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Unlock the Power of Automation with God Mode: The AI Tool that Automates Complex Tasks! Boost Efficiency, Save Time and Streamline Your Workflow Today! Try Now!
God Mode is an AI-powered tool that has the ability to self-generate tasks, take user prompts, and act on new tasks until it meets the original objective. It’s a unique tool that has been designed to automate complex tasks that would otherwise take a lot longer to complete manually. The tool is not entirely automated, as the user has approval rights for every step, allowing for redirection as well.
I began testing the tool with a task that I have already done manually, which was to create a strategy plan to research and engage with art buyers inside large retailers and merch brands. God Mode immediately conducted market research via Google, found lists, and started writing text files with notes.
After letting it run for over an hour, I added a couple of feedback notes to course correct the results. The tool successfully researched and developed a plan, created documents with engagement steps, and created a Python file to perform a specific task. However, it did not pull any contact information, which was a problem. It began to loop over and over, trying to pull contacts from LinkedIn, Google, and directories, but couldn’t pull the data properly.
I decided to test another idea, inspired by @elonmusk’s interview on Monday night, where he talked about finding the meaning of life. I set out to create “TruthGPT” to automate data research, store the data, interpret the dataset, and output findings and understandings on its own.
It worked much more effectively this time, and below are the list of the initial tasks of research.
See More: God Mode Auto GPT: How AI is Revolutionizing Automation
God Mode successfully researched the concept extensively, then created its own documentation to store the findings. It then trained itself on the data, which is quite impressive. After that, it created and ran a Python file, our own “TruthGPT”, to interpret its own dataset and give an output.
The tool successfully researched the concept extensively, then created its own documentation to store the findings. It then trained itself on the data, which is quite impressive. After that, it created and ran a Python file, our own “TruthGPT”, to interpret its own dataset and give an output.
The tool successfully created a text file with the five potential keys to reality as tasked to do, and well, simply put, we made a “TruthGPT” and found the meaning of life. (YAY! 🎉)
(Jokes aside, no, I don’t believe this is an actual “TruthGPT”). However, the process of automating complex tasks with ChatGPT is quite interesting, and soon, I don’t think there will be any gaps.
God Mode takes user prompts and acts on new tasks until it meets the original objective. The user has approval rights for every step, which allows for redirection if needed.
God Mode can automate complex tasks that would otherwise take a lot longer to complete manually.
The benefits of using God Mode include faster task completion, increased efficiency, and the ability to redirect tasks if needed.
In conclusion, God Mode is an AI-powered tool that is capable of automating complex tasks, thus increasing efficiency and reducing the time required to complete them. The tool takes user prompts and acts on new tasks until the original objective is met, with the user having approval rights for every step. While the tool is not entirely automated, it offers a unique approach to automating tasks with the ability to redirect tasks if necessary.
The tool has been tested, and it has shown its ability to conduct market research, create plans, and run Python files. Although there were some limitations in pulling data from sources, the tool was able to perform the desired tasks effectively. Additionally, the tool was tested on the creation of “TruthGPT,” which successfully researched and interpreted data to provide an output, even if it was just for fun.
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If you’re looking for a new AI image generator, Leonardo AI art might fit the bill.
Leonardo AI provides a simple, yet powerful, interface to access tons of ready-to-go AI image models.
This saves non-technical users countless hours trying to figure out how to set all of this up.
Not to mention, you won’t need to fork over thousands of dollars for a desktop capable of generating AI images locally.
In this post, I will provide an overview of Leonardo AI, how to get started, and a comparison to Midjourney.
Let’s get started!
Leonardo AI Example
Leonardo AI is an AI image generator platform that provides easy access to a wide variety of pre-trained image models.
According to the Leonardo AI team, the generative AI app aims to revolutionize content production in entertainment verticals like gaming.
Leonardo AI runs on Stable Diffusion and features a text-to-image generation process similar to Midjourney, Dall-E, and similar services.
Also: Adobe Firefly Alternatives
The platform is currently limited to early access, but free to use for users that are accepted.
Leonardo AI has experienced tremendous growth.
The Discord server has over 1 million registered users.
First, you will need to sign up for an account on Leonardo AI’s website.
The platform is still limited to early access, so there is no guarantee you will receive access to the service immediately.
Leonardo AI Sign Up
You can speed up this process by joining the Leonardo AI Discord server and filling out the priority white list form.
Once you have created an account, visit the Leonardo AI login screen.
You will then be greeted by the home screen dashboard.
Each model includes a sample image that reflects what you can expect to generate from a particular mode.
Generate with this Model
This will open up the generation view.
Leonardo AI Image Generation Options
The generation view shows:
Number of image generation tokens remaining
Number of images to output
Prompt Magic: Forces image to more strictly adhere to your prompt
Public Images: Anyone can see your images; default on ‘free tier’
Lastly, you enter your image prompt into the field.
You also have the option to include negative prompts that will block various attributes from appearing in your images.
Leonardo AI Assets
Initially, Leonardo AI was created for game developers and artists to generate assets for their projects.
A few examples of types of games assets that work well with generative AI:
While this content is primarily gaming-focused, it also has applications in the broader entertainment industry, marketing, and consumer goods spaces.
Leonardo AI and Midjourney both use similar processes for AI image generation, but there are some key differences to consider.
For most users, Midjourney functions primarily through Discord, while Leonardo AI features a user-friendly visual web app.
The Leonardo AI web app includes graphical elements like sliders and buttons to control properties such as resolution.
On the other hand, Midjourney requires users to adjust parameters within the prompt or Discord command.
Related: Midjourney Tips & Tricks
While Midjourney does not currently offer a free version, Leonardo AI users receive 150 free tokens each day, which translates to roughly 150 images per day.
Lastly, Leonardo AI’s wide selection of internal and community models offers users a wider variety of potential outputs and control over these outputs.
At the end of the day, these platforms are only as powerful as the models they are built on.
Midjourney still appears to have better quality image outputs out of the box.
But with some proper prompt engineering, I wouldn’t be surprised to see Leonardo AI capable of eventually matching this quality.
Leonardo AI is an AI image generation platform that provides users with easy access to a wide variety of Stable Diffusion-based models.
The platform provides an easy-to-use visual dashboard to make the AI image creation process more approachable to new users.
Leonardo AI leverages internal and community AI models to help users generate images from text-based prompts.
Each image generated on the platform consumes roughly one token.
Leonardo AI offers a free version that includes 150 tokens, or roughly 150 AI images.
You can access Leonardo AI by signing up for an account on their website.
The platform is currently in early access mode, but you can speed up this approval process by joining the Leonardo AI discord and filling out a white list form.
Yes, Leonardo AI is capable of producing high-quality AI images based on a wide variety of Stable Diffusion models.
The platform makes this process much easier for less technical users who do not want to go through the trouble of running AI image models on their personal devices.
JJ Fiasson is the Austrailian-based founder of Leonardo AI.
Yes, under the chúng tôi Terms of Service, all rights to an image belong to the person who has generated it.
Yes, it is okay to sell AI art generated by chúng tôi on various platforms like Etsy and stock image websites.
Learn more about how to sell AI art.
Quantum physics phenomena is perhaps the most smoking subject in contemporary physical science. It takes a look at how particles in nature “meet up” and bring along their interesting properties, for example, electrical conductivity or magnetism. Nonetheless, it has been practically incomprehensible for even the most seasoned researchers to get more than a look at these unpredictable phenomena. This is a direct result of the colossal number of particles these phenomena contain (more than one billion billion in every gram) and the tremendous number of interactions between them. In the fast-paced, confusing universe of quantum science, AI’s are utilized to assist scientific experts with ascertaining significant substance properties and make predictions about experimental results. However, so as to do this precisely, these AI need to have a truly solid comprehension of the key standards of quantum mechanics and researchers of another interdisciplinary examination on the theme say these quantum predictions have been missing for quite a while. Another machine learning system could be the appropriate response. Artificial intelligence and machine learning algorithms are routinely used to foresee our purchasing behaviour and to perceive our faces or handwriting. In scientific research, artificial intelligence is building up itself as an essential tool for scientific discovery. In science, AI has gotten instrumental in anticipating the results of experiments or simulations of quantum systems. Artificial intelligence accomplishes this by figuring out how to comprehend principal equations of quantum mechanics. Settling these equations in the ordinary manner requires massive high-performance computing resources (long stretches of computing time) which is regularly the bottleneck to the computational design of new purpose-built molecules for medicinal and industrial applications. The recently created AI algorithm can supply precise forecasts within seconds on a laptop or cell phone. An interdisciplinary group of chemists, physicists, and computer scientists from the University of Luxembourg, the University of Warwick and the Technical University of Berlin have built up a deep machine learning that can foresee the quantum conditions of molecules, supposed wave functions, which decide all properties of molecules. Dr. Reinhard Maurer from the Department of Chemistry at the University of Warwick remarks says this has been a joint multi-year effort, which required computer science know-how to build up an artificial intelligence algorithm flexible enough to catch the shape and conduct of wave capacities, yet additionally, science and physics know-how to process and speak to quantum chemical information in a structure that is sensible for the algorithm. Quantum mechanics, broadly, takes into account states to simultaneously exist and not exist, and utilizing degrees of freedom can assist researchers better understand how to precisely and conveniently portray a framework. Without representing these degrees of freedom, past AI’s have depicted these quantum chemistry experiments in increasingly classical scalar, vector and tensor fields, which required much more calculation time and energy. The study writers compose that this deep learning system, called SchNOrb (which we can just envision is as amusing to pronounce as it looks), enables them to anticipate molecular orbits with “close to ‘chemical accuracy’” which thus gives a precise forecast of the molecules’ electronic structure and a “rich chemical interpretation” of its reaction dynamics. The abilities exhibited by this algorithm would help scientific experts all the more adequately design “purpose-built molecules” for medical and industrial use.
How to Build your Resume with Appy Pie’s Online CV Generator?
Appy Pie’s resume builder is one of the most popular CV makers because it simplifies the process into 3 easy steps:
Find the right template.
Sign up/Log in to Appy Pie CV creator. Find the right pre-set template from our vast library of options. Make sure the template that you choose matches the job type. You can also start from scratch if you wish to build an entirely unique resume.
Add your details
Add your details in the right boxes and columns using the easy-to-use drag-and-drop editor to create your CV. You can also include images if your job is creative or you need to showcase work samples.
Finalize, save, and share
Once you have added the text and images, you can finalize it with filters. Appy Pie’s free resume maker lets you save the resume, print it directly, share it, or even embed it on your blog or website.Make your own Job-Winning Resume with Appy Pie’s Free Online Resume Maker
A resume is a one or two-page document that highlights your top skills. While the real test of your talent will be the interview, to be able to get that interview, you need a killer resume. It is like a marketing copy that aims to market your skills and talent. Most hiring managers get hundreds of resumes each day. And most of them look quite similar. If you want your resume to stand out from the pile of other papers, you need a powerful resume creator.
Among all the available resume builders online, Appy Pie’s CV generator is the best platform to create CV online. Appy Pie’s professional resume builder is easily the best resume builder and has gained massive popularity.
A professional CV maker lets you make your CV unique and attractive so that your future employers are compelled to shortlist you immediately, taking you a step closer to your dream job. Seize the opportunity with a creative, professional, and effective resume. Appy Pie’s online CV maker – taking you one step closer to your dream job.
You need no tech skills and no prior experience to use this unique CV maker. Beautiful visual resumes for creative jobs and minimalistic, professional-looking CVs to impress the traditional hiring managers, Appy Pie’s CV builder and online resume editor has it all.Why Choose Appy Pie Design to Create a Professional Resume?
There are many free online resume builders to create resumes online that can help you apply for your dream job with confidence. The free CV maker from Appy Pie stands apart from other free CV builders.
Templates for Every Industry
Creative, visual, minimalistic, or formal. Choose from a wide range of resume templates and create a resume to suit the kind of job you are looking for. Appy Pie’s resume maker has the right template for all industries. The right resume helps job seekers highlight their skills and land their dream job with ease.
Easy and Free
Making professional resumes shouldn’t take up all your time. With the free resume builder from Appy Pie, you can create impressive and effective resumes with ease. The drag-and-drop editor lets you choose, customize, and create CVs and cover letters with minimum effort.
Save Multiple Versions
Every job is unique. And you need to tweak your resume for each job that you apply to. Appy Pie’s online resume maker lets you create multiple versions of your CV. Make suitable versions of your resume for the jobs that you want to apply to — landing a job made quick and easy.
One notable example is the General Data Protection Regulation (GDPR) in the European Union, which includes specific provisions related to AI. The GDPR requires that organizations using AI must provide clear and transparent information about the use of personal data and must obtain explicit consent for certain uses of data.
Another example is the IEEE’s Ethically Aligned Design (EAD) guidelines, which provide a framework for designing AI systems that are aligned with human values. The guidelines cover a wide range of topics, including privacy, transparency, and accountability.
Additionally, there are a number of industry-specific guidelines and regulations for AI. For example, the National Institute of Standards and Technology (NIST) has published guidelines for the responsible use of AI in the financial sector. Similarly, the Federal Aviation Administration (FAA) has issued guidelines for drones’ safe and ethical operation.
In the United States, the government has yet to pass any federal laws specifically related to AI, but some states have passed laws, such as the Artificial Intelligence Video Interview Fairness Act in California.Principle ies for Ethical AI
When it comes to ensuring responsible and ethical AI development and deployment, there are several key principles and strategies that organizations should keep in mind.Key Principles:
Transparency: Organizations should be transparent about data collection and use, as well as AI decision-making processes, to build trust with users a duce unintended consequences
Accountability: Organizations should be held accountable for the actions of their AI systems and able to explain and justify decisions to ensure alignment with human values and address negative consequences
Fairness: Organizations should ensure AI systems do not perpetuate societal biases in decision-making by using diverse data sets and regularly testing and monitoring systems’ performance
Implement robust testing and validation processes for AI systems to ensure they are working as intended, and errors or biases are identified and addressed
Establish internal review processes to ensure compliance with relevant regulations and guidelines
Invest in building a culture of ethics within the company by providing training and education on AI ethics and fostering transparency, accountability, and fairness
Constantly evaluate and adapt approaches to ensure responsible and ethical AI development and deployment.
Ethical AI in the Government & Private Sector
Both government and private sector organizations have important roles to play in promoting ethical AI.
Government organizations have a responsibility to establish regulations and guidelines for the development and use of AI, in order to protect citizens’ rights and ensure that AI is used responsibly and ethically. This can include measures to protect citizens’ privacy, prevent discrimination, and ensure that AI systems are transparent and accountable. Government organizations can also invest in research and development to support the development of ethical AI and can provide funding and resources for the training and education of AI professionals.
Private sector organizations, on the other hand, have a responsibility to ensure that their own AI systems and practices are in compliance with relevant regulations and guidelines. They should establish internal review processes to ensure that their AI systems are aligned with human values and should be transparent about the data they are collecting and how it is being used. Private sector organizations should also invest in building a culture of ethics within the company and provide their employees with training and education on AI ethics.
In addition, both government and private sector organizations can work together to promote ethical AI by collaborating on research and development, sharing best practices, and participating in industry-wide initiatives and standards-setting bodies.
It’s important to note that promoting ethical AI is a shared responsibility and requires a collaborative effort between the government, the private sector, and society at large.Navigating Trends & Challenges of AI Governance
One trend is the increasing use of AI in critical infrastructure and high-stakes decision-making, such as healthcare, transportation, and criminal justice. As AI is increasingly used in these areas, it’s crucial to ensure that these systems are safe, reliable, and unbiased.
Another trend is the growing use of AI in the public sector, such as in government services and decision-making. This presents new challenges in terms of transparency, accountability, and public trust.
In addition, there is a growing concern about the potential for AI to be used for malicious purposes, such as cyber-attacks and disinformation campaigns. As AI becomes more sophisticated, it is becoming easier to create realistic fake videos and images, which can be used to spread misinformation and propaganda.
To address these challenges, governments and private sector organizations can work together to establish regulations and guidelines for using AI in critical infrastructure and high-stakes decision-making and promote transparency, accountability, and public trust. Additionally, organizations can invest in research and development to improve the security and robustness of AI systems and to develop technologies that can detect and mitigate malicious use of AI.
Moreover, Governments and organizations should also invest in education and training programs to build a workforce with the necessary skills and knowledge to develop and govern AI ethically and responsibly.Conclusion
In conclusion, the development and use of Artificial intelligence (AI) have the potential to bring significant benefits to society, but it also presents a range of ethical and governance challenges. From job displacement and privacy violations to biased decision-making, it’s crucial to establish guidelines and regulations to govern the ethical use of AI in today’s society. The blog post has discussed the potential negative consequences of AI, current efforts to govern AI, best practices for ethical AI, the role of government and industry in governing AI, and the future of AI governance. It’s essential to understand the importance of AI governance and to work towards ensuring that AI is developed and deployed responsibly and ethically.
Establishing regulations and guidelines for the ethical use of AI is crucial to protect citizens’ rights and prevent negative consequences such as job displacement and privacy violations.
Transparency, accountability, and fairness are key principles for ensuring responsible and ethical AI development and deployment.
Government and private sector organizations are responsible for promoting ethical AI and should work together to establish regulations, share best practices, and invest in research and development.
Ongoing efforts and investments in research, development, education and training are necessary to build a workforce with the necessary skills and knowledge to develop and govern AI ethically and responsibly.
The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.
China is taking a significant step forward in regulating generative artificial intelligence (Generative AI) services with the release of draft measures by the Cyberspace Administration of China (CAC). These proposed rules aim to manage and regulate the use of Generative AI in the country. The draft measures, which were issued in April 2023, are part of China’s ongoing efforts to ensure the responsible use of AI technology. Let us look at the key provisions of the draft measures and their implications for Generative AI service providers.
Also Read: China Takes Bold Step to Regulate Generative AI Services1. Draft Measures Aim to Regulate Generative AI in China
The draft measures, known as the “Measures for the Management of Generative Artificial Intelligence Services,” outline the regulations for using Generative AI in the People’s Republic of China (PRC). These measures align with existing cybersecurity laws, including the PRC Cybersecurity Law, the Personal Information Protection Law (PIPL), and the Data Security Law. They follow earlier legislation, such as the “Internet Information Service Algorithmic Recommendation Management Provisions” and the “Provisions on the Administration of Deep Synthesis Internet Information Services.”
Also Read: China Sounds the Alarm on Artificial Intelligence Risks2. Scope of the Draft Measures
The draft measures are designed to apply to organizations and individuals providing Generative AI services, referred to as Service Providers, to the public within China. This includes chat and content generation services. Interestingly, even non-PRC providers of Generative AI services will be subject to these measures if their services are accessible to the public within China. These extraterritorial provisions reflect the government’s intent to regulate Generative AI services comprehensively.3. Filing Requirements for Service Providers
Service Providers must comply with two filing requirements outlined in the draft measures. Firstly, they must submit a security assessment to the CAC, adhering to the “Provisions on the Security Assessment of Internet Information Services with Public Opinion Properties or Social Mobilization Capacity.” Secondly, they are required to file their algorithm according to the Algorithmic Recommendation Provisions. While these requirements have been in place since 2023 and 2023, respectively, the draft measures explicitly clarify that Generative AI services are also subject to these filing obligations.
Also Read: China’s Billion-Dollar Bet: Baidu’s $145M AI Fund Signals a New Era of AI Self-Reliance4. Ensuring Legal Training Data and Record-Keeping
Service Providers must ensure the legality of the Training Data used to train Generative AI models. This includes verifying that the data does not infringe upon intellectual property rights or contain non-consensually collected personal information. Additionally, Service Providers must maintain meticulous records of the Training Data used. This requirement is crucial for potential audits by the CAC or other authorities, who may request detailed information on the training data’s source, scale, type, and quality.5. Challenges in Compliance
Complying with these requirements presents challenges for Service Providers. Training AI models is an iterative process that heavily relies on user input. Capturing and filtering all user input in real-time would be arduous, if not impossible. This aspect raises questions about the practical implementation and enforcement of the draft measures on Service Providers, particularly those operating outside the CAC’s geographical reach.6. Content Guidelines and Limitations
The draft measures mandate that AI-generated content must adhere to specific guidelines. This includes respecting social virtue, public order customs, and reflecting socialist core values. The content must not subvert state power, disrupt economic or social order, discriminate, infringe upon intellectual property rights, or spread untruthful information. Additionally, Service Providers must respect the lawful rights and interests of others.7. Concerns About Feasibility
The requirements regarding AI-generated content raise concerns about feasibility. AI models excel at predicting patterns rather than understanding the intrinsic meaning or verifying the truthfulness of statements. Instances of AI models fabricating answers, commonly known as “hallucination,” highlight the limitations of the technology in meeting the stringent guidelines set by the draft measures.8. Personal Information Protection Obligations
Service Providers are held legally responsible as “personal information processors” under the draft measures. This places obligations similar to the “data controller” concept under other data protection legislation. If AI-generated content involves personal information, Service Providers must comply with personal information protection obligations outlined in the PIPL. Furthermore, they must establish a complaint mechanism to handle data subject requests for revision, deletion, or masking of personal information.9. User Reporting and Retraining
The draft measures include a “whistle-blowing” provision to address concerns about inappropriate AI-generated content. Users of Generative AI services are empowered to report inappropriate content to the CAC or relevant authorities. In response, Service Providers have three months to retrain their Generative AI models and ensure non-compliant content is no longer generated.10. Preventing Excessive Reliance and Addiction
Service Providers must define appropriate user groups, occasions, and purposes for using Generative AI services. They must also adopt measures to prevent users from excessively relying on or becoming addicted to AI-generated content. Furthermore, Service Providers must provide user guidance to foster scientific understanding and rational use of AI-generated content, thereby discouraging improper use.
Also Read: Alibaba and Huawei’s Announce Debut of Their Chatbots: The Rise of Generative AI Chatbots in China11. Limitations on User Information Retention and Profiling
The draft measures prohibit Service Providers from retaining information that could be used to trace the identity of specific users. User profiling based on the input information and usage details and providing such information to third parties is also prohibited. This provision aims to protect user privacy and prevent the misuse of personal information.12. Consequences for Non-Compliance
Non-compliance with the draft measures may result in fines of up to RMB100,000 (~USD14,200). In cases of refusal to rectify or under “grave circumstances,” the CAC and relevant authorities can suspend or terminate a Service Provider’s use of Generative AI. In severe cases, perpetrators may be liable if their actions violate criminal provisions.Our Say
China’s decision to regulate AI comes at a time of global discussions on the potential risks of the technology. As one of the pioneering regulatory frameworks for Generative AI, the draft measures are crucial for ensuring responsible AI use in China. However, the broad obligations imposed on Service Providers require careful consideration to strike a balance between regulation and fostering the competitiveness of Chinese Generative AI companies. Service Providers and related businesses should stay alert for any future updates as the CAC finalizes the measures.
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