Posted on : June 5, 2025 By Tech World Times AI  Rate this post Artificial Intelligence is now part of everyday life. Many apps use it to make things easier and smarter. One new and fun tool is Candy AI. In this article, we will explore what Candy AI is. You will also learn its top features, key benefits, and how it works. What Is Candy AI? Candy AI is a smart chatbot powered by advanced AI technology. It helps users talk, share, and interact. The app is designed for fun and emotional support. Many people use it to chat, relax, and feel better. Candy AI uses text, voice, and visuals to talk to users. Key Features of Candy AI Candy AI offers many useful and fun features. Here are the main ones: 1. Custom AI Characters You can create your AI friend. Choose how they look, sound, and act. This makes each chat personal and exciting. Your AI friend can have a name, a job, and a background story. 2. Real-Time Chatting You can talk with Candy AI like you talk to a real friend. It replies fast and feels natural. The chat is smooth and always available, 24/7. 3. Voice Interaction Candy AI lets you talk using your voice. The AI answers back with a clear and friendly voice. This adds a human touch to the chat experience. 4. Roleplay and Stories You can ask the AI to roleplay. It can be a friend, teacher, hero, or anything else. The AI can also tell you stories or help you write one. 5. Memory Feature Candy AI remembers past chats. This helps build strong and meaningful connections over time. The AI can refer to old chats like a real friend. 6. Emotion Support Mode Feeling lonely or sad? Candy AI can help. It gives kind words, emotional support, and good advice. It is made to be caring and helpful. Benefits of Using Candy AI Candy AI is more than just a chatbot. It offers many benefits to users of all ages. Let’s look at some top benefits: 1. Always Available Candy AI is always online. You can chat anytime, day or night. There’s no waiting or long loading times. 2. Stress Relief Talking with Candy AI can calm your mind. It helps reduce stress, fear, and sadness. Just a short chat can help you feel better. 3. Improves Communication Skills You can use the AI to improve your English or writing. It helps you speak and write better. It is useful for students and language learners. 4. Fun and Entertainment Candy AI is fun to use. You can joke, play games, or write a story together. It makes your free time more enjoyable. 5. Safe Environment The app is safe and secure. There are no harmful ads or messages. Your chats stay private. How Does Candy AI Work? Candy AI uses advanced artificial intelligence. It is based on large language models. These models help the AI understand and respond to your messages. 1. Input and Understanding You type or say something. Candy AI reads your message and understands its meaning. It uses machine learning to figure out your emotions and topic. 2. Generating a Reply The AI then creates a reply. The reply is based on what you said and past chats. It tries to sound human and friendly. 3. Personalized Response If the AI knows you well, it gives better answers. It uses memory to make replies that feel more personal. 4. Using Visual and Audio Tools You can also use voice and images. Candy AI can speak and show you visual stories. This makes the chat more lively and real. Is Candy AI Free? Candy AI offers a free version. You can chat with basic features without paying. There is also a premium version. The premium plan gives access to more features like better memory and roleplay tools. Who Can Use Candy AI? Candy AI is great for many types of users: Students who need writing help People who feel lonely or need company Language learners looking to practice Writers who want story ideas Anyone who enjoys chatting with AI The app is easy to use for all age groups. You don’t need any tech skills to get started. Where Can You Use Candy AI? Candy AI is available on mobile and desktop. You can download the app or use it on a web browser. It works on Android, iOS, and most computers. Final Thoughts Candy AI is more than just an app. It is a smart friend in your pocket. It helps you talk, write, learn, and feel better. With features like voice chat, memory, and story mode, it stands out from other chatbots. If you’re looking for a fun, kind, and smart AI, Candy AI is worth trying. FAQs 1. Is Candy AI safe to use? Yes. Candy AI protects your data and keeps your chats private. It follows strong safety rules. 2. Does Candy AI support voice chatting? Yes. You can speak to it and hear it talk back with clear voice replies. 3. Can I create my own AI character? Yes. You can fully customize your AI friend’s look, voice, and personality. 4. Is Candy AI good for students? Yes. Students can use it for writing help, language learning, or just to relax and chat. 5. How much does Candy AI cost? Candy AI has a free version. The premium plan offers extra features and better memory. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com

Published June 7, 2025 10:00am EDT close Tennessee DMV experiencing long lines ahead of REAL ID deadline May 7 is the deadline to get a REAL ID, and some DMVs are facing large crowds and major backup. FOX's Asher Reed spoke with FOX 35 Orlando from outside a DMV in Antioch, Tennessee, with more on the issue. NEWYou can now listen to Fox News articles! If you've received a text message claiming to be from your state's Department of Motor Vehicles (DMV) and threatening you with fines or penalties unless you pay up, you're not alone. A new wave of scam texts is sweeping across the country, targeting drivers in states like Connecticut, Pennsylvania, Georgia, Florida, New York, California, Illinois, New Jersey, Virginia, Colorado, Vermont, Texas, North Carolina and even Washington, D.C.These messages look official and urgent, warning you about supposed unpaid tickets or tolls and demanding immediate payment. But don't be fooled, as these texts are sophisticated scams designed to steal your personal information or money. The scammers are getting better at making their messages look real, so it can be tricky to spot the fraud. But with a few simple tips, you can learn how to recognize these scams and protect yourself before you click or respond. DMV scam text. (Kurt "CyberGuy" Knutsson)How the DMV scam text message worksThese scam messages vary slightly depending on the state you're in, but they’re generally structured in the same way. The text threatens consequences, such as credit score damage, revoked driving privileges, suspended vehicle registration or increased toll fees, if you do not pay the bill you have supposedly incurred. To make the message appear legit, the scammers often include a date for penalties to begin, a fake administrative code and a link that appears to be an official DMV website.FBI WARNS OF SCAM TARGETING VICTIMS WITH FAKE HOSPITALS AND POLICEPro tip: If you're instructed to copy the link into your browser rather than clicking it directly, it's a scam. A person receiving a scam text message on their phone. (Kurt "CyberGuy" Knutsson)Why DMV text scams are so convincingThe scam relies on two key elements to be effective: fear and a sense of urgency. These are two powerful psychological motivators that can send you into a panic since your driving privileges are at risk, or you're facing financial consequences. The aim is to get you to act hastily without pausing to verify the source. The messages also mimic legitimate government communications by including familiar terms, official-sounding codes and web addresses that appear authentic. Here is an example of what the text might look like: DMV scam text. (Kurt "CyberGuy" Knutsson)States known to have issued warnings about DMV scam texts (as of June 2025):ConnecticutPennsylvaniaGeorgiaFloridaNew YorkCaliforniaIllinoisNew JerseyVirginiaColoradoVermontTexasNorth CarolinaWashington, D.C.Reports are surfacing across the U.S., and the list of affected states is likely to continue growing as more residents come forward.How to spot and avoid DMV text message scamsIf you receive a suspicious text message claiming to be from your state's DMV and demanding payment or personal information, follow these steps to protect yourself:1. Be skeptical of any message creating urgency or panic: Scammers rely on fear and urgency to trick you into acting without thinking. If a message pressures you to act immediately, that's a major red flag.2. Check for obvious red flags: Look for signs like strange sender addresses, awkward language, misspellings or links that don't match your state's official DMV website.3. Do not click any links or reply, and use strong antivirus software: Legitimate DMVs will not ask for payments, personal details or sensitive information via unsolicited text messages. The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Verify directly with your DMV: If you're concerned the message might be real, contact your state's DMV using the official website or a trusted phone number. Never use the contact information provided in the suspicious text.5. Consider a Personal Data Removal Service: Your personal information is widely available online, which can make you a bigger target for these types of scams, therefore you might look into a personal data removal service. These services work by submitting opt-out requests to data brokers that collect and sell your information, helping to reduce your digital footprint and making it harder for scammers to find your contact details. GET FOX BUSINESS ON THE GO BY CLICKING HEREWhile no service can guarantee the complete removal of your data from the internet, a data removal service is really a smart choice. They aren’t cheap — and neither is your privacy.  These services do all the work for you by actively monitoring and systematically erasing your personal information from hundreds of websites. It’s what gives me peace of mind and has proven to be the most effective way to erase your personal data from the internet.  By limiting the information available, you reduce the risk of scammers cross-referencing data from breaches with information they might find on the dark web, making it harder for them to target you. Check out my top picks for data removal services here.6. Delete the message immediately and block the sender: Removing the text helps prevent accidental clicks and reduces the risk of falling for the scam later. Also, be sure to block phone numbers and texts that send spam or scam messages, reducing future risk.7. Register your number with the National Do Not Call Registry: While this won't stop all scams, it can help reduce unwanted communications.8. Don't provide any personal or financial information: Never share your Social Security number, driver's license number, banking information, or passwords in response to an unsolicited text.9. If you clicked the link or gave out information, act quickly: If you accidentally entered personal or financial information, contact your bank, credit card provider or local law enforcement right away to minimize potential damage.10. Keep your phone's security features updated: Ensure your device's operating system and security software are current to help block known scam numbers and malicious links.11. Report the scam: Forward the message to 7726 (SPAM) to alert your mobile provider and help block similar messages in the future. Mark the message as junk or spam within your messaging app, if possible. File a complaint with the Federal Trade Commission at reportfraud.ftc.gov or the FBI's Internet Crime Complaint Center at ic3.gov.Kurt’s key takeawaysScam texts pretending to be from the DMV are getting more convincing, but you don't have to be their next victim. Staying skeptical of urgent messages, double-checking anything that seems off and never clicking suspicious links can go a long way in protecting your personal information. Remember, the real DMV will never pressure you for payment or sensitive details over text. By staying alert, you can help prevent these scams and keep your personal information and money secure.CLICK HERE TO GET THE FOX NEWS APPShould tech companies and telecom providers be doing more to protect you from scam texts, or does the responsibility ultimately fall on you to keep your digital life safe? Let us know by writing to us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to cover.Follow Kurt on his social channels:Answers to the most-asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com. All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.

Study the Secrets of Early American Photography at This New Exhibition “The New Art: American Photography, 1839-1910” at the Metropolitan Museum of Art will feature more than 250 photographs Lillian Ali - Staff Contributor June 6, 2025 This image, taken by an unknown photographer in 1905, is an example of a cyanotype. The Metropolitan Museum of Art, William L. Schaeffer Collection A new exhibition at the crossroads of art, history and technology chronicles the beginnings of early American photography. Titled “The New Art: American Photography, 1839-1910,” the show at the Metropolitan Museum of Art in New York City features more than 250 photographs that capture “the complexities of a nation in the midst of profound transformation,” says Max Hollein, the Met’s CEO, in a statement. Curator Jeff Rosenheim tells the Wall Street Journal’s William Meyers that the exhibition focuses “on how early artists used the different formats to record individuals and the built and natural environments surrounding them.” A daguerrotype from around 1850 depicts a woman wearing a tignon, a headcovering popular among Creole women of African descent. The Metropolitan Museum of Art, William L. Schaeffer Collection The oldest photographs on display are daguerreotypes, named for inventor Louis Daguerre, which were introduced in 1839 as the first publicly available form of photography. Creating a daguerreotype was a delicate, sometimes painstaking process that involved several chemical treatments and variable exposure times. The process yielded a sharply detailed picture on a silver background and was usually used for studio portraiture. The exhibition moves through the history of photography, from daguerreotypes and other photographs made on metal to those made on glass and, eventually, paper. It even features stereographs, two photos showing an object from slightly different points of view, creating an illusion of three-dimensionality. Installation view of "The New Art: American Photography, 1839-1910" Eugenia Tinsely / The Met Rosenheim believes that early photographic portraits empowered working-class Americans. “Photographic portraits play a role in people feeling like they could be a citizen,” Rosenheim tells the Guardian’s Veronica Esposito. “It’s a psychological, empowering thing to own your own likeness.” Photographs in the exhibition also spotlight key moments in American history. Items on view include a portrait of formerly enslaved individuals and an image of a conspirator in the assassination of Abraham Lincoln. The exhibition features big names in American photography, such as John Moran, who advocated for the recognition of photography as an art form, and Alice Austen, a pioneering landscape photographer. Group on Petria, Lake Mahopac​​​​​​, photographed in 1888 by Alice Austen The Metropolitan Museum of Art, William L. Schaeffer Collection Many of the photographs on display were taken by unknown artists. One of the most recent photos in the exhibition, taken by an unknown artist in 1905, is a cyanotype depicting figures tobogganing on a hill in Massachusetts. Cyanotypes were created by exposing a chemically treated paper to UV light, such as sunlight, yielding the blue pigment it was named for. Beyond portraits and landscapes, the exhibition features several enigmatic images, such as one of a boot placed in a roller skate and positioned on top of a stool. Rosenheim tells the Guardian that the mysterious photo “asks more questions than it answers.” An unknown photographer took this unconventional still life in the 1860s. The Metropolitan Museum of Art, William L. Schaeffer Collection “It’s very emblematic of the whole of 19th-century American photography,” he adds. The exhibition features photographs from across time and economic divides, with portraits of the working-class and wealthy alike. “The collection is just filled with the everyday stories of people,” Rosenheim tells the Guardian. “I don’t think painting can touch that.” “The New Art: American Photography, 1839-1910” is on view at the Metropolitan Museum of Art in New York City through July 20, 2025. Get the latest stories in your inbox every weekday.

Looking for NYT Connections answers and hints? Here's all you need to know to solve today's game, plus my commentary on the puzzles.

Looking for NYT Strands answers and hints? Here's all you need to know to solve today's game, including the spangram.

Looking for Quordle clues? We can help. Plus get the answers to Quordle today and past solutions.

Here are hints and the answers for the NYT Connections: Sports Edition puzzle, No. 257, for June 7.

Here are hints and answers for the NYT Strands puzzle No. 461 for June 7.

Here are some hints and the answers for Connections for June 7, #727.

One of the key use cases for generative AI involves answering questions over private datasets, with retrieval-augmented generation (RAG) as the go-to framework. As new RAG techniques emerge, there’s a growing need to benchmark their performance across diverse datasets and metrics.  To meet this need, we’re introducing BenchmarkQED, a new suite of tools that automates RAG benchmarking at scale, available on GitHub (opens in new tab). It includes components for query generation, evaluation, and dataset preparation, each designed to support rigorous, reproducible testing.   BenchmarkQED complements the RAG methods in our open-source GraphRAG library, enabling users to run a GraphRAG-style evaluation across models, metrics, and datasets. GraphRAG uses a large language model (LLM) to generate and summarize entity-based knowledge graphs, producing more comprehensive and diverse answers than standard RAG for large-scale tasks.  In this post, we walk through the core components of BenchmarkQED that contribute to the overall benchmarking process. We also share some of the latest benchmark results comparing our LazyGraphRAG system to competing methods, including a vector-based RAG with a 1M-token context window, where the leading LazyGraphRAG configuration showed significant win rates across all combinations of quality metrics and query classes. In the paper, we distinguish between local queries, where answers are found in a small number of text regions, and sometimes even a single region, and global queries, which require reasoning over large portions of or even the entire dataset.  Conventional vector-based RAG excels at local queries because the regions containing the answer to the query resemble the query itself and can be retrieved as the nearest neighbor in the vector space of text embeddings. However, it struggles with global questions, such as, “What are the main themes of the dataset?” which require understanding dataset qualities not explicitly stated in the text.   AutoQ: Automated query synthesis This limitation motivated the development of GraphRAG a system designed to answer global queries. GraphRAG’s evaluation requirements subsequently led to the creation of AutoQ, a method for synthesizing these global queries for any dataset. AutoQ extends this approach by generating synthetic queries across the spectrum of queries, from local to global. It defines four distinct classes based on the source and scope of the query (Figure 1, top) forming a logical progression along the spectrum (Figure 1, bottom). Figure 1. Construction of a 2×2 design space for synthetic query generation with AutoQ, showing how the four resulting query classes map onto the local-global query spectrum.  AutoQ can be configured to generate any number and distribution of synthetic queries along these classes, enabling consistent benchmarking across datasets without requiring user customization. Figure 2 shows the synthesis process and sample queries from each class, using an AP News dataset. Figure 2. Synthesis process and example query for each of the four AutoQ query classes.  About Microsoft Research Advancing science and technology to benefit humanity View our story Opens in a new tab AutoE: Automated evaluation framework  Our evaluation of GraphRAG focused on analyzing key qualities of answers to global questions. The following qualities were used for the current evaluation: Comprehensiveness: Does the answer address all relevant aspects of the question?  Diversity: Does it present varied perspectives or insights?  Empowerment: Does it help the reader understand and make informed judgments?  Relevance: Does it address what the question is specifically asking?   The AutoE component scales evaluation of these qualities using the LLM-as-a-Judge method. It presents pairs of answers to an LLM, along with the query and target metric, in counterbalanced order. The model determines whether the first answer wins, loses, or ties with the second. Over a set of queries, whether from AutoQ or elsewhere, this produces win rates between competing methods. When ground truth is available, AutoE can also score answers on correctness, completeness, and related metrics. An illustrative evaluation is shown in Figure 3. Using a dataset of 1,397 AP News articles on health and healthcare, AutoQ generated 50 queries per class (200 total). AutoE then compared LazyGraphRAG to a competing RAG method, running six trials per query across four metrics, using GPT-4.1 as a judge. These trial-level results were aggregated using metric-based win rates, where each trial is scored 1 for a win, 0.5 for a tie, and 0 for a loss, and then averaged to calculate the overall win rate for each RAG method. Figure 3. Win rates of four LazyGraphRAG (LGR) configurations across methods, broken down by the AutoQ query class and averaged across AutoE’s four metrics: comprehensiveness, diversity, empowerment, and relevance. LazyGraphRAG outperforms comparison conditions where the bar is above 50%. The four LazyGraphRAG conditions (LGR_b200_c200, LGR_b50_c200, LGR_b50_c600, LGR_b200_c200_mini) differ by query budget (b50, b200) and chunk size (c200, c600). All used GPT-4o mini for relevance tests and GPT-4o for query expansion (to five subqueries) and answer generation, except for LGR_b200_c200_mini, which used GPT-4o mini throughout. Comparison systems were GraphRAG (Local, Global, and Drift Search), Vector RAG with 8k- and 120k-token windows, and three published methods: LightRAG (opens in new tab), RAPTOR (opens in new tab), and TREX (opens in new tab). All methods were limited to the same 8k tokens for answer generation. GraphRAG Global Search used level 2 of the community hierarchy. LazyGraphRAG outperformed every comparison condition using the same generative model (GPT-4o), winning all 96 comparisons, with all but one reaching statistical significance. The best overall performance came from the larger budget, smaller chunk size configuration (LGR_b200_c200). For DataLocal queries, the smaller budget (LGR_b50_c200) performed slightly better, likely because fewer chunks were relevant. For ActivityLocal queries, the larger chunk size (LGR_b50_c600) had a slight edge, likely because longer chunks provide a more coherent context. Competing methods performed relatively better on the query classes for which they were designed: GraphRAG Global for global queries, Vector RAG for local queries, and GraphRAG Drift Search, which combines both strategies, posed the strongest challenge overall. Increasing Vector RAG’s context window from 8k to 120k tokens did not improve its performance compared to LazyGraphRAG. This raised the question of how LazyGraphRAG would perform against Vector RAG with 1-million token context window containing most of the dataset. Figure 4 shows the follow-up experiment comparing LazyGraphRAG to Vector RAG using GPT-4.1 that enabled this comparison. Even against the 1M-token window, LazyGraphRAG achieved higher win rates across all comparisons, failing to reach significance only for the relevance of answers to DataLocal queries. These queries tend to benefit most from Vector RAG’s ranking of directly relevant chunks, making it hard for LazyGraphRAG to generate answers that have greater relevance to the query, even though these answers may be dramatically more comprehensive, diverse, and empowering overall. Figure 4. Win rates of LazyGraphRAG (LGR) over Vector RAG across different context window sizes, broken down by the four AutoQ query classes and four AutoE metrics: comprehensiveness, diversity, empowerment, and relevance. Bars above 50% indicate that LazyGraphRAG outperformed the comparison condition.  AutoD: Automated data sampling and summarization Text datasets have an underlying topical structure, but the depth, breadth, and connectivity of that structure can vary widely. This variability makes it difficult to evaluate RAG systems consistently, as results may reflect the idiosyncrasies of the dataset rather than the system’s general capabilities. The AutoD component addresses this by sampling datasets to meet a target specification, defined by the number of topic clusters (breadth) and the number of samples per cluster (depth). This creates consistency across datasets, enabling more meaningful comparisons, as structurally aligned datasets lead to comparable AutoQ queries, which in turn support consistent AutoE evaluations. AutoD also includes tools for summarizing input or output datasets in a way that reflects their topical coverage. These summaries play an important role in the AutoQ query synthesis process, but they can also be used more broadly, such as in prompts where context space is limited. Since the release of the GraphRAG paper, we’ve received many requests to share the dataset of the Behind the Tech (opens in new tab) podcast transcripts we used in our evaluation. An updated version of this dataset is now available in the BenchmarkQED repository (opens in new tab), alongside the AP News dataset containing 1,397 health-related articles, licensed for open release.   We hope these datasets, together with the BenchmarkQED tools (opens in new tab), help accelerate benchmark-driven development of RAG systems and AI question-answering. We invite the community to try them on GitHub (opens in new tab).  Opens in a new tab