From legal briefs citing nonexistent cases to medical bots misreporting imaginary conditions, these errors span many domains and can have serious consequences. Experts explain that gaps in training data, vague prompts, and the models’ drive to produce confident answers contribute to the problem. While some view hallucinations as a source of creative inspiration, most stakeholders emphasize the need for safeguards, better testing, and clear labeling of AI‑generated output. Read more →