ChatGPT has added a new image library — here's how to use it
OpenAI has introduced an image library to ChatGPT, addressing a pain point many users have experienced when creating AI-generated images. Previously, finding images you'd created meant scrolling through conversation history or downloading each image immediately.
The new library creates a centralized space where all images generated with the ChatGPT 4o model are automatically stored and displayed chronologically. While this might seem like a simple addition, this is particularly useful or those who use image generation regularly.
Let's explore what this new feature offers, where to find it, and how to make the most of your growing collection of AI-generated imagery.
Finding the new Image Library is straightforward. First, log in in to your ChatGPT account.
Now you're logged in, look at the left-hand navigation sidebar.
You'll find Library listed beneath above Explore GPTs, with a number displayed alongside it showing your total image count so far.
Upon opening the library, you'll see all your images arranged in reverse chronological order, with the most recent creations appearing first.
This makes it easy to quickly locate your latest work without scrolling through conversation history.
For a better view, you can click on any image to open an enlarged version.
Once in this view, arrow buttons will appear, allowing you to browse through your entire collection in a carousel-style interface without returning to the grid view.
Each image in your library receives an automatically generated title from ChatGPT. Interestingly, these titles don't simply repeat your original prompts but instead describe what's actually in the image.
This AI interpretation adds an extra layer of organization to your collection, making specific images easier to identify at a glance.
Each image includes an Edit image button that lets you make additional adjustments to existing creations. This feature is particularly valuable when you've created something close to your vision but want to refine specific elements without starting over completely.
The edit function reopens your image in the generation interface, allowing you to add new prompt instructions to guide further modifications.
You can generate an image directly in the Image Library, by clicking Create Image in the top right of the screen. This will bring you back the main prompting interface.
While the library significantly improves image organization, there are some limitations to be aware of. There is no direct link back to the original conversation where the image was created, which makes it harder to track the prompting process that led to successful generations.
The library also lacks a dedicated delete button within its interface. To remove an image from your library, you must delete the entire conversation it came from.
Now that you've learned how to navigate and use ChatGPT's image library, here's a few more AI-related tutorials you may find useful.
Check out I use ChatGPT every day to boost my productivity — and these 5 prompts always deliver and how to make GIFs using ChatGPT. And you can keep your data private by stoping ChatGPT from training with it.
Get instant access to breaking news, the hottest reviews, great deals and helpful tips.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
New York Post
30 minutes ago
- New York Post
Google's AI is ‘hallucinating,' spreading dangerous info — including a suggestion to add glue to pizza sauce
Google's AI Overviews, designed to give quick answers to search queries, reportedly spits out 'hallucinations' of bogus information and undercuts publishers by pulling users away from traditional links. The Big Tech giant — which landed in hot water last year after releasing a 'woke' AI tool that generated images of female Popes and black Vikings — has drawn criticism for providing false and sometimes dangerous advice in its summaries, according to The Times of London. 3 Google's latest artificial intelligence tool which is designed to give quick answers to search queries is facing criticism. Google CEO Sundar Pichai is pictured. AFP via Getty Images In one case, AI Overviews advised adding glue to pizza sauce to help cheese stick better, the outlet reported. In another, it described a fake phrase — 'You can't lick a badger twice' — as a legitimate idiom. The hallucinations, as computer scientists call them, are compounded by the AI tool diminishing the visibility of reputable sources. Instead of directing users straight to websites, it summarizes information from search results and presents its own AI-generated answer along with a few links. Laurence O'Toole, founder of the analytics firm Authoritas, studied the impact of the tool and found that click-through rates to publisher websites drop by 40%–60% when AI Overviews are shown. 'While these were generally for queries that people don't commonly do, it highlighted some specific areas that we needed to improve,' Liz Reid, Google's head of Search, told The Times in response to the glue-on-pizza incident. 3 Google AI Mode is an experimental mode utilizing artificial intelligence and large language models to process Google search queries. Gado via Getty Images The Post has sought comment from Google. AI Overviews was introduced last summer and powered by Google's Gemini language model, a system similar to OpenAI's ChatGPT. Despite public concerns, Google CEO Sundar Pichai has defended the tool in an interview with The Verge, stating that it helps users discover a broader range of information sources. 'Over the last year, it's clear to us that the breadth of area we are sending people to is increasing … we are definitely sending traffic to a wider range of sources and publishers,' he said. Google appears to downplay its own hallucination rate. When a journalist searched Google for information on how often its AI gets things wrong, the AI response claimed hallucination rates between 0.7% and 1.3%. 3 Google's AI Overviews, was introduced last summer and is powered by the Gemini language model, a system similar to ChatGPT. AP However, data from the AI monitoring platform Hugging Face indicated that the actual rate for the latest Gemini model is 1.8%. Google's AI models also seem to offer pre-programmed defenses of their own behavior. In response to whether AI 'steals' artwork, the tool said it 'doesn't steal art in the traditional sense.' When asked if people should be scared of AI, the tool walked through some common concerns before concluding that 'fear might be overblown.' Some experts worry that as generative AI systems become more complex, they're also becoming more prone to mistakes — and even their creators can't fully explain why. The concerns over hallucinations go beyond Google. OpenAI recently admitted that its newest models, known as o3 and o4-mini, hallucinate even more frequently than earlier versions. Internal testing showed o3 made up information in 33% of cases, while o4-mini did so 48% of the time, particularly when answering questions about real people.
CNET
41 minutes ago
- CNET
Google's AI Mode Now Creates Interactive Stock Charts For You
Google's AI Mode now can create interactive charts when users ask questions about stocks and mutual funds, the company said in a blog post Thursday. Users might ask the site to compare five years of stock performances for the biggest tech companies, or request to see mutual funds with the best rates of return over the past decade. Gemini, Google's AI engine, will then create an interactive graph and comprehensive explanation. I created a sample by going to the webpage for the new experiment (if you try it at work, you might learn that your admin has banned it, but it should work on a personal computer). Once there, I told it exactly what I wanted, "make me an interactive chart showing MSFT stock over the past five years." It produced the chart, and I was able to move the slider from one date to another, showing the stock price on that date. It's the same kind of chart you can probably get at your financial advisor's site, but it did work. Tell Google AI what chart you want, and it will create one that you can interact with. CNET But be warned: AI has accuracy issues, and users need to be extra-careful with financial information of any kind. "AI has historically struggled with quantitative reasoning tasks," said Sam Taube, lead investing writer at personal finance company NerdWallet. "It looks like Google's AI mode will often provide links to its data sources when answering financial queries. It's probably worth clicking those links to make sure that the raw data does, in fact, match the AI's output. If there's no link to a data source, proceed with caution; consider manually double-checking any numbers in the AI's output. I wouldn't trust any AI model to do its own math yet." The feature is a new experiment from Google Labs. At its I/O conference last month, Google announced AI Mode's ability to create interactive graphics for complex sets of data. The feature is now only for queries about stocks and mutual funds, but it will be expanded to other topics eventually. "I'd avoid asking AI any 'should I invest in XYZ' type questions," Taube told CNET. "The top AI models may be smart, but they aren't credentialed financial advisors and probably don't know enough about your personal financial situation to give good advice. What's more, AI doesn't have a great track record at picking investments, at least so far. Many AI-powered ETFs (funds that use AI to pick stocks to invest in) are underperforming the S&P 500 this year."
Business Insider
an hour ago
- Business Insider
DeepWho? DeepSeek rolled out even more powerful, cheap AI tech. If you missed it, you're not alone.
DeepSeek updated its R1 AI model a few days ago. It performs better and it's still cheaper than most other top models. Did you miss it? I missed it. Or I saw the news briefly and then forgot about it. Most of the tech industry and investors greeted the launch with a giant shrug. This is a pretty stark contrast to early 2025 when DeepSeek's R1 model freaked everyone out. Tech stocks plunged and the generative AI spending boom was seriously questioned. This time, DeepSeek's rollout "came and went without a blip," Ross Sandler, a top tech analyst at Barclays, wrote in a note to investors. "The stock market couldn't care less," he added. "This tells us that the investment community's level of understanding on the AI trade has greatly improved in just five short months." An unscientific DeepSeek poll I polled my colleagues on Business Insider's tech team on Friday, just to see if I'd been spending too much time watching Elon Musk and Donald Trump argue on social media (rather than doing my real job). Here are some of their responses: One editor said they didn't notice DeepSeek's update, but now they feel guilty for not spotting it. (Solid thinking. Only the paranoid survive in journalism). Another colleague said they knew about it from their quick headline scans, but didn't read too much into it. A tech reporter saw a Reddit thread about it, scanned it, and didn't think about it again. Another reporter said they missed it entirely. So, it barely registered. And these folks are glued to tech news every second of the day. Why does no one really care now? DeepSeek's latest R1 model is probably the third best in the world right now, so why isn't it making waves like before? Sandler, the Barclays analyst, noted that DeepSeek's latest offering is not quite as cheap as it used to be, relatively speaking. It costs just under $1 per million tokens, which was roughly 27 times cheaper than OpenAI's o1 model earlier this year. Now, DeepSeek's R1 is "only" about 17 times cheaper than the top model, according to Barclays research and data from Artificial Analysis' AI Intelligence Index. This illustrates a broader and more important point. Something I've been telling you about since last year: Most top AI models are roughly similar in performance because they've mostly been training on the same data from the internet. This makes it hard to stand out from the crowd, based just on performance. When you leap ahead, your inventions and gains are incorporated quickly into everyone else's offerings. Price is important, yes. But distribution is becoming key. If your employer has an enterprise ChatGPT account, for instance, you're highly likely to use OpenAI models at work. It's just easier. If you have an Android smartphone, you'll probably be talking to Google's Gemini chatbot and getting responses from the search giant's AI models. DeepSeek doesn't have this type of broad distribution yet, at least in the Western world. Was the AI infrastructure freakout misplaced? Then, there's the realization that "reasoning" models, such as DeepSeek's R1 and OpenAI's o3, require a massive amount of computing power to run. This is due to their ability to break requests down into multiple "thinking" steps. Each step is a new kind of prompt that is turned into a huge number of new tokens that need to be processed. The DeepSeek freakout in January happened mostly because the tech industry worried that the Chinese lab had developed more efficient models that didn't need as much computing infrastructure. In fact, this Chinese lab may have instead helped popularize these new types of reasoning models, which might require even more GPUs and other computing gear to run.
