#ai can do better help then chatpgt

 ai mentor

#Aitools #aicontentscreater

aitools 

#aitools #aidesign #aiimagegenerator

If you want to create better graphics and photos for your marketing campaigns, you might want to try some of the AI tools that are available online.

These tools can help you design logos, edit images, generate videos, and more, using artificial intelligence to save you time and money.

Here are six AI tools that you can use to create stunning visuals for your business:

* Adobe Firefly: This tool is for graphic designers who use Adobe products like Photoshop and Express. It lets you create images, transform text, and play with color using simple text prompts. You can also use it to automate some of the manual tasks in design, such as filling in gaps or removing objects from images.

* Uizard: This tool is for people who have no design experience but want to create user interfaces or user experiences for their products. It lets you turn a sketch into a mock-up or a wireframe in minutes. You can also use it to create landing pages, apps, or websites.

* Midjourney: This tool is for anyone who wants to generate realistic images from any prompt. It is hosted on Discord, so you need to create an account there first. Then you can use the Midjourney bot to create images and graphics for personal or professional use.

* Canva: This tool is a popular online graphic design platform that lets you create stunning visuals for your social media posts. You can choose from thousands of templates, icons, fonts, and images, or upload your own. Canva also has a feature called Design Assistant that uses AI to suggest improvements and ideas for your designs.

* Google’s AutoDraw: This tool is a free online service that uses AI to turn your doodles into refined illustrations. You just need to draw something with your mouse or finger, and AutoDraw will suggest matching icons or shapes that you can use or edit.

* Khroma: This tool is an online platform that uses AI to help you find color palettes for your design projects. You can train the AI by choosing colors you like or dislike, and Khroma will generate custom palettes that match your preferences.

What’s your go-to tool when designing images?

give your suggestions  if  you any other that work better

Request a demo

Sprout Blog / All Marketing Insights / AI

How to craft an effective AI use policy for marketing

Annette Chacko

Written by @nasirkaleem

Published on nasirkaleem12    30September 2023

R

#aiusepolicy

  AI can be a game-changer for your marketing strategy, but it also comes with some risks. 

That’s why you need an AI use policy for your team. 📝

It’s a document that outlines how you’ll use AI tools in a safe and ethical way.

Here are some tips from Sprout Social to create your own AI use policy:

* Assign someone to oversee AI governance in your company. They’ll check if the tools are working well and following the rules. 🕵️‍♂️

* Introduce AI tools gradually and carefully. Watch how they perform and protect your data privacy. 🛡️

* Define low-risk and high-risk tasks for AI usage. For example, writing social media posts is low-risk, but giving legal advice is high-risk. 🙅‍♀️

* Know your intellectual property rights. Content made by AI may not be protected by law. Don’t share any sensitive information with AI systems. 🔐

* Tell your audience when you use AI-generated content. It’s the law and it’s the right thing to do. 🙌

Want to learn more? Check out this article from Sprout Social.👇👇

Technology, like art, stirs emotions

 and sparks ideas and discussions. The emergence of artificial intelligence (AI) in marketing is no exception. While millions are enthusiastic about embracing AI to achieve greater speed and agility within their organizations, there are others who remain skeptical—pretty common in the early phases of tech adoption cycles.

In fact, the pattern mirrors the early days of cloud computing when the technology felt like unchartered territory. Most companies were uncertain of the groundbreaking tech—concerned about data security and compliance requirements. Others jumped on the bandwagon without truly understanding migration complexities or associated costs. Yet today, cloud computing is ubiquitous. It has evolved into a transformative force, from facilitating remote work to streaming entertainment.

As technology advances at breakneck speed and leaders recognize AI’s value for business innovation and competitiveness, crafting an organization-wide AI use policy has become very important. In this article, we shed light on why time is of the essence for establishing a well-defined internal AI usage framework and the important elements leaders should factor into it.

Please note: The information provided in this article does not, and is not intended to, constitute formal legal advice. Please review our full disclaimer before reading any further.

Why organizations need an AI use policy

Marketers are already investing in AI to increase efficiency. In fact, The State of Social Report 2023 shows 96% of leaders believe AI and machine learning (ML) capabilities can help them improve decision-making processes significantly. Another 93% also aim to increase AI investments to scale customer care functions in the coming three years. Brands actively adopting AI tools are likely going to have a greater advantage over those who are hesitant.

Given this steep upward trajectory in AI adoption, it is equally necessary to address the risks brands face when there are no clear internal AI use guidelines set. To effectively manage these risks, a company’s AI use policy should center around three key elements:

Vendor risks

Before integrating any AI vendors into your workflow, it is important for your company’s IT and legal compliance teams to conduct a thorough vetting process. This is to ensure vendors adhere to stringent regulations, comply with open-source licenses and appropriately maintain their technology.

Sprout’s Director, Associate General Counsel, Michael Rispin, provides his insights on the subject. “Whenever a company says they have an AI feature, you must ask them—How are you powering that? What is the foundational layer?”

It’s also crucial to pay careful attention to the terms and conditions (T&C) as the situation is unique in the case of AI vendors. “You will need to take a close look at not only the terms and conditions of your AI vendor but also any third-party AI they are using to power their solution because you’ll be subject to the T&Cs of both of them. For example, Zoom uses OpenAI to help power its AI capabilities,” he adds.

Mitigate these risks by ensuring close collaboration between legal teams, functional managers and your IT teams so they choose the appropriate AI tools for employees and ensure vendors are closely vetted.

AI input risks

Generative AI tools accelerate several functions such as copywriting, design and even coding. Many employees are already using free AI tools as collaborators to create more impactful content or to work more efficiently. Yet, one of the biggest threats to intellectual property (IP) rights arises from inputting data into AI tools without realizing the consequences, as a Samsung employee realized only too late.

“They (Samsung) might have lost a major legal protection for that piece of information,” Rispin says regarding Samsung’s recent data leak. “When you put something into ChatGPT, you’re sending the data outside the company. Doing that means it’s technically not a secret anymore and this can endanger a company’s intellectual property rights,” he cautions.

Educating employees about the associated risks and clearly defined use cases for AI-generated content helps alleviate this problem. Plus, it securely enhances operational efficiency across the organization.

AI output risks

Similar to input risks, output from AI tools poses a serious threat if they are used without checking for accuracy or plagiarism.

To gain a deeper understanding of this issue, it is important to delve into the mechanics of AI tools powered by generative pre-trained models (GPT). These tools rely on large language models (LLMs) that are frequently trained on publicly available internet content, including books, dissertations and artwork. In some cases, this means they’ve accessed proprietary data or potentially illegal sources on the dark web.

These AI models learn and generate content by analyzing patterns in the vast amount of data they consume daily, making it highly likely that their output is not entirely original. Neglecting to detect plagiarism poses a huge risk to a brand’s reputation, also leading to legal consequences, if an employee uses that data.

In fact, there is an active lawsuit filed by Sarah Silverman against ChatGPT for ingesting and providing summaries from her book even though it’s not free to the public. Other well-known authors like George RR Martin and John Grisham too, are suing parent company, OpenAI, over copyright infringement. Considering these instances and future repercussions, the U.S. Federal Trade Commission has set a precedent by forcing companies to delete their AI data gathered through unscrupulous means.

Another major problem with generative AI like ChatGPT is that it uses old data, leading to inaccurate output. If there was a recent change in areas you’re researching using AI, there is a high probability that the tool would have overlooked that information as it wouldn’t have had time to incorporate the new data. Since these models take time to train themselves on new information, they may overlook the newly added information. This is harder to detect than something wholly inaccurate.

To meet these challenge, you should have an internal AI use framework that specifies scenarios where plagiarism and accuracy checks are necessary when using generative AI. This approach is especially helpful when scaling AI use and integrating it into the larger organization as well.

As in all things innovative, there are risks that exist. But they can be navigated safely through a thoughtful, intentional approach.