Shutterstock launches AI image generator with ethical focus

AI Image Generator Text to Image Online App

Implement image anomaly detection today to avoid false positives in your quality control processes. Before we put FMs to work, traditional forms of machine learning allowed us to take simple inputs, like numeric values, and map them to simple outputs, like predicted values. With more advanced ML techniques, especially deep learning, we could take somewhat more complicated inputs, like videos or images, and map them to relatively simple outputs.

generative image ai

We encourage your company to discard static modifications or software that cannot detect all anomalies and issues real-time. Instead, think of ways to implement generative deep learning and image anomaly detection into your company’s manufacturing tasks. Generative deep learning models can be trained and taught to detect anomalies at the most minute level. Unlike other softwares or coding, generative deep learning is dynamic and uses predictive analysis to detect anomalies.

Shutterstock launches AI image generator with ethical focus

The process is not a static technical code, instead, it is a generative deep learning algorithm. Implementing generative deep learning allows tasks to be performed with near-zero efficiency loss. Generative deep learning can handle even the rarest of anomaly detection cases. At Gemmo, we offer AI manufacturing solutions, including object detection and object tracking for anomaly detection. Gemmo can help you today to set up a fault detection system with computer-vision solutions, which will boost your company’s quality control, performance, and safety.

AI-powered BeFake is a real app, not a BeReal parody…and it has $3M in funding – TechCrunch

AI-powered BeFake is a real app, not a BeReal parody…and it has $3M in funding.

Posted: Thu, 31 Aug 2023 12:48:22 GMT [source]

In one particularly intriguing use case, some Chinese office complexes have vending machines that identify shoppers through facial recognition technology and track the items they take from the machine to ultimately bill the shoppers’ accounts. Even anonymous data about shoppers collected from cameras such as age, gender, and body language can help retailers improve their marketing efforts and provide a better customer experience. And then we’ve got generative AI platforms that harness the full might of AI to create, edit, and optimise content, given a human mind knows how to make the most of them. Combined with the power of visual storytelling, it offers a plethora of benefits (e.g. personalisation, data in abundance, and a focus on creativity instead of mundane tasks) that should entice marketers to embrace this forward-looking tech. Especially considering today’s digital landscape, moving and evolving at hypersonic speed, where the human attention span has been demoted to that of one below a goldfish. Webdam (now Bynder) found that social media posts with images receive 650% more engagement than text-only ones.

Generative AI’s copyright implications

More conceptually, while some see AI image generators as useful springboards for ideas, others point out that they can’t create images of anything they haven’t already seen. That means that, unlike humans, they’re not capable of creating anything truly original. Our signals coverage is powered by GlobalData’s Thematic Engine, which tags millions of data items across six alternative datasets — patents, jobs, deals, company filings, social media mentions and news — to themes, sectors and companies. These signals enhance our predictive capabilities, helping us to identify the most disruptive threats across each of the sectors we cover and the companies best placed to succeed. Shutterstock is partnering with NVIDIA to develop models to generate 3D assets trained on fully licensed content from Shutterstock.

generative image ai

Although it depends on what the AI model has been trained on, words like ‘masterpiece’, ‘ultrarealistic’, ‘art photography’, ‘UHD’ and ‘Kodak’ are said to work well. Specifying focal lengths, camera models or even the name of stock photography sites also seems to help when aiming for photorealistic results. The tool will allow users to generate objects in their image, generate new backgrounds behind an image’s subject, extend images, and remove objects – all via a simple selection and text prompt. According to GlobalData’s social media database, tech regulation has been a major discussion point for social media users over the last 12 months.

Something I already advocate for anyone wanting to improve their search performance is to pay attention to the singles in the SERP in particular the ‘People also ask’ box. These are normally based on longer phrases along the same topic and generally have less competition than the shorter top of funnel queries. Lastly generative AI should help us, “discover a range of products and things to consider while shopping.” This doesn’t sound particularly ground breaking but in practice it could be quite clever.

A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

generative image ai

However, this was not done out of privacy concerns but to “minimise drama,” according to the company’s founder and CEO David Holz, who wrote this in a post on the chat service Discord, as reported by the Washington Post. Some news organisations have also been working to develop tools to let audiences know that their content is real. Adobe’s recently introduced image-generating tool Firefly will include ‘content credentials’ in each image or a label that would tell genrative ai users if an image was created by AI or not, according to the company’s Chief Trust Officer Dana Rao. Rao cited the fight against misinformation and sorting what is real and what is fake going forward as one of the reasons why the company is introducing this caveat. NLG (Natural Language Generation) is a field of computer science that deals with the generation of human language. NLG systems are used to create text, speech, and other forms of human language output.


Adobe says that it’s implemented filters to prevent Generative Expand from generating toxic content — a notorious problem for generative art AI. So yes, you need to go through the chat app for access – but don’t let that stop you. Midjourney is one of the top picks for image generation, and it doesn’t take long to see why.

The company says it has buy-in from Midjourney and Shutterstock on this, with others set to follow. With this information, users can get a better idea of where the image originated and how it spread. Is the context in which it’s used elsewhere completely different to the description you’ve seen it with? Google, which has its own big plans for generative AI over the coming months, has announced two features to help people establish which pictures are real and which are algorithmically generated.

For instance, in a photo of a fruit-filled table, we can easily replace an apple with a pineapple. Generative Fill generates a seamless and convincing pineapple substitution by selecting the apple and typing Pineapple in the text prompt. Easily remove unwanted objects from your image by following a simple process. First, use the lasso tool to draw a rough outline around the objects you want to eliminate.

Artificial Intelligence Can Now Generate Amazing Images – What Does This Mean For Humans?

Adobe’s AI-powered Generative Fill is not difficult to use and can actually provide some spectacular results – after a fair amount of trial and error. All you need to do is select the area for editing, input your prompt in the text box, and click ‘generate’. Leave the text box blank if you want Adobe to remove an object or fill in the background space.

  • They demonstrate this by replacing the interviewers face with Chris’s in a live video, and even replicating the voice.
  • Currently, SynthID is only available to paying customers who are using Google’s Cloud computing services, and it is reported to only work on images that are generated using Google’s Imagen image generator.
  • This allows it to assess, identify and make connections between billions of words, images, and other data types to understand the relationships between them.

It’s a major driver of long hold times and delayed chat responses for healthcare organizations, and it hurts the patient experience as well as the team’s efficiency. Agents supporting important functions like patient access, revenue cycle, and patient services can spend large amounts of time recording, summarizing, and categorizing their chats and calls with patients, usually into the EHR. Google’s objective is to keep us happy using them as a search engine and they do a very good job of it.

Generative AI is a broader field that encompasses Natural Language Processing (NLP) and Natural Language Generation (NLG) as specific areas of focus. Generative AI refers to the use of artificial intelligence techniques to generate genrative ai new content, such as text, images, music, and more. Smart ideas are explored and good journalism is done on how AI technologies affect society, such as Studio Ett’s special broadcast on AI and Vetenskapsradion’s in-depth studies.

At simply we would be happy to use any of those four assets as part of a sustainability campaign. It has a regular issues with misshaping faces and the pop up frenzy is because it’s a completely free tool. You are, however, allowed on the Stable Diffusion Playground for free so you can prompt and generate away so take a look for yourself. After downloading the app, we were only offered a one-month plan and a one-year plan despite already having an account. Opting the one month it then immediately took payment from another card, so we have ended up with two licenses. The fact this YouTube tutorial on onboarding takes half an hour says all you need to know.

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