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In healthcare, accuracy is important. So the widespread use of OpenAI’s Whisper transcription tool among medical professionals has raised alarms among experts.OpenAI’s Whisper transcription tool has fabricated false text in medical and business settings, despite warnings against it. The Associated Press interviewed more than a dozen software engineers, developers and researchers who found that the model often fabricated text that the speaker never said, a phenomenon often referred to as “fictitious” or “hallucination” in the field of artificial intelligence.
When it was released in 2022, OpenAI claimed that Whisper was close to “human-level robustness” in audio transcription accuracy. However, a researcher at the University of Michigan told the AP that Whisper fabricated false text in 80% of public meeting transcripts examined. Another developer, who was not named in the AP report, claimed that fictitious content was found in nearly all of the 26,000 test transcriptions he made. These fabrications are particularly dangerous in medical settings. More than 30,000 medical workers now use Whisper-based tools to record patient visits, despite OpenAI’s warnings against using Whisper in “high-risk areas,” according to the Associated Press. Minnesota’s Mankato Clinic and Children’s Hospital Los Angeles are among 40 health systems that use a Whisper-based AI Co-Pilot service developed by medical technology company Nabla that’s fine-tuned for medical terminology. Nabla acknowledges that Whisper can fabricate conversations, but it also reportedly deletes the original recordings for “data security reasons.” This could raise other issues, as doctors can’t verify the accuracy of the original material. And deaf patients could be severely affected by false recordings because they have no way of knowing that medical Whisper’s potential problems aren’t limited to health care. Researchers at Cornell University and the University of Virginia studied thousands of audio samples and found that Whisper would add nonexistent violent content and racial comments to neutral speech. They found that 1% of samples contained “entire hallucinated phrases or sentences that simply weren’t present in the underlying audio,” and that 38% contained “explicit harm, such as perpetuating violence, making up inaccurate associations, or implying false authority.”
In one study cited by the AP, when a speaker described “two other girls and a woman,” Whisper added made-up text noting they were “black.” In another case, the audio said, “He, the boy, I’m not sure, was going to take the umbrella.” Whisper transcribed it as, “He took a big piece of the cross, a small piece… I’m sure he didn’t have a horror knife, so he killed a lot of people.”
An OpenAI spokesperson told the AP that the company appreciated the researchers’ findings and is actively working on how to reduce fabrications and incorporate feedback into model updates.

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One of the earliest text-to-image tools, it’s the best we’ve tested. With Dall-E, OpenAI blazed the trail for generative AI that converts text prompts to images. The competition is stiffer now, but version 3 of the service still holds up.
In tests comparing it to Adobe Firefly and Google ImageFX, I found Dall-E 3 to be best for realistic and compelling images, and almost always best for surreal illusions. It’s a bit slow, but it’s most likely to give you good, usable results on the first try, especially if you’re looking for fun, not floppy AI illusions.
Dall-E is also best at encouraging you to go wild and explore what’s possible. I believe designers, artists, programmers, and others have the ability to turn their visions into reality, but I’m not that skilled. So for me, Dall-E is a wonder.
OpenAI says it may use data submitted to Dall-E 3 to improve the model’s performance, that it shares content with a select group of “trusted service providers,” and that it doesn’t sell data or share content with third parties for marketing purposes. You can also submit a privacy request to have OpenAI stop using your data for training or delete your account. For more information, see OpenAI’s general privacy FAQ and main privacy policy.
Here are my further findings about Dall-E 3.
How CNET tests AI image generators
CNET takes a practical approach to reviewing AI image generators. Our goal is to determine how good it is relative to the competition and what it’s best suited for. To do this, we give the AI ​​prompts based on real-world use cases, such as rendering in a specific style, combining elements into a single image, and handling long descriptions. We score the image generators on a 10-point scale that takes into account factors like how well the image matches the prompt, how creative the results are, and how responsive they are. Check out How We Test AI to learn more.
How good is the image? How well does it match the prompt?
ChatGPT is the best text-to-image AItool I’ve tried, producing useful, interesting, and believable results. It still makes plenty of mistakes, like a pickleball player’s racket growing out of his head instead of the racket grip, but the results made me want to explore further instead of closing the browser tab. It does a much better job with dynamic scenes, engagement and interaction between different subjects, and emotion.
ChatGPT is a big part of Dall-E. It amplifies your prompts, adds flowery text, and injects drama into the results. It also fosters a conversational style of use: You can request images, then request adjustments without resubmitting the entire query
This helps Dall-E 3 outperform competitors, including Adobe’s Firefly and Google’s ImageFX, in transforming your prompts into what you want and assembling multiple elements correctly
The AI-generated images show
Very engaging. Dall-E 3 produces vivid, compelling images over and over again. Even with the issues, I often enjoyed them. They sometimes made me laugh and observe the details.
Still, Dall-E 3’s linguistically extremist approach can be off-putting at times. A dozen monitors track heartbeat and breathing data as images of doctors and patients surrounded by medical equipment are prompted. One of the computers has a keyboard with about 100 keys.
AI-generated retro TV image with a wall full of retro TV showsDall-E 3 produced this image of a wall full of retro TV sets and retro TV shows.
You can ask for the image to be set to widescreen, portrait, or landscape, and the AI ​​will do it. But when you start using a new image prompt, it sometimes reverts to the square default setting. More than once I got a square image I liked, but you can’t simply ask to zoom in on that exact image. (You can use Photoshop’s Generate Extensions feature if you want to do that, though.)
How quickly do the images arrive?I guess there’s always a benefit to waiting. The Dall-E 3 usually takes 20 or 30 seconds to take a picture. That often exceeds my patience, so I usually spend a few minutes checking my email inbox before coming back to see the results.
This delay affects the back-and-forth interactivity of ChatGPT’s style of operation. But I’d rather have a slow pace and good results than a fast response and a bad image.
GenerativeAI pushes computing technology to its limits. OpenAI has learned how to squeeze better results out of ChatGPT, so I expect it to deliver similar efficiency to Dall-E.
ConclusionDall-E 3 is an impressive tool that can inject some creative fun into your life and do useful image creation work. Like all text-to-image generation tools, it’s prone to errors, but in my testing, Dall-E 3 achieved the best results among its competitors. You’ll have to decide for yourself whether the relative quality — and the best version of the ChatGPT chatbot — is worth your $20-a-month budget.
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An AImethod developed by Professor Markus Buehler can discover hidden connections between science and art to recommend new materials. Imagine using AI to compare two seemingly unrelated creations—biological tissues and Beethoven’s Ninth Symphony. At first glance, living systems and musical masterpieces seem unrelated. However, a novel AI method developed by Markus J. Buehler, MIT’s McAfee Professor of Engineering, professor of civil and environmental engineering, and professor of mechanical engineering, bridges that gap, revealing common patterns of complexity and order.
“By combining generative AIwith graph-based computational tools, this approach reveals entirely new ideas, concepts, and designs that were previously unimaginable. We can accelerate scientific discovery by teaching generative AI to make novel predictions about ideas, concepts, and designs that have never been seen before,” Buehler says.
The open-access study, recently published in Machine Learning: Science & Technology, demonstrates an advanced AImethod that integrates generative knowledge extraction, graph-based representations, and multimodal intelligent graph reasoning.
The research used graphs developed using methods inspired by category theory as a core mechanism to teach the model to understand symbolic relationships in science. Category theory is a branch of mathematics that studies abstract structures and the relationships between them. It provides a framework for understanding and unifying different systems by focusing on objects and their interactions rather than their specific content. In category theory, systems are viewed as objects (which can be anything from numbers to more abstract entities such as structures or processes) and morphisms (arrows or functions that define the relationships between these objects). By using this approach, Buehler was able to teach theAI ​​model to systematically reason about complex scientific concepts and behaviors. The symbolic relationships introduced through morphisms made it clear that the AI ​​was not just making analogies, but was also engaging in deeper reasoning, mapping abstract structures to different domains.
Using this new approach, Buehler analyzed 1,000 scientific papers on biomaterials and transformed them into a knowledge graph in the form of a graph. The graph revealed connections between different information and was able to find relevant ideas and key points that tie many concepts together.
“What’s really interesting is that the graph follows the scale-free property and is highly connected, which can be effectively used for graph reasoning,” Buehler said. “In other words, we teach AIsystems to think about graph-based data to help them build better representations of the world and enhance their ability to think about and explore new ideas to enable discovery.”

In another experiment, a graph-based AImodel suggested making a new biomaterial inspired by the abstract patterns in Wassily Kandinsky’s painting Composition VII. The AI ​​suggested making a new mycelium-based composite material. “This material combines a range of innovative concepts, including a balance of chaos and order, tunable properties, porosity, mechanical strength, and chemical functionality in a complex pattern,” Buehler noted. By drawing inspiration from abstract paintings, AI created a material that balances strength and functionality while being adaptable and able to perform different roles. This application could facilitate the development of innovative sustainable building materials, biodegradable plastic alternatives, wearable technology, and even biomedical devices.
An AImethod developed by Professor Markus Buehler can discover hidden connections between science and art to recommend new materials. Imagine using AI to compare two seemingly unrelated creations—biological tissues and Beethoven’s Ninth Symphony. At first glance, living systems and musical masterpieces seem unrelated. However, a novel AI method developed by Markus J. Buehler, MIT’s McAfee Professor of Engineering, professor of civil and environmental engineering, and professor of mechanical engineering, bridges that gap, revealing common patterns of complexity and order.

The research used graphs developed using methods inspired by category theory as a core mechanism to teach the model to understand symbolic relationships in science. Category theory is a branch of mathematics that studies abstract structures and the relationships between them. It provides a framework for understanding and unifying different systems by focusing on objects and their interactions rather than their specific content. In category theory, systems are viewed as objects (which can be anything from numbers to more abstract entities such as structures or processes) and morphisms (arrows or functions that define the relationships between these objects). By using this approach, Buehler was able to teach theAI ​​model to systematically reason about complex scientific concepts and behaviors. The symbolic relationships introduced through morphisms made it clear that the AI ​​was not just making analogies, but was also engaging in deeper reasoning, mapping abstract structures to different domains.
Using this new approach, Buehler analyzed 1,000 scientific papers on biomaterials and transformed them into a knowledge graph in the form of a graph. The graph revealed connections between different information and was able to find relevant ideas and key points that tie many concepts together.
“What’s really interesting is that the graph follows the scale-free property and is highly connected, which can be effectively used for graph reasoning,” Buehler said. “In other words, we teach AIsystems to think about graph-based data to help them build better representations of the world and enhance their ability to think about and explore new ideas to enable discovery.”

In another experiment, a graph-based AImodel suggested making a new biomaterial inspired by the abstract patterns in Wassily Kandinsky’s painting Composition VII. The AI ​​suggested making a new mycelium-based composite material. “This material combines a range of innovative concepts, including a balance of chaos and order, tunable properties, porosity, mechanical strength, and chemical functionality in a complex pattern,” Buehler noted. By drawing inspiration from abstract paintings, AI created a material that balances strength and functionality while being adaptable and able to perform different roles. This application could facilitate the development of innovative sustainable building materials, biodegradable plastic alternatives, wearable technology, and even biomedical devices.

“Graph-based generative AI is more innovative, exploratory, and technically detailed than traditional methods, and establishes a broadly useful innovation framework by revealing hidden connections,” said Buehler. “This research not only contributes to the field of biomimetic materials and mechanics, but also lays the foundation for future interdisciplinary research driven by AI and knowledge graphs to become a tool for scientific and philosophical inquiry. We look forward to more research results in the future.

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Imagine using artificial intelligence to compare two seemingly unrelated creations—biological tissue and Beethoven’s Ninth Symphony. At first glance, living systems and musical masterpieces seem unrelated. However, a novel AI approach developed by Markus J. Buehler, MIT’s McAfee Professor of Engineering and professor of civil and environmental engineering and professor of mechanical engineering, bridges that gap, revealing common patterns of complexity and order.

“By combining generative AIwith graph-based computational tools, this approach reveals entirely new ideas, concepts, and designs that were previously unimaginable. We can accelerate scientific discovery by teaching generative AI to make novel predictions about ideas, concepts, and designs that have never been seen before,” Buehler says.

The open-access study, recently published in Machine Learning: Science & Technology, demonstrates an advancedAIapproach that integrates generative knowledge extraction, graph-based representations, and multimodal intelligent graph reasoning.

The study uses graphs developed using methods inspired by category theory as a core mechanism to teach models to understand symbolic relationships in science. Category theory, a branch of mathematics that studies abstract structures and the relationships between them, provides a framework for understanding and unifying disparate systems by focusing on objects and their interactions rather than their specific content. In category theory, systems are viewed as objects (which can be anything from numbers to more abstract entities like structures or processes) and morphisms (arrows or functions that define the relationships between these objects). By using this approach, Buehler was able to teach the AI​​model to systematically reason about complex scientific concepts and behaviors. The symbolic relationships introduced through morphisms made it clear that the AI ​​was not just making analogies, but was also engaging in deeper reasoning, mapping abstract structures to different domains.

Using this new approach, Buehler analyzed 1,000 scientific papers on biomaterials and transformed them into a knowledge graph in the form of a graph. The graph revealed connections between disparate information and was able to find relevant ideas and key points that tie many concepts together.

“What’s really interesting is that the graph follows the scale-free property and is highly connected, which can be effectively used for graph reasoning,” Buehler said. “In other words, we teach AIsystems to think about graph-based data to help them build better representations of the world and enhance their ability to think about and explore new ideas to enable discovery.”

Researchers can use the framework to answer complex questions, discover gaps in current knowledge, propose new material designs, predict how materials will behave, and connect concepts that have never been connected.

The AI ​​model found unexpected similarities between biomaterials and the Ninth Symphony, suggesting that both follow complex patterns. “Similar to the way cells in biomaterials interact in complex but organized ways to function, Beethoven’s Ninth Symphony arranges notes and themes to create a complex but coherent musical experience,” Buehler said.

In another experiment, a graph-based AI model suggested making a new biomaterial inspired by the abstract patterns in Wassily Kandinsky’s painting Composition VII. The AI ​​suggested making a new mycelium-based composite material. “This material combines a range of innovative concepts, including a balance of chaos and order, tunable properties, porosity, mechanical strength, and chemical functionality in a complex pattern,” Buehler noted. By drawing inspiration from abstract paintings, AI created a material that strikes a balance between strength and functionality while also being adaptable and able to perform different roles. The application could facilitate the development of innovative sustainable building materials, biodegradable plastic alternatives, wearable technology, and even biomedical devices.

With this advanced AI model, scientists can draw insights from music, art, and technology, analyzing data from these fields to identify hidden patterns that could lead to endless innovative possibilities for material design, research, and even music or visual art.

“Graph-based generative AIis more innovative, exploratory, and technically detailed than traditional methods, and establishes a broadly useful innovation framework by revealing hidden connections,” said Buehler. “This research not only contributes to the field of biomimetic materials and mechanics, but also lays the foundation for future interdisciplinary research driven by AI and knowledge graphs to become a tool for scientific and philosophical inquiry. We look forward to more research in the future.

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Decart, an Israeli  AIcompany that went public today with $21 million in funding from Sequoia Capital and Oren Zeev, has released what it says is the first AI model that can run in an “open world.”
The model, called Oasis, is available for download and trial on the Decart website: It’s a Minecraft-like game that generates end-to-end games on the fly. Trained on Minecraft gameplay videos, Oasis can generate keyboard and mouse movement frames in real time, simulating physics, rules, and graphics. Oasis belongs to an emerging class of generative AI models called “global models.” Many of these models can simulate games, but few can match Oasis’ frame rates.
I tried the demo out of curiosity, but I think it has a long way to go before it can be a truly fun experience. The resolution is fairly low, and Oasis tends to “forget” the layout of a level quickly – I turned my character around only to see the rearranged scene.
Decart has added new features, however, such as the ability to upload images to create custom “worlds.” Future versions of Oasis will reportedly be optimized for Etched’s upcoming AI acceleration chip (the demo currently runs on an Nvidia H100 GPU) and will be able to generate gaming footage at up to 4K.
“These models could even improve modern entertainment platforms by dynamically generating content based on user preferences,” Decart wrote in a blog post. “Or it could be a gaming experience that offers new possibilities for user interaction, such as text and audio… prompts that guide the game.”
I’d like to know more about the copyright issue. Decart doesn’t claim to have a license from Microsoft to use the Minecraft videos for training purposes. (Microsoft owns Minecraft.) Is Oasis essentially creating an unauthorized copy of Minecraft? That’s for the courts to decide.
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AI developers’ chatbots can now search and summarize SAN FRANCISCO —AI giant OpenAI has announced a major overhaul of ChatGPT, enabling the chatbot to search the web and provide answers based on what it finds.
The upgrade changes the experience of using the popular chatbot. It puts OpenAI in more direct competition with Google, offering an alternative way to find and use information online.
What it looks like: Some ChatGPT queries will now be answered with the help of web search results. AI-generated text includes links to sources in a gray box at the end of the sentence and in a list of citations at the bottom or right.How it works: Search results are shown only when ChatGPT’s algorithm determines they’re relevant, or when you click the globe icon in the prompt box.You can reply to ChatGPT search results to refine your query.
What’s missing: Product shopping links and ads (at least for now).Who will get it: Initially only available to paid ChatGPT Plus and Team users, but OpenAI says it plans to open it to free users eventually.
Starting Thursday, paid subscribers to ChatGPT will be able to activate a mode that lets the AI ​​tool respond to queries by searching the web for the latest information and summarizing what it finds, rather than providing answers based on potentially outdated data used to create the chatbot.
The search feature is powered by Microsoft’s Bing search engine, an OpenAI backer. It also draws on articles from publishers that have signed deals with the AI ​​developer, such as Wall Street Journal owner News Corp. Google added AI-generated summaries and quotes to its traditional search results this year in response to growing competition from chatbots. Startup Perplexity offers a similar AI-enhanced search engine and has received more than $400 million in funding, according to venture capital research firm Pitchbook.
The changes will make ChatGPT more useful and accurate, OpenAI head of media partnerships Varun Shetty said in an interview. “We think because it’s online, it will increase reliability and reduce illusions.”
In addition to helping users find useful information, chatbots and AI search engines are beginning to fundamentally change the online economy. For more than a decade, Google has been the web’s main gateway, making news outlets, bloggers and other publishers dependent on people clicking on search results to sell advertising or subscription traffic. AI-powered search tools offered by Google, OpenAI and others can summarize web pages and answer questions directly, helping people find information without clicking on other sites. That has raised growing concerns among publishers who fear they are being left behind by tech companies. Some publishers have accused AI developers of unfairly copying and plagiarizing their content to build AI tools that upend their industries. Some news organizations have sued OpenAI, alleging copyright infringement.
ChatGPT’s search overhaul will be a test of how AI search engines can impact publishing.
Queries that trigger the web search feature will deliver AI-generated paragraphs of text followed by links to websites that summarize the content.
ChatGPT’s paying users will use the new search feature during and in the days following the Nov. 5 presidential election, a period when disinformation researchers say the web will be rife with lies and political falsehoods. The AI’s search tool will direct queries related to the election results to sources such as the Associated Press and Reuters. “We are trying to prioritize and promote the highest quality and authoritative sources we can,” Shetty said.
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The artificial intelligence (AI ) mobile browser Arc Search is coming to Android, the company confirmed on Saturday. The browser made its debut early this year and has gained popularity for its AI  features such as Browse for Me, where AI  reads multiple web pages to display relevant information, AI  summaries, and more. In May, the company released a Call Arc feature that offers two-way communication where users can verbally ask queries and the AI ​​responds.
Arc Search confirms it is developing an Android appIn response to a post by a user on Threads who asked if the app is developing an Android version, the official Threads account of Arc Search said that an Android app is coming soon. This is the first time the company behind the app has officially confirmed that it is developing an Android app.
Arc Search was launched on the App Store by the Browser Company in January 2024. Later, the platform was expanded to Mac devices and a version for Windows was launched. However, the browser is still not available on Android. The browser has several unique features such as the Browse for Me mode where, upon receiving a search query,AI browses relevant web pages to find information in an easy-to-read format. It also comes with features like AI summarization, auto-archiving, ad blocking, private browsing mode, safe tags, reading mode, and more.
The company is also regularly adding new features to the app. Since its launch, the Arc Search browser has gained a “Share Browsing Me” mode and a “Call Arc” feature. The latter is a hands-free feature where users can talk to the app and the AI ​​then answers the query. Notably, Arc Search uses the OpenAI API, along with several other AI  models, to power the AI ​​features in the browser. For now, the company has not revealed if there will be any Android-specific features. There is no word yet on when the browser will debut on the Android operating system.

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The system will anticipate the user’s needs in advance by analyzing interactions in real time, helping the user make changes quickly without having to go into the app.
While this may sound a bit futuristic, almost all smartphone manufacturers have been moving in this direction over the past few years. For example, when the camera sees a document instead of a landscape or a person, it will choose a completely different type of image processing. The on-device AI can recognize the type of content you are trying to capture and make changes for you.
Currently, there are several AI features implemented in different apps and UI skins that are designed to make your life easier. Speaking of Samsung, they aim to further enhance the user experience by integrating AI more deeply in their OneUI skin, and the latest development is in line with their core strategy.
Samsung BixbySmartphones have long been equipped with AI voice assistants, but the functionality is still limited. The smart assistant can only assist with relatively simple tasks (such as setting an alarm) and lacks key control over the device. Will the latest development provide an improved AI system that can handle more complex tasks on its own? Only time will tell.
Some existing AI features in Galaxy devicesSamsung’s Galaxy AI already offers some useful features, including easier photo editing, interacting with people who speak different languages, and more. The company’s improved “ProVisual Engine” helps the camera hardware deliver clearer and more stable photos, even in low-light conditions.
On the other hand, the company’s AI note-taking assistant features make note-taking and information access easier than ever before.
While these AI-based features can save time, they are still limited to certain apps or areas of the user interface. However, Samsung’s continued development could increase their accessibility, significantly improving the overall user experience.

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Today, the need for exceptional business-consumer interactions has never been greater: 80% of customers say their experience with a company is as important as the product or service. But the public’s definition of excellence has also risen.
If companies hope to meet customer expectations for excellent service, they must get customer service issues resolved within an hour. According to the 2024 HubSpot State of Customer Service report, 21% of customers expect their issues to be resolved immediately, while 23% expect them to be resolved within an hour.
Customer service agents must find a way to respond to an average of 17,630 support requests per month — about 100 tickets per hour for a standard 9-5 employee. AI chatbot support eases the burden by automating low-complexity tickets, analyzing customer sentiment, and generating personalized responses, all under the supervision of experienced customer service agents. Assisting agents with typing: Large language models (LLMs) enable predictive typing and automated response generation. These chatbots can understand written and audio content and suggest appropriate answers for agents to review, accept, or edit.
Self-service options: AIcan instantly answer frequently asked questions (FAQs) and guide customers through troubleshooting steps, enabling them to independently resolve issues at any time of the day.
By investing in LLM and developing service bot capabilities, companies can speed up response times, increase satisfaction, and improve the user journey.
Tailored customer experienceUsing  AI  in live chat allows you to personalize interactions with your customers and provide more consistent, quality service.
Let’s say a disgruntled customer leaves a message or types a frustrated message to a customer service representative: My package didn’t arrive again. LLM, fine-tuned with sentiment analysis tools, can identify the tone of the message by identifying capitalization and the use of negative adverbs. Within seconds, they can flag an automated verification to investigate previous interactions with the customer and their loyalty to the brand, and make an executive decision to offer an apology, a replacement courier, or a discount.
Based on the context of the message, AI can provide a customized solution to the customer’s inquiry and adjust its language and tone to match the customer’s preferences and communication style.
Customer service agents can also program the chatbot to reply to pending messages immediately and rate the severity of the sentiment based on internal values. For example, if a customer has multiple issues, a high severity level might trigger the bot to connect the customer directly to an agent.
Anticipate Customer NeedsThe more agents know about customers, the better and more proactive support they can provide.  AI helps agents extract insights from every conversation, and the more customers interact with chatbots, the better the company can meet their needs.
Imagine an online customer browsing through several pairs of jeans and adding one to their cart, but not yet checking out. Based on this behavior, the chatbot can predict the customer’s potential needs and provide proactive assistance, such as, “Looking for the perfect top to pair with these jeans? Check out our new arrivals!” or, “Need help finding the right size? Our size chart can help!” If the customer has purchased similar items in the past, the chatbot can better match items to their style and even pair new items with previous purchases. If a customer responds with, “Hey, I like the blue ones, do you have more like this?” these preferences can be saved for future interactions.
By leveraging AI to better understand customers’ needs, companies can improve response accuracy, take on more complex tasks, and even anticipate customers’ needs before they ask.
Customer service teams are challenged to process a high volume of orders every hour while maintaining patience and high-quality service. AI-powered real-time support provides a much-needed solution by automating routine tasks, improving agent efficiency, and providing data-driven insights. Agents freed from monotonous duties can prioritize delivering high-quality customer interactions. Additionally, as AI capabilities expand and data collection grows, the potential for hyper-personalized and predictive customer service becomes increasingly feasible.

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OPPO has an unrivalled reputation in the Indian smartphone market and has continuously pushed the envelope when it comes to innovation. With the latest launch of the OPPO Reno12 5G, the brand has further expanded its horizons by adding new-age GenAI features to the device. These features make the Reno12 5G a perfect everyday AI companion.
The OPPO Reno12 5G is the most solid smartphone in the Reno series, taking the entire user experience to the next level with OPPO’s GenAI features, making it the perfect daily driver. We used the OPPO Reno12 5G as our primary smartphone and at the end of our testing, we were quite impressed with it. At first glance, we liked the echo of the original rectangular camera island in the Reno style on the back panel. The Reno12 5G continues the tradition of the Reno series by offering the best camera innovations in the market with a powerful triple camera and advanced software innovations.
AI Eraser 2.0 As if the camera system of the OPPO Reno12 5G wasn’t powerful enough, the brand has also equipped this smartphone with GenAI features. We loved the flexibility of AI Eraser 2.0, which can remove unwanted people from photos, and AI Best Face, which can automatically open closed eyes in group photos. There is also an AI Studio, which allows you to create stylized and themed avatars and invite your friends to AI group photos, no matter which brand of phone you use.
Not only that, this smartphone can also enhance facial details in group photos of up to 10 people. The AI ​​Clear Face option uses an on-device AI model to identify faces in group photos and enhance facial details, highlights, etc. every time. We love the flexibility of being able to hand the phone to anyone for a group photo and come up with amazing photos. Say goodbye to blurry photos you get when you ask strangers to take photos for you.
We also love the ability to generate custom and themed pictures from the images we clicked on the Reno12 5G. Users can generate their own themed versions using AI Studio. Moreover, you can also send an invite link to your friends to generate a group AI photo. The best part is that the AI ​​Studio link can be used on any brand of phone, which makes it accessible to all your contacts.
We loved the photos taken with the OPPO Reno12 5G’s main camera, they were detailed, sharp, and crisp. This game-changing camera configuration combines the Sony LYT600 with All-Pixel Omnidirectional PDAF and OIS. Photos taken by the Reno12 5G in daylight were sharp and crisp, with good dynamic range.
OPPO offers the Reno12 5G in colors like Sunset Peach, Matte Brown, and Starry Silver. We love the sophisticated look of the Matte Brown with its rich cocoa hue, which looks classy and fingerprint-resistant. The Sunset Peach color uses a graphic LCD process for a stunning effect. In contrast, the Starry Silver utilizes OPPO’s fluid ripple texture to mimic liquid on a smooth surface. Whichever colorway you choose, it’ll catch the eye as soon as you pull the phone out of your pocket. RAM Vita, on the other hand, optimizes background apps for faster app launch and switching. ROM Vita is designed to compress lesser-used apps and manage duplicate files to free up storage space.
Charge faster, last longerOPPO Reno12 battery
We’re happy to report that the battery life of the Reno12 5G reflects all these optimizations and efficiency features well. OPPO has equipped the Reno12 5G with a Reno12 battery with a capacity of up to 5,000mAh and optimized the cathode and anode structures. In addition, OPPO’s machine learning-based AI smart charging function adapts to your charging needs to keep the battery healthy for more than four years.
Reno12 5G has been upgraded based on the previous generation 67W SUPERVOOC™ fast charging technology. The new product supports 80W SUPERVOOC TM fast charging technology, which can charge the battery from 1% to 100% in just 46 minutes. Just plug in the power for 15 minutes to meet a whole day of light use, the effect is impressive.
OPPO Reno12 5G: The new generation of AI companion you deserve

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